Descubriendo el potencial de la computación cuántica
Conocimiento al servicio de la ciencia y la innovación
Del desarrollo a la aplicación
Encuentra las últimas publicaciones disponibles para cada una de nuestras actividades
Arquitecturas de simulación cuántica en sistemas HPC
IA cuántica para aplicaciones científicas e industriales
IA cuántica para la caracterización del ruido de los ordenadores cuánticos
Algoritmos de aprendizaje automático de inspiración cuántica y sus aplicaciones en la privacidad
Algoritmos de cadenas de Markov cuánticas
Computación cuántica analógico-digital
Algoritmos genéticos cuánticos, variacionales y adiabáticos y sus aplicaciones
Aplicaciones de la IA cuántica a la química cuántica, ciencia de materiales y finanzas
“Quantum reservoir computing” para aprendizaje automático
Algoritmos de corrección cuántica de errores e IA
Modelos de clasificación y generativos cuánticos aplicados a física de partículas y medicina
Análisis de complejidad computacional de algoritmos cuánticos e IA para analizar procesos cuánticos
Optimización con algoritmos de templado cuántico (“quantum annealing”)
Técnicas de IA y quantum machine learning para la identificación de procesos cuánticos
Desarrollo de software de control de simuladores cuánticos para quantum machine learning
Desarrollo y certificación de algoritmos cuánticos en hardware NISQ
Redes neuronales cuánticas y sus aplicaciones al aprendizaje de procesos cuánticos
Algoritmos cuánticos y de inspiración cuántica para problemas matemáticos complejos
Desarrollo de algoritmos y tecnología de control para simuladores cuánticos
Estudio pormenorizado de las arquitecturas cuánticas y sus desafíos de software y hardware
El trayecto de Quantum Spain
Lee los logros más recientes del proyecto
Capel, A.; Alhambra, A. M.; Gondolf, P.; Ruiz-de-Alarcón, A.; Scalet, S. O.
Conditional Independence of 1D Gibbs States with Applications to Efficient Learning Sin publicar
Preprint, 2025.
Resumen | Enlaces | BibTeX | Etiquetas: UCM
@unpublished{nokey,
title = {Conditional Independence of 1D Gibbs States with Applications to Efficient Learning},
author = {Capel, A. and Alhambra, A.M. and Gondolf, P. and Ruiz-de-Alarcón, A. and Scalet, S.O.},
url = {https://doi.org/10.48550/arXiv.2402.18500},
doi = {doi.org/10.48550/arXiv.2402.18500},
year = {2025},
date = {2025-12-02},
abstract = {We show that spin chains in thermal equilibrium have a correlation structure in which individual regions are strongly correlated at most with their near vicinity. We quantify this with alternative notions of the conditional mutual information, defined through the so-called Belavkin-Staszewski relative entropy. We prove that these measures decay superexponentially at every positive temperature, under the assumption that the spin chain Hamiltonian is translation-invariant. Using a recovery map associated with these measures, we sequentially construct tensor network approximations in terms of marginals of small (sublogarithmic) size. As a main application, we show that classical representations of the states can be learned efficiently from local measurements with a polynomial sample complexity. We also prove an approximate factorization condition for the purity of the entire Gibbs state, which implies that it can be efficiently estimated to a small multiplicative error from a small number of local measurements. The results extend from strictly local to exponentially-decaying interactions above a threshold temperature, albeit only with exponential decay rates. As a technical step of independent interest, we show an upper bound to the decay of the Belavkin-Staszewski relative entropy upon the application of a conditional expectation.},
howpublished = {Preprint},
keywords = {UCM},
pubstate = {published},
tppubtype = {unpublished}
}
We show that spin chains in thermal equilibrium have a correlation structure in which individual regions are strongly correlated at most with their near vicinity. We quantify this with alternative notions of the conditional mutual information, defined through the so-called Belavkin-Staszewski relative entropy. We prove that these measures decay superexponentially at every positive temperature, under the assumption that the spin chain Hamiltonian is translation-invariant. Using a recovery map associated with these measures, we sequentially construct tensor network approximations in terms of marginals of small (sublogarithmic) size. As a main application, we show that classical representations of the states can be learned efficiently from local measurements with a polynomial sample complexity. We also prove an approximate factorization condition for the purity of the entire Gibbs state, which implies that it can be efficiently estimated to a small multiplicative error from a small number of local measurements. The results extend from strictly local to exponentially-decaying interactions above a threshold temperature, albeit only with exponential decay rates. As a technical step of independent interest, we show an upper bound to the decay of the Belavkin-Staszewski relative entropy upon the application of a conditional expectation.
Biswas, S.; Rico, E.; Grass, T.
Ring-exchange physics in a chain of three-level ions Artículo de revista
En: Quantum , 2025.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Ring-exchange physics in a chain of three-level ions},
author = {Biswas, S. and Rico, E. and Grass, T. },
url = {https://quantum-journal.org/papers/q-2025-04-01-1683/},
doi = {doi.org/10.22331/q-2025-04-01-1683},
year = {2025},
date = {2025-04-01},
journal = {Quantum },
abstract = {In the presence of ring exchange interactions, bosons in a ladder-like lattice may form the bosonic analogon of a correlated metal, known as the d-wave Bose liquid (DBL). In this paper, we show that a chain of trapped ions with three internal levels can mimic a ladder-like system constrained to a maximum occupation of one boson per rung. The setup enables tunable ring exchange interactions, transitioning between a polarized regime with all bosons confined to one leg and the DBL regime. The latter state is characterized by a splitting of the peak in the momentum distribution and an oscillating pair correlation function.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
In the presence of ring exchange interactions, bosons in a ladder-like lattice may form the bosonic analogon of a correlated metal, known as the d-wave Bose liquid (DBL). In this paper, we show that a chain of trapped ions with three internal levels can mimic a ladder-like system constrained to a maximum occupation of one boson per rung. The setup enables tunable ring exchange interactions, transitioning between a polarized regime with all bosons confined to one leg and the DBL regime. The latter state is characterized by a splitting of the peak in the momentum distribution and an oscillating pair correlation function.
Hernández Caceres, J. M.; Fernández Rúa, I.; Fernández-Combarro Álvarez, E.
Efficient quantum algorithms to find substructures on finite algebras Artículo de revista
En: Quantum Information and Computation , vol. 23, no 15, 2024, ISBN: 1533-7146.
Resumen | Enlaces | BibTeX | Etiquetas: UNIOVI
@article{nokey,
title = {Efficient quantum algorithms to find substructures on finite algebras},
author = {Hernández Caceres, J. M. and Fernández Rúa, I. and Fernández-Combarro Álvarez, E. },
url = {https://www.rintonpress.com/xxqic23/qic-23-1516/1275-1290.pdf},
doi = {doi.org/10.26421/QIC23.15-16-2},
isbn = {1533-7146},
year = {2024},
date = {2024-12-16},
journal = {Quantum Information and Computation },
volume = {23},
number = {15},
abstract = {When classifying a collection of finite algebras (for instance, in the computational classification of finite semifields), an important task is the determination of substructures such as the right, middle, and left nuclei, the nucleus, and the center. Finding these structures may become computationally expensive when there is no additional information about the algebra properties. In this paper, we introduce quantum algorithms than solve this task efficiently, by formulating it as an instance of the Hidden Subgroup Problem (HSP) {over Abelian groups}. We give detailed constructions of the quantum circuits involved in the process and prove that the overall (quantum) complexity of our algorithm is polynomial in the dimension of the algebra, while a similar approach with classical computers would require an exponential number of queries to the HSP function},
keywords = {UNIOVI},
pubstate = {published},
tppubtype = {article}
}
When classifying a collection of finite algebras (for instance, in the computational classification of finite semifields), an important task is the determination of substructures such as the right, middle, and left nuclei, the nucleus, and the center. Finding these structures may become computationally expensive when there is no additional information about the algebra properties. In this paper, we introduce quantum algorithms than solve this task efficiently, by formulating it as an instance of the Hidden Subgroup Problem (HSP) {over Abelian groups}. We give detailed constructions of the quantum circuits involved in the process and prove that the overall (quantum) complexity of our algorithm is polynomial in the dimension of the algebra, while a similar approach with classical computers would require an exponential number of queries to the HSP function
Espinosa, E. M.; Wu, L. A.
Study on quantum thermalization from thermal initial states in a superconducting quantum computer Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@unpublished{nokey,
title = {Study on quantum thermalization from thermal initial states in a superconducting quantum computer},
author = {Espinosa, E.M. and Wu, L.A.},
url = {https://arxiv.org/abs/2403.14630},
doi = {doi.org/10.48550/arXiv.2403.14630},
year = {2024},
date = {2024-12-04},
abstract = {Quantum thermalization in contemporary quantum devices, in particular quantum computers, has recently attracted significant theoretical interest. Unusual thermalization processes, such as the Quantum Mpemba Effect (QME), have been explored theoretically. However, there is a shortage of experimental results due to the difficulty in preparing thermal states. In this paper, we propose a protocol to indirectly address this challenge. Moreover, we experimentally validate our protocol using IBM quantum devices, providing results for unusual relaxation in equidistant quenches as predicted for the IBM qubit. We also assess the formalism introduced for the QME, obtaining results consistent with the theoretical predictions. This demonstration underscores that our protocol can provide an alternative way of studying thermal states physics when their direct preparation may be too difficult.},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {unpublished}
}
Quantum thermalization in contemporary quantum devices, in particular quantum computers, has recently attracted significant theoretical interest. Unusual thermalization processes, such as the Quantum Mpemba Effect (QME), have been explored theoretically. However, there is a shortage of experimental results due to the difficulty in preparing thermal states. In this paper, we propose a protocol to indirectly address this challenge. Moreover, we experimentally validate our protocol using IBM quantum devices, providing results for unusual relaxation in equidistant quenches as predicted for the IBM qubit. We also assess the formalism introduced for the QME, obtaining results consistent with the theoretical predictions. This demonstration underscores that our protocol can provide an alternative way of studying thermal states physics when their direct preparation may be too difficult.
Sun, Y.; Wu, L. A.
Quantum search algorithm on weighted databases Sin publicar
2024.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@unpublished{nokey,
title = {Quantum search algorithm on weighted databases},
author = {Sun, Y. and Wu, L.A. },
url = {https://arxiv.org/abs/2312.01590},
doi = {doi.org/10.48550/arXiv.2312.01590},
year = {2024},
date = {2024-12-03},
abstract = {The Grover algorithm is a crucial solution for addressing unstructured search problems and has emerged as an essential quantum subroutine in various complex algorithms. By using a different approach with previous studies, this research extensively investigates Grover's search methodology within non-uniformly distributed databases, a scenario frequently encountered in practical applications. Our analysis reveals that the behavior of the Grover evolution differs significantly when applied to non-uniform databases compared to uniform or 'unstructured databases'. Based on the property of differential equation, it is observed that the search process facilitated by this evolution does not consistently result in a speed-up, and we have identified specific criteria for such situations. Furthermore, we have extended this investigation to databases characterized by coherent states, confirming the speed-up achieved through Grover evolution via rigorous numerical verification. In conclusion, our study provides an enhancement to the original Grover algorithm, offering insights to optimize implementation strategies and broaden its range of applications.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {unpublished}
}
The Grover algorithm is a crucial solution for addressing unstructured search problems and has emerged as an essential quantum subroutine in various complex algorithms. By using a different approach with previous studies, this research extensively investigates Grover's search methodology within non-uniformly distributed databases, a scenario frequently encountered in practical applications. Our analysis reveals that the behavior of the Grover evolution differs significantly when applied to non-uniform databases compared to uniform or 'unstructured databases'. Based on the property of differential equation, it is observed that the search process facilitated by this evolution does not consistently result in a speed-up, and we have identified specific criteria for such situations. Furthermore, we have extended this investigation to databases characterized by coherent states, confirming the speed-up achieved through Grover evolution via rigorous numerical verification. In conclusion, our study provides an enhancement to the original Grover algorithm, offering insights to optimize implementation strategies and broaden its range of applications.
Wang, Z. M.; Wu, S. L.; Byrd, M. S.; Wu, L. A.
Going beyond quantum Markovianity and back to reality: An exact master equation study Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@unpublished{nokey,
title = {Going beyond quantum Markovianity and back to reality: An exact master equation study},
author = {Wang, Z.M. and Wu, S.L. and Byrd, M.S. and Wu, L.A. },
url = {https://arxiv.org/abs/2411.17197},
doi = {doi.org/10.48550/arXiv.2411.17197},
year = {2024},
date = {2024-12-03},
abstract = {The precise characterization of dynamics in open quantum systems often presents significant challenges, leading to the introduction of various approximations to simplify a model. One commonly used strategy involves Markovian approximations, assuming a memoryless environment. In this study, such approximations are not used and an analytical dynamical depiction of an open quantum system is provided. The system under consideration is an oscillator that is surrounded by a bath of oscillators. The resulting dynamics are characterized by a second-order complex coefficient linear differential equation, which may be either homogeneous or inhomogeneous. Moreover, distinct dynamical regions emerge, depending on certain parameter values. Notably, the steady-state average excitation number (AEN) of the system shows rapid escalation with increasing non-Markovianity, reflecting the intricacies of real-world dynamics. In cases where there is detuning between the system frequency and the environmental central frequency within a non-Markovian regime, the AEN maintains its initial value for an extended period. Furthermore, the application of pulse control can effectively protect the quantum system from decoherence effects without using approximations. The pulse control can not only prolong the relaxation time of the oscillator, but can also be used to speed up the relaxation process, depending on the specifications of the pulse. By employing a kick pulse, the Mpemba effect can be observed in the non-Markovian regime in a surprisingly super-cooling-like effect.},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {unpublished}
}
The precise characterization of dynamics in open quantum systems often presents significant challenges, leading to the introduction of various approximations to simplify a model. One commonly used strategy involves Markovian approximations, assuming a memoryless environment. In this study, such approximations are not used and an analytical dynamical depiction of an open quantum system is provided. The system under consideration is an oscillator that is surrounded by a bath of oscillators. The resulting dynamics are characterized by a second-order complex coefficient linear differential equation, which may be either homogeneous or inhomogeneous. Moreover, distinct dynamical regions emerge, depending on certain parameter values. Notably, the steady-state average excitation number (AEN) of the system shows rapid escalation with increasing non-Markovianity, reflecting the intricacies of real-world dynamics. In cases where there is detuning between the system frequency and the environmental central frequency within a non-Markovian regime, the AEN maintains its initial value for an extended period. Furthermore, the application of pulse control can effectively protect the quantum system from decoherence effects without using approximations. The pulse control can not only prolong the relaxation time of the oscillator, but can also be used to speed up the relaxation process, depending on the specifications of the pulse. By employing a kick pulse, the Mpemba effect can be observed in the non-Markovian regime in a surprisingly super-cooling-like effect.
Rout, S.; Sankar Bhattacharya, S.; Horodecki, P.
Randomness-free Detection of Non-projective Measurements: Qubits & beyond Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UAB
@unpublished{nokey,
title = {Randomness-free Detection of Non-projective Measurements: Qubits & beyond},
author = {Rout, S. and Sankar Bhattacharya, S. and Horodecki, P.},
url = {https://doi.org/10.48550/arXiv.2412.00213},
doi = {doi.org/10.48550/arXiv.2412.00213},
year = {2024},
date = {2024-11-29},
abstract = {Non-projective measurements are resourceful in several information-processing protocols. In this work, we propose an operational task involving space-like separated parties to detect measurements that are neither projective nor a classical post-processing of data obtained from a projective measurement. In the case of qubits, we consider a bipartite scenario and different sets of target correlations. While some correlations in each of these sets can be obtained by performing non-projective measurements on some shared two-qubit state it is impossible to simulate correlation in any of them using projective simulable measurements on bipartite qubit states or equivalently one bit of shared randomness. While considering certain sets of target correlations we show that the detection of qubit non-projective measurement is robust under arbitrary depolarising noise (except in the limiting case). For qutrits, while considering a similar task we show that some correlations obtained from local non-projective measurements are impossible to be obtained while performing the same qutrit projective simulable measurements by both parties. We provide numerical evidence of its robustness under arbitrary depolarising noise. For a more generic consideration (bipartite and tripartite scenario), we provide numerical evidence for a projective-simulable bound on the reward function for our task. We also show a violation of this bound by using qutrit POVMs. From a foundational perspective, we extend the notion of non-projective measurements to general probabilistic theories (GPTs) and use a randomness-free test to demonstrate that a class of GPTs, called square-bits or box-world are unphysical.},
howpublished = {Preprint},
keywords = {UAB},
pubstate = {published},
tppubtype = {unpublished}
}
Non-projective measurements are resourceful in several information-processing protocols. In this work, we propose an operational task involving space-like separated parties to detect measurements that are neither projective nor a classical post-processing of data obtained from a projective measurement. In the case of qubits, we consider a bipartite scenario and different sets of target correlations. While some correlations in each of these sets can be obtained by performing non-projective measurements on some shared two-qubit state it is impossible to simulate correlation in any of them using projective simulable measurements on bipartite qubit states or equivalently one bit of shared randomness. While considering certain sets of target correlations we show that the detection of qubit non-projective measurement is robust under arbitrary depolarising noise (except in the limiting case). For qutrits, while considering a similar task we show that some correlations obtained from local non-projective measurements are impossible to be obtained while performing the same qutrit projective simulable measurements by both parties. We provide numerical evidence of its robustness under arbitrary depolarising noise. For a more generic consideration (bipartite and tripartite scenario), we provide numerical evidence for a projective-simulable bound on the reward function for our task. We also show a violation of this bound by using qutrit POVMs. From a foundational perspective, we extend the notion of non-projective measurements to general probabilistic theories (GPTs) and use a randomness-free test to demonstrate that a class of GPTs, called square-bits or box-world are unphysical.
Rout, S.; N. Bhattacharya Sakharwade, S. S.; Ramanathan, R.; Horodecki, P.
Unbounded Quantum Advantage in Communication with Minimal Input Scaling Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UAB
@unpublished{nokey,
title = {Unbounded Quantum Advantage in Communication with Minimal Input Scaling},
author = {Rout,S. and Sakharwade, N. Bhattacharya, S.S. and Ramanathan, R. and Horodecki, P.},
url = {https://arxiv.org/pdf/2305.10372},
doi = {doi.org/10.48550/arXiv.2305.10372},
year = {2024},
date = {2024-11-29},
urldate = {2024-11-29},
abstract = {In communication complexity-like problems, previous studies have shown either an exponential quantum advantage or an unbounded quantum advantage with an exponentially large input set Θ(2n) bits with respect to classical communication Θ(n) bits. In the former, the quantum and classical separation grows exponentially in input while the latter's quantum communication resource is a constant. Remarkably, it was still open whether an unbounded quantum advantage exists while the inputs do not scale exponentially. Here we answer this question affirmatively using an input size of optimal order. Considering two variants as tasks: 1) distributed computation of relation and 2) {it relation reconstruction}, we study the one-way zero-error communication complexity of a relation induced by a distributed clique labelling problem for orthogonality graphs. While we prove no quantum advantage in the first task, we show an {it unbounded quantum advantage} in relation reconstruction without public coins. Specifically, for a class of graphs with order m, the quantum complexity is Θ(1) while the classical complexity is Θ(logm). Remarkably, the input size is Θ(logm) bits and the order of its scaling with respect to classical communication is {it minimal}. This is exponentially better compared to previous works. Additionally, we prove a lower bound (linear in the number of maximum cliques) on the amount of classical public coin necessary to overcome the separation in the scenario of restricted communication and connect this to the existence of Orthogonal Arrays. Finally, we highlight some applications of this task to semi-device-independent dimension witnessing as well as to the detection of Mutually Unbiased Bases.},
howpublished = {Preprint},
keywords = {UAB},
pubstate = {published},
tppubtype = {unpublished}
}
In communication complexity-like problems, previous studies have shown either an exponential quantum advantage or an unbounded quantum advantage with an exponentially large input set Θ(2n) bits with respect to classical communication Θ(n) bits. In the former, the quantum and classical separation grows exponentially in input while the latter's quantum communication resource is a constant. Remarkably, it was still open whether an unbounded quantum advantage exists while the inputs do not scale exponentially. Here we answer this question affirmatively using an input size of optimal order. Considering two variants as tasks: 1) distributed computation of relation and 2) {it relation reconstruction}, we study the one-way zero-error communication complexity of a relation induced by a distributed clique labelling problem for orthogonality graphs. While we prove no quantum advantage in the first task, we show an {it unbounded quantum advantage} in relation reconstruction without public coins. Specifically, for a class of graphs with order m, the quantum complexity is Θ(1) while the classical complexity is Θ(logm). Remarkably, the input size is Θ(logm) bits and the order of its scaling with respect to classical communication is {it minimal}. This is exponentially better compared to previous works. Additionally, we prove a lower bound (linear in the number of maximum cliques) on the amount of classical public coin necessary to overcome the separation in the scenario of restricted communication and connect this to the existence of Orthogonal Arrays. Finally, we highlight some applications of this task to semi-device-independent dimension witnessing as well as to the detection of Mutually Unbiased Bases.
Mariella, N.; Murphy, T.; Di Marcantonio, F.; Najafi, K.; Vallecorsa, S.; Zhuk, S.; Rico, E.
Order Parameter Discovery for Quantum Many-Body Systems Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@unpublished{nokey,
title = {Order Parameter Discovery for Quantum Many-Body Systems},
author = {Mariella, N. and Murphy, T. and Di Marcantonio, F. and Najafi, K. and Vallecorsa, S. and Zhuk, S. and Rico, E.},
url = {https://arxiv.org/abs/2408.01400},
doi = {doi.org/10.48550/arXiv.2408.01400},
year = {2024},
date = {2024-11-18},
abstract = {Quantum phase transitions reveal deep insights into the behavior of many-body quantum systems, but identifying these transitions without well-defined order parameters remains a significant challenge. In this work, we introduce a novel approach to constructing phase diagrams using the vector field of the reduced fidelity susceptibility (RFS). This method maps quantum phases and formulates an optimization problem to discover observables corresponding to order parameters. We demonstrate the effectiveness of our approach by applying it to well-established models, including the Axial Next Nearest Neighbour Interaction (ANNNI) model, a cluster state model, and a chain of Rydberg atoms. By analyzing observable decompositions into eigen-projectors and finite-size scaling, our method successfully identifies order parameters and characterizes quantum phase transitions with high precision. Our results provide a powerful tool for exploring quantum phases in systems where conventional order parameters are not readily available.},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {unpublished}
}
Quantum phase transitions reveal deep insights into the behavior of many-body quantum systems, but identifying these transitions without well-defined order parameters remains a significant challenge. In this work, we introduce a novel approach to constructing phase diagrams using the vector field of the reduced fidelity susceptibility (RFS). This method maps quantum phases and formulates an optimization problem to discover observables corresponding to order parameters. We demonstrate the effectiveness of our approach by applying it to well-established models, including the Axial Next Nearest Neighbour Interaction (ANNNI) model, a cluster state model, and a chain of Rydberg atoms. By analyzing observable decompositions into eigen-projectors and finite-size scaling, our method successfully identifies order parameters and characterizes quantum phase transitions with high precision. Our results provide a powerful tool for exploring quantum phases in systems where conventional order parameters are not readily available.
Farreras, M.; Cervera-Lierta, A.
Simulation of the 1d XY model on a quantum computer Sin publicar
Preprint, 2024.
Enlaces | BibTeX | Etiquetas: quantic
@unpublished{nokey,
title = {Simulation of the 1d XY model on a quantum computer},
author = {Farreras, M. and Cervera-Lierta, A.},
url = {https://doi.org/10.48550/arXiv.2410.21143
},
doi = {doi.org/10.48550/arXiv.2410.21143},
year = {2024},
date = {2024-10-28},
howpublished = {Preprint},
keywords = {quantic},
pubstate = {published},
tppubtype = {unpublished}
}
Fanchiotti, H.; García-Canal, C. A.; Mayosky, M.; Pérez, A.; Veiga, A.
Quantum and classical dynamics correspondence and the brachistochrone problem Artículo de revista
En: Physical Review A, vol. 110, iss. 4, 2024, ISSN: 2469-9926 .
Resumen | Enlaces | BibTeX | Etiquetas: UV
@article{nokey,
title = {Quantum and classical dynamics correspondence and the brachistochrone problem},
author = {Fanchiotti, H. and García-Canal, C.A. and Mayosky, M. and Pérez, A. and Veiga, A. },
url = {https://journals.aps.org/pra/abstract/10.1103/PhysRevA.110.042219},
doi = {doi.org/10.1103/PhysRevA.110.042219},
issn = {2469-9926 },
year = {2024},
date = {2024-10-22},
journal = {Physical Review A},
volume = {110},
issue = {4},
abstract = {The decomplexification procedure, which allows showing mathematically the isomorphism between classical and quantum dynamics of systems with a finite number of basis states, is exploited to propose resonant electric circuits with gyrator-based couplings and to experimentally study the quantum brachistochrone problem, particularly the passage time in Hermitian and parity-time-symmetric cases.},
keywords = {UV},
pubstate = {published},
tppubtype = {article}
}
The decomplexification procedure, which allows showing mathematically the isomorphism between classical and quantum dynamics of systems with a finite number of basis states, is exploited to propose resonant electric circuits with gyrator-based couplings and to experimentally study the quantum brachistochrone problem, particularly the passage time in Hermitian and parity-time-symmetric cases.
Ugo Nzongani, U.; Eon, N.; Márquez-Martín, I.; Pérez, A.; Di Molfetta, G.; Arrighi, P.
Dirac quantum walk on tetrahedra Artículo de revista
En: Physical Review A, vol. 110, iss. 4, 2024, ISSN: 2469-9926 .
Resumen | Enlaces | BibTeX | Etiquetas: UV
@article{nokey,
title = {Dirac quantum walk on tetrahedra},
author = {Ugo Nzongani, U. and Eon, N. and Márquez-Martín, I. and Pérez, A. and Di Molfetta, G. and Arrighi, P.},
url = {https://journals.aps.org/pra/abstract/10.1103/PhysRevA.110.042418},
doi = {doi.org/10.1103/PhysRevA.110.042418},
issn = {2469-9926 },
year = {2024},
date = {2024-10-16},
journal = {Physical Review A},
volume = {110},
issue = {4},
abstract = {Discrete-time quantum walks (QWs) are transportation models of single quantum particles over a lattice. Their evolution is driven through causal and local unitary operators. QWs are a powerful tool for quantum simulation of fundamental physics, as some of them have a continuum limit converging to well-known physics partial differential equations, such as the Dirac or the Schrödinger equation. In this paper, we show how to recover the Dirac equation in (3+1) dimensions with a QW evolving in a tetrahedral space. This paves the way to simulate the Dirac equation on a curved space-time. This also suggests an ordered scheme for propagating matter over a spin network, of interest in loop quantum gravity, where matter propagation has remained an open problem.},
keywords = {UV},
pubstate = {published},
tppubtype = {article}
}
Discrete-time quantum walks (QWs) are transportation models of single quantum particles over a lattice. Their evolution is driven through causal and local unitary operators. QWs are a powerful tool for quantum simulation of fundamental physics, as some of them have a continuum limit converging to well-known physics partial differential equations, such as the Dirac or the Schrödinger equation. In this paper, we show how to recover the Dirac equation in (3+1) dimensions with a QW evolving in a tetrahedral space. This paves the way to simulate the Dirac equation on a curved space-time. This also suggests an ordered scheme for propagating matter over a spin network, of interest in loop quantum gravity, where matter propagation has remained an open problem.
deMarti iOlius, A.; Fuentes, P.; Orús, R.; Crespo, P.; Etxezarreta Martinez, J.
Decoding algorithms for surface codes Artículo de revista
En: Quantum, vol. 8, pp. 1498, 2024, ISBN: 2521-327X.
Resumen | Enlaces | BibTeX | Etiquetas: tecnun
@article{nokey,
title = {Decoding algorithms for surface codes},
author = {deMarti iOlius, A. and Fuentes, P. and Orús, R. and Crespo, P. and Etxezarreta Martinez, J. },
url = {https://quantum-journal.org/papers/q-2024-10-10-1498/pdf/},
doi = {doi.org/10.22331/q-2024-10-10-1498},
isbn = {2521-327X},
year = {2024},
date = {2024-10-10},
journal = {Quantum},
volume = {8},
pages = {1498},
abstract = {Quantum technologies have the potential to solve certain computationally hard problems with polynomial or super-polynomial speedups when compared to classical methods. Unfortunately, the unstable nature of quantum information makes it prone to errors. For this reason, quantum error correction is an invaluable tool to make quantum information reliable and enable the ultimate goal of fault-tolerant quantum computing. Surface codes currently stand as the most promising candidates to build near term error corrected qubits given their two-dimensional architecture, the requirement of only local operations, and high tolerance to quantum noise. Decoding algorithms are an integral component of any error correction scheme, as they are tasked with producing accurate estimates of the errors that affect quantum information, so that they can subsequently be corrected. A critical aspect of decoding algorithms is their speed, since the quantum state will suffer additional errors with the passage of time. This poses a connundrum, where decoding performance is improved at the expense of complexity and viceversa. In this review, a thorough discussion of state-of-the-art decoding algorithms for surface codes is provided. The target audience of this work are both readers with an introductory understanding of the field as well as those seeking to further their knowledge of the decoding paradigm of surface codes. We describe the core principles of these decoding methods as well as existing variants that show promise for improved results. In addition, both the decoding performance, in terms of error correction capability, and decoding complexity, are compared. A review of the existing software tools regarding surface codes decoding is also provided.},
keywords = {tecnun},
pubstate = {published},
tppubtype = {article}
}
Quantum technologies have the potential to solve certain computationally hard problems with polynomial or super-polynomial speedups when compared to classical methods. Unfortunately, the unstable nature of quantum information makes it prone to errors. For this reason, quantum error correction is an invaluable tool to make quantum information reliable and enable the ultimate goal of fault-tolerant quantum computing. Surface codes currently stand as the most promising candidates to build near term error corrected qubits given their two-dimensional architecture, the requirement of only local operations, and high tolerance to quantum noise. Decoding algorithms are an integral component of any error correction scheme, as they are tasked with producing accurate estimates of the errors that affect quantum information, so that they can subsequently be corrected. A critical aspect of decoding algorithms is their speed, since the quantum state will suffer additional errors with the passage of time. This poses a connundrum, where decoding performance is improved at the expense of complexity and viceversa. In this review, a thorough discussion of state-of-the-art decoding algorithms for surface codes is provided. The target audience of this work are both readers with an introductory understanding of the field as well as those seeking to further their knowledge of the decoding paradigm of surface codes. We describe the core principles of these decoding methods as well as existing variants that show promise for improved results. In addition, both the decoding performance, in terms of error correction capability, and decoding complexity, are compared. A review of the existing software tools regarding surface codes decoding is also provided.
Pranav, C.; Koushik, P.; Garcia-de-Andoin, M.; Ban, Y.; Sanz, M.; Chen, X.
Photonic counterdiabatic quantum optimization algorithm Artículo de revista
En: Communications Physics, no 315, 2024, ISBN: 2399-3650.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Photonic counterdiabatic quantum optimization algorithm},
author = {Pranav, C. and Koushik, P. and Garcia-de-Andoin, M. and Ban, Y. and Sanz, M. and Chen, X.},
url = {https://www.nature.com/articles/s42005-024-01807-2.pdf},
doi = {doi.org/10.1038/s42005-024-01807-2},
isbn = {2399-3650},
year = {2024},
date = {2024-09-30},
journal = {Communications Physics},
number = {315},
abstract = {One of the key applications of near-term quantum computers has been the development of quantum optimization algorithms. However, these algorithms have largely been focused on qubit-based technologies. Here, we propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm reduces the required quantum operations for optimization compared to adiabatic protocols. This reduction enables us to tackle non-convex continuous optimization within the near-term era of quantum computing. Through illustrative benchmarking, we show that our approach can outperform existing state-of-the-art hybrid adiabatic quantum algorithms in terms of convergence and implementability. Our algorithm offers a practical and accessible experimental realization, bypassing the need for high-order operations and overcoming experimental constraints. We conduct a proof-of-principle demonstration on Xanadu’s eight-mode nanophotonic quantum chip, successfully showcasing the feasibility and potential impact of the algorithm.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
One of the key applications of near-term quantum computers has been the development of quantum optimization algorithms. However, these algorithms have largely been focused on qubit-based technologies. Here, we propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm reduces the required quantum operations for optimization compared to adiabatic protocols. This reduction enables us to tackle non-convex continuous optimization within the near-term era of quantum computing. Through illustrative benchmarking, we show that our approach can outperform existing state-of-the-art hybrid adiabatic quantum algorithms in terms of convergence and implementability. Our algorithm offers a practical and accessible experimental realization, bypassing the need for high-order operations and overcoming experimental constraints. We conduct a proof-of-principle demonstration on Xanadu’s eight-mode nanophotonic quantum chip, successfully showcasing the feasibility and potential impact of the algorithm.
Reichert, M.; Zhuang, Q.; Sanz, M.
Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation Artículo de revista
En: Physical Review Letters (PRL), vol. 133, iss. 13, 2024, ISBN: 0031-9005.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation},
author = {Reichert, M. and Zhuang, Q. and Sanz, M.
},
doi = {10.1103/PhysRevLett.133.130801},
isbn = {0031-9005},
year = {2024},
date = {2024-09-26},
journal = {Physical Review Letters (PRL)},
volume = {133},
issue = {13},
abstract = {We propose a quantum lidar protocol to jointly estimate the range and velocity of a target by illuminating it with a single beam of pulsed displaced squeezed light. In the lossless scenario, we show that the mean-squared errors of both range and velocity estimations are inversely proportional to the squared number of signal photons, simultaneously attaining the Heisenberg limit. This is achieved by engineering the multiphoton squeezed state of the temporal modes and adopting standard homodyne detection. To assess the robustness of the quantum protocol, we incorporate photon losses and detuning of the homodyne receiver. Our findings reveal a quantum advantage over the best-known classical strategy across a wide range of round-trip transmissivities. Particularly, the quantum advantage is substantial for sufficiently small losses, even when compared to the optimal—potentially unattainable—classical performance limit. The quantum advantage also extends to the practical case where quantum engineering is done on top of a strong classical coherent state with watts of power. This, together with the robustness against losses and the feasibility of the measurement with state-of-the-art technology, make the protocol highly promising for near-term implementation.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
We propose a quantum lidar protocol to jointly estimate the range and velocity of a target by illuminating it with a single beam of pulsed displaced squeezed light. In the lossless scenario, we show that the mean-squared errors of both range and velocity estimations are inversely proportional to the squared number of signal photons, simultaneously attaining the Heisenberg limit. This is achieved by engineering the multiphoton squeezed state of the temporal modes and adopting standard homodyne detection. To assess the robustness of the quantum protocol, we incorporate photon losses and detuning of the homodyne receiver. Our findings reveal a quantum advantage over the best-known classical strategy across a wide range of round-trip transmissivities. Particularly, the quantum advantage is substantial for sufficiently small losses, even when compared to the optimal—potentially unattainable—classical performance limit. The quantum advantage also extends to the practical case where quantum engineering is done on top of a strong classical coherent state with watts of power. This, together with the robustness against losses and the feasibility of the measurement with state-of-the-art technology, make the protocol highly promising for near-term implementation.
Sannia, A.; Tacchino, F.; I. Giorgi Tavernelli, G. L.; Zambrini, R.
Engineered dissipation to mitigate barren plateaus Artículo de revista
En: NPJ/Quantum Information, vol. 10, iss. 81, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: csic1
@article{nokey,
title = {Engineered dissipation to mitigate barren plateaus},
author = { Sannia, A. and Tacchino, F. and Tavernelli, I. Giorgi, G.L. and Zambrini, R.},
url = {https://www.nature.com/articles/s41534-024-00875-0#citeas},
doi = {doi.org/10.1038/s41534-024-00875-0},
year = {2024},
date = {2024-09-04},
journal = {NPJ/Quantum Information},
volume = {10},
issue = {81},
abstract = {Variational quantum algorithms represent a powerful approach for solving optimization problems on noisy quantum computers, with a broad spectrum of potential applications ranging from chemistry to machine learning. However, their performances in practical implementations crucially depend on the effectiveness of quantum circuit training, which can be severely limited by phenomena such as barren plateaus. While, in general, dissipation is detrimental for quantum algorithms, and noise itself can actually induce barren plateaus, here we describe how the inclusion of properly engineered Markovian losses after each unitary quantum circuit layer allows for the trainability of quantum models. We identify the required form of the dissipation processes and establish that their optimization is efficient. We benchmark the generality of our proposal in both a synthetic and a practical quantum chemistry example, demonstrating its effectiveness and potential impact across different domains.},
keywords = {csic1},
pubstate = {published},
tppubtype = {article}
}
Variational quantum algorithms represent a powerful approach for solving optimization problems on noisy quantum computers, with a broad spectrum of potential applications ranging from chemistry to machine learning. However, their performances in practical implementations crucially depend on the effectiveness of quantum circuit training, which can be severely limited by phenomena such as barren plateaus. While, in general, dissipation is detrimental for quantum algorithms, and noise itself can actually induce barren plateaus, here we describe how the inclusion of properly engineered Markovian losses after each unitary quantum circuit layer allows for the trainability of quantum models. We identify the required form of the dissipation processes and establish that their optimization is efficient. We benchmark the generality of our proposal in both a synthetic and a practical quantum chemistry example, demonstrating its effectiveness and potential impact across different domains.
J. and Cobos, Locher; Bermudez, A.; Müller, M.; Rico, E.
Noise-Aware Variational Eigensolvers: A Dissipative Route for Lattice Gauge Theories Artículo de revista
En: PRX Quantum, vol. 5, iss. 3, pp. 030340, 2024.
BibTeX | Etiquetas:
@article{nokey,
title = {Noise-Aware Variational Eigensolvers: A Dissipative Route for Lattice Gauge Theories},
author = {Cobos, J. and, Locher, D.F. and Bermudez, A. and Müller, M. and Rico, E. },
year = {2024},
date = {2024-08-26},
journal = {PRX Quantum},
volume = {5},
issue = {3},
pages = {030340},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cobos, J.; Locher, D. F.; Bermudez, A.; Müller, M.; Rico, E.
Noise-Aware Variational Eigensolvers: A Dissipative Route for Lattice Gauge Theories Artículo de revista
En: PRX Quantum, vol. 5, iss. 3, pp. 030340, 2024, ISSN: 2691-3399.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Noise-Aware Variational Eigensolvers: A Dissipative Route for Lattice Gauge Theories},
author = {Cobos, J. and Locher, D.F. and Bermudez, A. and Müller, M. and Rico, E. },
url = {https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.5.030340},
doi = {doi.org/10.1103/PRXQuantum.5.030340},
issn = {2691-3399},
year = {2024},
date = {2024-08-26},
urldate = {2024-08-26},
journal = {PRX Quantum},
volume = {5},
issue = {3},
pages = {030340},
abstract = {We propose a novel variational ansatz for the ground-state preparation of the lattice gauge theory (LGT) in quantum simulators. It combines dissipative and unitary operations in a completely deterministic scheme with a circuit depth that does not scale with the size of the considered lattice. We find that, with very few variational parameters, the ansatz can achieve precision in energy in both the confined and deconfined phase of the LGT. We benchmark our proposal against the unitary Hamiltonian variational ansatz showing a reduction in the required number of variational layers to achieve a target precision. After performing a finite-size scaling analysis, we show that our dissipative variational ansatz can predict accurate critical exponents without requiring a number of layers that scales with the system size, which is the standard situation for unitary ansätze. Furthermore, we investigate the performance of this variational eigensolver subject to circuit-level noise, determining variational error thresholds that fix the error rate below which it would be beneficial to increase the number of layers. In light of these quantities and for typical gate errors in current quantum processors, we provide a detailed assessment of the prospects of our scheme to explore the LGT on near-term devices.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
We propose a novel variational ansatz for the ground-state preparation of the lattice gauge theory (LGT) in quantum simulators. It combines dissipative and unitary operations in a completely deterministic scheme with a circuit depth that does not scale with the size of the considered lattice. We find that, with very few variational parameters, the ansatz can achieve precision in energy in both the confined and deconfined phase of the LGT. We benchmark our proposal against the unitary Hamiltonian variational ansatz showing a reduction in the required number of variational layers to achieve a target precision. After performing a finite-size scaling analysis, we show that our dissipative variational ansatz can predict accurate critical exponents without requiring a number of layers that scales with the system size, which is the standard situation for unitary ansätze. Furthermore, we investigate the performance of this variational eigensolver subject to circuit-level noise, determining variational error thresholds that fix the error rate below which it would be beneficial to increase the number of layers. In light of these quantities and for typical gate errors in current quantum processors, we provide a detailed assessment of the prospects of our scheme to explore the LGT on near-term devices.
Xu, T. N.; Ding, Y.; Martín-Guerrero, J. D.; Chen, X.
Robust two-qubit gate with reinforcement learning and dropout Artículo de revista
En: Physical Review A, vol. 110, iss. 3, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UV
@article{nokey,
title = {Robust two-qubit gate with reinforcement learning and dropout},
author = {Xu, T.N. and Ding, Y. and Martín-Guerrero, J.D. and Chen, X.},
url = {https://journals.aps.org/pra/abstract/10.1103/PhysRevA.110.032614},
doi = {doi.org/10.1103/PhysRevA.110.032614},
year = {2024},
date = {2024-08-13},
urldate = {2024-08-13},
journal = {Physical Review A},
volume = {110},
issue = {3},
abstract = {In the realm of quantum control, reinforcement learning, a prominent branch of machine learning, emerges as a competitive candidate for computer-assisted optimal experiment design. This paper investigates the extent to which guidance from human experts is necessary for effectively implementing reinforcement learning in the design of quantum control protocols. Specifically, our focus lies on engineering a robust two-qubit gate, utilizing a combination of analytical solutions as prior knowledge and techniques from computer science. Through thorough benchmarking of various models, we identify dropout—a widely used method for mitigating overfitting in machine learning—as a particularly robust approach. Our findings demonstrate the potential of integrating computer science concepts to propel the development of advanced quantum technologies.},
howpublished = {Preprint},
keywords = {UV},
pubstate = {published},
tppubtype = {article}
}
In the realm of quantum control, reinforcement learning, a prominent branch of machine learning, emerges as a competitive candidate for computer-assisted optimal experiment design. This paper investigates the extent to which guidance from human experts is necessary for effectively implementing reinforcement learning in the design of quantum control protocols. Specifically, our focus lies on engineering a robust two-qubit gate, utilizing a combination of analytical solutions as prior knowledge and techniques from computer science. Through thorough benchmarking of various models, we identify dropout—a widely used method for mitigating overfitting in machine learning—as a particularly robust approach. Our findings demonstrate the potential of integrating computer science concepts to propel the development of advanced quantum technologies.
Edmunds, C. L.; Rico, E.; Arrazola, I.; Brennen, G. K.; Meth, M.; Blatt, R.; Ringbauer, M.
Constructing the spin-1 Haldane phase on a qudit quantum processor Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@unpublished{nokey,
title = {Constructing the spin-1 Haldane phase on a qudit quantum processor},
author = {Edmunds, C. L. and Rico, E. and Arrazola, I. and Brennen, G. K. and Meth, M. and Blatt, R. and Ringbauer, M.},
url = {https://arxiv.org/abs/2408.04702},
doi = {doi.org/10.48550/arXiv.2408.04702},
year = {2024},
date = {2024-08-08},
abstract = {Symmetry-protected topological phases have fundamentally changed our understanding of quantum matter. An archetypal example of such a quantum phase of matter is the Haldane phase, containing the spin-1 Heisenberg chain. The intrinsic quantum nature of such phases, however, often makes it challenging to study them using classical means. Here, we use trapped-ion qutrits to natively engineer spin-1 chains within the Haldane phase. Using a scalable, deterministic procedure to prepare the Affleck-Kennedy-Lieb-Tasaki (AKLT) state within the Haldane phase, we study the topological features of this system on a qudit quantum processor. Notably, we verify the long-range string order of the state, despite its short-range correlations, and observe spin fractionalization of the physical spin-1 particles into effective qubits at the chain edges, a defining feature of this system. The native realization of Haldane physics on a qudit quantum processor and the scalable preparation procedures open the door to the efficient exploration of a wide range of systems beyond spin-1/2},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {unpublished}
}
Symmetry-protected topological phases have fundamentally changed our understanding of quantum matter. An archetypal example of such a quantum phase of matter is the Haldane phase, containing the spin-1 Heisenberg chain. The intrinsic quantum nature of such phases, however, often makes it challenging to study them using classical means. Here, we use trapped-ion qutrits to natively engineer spin-1 chains within the Haldane phase. Using a scalable, deterministic procedure to prepare the Affleck-Kennedy-Lieb-Tasaki (AKLT) state within the Haldane phase, we study the topological features of this system on a qudit quantum processor. Notably, we verify the long-range string order of the state, despite its short-range correlations, and observe spin fractionalization of the physical spin-1 particles into effective qubits at the chain edges, a defining feature of this system. The native realization of Haldane physics on a qudit quantum processor and the scalable preparation procedures open the door to the efficient exploration of a wide range of systems beyond spin-1/2
Nokkala, J.; Giorgi, G. L.; Zambrini, R.
Retrieving past quantum features with deep hybrid classical-quantum reservoir computing Artículo de revista
En: Machine Learning: Science and Technology, vol. 5, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: csic1
@article{nokey,
title = {Retrieving past quantum features with deep hybrid classical-quantum reservoir computing},
author = {Nokkala, J. and Giorgi, G.L. and Zambrini, R. },
url = {https://iopscience.iop.org/article/10.1088/2632-2153/ad5f12},
doi = {10.1088/2632-2153/ad5f12},
year = {2024},
date = {2024-07-19},
journal = {Machine Learning: Science and Technology},
volume = {5},
abstract = {Machine learning techniques have achieved impressive results in recent years and the possibility of harnessing the power of quantum physics opens new promising avenues to speed up classical learning methods. Rather than viewing classical and quantum approaches as exclusive alternatives, their integration into hybrid designs has gathered increasing interest, as seen in variational quantum algorithms, quantum circuit learning, and kernel methods. Here we introduce deep hybrid classical-quantum reservoir computing for temporal processing of quantum states where information about, for instance, the entanglement or the purity of past input states can be extracted via a single-step measurement. We find that the hybrid setup cascading two reservoirs not only inherits the strengths of both of its constituents but is even more than just the sum of its parts, outperforming comparable non-hybrid alternatives. The quantum layer is within reach of state-of-the-art multimode quantum optical platforms while the classical layer can be implemented in silico.},
keywords = {csic1},
pubstate = {published},
tppubtype = {article}
}
Machine learning techniques have achieved impressive results in recent years and the possibility of harnessing the power of quantum physics opens new promising avenues to speed up classical learning methods. Rather than viewing classical and quantum approaches as exclusive alternatives, their integration into hybrid designs has gathered increasing interest, as seen in variational quantum algorithms, quantum circuit learning, and kernel methods. Here we introduce deep hybrid classical-quantum reservoir computing for temporal processing of quantum states where information about, for instance, the entanglement or the purity of past input states can be extracted via a single-step measurement. We find that the hybrid setup cascading two reservoirs not only inherits the strengths of both of its constituents but is even more than just the sum of its parts, outperforming comparable non-hybrid alternatives. The quantum layer is within reach of state-of-the-art multimode quantum optical platforms while the classical layer can be implemented in silico.
Dastbasteh, R.; Etxezarreta Martinez, J.; A. deMarti iOlius Nemec, A. Crespo Bofill.
Infinite class of quantum codes derived from duadic constacyclic codes Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: tecnun
@unpublished{nokey,
title = {Infinite class of quantum codes derived from duadic constacyclic codes},
author = {Dastbasteh, R. and Etxezarreta Martinez, J. and Nemec, A. deMarti iOlius, A. Crespo Bofill.},
url = {https://arxiv.org/pdf/2312.06504},
doi = {doi.org/10.48550/arXiv.2312.06504},
year = {2024},
date = {2024-05-27},
abstract = {We present a family of quantum stabilizer codes using the structure of duadic constacyclic codes over F4. Within this family, quantum codes can possess varying dimensions, and their minimum distances are lower bounded by a square root bound. For each fixed dimension, this allows us to construct an infinite sequence of binary quantum codes with a growing minimum distance. Additionally, we prove that this family of quantum codes includes an infinite subclass of degenerate codes. We also introduce a technique for extending splittings of duadic constacyclic codes, providing new insights into the minimum distance and minimum odd-like weight of specific duadic constacyclic codes. Finally, we provide numerical examples of some quantum codes with short lengths within this family.},
howpublished = {Preprint},
keywords = {tecnun},
pubstate = {published},
tppubtype = {unpublished}
}
We present a family of quantum stabilizer codes using the structure of duadic constacyclic codes over F4. Within this family, quantum codes can possess varying dimensions, and their minimum distances are lower bounded by a square root bound. For each fixed dimension, this allows us to construct an infinite sequence of binary quantum codes with a growing minimum distance. Additionally, we prove that this family of quantum codes includes an infinite subclass of degenerate codes. We also introduce a technique for extending splittings of duadic constacyclic codes, providing new insights into the minimum distance and minimum odd-like weight of specific duadic constacyclic codes. Finally, we provide numerical examples of some quantum codes with short lengths within this family.
Gonzalez-Raya, T.; Pirandola, S.; Sanz, M.
Satellite-based entanglement distribution and quantum teleportation with continuous variables Artículo de revista
En: Communications Physics, vol. 7, no 126, 2024, ISBN: 2399-3650.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Satellite-based entanglement distribution and quantum teleportation with continuous variables},
author = {Gonzalez-Raya, T. and Pirandola, S. and Sanz, M. },
url = {https://www.nature.com/articles/s42005-024-01612-x.pdf},
doi = {doi.org/10.1038/s42005-024-01612-x},
isbn = {2399-3650},
year = {2024},
date = {2024-04-11},
journal = {Communications Physics},
volume = {7},
number = {126},
abstract = {Advances in satellite quantum communications aim at reshaping the global telecommunication network by increasing the security of the transferred information. Here, we study the effects of atmospheric turbulence in continuous-variable entanglement distribution and quantum teleportation in the optical regime between a ground station and a satellite. More specifically, we study the degradation of entanglement due to various error sources in the distribution, namely, diffraction, atmospheric attenuation, turbulence, and detector inefficiency, in both downlink and uplink scenarios. As the fidelity of a quantum teleportation protocol using these distributed entangled resources is not sufficient, we include an intermediate station for either state generation, or beam refocusing, in order to reduce the effects of atmospheric turbulence and diffraction, respectively. The results show the feasibility of free-space entanglement distribution and quantum teleportation in downlink paths up to the LEO region, but also in uplink paths with the help of the intermediate station. Finally, we complete the study with microwave-optical comparison in bad weather situations, and with the study of horizontal paths in ground-to-ground and inter-satellite quantum communication.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Advances in satellite quantum communications aim at reshaping the global telecommunication network by increasing the security of the transferred information. Here, we study the effects of atmospheric turbulence in continuous-variable entanglement distribution and quantum teleportation in the optical regime between a ground station and a satellite. More specifically, we study the degradation of entanglement due to various error sources in the distribution, namely, diffraction, atmospheric attenuation, turbulence, and detector inefficiency, in both downlink and uplink scenarios. As the fidelity of a quantum teleportation protocol using these distributed entangled resources is not sufficient, we include an intermediate station for either state generation, or beam refocusing, in order to reduce the effects of atmospheric turbulence and diffraction, respectively. The results show the feasibility of free-space entanglement distribution and quantum teleportation in downlink paths up to the LEO region, but also in uplink paths with the help of the intermediate station. Finally, we complete the study with microwave-optical comparison in bad weather situations, and with the study of horizontal paths in ground-to-ground and inter-satellite quantum communication.
Martínez-Peña, R.; Soriano, M. C.; Zambrini, R.
Quantum fidelity kernel with a trapped-ion simulation platform Artículo de revista
En: Physical Review A, vol. 109, iss. 4, 2024, ISSN: 2469-9926.
Resumen | Enlaces | BibTeX | Etiquetas: csic1
@article{nokey,
title = {Quantum fidelity kernel with a trapped-ion simulation platform},
author = {Martínez-Peña, R. and Soriano, M.C. and Zambrini, R.
},
url = {https://journals.aps.org/pra/abstract/10.1103/PhysRevA.109.042612},
doi = {10.1103/PhysRevA.109.042612},
issn = {2469-9926},
year = {2024},
date = {2024-04-08},
urldate = {2024-04-08},
journal = {Physical Review A},
volume = {109},
issue = {4},
abstract = {Quantum kernel methods leverage a kernel function computed by embedding input information into the Hilbert space of a quantum system. However, large Hilbert spaces can hinder generalization capability, and the scalability of quantum kernels becomes an issue. To overcome these challenges, various strategies under the concept of inductive bias have been proposed. Bandwidth optimization is a promising approach that can be implemented using quantum simulation platforms. We propose trapped-ion simulation platforms as a means to compute quantum kernels, filling a gap in the previous literature and demonstrating their effectiveness for binary classification tasks. We compare the performance of the proposed method with an optimized classical kernel and evaluate the robustness of the quantum kernel against noise. The results show that ion trap platforms are well-suited for quantum kernel computation and can achieve high accuracy with only a few qubits.},
keywords = {csic1},
pubstate = {published},
tppubtype = {article}
}
Quantum kernel methods leverage a kernel function computed by embedding input information into the Hilbert space of a quantum system. However, large Hilbert spaces can hinder generalization capability, and the scalability of quantum kernels becomes an issue. To overcome these challenges, various strategies under the concept of inductive bias have been proposed. Bandwidth optimization is a promising approach that can be implemented using quantum simulation platforms. We propose trapped-ion simulation platforms as a means to compute quantum kernels, filling a gap in the previous literature and demonstrating their effectiveness for binary classification tasks. We compare the performance of the proposed method with an optimized classical kernel and evaluate the robustness of the quantum kernel against noise. The results show that ion trap platforms are well-suited for quantum kernel computation and can achieve high accuracy with only a few qubits.
Gonzalez-Conde, J.; Watts, T. W.; Rodriguez-Grasa, P.; Sanz, M.
Efficient quantum amplitude encoding of polynomial functions Artículo de revista
En: Quantum, vol. 8, pp. 1297, 2024, ISBN: 2521-327X.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Efficient quantum amplitude encoding of polynomial functions},
author = {Gonzalez-Conde, J. and Watts, T.W. and Rodriguez-Grasa, P. and Sanz, M.},
url = {https://quantum-journal.org/papers/q-2024-03-21-1297/},
doi = {doi.org/10.22331/q-2024-03-21-1297},
isbn = {2521-327X},
year = {2024},
date = {2024-03-21},
urldate = {2024-03-21},
journal = {Quantum},
volume = {8},
pages = {1297},
abstract = {Loading functions into quantum computers represents an essential step in several quantum algorithms, such as quantum partial differential equation solvers. Therefore, the inefficiency of this process leads to a major bottleneck for the application of these algorithms. Here, we present and compare two efficient methods for the amplitude encoding of real polynomial functions on n qubits. This case holds special relevance, as any continuous function on a closed interval can be uniformly approximated with arbitrary precision by a polynomial function. The first approach relies on the matrix product state representation. We study and benchmark the approximations of the target state when the bond dimension is assumed to be small. The second algorithm combines two subroutines. Initially we encode the linear function into the quantum registers with a shallow sequence of multi-controlled gates that loads the linear function's Hadamard-Walsh series, exploring how truncating the Hadamard-Walsh series of the linear function affects the final fidelity. Applying the inverse discrete Hadamard-Walsh transform transforms the series coefficients into an amplitude encoding of the linear function. Then, we use this construction as a building block to achieve a block encoding of the amplitudes corresponding to the linear function on k0 qubits and apply the quantum singular value transformation that implements a polynomial transformation to the block encoding of the amplitudes. This unitary together with the Amplitude Amplification algorithm will enable us to prepare the quantum state that encodes the polynomial function on k0 qubits. Finally we pad n−k0 qubits to generate an approximated encoding of the polynomial on n qubits, analyzing the error depending on k0. In this regard, our methodology proposes a method to improve the state-of-the-art complexity by introducing controllable errors.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Loading functions into quantum computers represents an essential step in several quantum algorithms, such as quantum partial differential equation solvers. Therefore, the inefficiency of this process leads to a major bottleneck for the application of these algorithms. Here, we present and compare two efficient methods for the amplitude encoding of real polynomial functions on n qubits. This case holds special relevance, as any continuous function on a closed interval can be uniformly approximated with arbitrary precision by a polynomial function. The first approach relies on the matrix product state representation. We study and benchmark the approximations of the target state when the bond dimension is assumed to be small. The second algorithm combines two subroutines. Initially we encode the linear function into the quantum registers with a shallow sequence of multi-controlled gates that loads the linear function's Hadamard-Walsh series, exploring how truncating the Hadamard-Walsh series of the linear function affects the final fidelity. Applying the inverse discrete Hadamard-Walsh transform transforms the series coefficients into an amplitude encoding of the linear function. Then, we use this construction as a building block to achieve a block encoding of the amplitudes corresponding to the linear function on k0 qubits and apply the quantum singular value transformation that implements a polynomial transformation to the block encoding of the amplitudes. This unitary together with the Amplitude Amplification algorithm will enable us to prepare the quantum state that encodes the polynomial function on k0 qubits. Finally we pad n−k0 qubits to generate an approximated encoding of the polynomial on n qubits, analyzing the error depending on k0. In this regard, our methodology proposes a method to improve the state-of-the-art complexity by introducing controllable errors.
Garcia-de-Andoin, M.; Saiz, A.; Perez-Fernandez, P.; Lamata, L.; Oregi, I.; Sanz, M.
Digital-analog quantum computation with arbitrary two-body Hamiltonians Artículo de revista
En: Physical Review Research, vol. 6, iss. 1, 2024, ISBN: 2643-1564.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Digital-analog quantum computation with arbitrary two-body Hamiltonians},
author = {Garcia-de-Andoin, M. and Saiz, A. and Perez-Fernandez, P. and Lamata, L. and Oregi, I. and Sanz, M. },
url = {https://journals.aps.org/prresearch/pdf/10.1103/PhysRevResearch.6.013280},
doi = {doi.org/10.1103/PhysRevResearch.6.013280},
isbn = {2643-1564},
year = {2024},
date = {2024-03-14},
urldate = {2024-03-14},
journal = {Physical Review Research},
volume = {6},
issue = {1},
abstract = {Digital-analog quantum computing is a computational paradigm which employs an analog Hamiltonian resource together with single-qubit gates to reach universality. Here, we design a new scheme which employs an arbitrary two-body source Hamiltonian, extending the experimental applicability of this computational paradigm to most quantum platforms. We show that the simulation of an arbitrary two-body target Hamiltonian of 𝑛 qubits requires 𝒪(𝑛2) analog blocks with guaranteed positive times, providing a polynomial advantage compared to the previous scheme. Additionally, we propose a classical strategy which combines a Bayesian optimization with a gradient descent method, improving the performance by ∼55% for small systems measured in the Frobenius norm.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Digital-analog quantum computing is a computational paradigm which employs an analog Hamiltonian resource together with single-qubit gates to reach universality. Here, we design a new scheme which employs an arbitrary two-body source Hamiltonian, extending the experimental applicability of this computational paradigm to most quantum platforms. We show that the simulation of an arbitrary two-body target Hamiltonian of 𝑛 qubits requires 𝒪(𝑛2) analog blocks with guaranteed positive times, providing a polynomial advantage compared to the previous scheme. Additionally, we propose a classical strategy which combines a Bayesian optimization with a gradient descent method, improving the performance by ∼55% for small systems measured in the Frobenius norm.
Labay-Mora, A.; Zambrini, R.; Giorgi, G. L.
Quantum memories for squeezed and coherent superpositions in a driven-dissipative nonlinear oscillator Artículo de revista
En: Physical Review A, vol. 109, iss. 3, 2024, ISSN: 2469-9926.
Resumen | Enlaces | BibTeX | Etiquetas: csic1
@article{nokey,
title = {Quantum memories for squeezed and coherent superpositions in a driven-dissipative nonlinear oscillator},
author = {Labay-Mora, A. and Zambrini, R. and Giorgi, G.L.
},
url = {https://journals.aps.org/pra/abstract/10.1103/PhysRevA.109.032407},
doi = {doi.org/10.1103/PhysRevA.109.032407},
issn = {2469-9926},
year = {2024},
date = {2024-03-08},
journal = {Physical Review A},
volume = {109},
issue = {3},
abstract = {Quantum oscillators with nonlinear driving and dissipative terms have gained significant attention due to their ability to stabilize cat states for universal quantum computation. Recently, superconducting circuits have been employed to realize such long-lived qubits stored in coherent states. We present a generalization of these oscillators, which are not limited to coherent states. The key ingredient lies in the presence of different nonlinearities in driving and dissipation, beyond the quadratic one. Through an extensive analysis of the asymptotic dynamical features for different nonlinearities, we identify the conditions for the storage and retrieval of quantum states, such as squeezed states, in both coherent and incoherent superpositions. We explore their applications in quantum computing, where squeezing prolongs the lifetime of memory storage for qubits encoded in the superposition of two symmetric squeezed states, and in quantum associative memory, which has so far been limited to the storage of classical patterns.},
keywords = {csic1},
pubstate = {published},
tppubtype = {article}
}
Quantum oscillators with nonlinear driving and dissipative terms have gained significant attention due to their ability to stabilize cat states for universal quantum computation. Recently, superconducting circuits have been employed to realize such long-lived qubits stored in coherent states. We present a generalization of these oscillators, which are not limited to coherent states. The key ingredient lies in the presence of different nonlinearities in driving and dissipation, beyond the quadratic one. Through an extensive analysis of the asymptotic dynamical features for different nonlinearities, we identify the conditions for the storage and retrieval of quantum states, such as squeezed states, in both coherent and incoherent superpositions. We explore their applications in quantum computing, where squeezing prolongs the lifetime of memory storage for qubits encoded in the superposition of two symmetric squeezed states, and in quantum associative memory, which has so far been limited to the storage of classical patterns.
Lugilde, G.; Combarro, E. F.; Rúa, I. F.
Functional quantum abstract detecting systems Artículo de revista
En: Quantum Information Processing, vol. 23, no 82, 2024, ISBN: 1570-0755.
Resumen | Enlaces | BibTeX | Etiquetas: UNIOVI
@article{nokey,
title = {Functional quantum abstract detecting systems},
author = {Lugilde, G. and Combarro, E.F. and Rúa, I.F.},
url = {https://link.springer.com/content/pdf/10.1007/s11128-024-04273-5.pdf},
doi = {doi.org/10.1007/s11128-024-04273-5},
isbn = {1570-0755},
year = {2024},
date = {2024-02-28},
journal = {Quantum Information Processing},
volume = {23},
number = {82},
abstract = {Quantum abstract detecting systems (QADS) provide a common framework to address detection problems in quantum computers. A particular QADS family, that of combinatorial QADS, has been proved to be useful for decision problems on eigenvalues or phase estimation methods. In this paper, we consider functional QADS, which not only have interesting theoretical properties (intrinsic detection ability, relation to the QFT), but also yield improved decision and phase estimation methods, as compared to combinatorial QADS. A first insight into the comparison with other phase estimation methods also shows promising results.},
keywords = {UNIOVI},
pubstate = {published},
tppubtype = {article}
}
Quantum abstract detecting systems (QADS) provide a common framework to address detection problems in quantum computers. A particular QADS family, that of combinatorial QADS, has been proved to be useful for decision problems on eigenvalues or phase estimation methods. In this paper, we consider functional QADS, which not only have interesting theoretical properties (intrinsic detection ability, relation to the QFT), but also yield improved decision and phase estimation methods, as compared to combinatorial QADS. A first insight into the comparison with other phase estimation methods also shows promising results.
Schenk, M.; Combarro, E. F.; Grossi, M.; Kain, V.; Shing-Brice, K.; Popa, M. M.; Vallecorsa, S.
Hybrid actor-critic algorithm for quantum reinforcement learning at CERN beam lines Artículo de revista
En: Quantum Science and Technology, vol. 9, 2024, ISBN: 2058-9565.
Resumen | Enlaces | BibTeX | Etiquetas:
@article{nokey,
title = {Hybrid actor-critic algorithm for quantum reinforcement learning at CERN beam lines},
author = {Schenk,M. and Combarro, E.F. and Grossi, M. and Kain, V. and Shing-Brice, K. and Popa, M.M. and Vallecorsa, S.},
url = {https://iopscience.iop.org/article/10.1088/2058-9565/ad261b},
doi = {10.1088/2058-9565/ad261b},
isbn = {2058-9565},
year = {2024},
date = {2024-02-21},
urldate = {2024-02-21},
journal = {Quantum Science and Technology},
volume = {9},
abstract = {Free energy-based reinforcement learning (FERL) with clamped quantum Boltzmann machines (QBM) was shown to significantly improve the learning efficiency compared to classical Q-learning with the restriction, however, to discrete state-action space environments. In this paper, the FERL approach is extended to multi-dimensional continuous state-action space environments to open the doors for a broader range of real-world applications. First, free energy-based Q-learning is studied for discrete action spaces, but continuous state spaces and the impact of experience replay on sample efficiency is assessed. In a second step, a hybrid actor-critic (A-C) scheme for continuous state-action spaces is developed based on the deep deterministic policy gradient algorithm combining a classical actor network with a QBM-based critic. The results obtained with quantum annealing (QA), both simulated and with D-Wave QA hardware, are discussed, and the performance is compared to classical reinforcement learning methods. The environments used throughout represent existing particle accelerator beam lines at the European Organisation for Nuclear Research. Among others, the hybrid A-C agent is evaluated on the actual electron beam line of the Advanced Wakefield Experiment (AWAKE).},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Free energy-based reinforcement learning (FERL) with clamped quantum Boltzmann machines (QBM) was shown to significantly improve the learning efficiency compared to classical Q-learning with the restriction, however, to discrete state-action space environments. In this paper, the FERL approach is extended to multi-dimensional continuous state-action space environments to open the doors for a broader range of real-world applications. First, free energy-based Q-learning is studied for discrete action spaces, but continuous state spaces and the impact of experience replay on sample efficiency is assessed. In a second step, a hybrid actor-critic (A-C) scheme for continuous state-action spaces is developed based on the deep deterministic policy gradient algorithm combining a classical actor network with a QBM-based critic. The results obtained with quantum annealing (QA), both simulated and with D-Wave QA hardware, are discussed, and the performance is compared to classical reinforcement learning methods. The environments used throughout represent existing particle accelerator beam lines at the European Organisation for Nuclear Research. Among others, the hybrid A-C agent is evaluated on the actual electron beam line of the Advanced Wakefield Experiment (AWAKE).
Sannia, A.; Martínez-Peña, R.; Soriano, M. C.; G.L Giorgi,; Zambrini, R.
Dissipation as a resource for Quantum Reservoir Computing Artículo de revista
En: Quantum, vol. 8, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: uib
@article{nokey,
title = {Dissipation as a resource for Quantum Reservoir Computing},
author = {Sannia, A. and Martínez-Peña, R. and Soriano, M.C. and Giorgi, G.L, and Zambrini, R. },
url = {https://quantum-journal.org/papers/q-2024-03-20-1291/},
doi = {doi.org/10.22331/q-2024-03-20-1291},
year = {2024},
date = {2024-02-20},
journal = {Quantum},
volume = {8},
abstract = {Dissipation induced by interactions with an external environment typically hinders the performance of quantum computation, but in some cases can be turned out as a useful resource. We show the potential enhancement induced by dissipation in the field of quantum reservoir computing introducing tunable local losses in spin network models. Our approach based on continuous dissipation is able not only to reproduce the dynamics of previous proposals of quantum reservoir computing, based on discontinuous erasing maps but also to enhance their performance. Control of the damping rates is shown to boost popular machine learning temporal tasks as the capability to linearly and non-linearly process the input history and to forecast chaotic series. Finally, we formally prove that, under non-restrictive conditions, our dissipative models form a universal class for reservoir computing. It means that considering our approach, it is possible to approximate any fading memory map with arbitrary precision.},
howpublished = {Preprint},
keywords = {uib},
pubstate = {published},
tppubtype = {article}
}
Dissipation induced by interactions with an external environment typically hinders the performance of quantum computation, but in some cases can be turned out as a useful resource. We show the potential enhancement induced by dissipation in the field of quantum reservoir computing introducing tunable local losses in spin network models. Our approach based on continuous dissipation is able not only to reproduce the dynamics of previous proposals of quantum reservoir computing, based on discontinuous erasing maps but also to enhance their performance. Control of the damping rates is shown to boost popular machine learning temporal tasks as the capability to linearly and non-linearly process the input history and to forecast chaotic series. Finally, we formally prove that, under non-restrictive conditions, our dissipative models form a universal class for reservoir computing. It means that considering our approach, it is possible to approximate any fading memory map with arbitrary precision.
Orts, F.; Ortega, G.; Combarro, E. F.; Rúa, I. F.; Garzón, E. M.
Quantum circuits for computing Hamming distance requiring fewer T gates Artículo de revista
En: The Journal of Supercomputing , vol. 80, pp. 12527–12542, 2024, ISBN: 0920-8542.
Resumen | Enlaces | BibTeX | Etiquetas:
@article{nokey,
title = {Quantum circuits for computing Hamming distance requiring fewer T gates},
author = {Orts, F. and Ortega, G. and Combarro, E.F. and Rúa, I.F. and Garzón, E.M. },
url = {https://link.springer.com/article/10.1007/s11227-024-05916-1},
doi = {doi.org/10.1007/s11227-024-05916-1},
isbn = {0920-8542},
year = {2024},
date = {2024-02-16},
journal = {The Journal of Supercomputing },
volume = {80},
pages = {12527–12542},
abstract = {The so-called Hamming distance measures the difference between two binary strings A and B. In simplified form, it measures the number of changes in A to get B. This type of distance is very useful in classical computing in applications such as error correction. It is also advantageous in quantum computing, being for example widely used in quantum machine learning. Since current quantum computers have limited resources, this type of distance is particularly attractive because it can be computed using fewer qubits and operations than other distances such as Euclidean or Manhattan distances. In this paper, two circuits for calculating Hamming distances using exclusively Clifford+T gates are presented. The aim of both circuits is to reduce the quantum cost and number of T gates needed to compute the Hamming distance. The T gate is more expensive than the other gates, so this reduction will have a significant impact on the total cost of the circuits. Furthermore, the proposed circuits are implemented using only Clifford+T gates. The circuits implemented exclusively with this group of gates are compatible with proven error detection and correction codes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The so-called Hamming distance measures the difference between two binary strings A and B. In simplified form, it measures the number of changes in A to get B. This type of distance is very useful in classical computing in applications such as error correction. It is also advantageous in quantum computing, being for example widely used in quantum machine learning. Since current quantum computers have limited resources, this type of distance is particularly attractive because it can be computed using fewer qubits and operations than other distances such as Euclidean or Manhattan distances. In this paper, two circuits for calculating Hamming distances using exclusively Clifford+T gates are presented. The aim of both circuits is to reduce the quantum cost and number of T gates needed to compute the Hamming distance. The T gate is more expensive than the other gates, so this reduction will have a significant impact on the total cost of the circuits. Furthermore, the proposed circuits are implemented using only Clifford+T gates. The circuits implemented exclusively with this group of gates are compatible with proven error detection and correction codes.
Cea, M.; Grossi, M.; Monaco, S.; Rico, E.; Tagliacozzo, L.; Vallecorsa, S.
Exploring the Phase Diagram of the quantum one-dimensional ANNNI model Sin publicar
Preprint, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@unpublished{nokey,
title = {Exploring the Phase Diagram of the quantum one-dimensional ANNNI model},
author = {Cea, M. and Grossi, M. and Monaco, S. and Rico, E. and Tagliacozzo, L. and Vallecorsa, S. },
url = {https://arxiv.org/abs/2402.11022},
doi = {doi.org/10.48550/arXiv.2402.11022},
year = {2024},
date = {2024-02-16},
abstract = {In this manuscript, we explore the intersection of QML and TN in the context of the one-dimensional ANNNI model with a transverse field. The study aims to concretely connect QML and TN by combining them in various stages of algorithm construction, focusing on phase diagram reconstruction for the ANNNI model, with supervised and unsupervised techniques. The model's significance lies in its representation of quantum fluctuations and frustrated exchange interactions, making it a paradigm for studying magnetic ordering, frustration, and the presence of a floating phase. It concludes with discussions of the results, including insights from increased system sizes and considerations for future work, such as addressing limitations in QCNN and exploring more realistic implementations of QC.},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {unpublished}
}
In this manuscript, we explore the intersection of QML and TN in the context of the one-dimensional ANNNI model with a transverse field. The study aims to concretely connect QML and TN by combining them in various stages of algorithm construction, focusing on phase diagram reconstruction for the ANNNI model, with supervised and unsupervised techniques. The model's significance lies in its representation of quantum fluctuations and frustrated exchange interactions, making it a paradigm for studying magnetic ordering, frustration, and the presence of a floating phase. It concludes with discussions of the results, including insights from increased system sizes and considerations for future work, such as addressing limitations in QCNN and exploring more realistic implementations of QC.
Combarro, E. F.; Rúa, I. F.; Ortega, O. G.; Puertas, A. M.; Garzón, E. M.
Quantum algorithms to compute the neighbour list of N-body simulations Artículo de revista
En: Quantum Information Processing, vol. 23, no 61, 2024, ISBN: 1570-0755.
Resumen | Enlaces | BibTeX | Etiquetas: UNIOVI
@article{nokey,
title = {Quantum algorithms to compute the neighbour list of N-body simulations},
author = {Combarro, E.F. and Rúa, I.F. and Ortega, O.G. and Puertas, A.M. and Garzón, E.M. },
url = {https://link.springer.com/article/10.1007/s11128-023-04245-1},
doi = {doi.org/10.1007/s11128-023-04245-1},
isbn = {1570-0755},
year = {2024},
date = {2024-02-13},
journal = {Quantum Information Processing},
volume = {23},
number = {61},
abstract = {One of the strategies to reduce the complexity of N-body simulations is the computation of the neighbour list. However, this list needs to be updated from time to time, with a high computational cost. This paper focuses on the use of quantum computing to accelerate such a computation. Our proposal is based on a well-known oracular quantum algorithm (Grover). We introduce an efficient quantum circuit to build the oracle that marks pairs of closed bodies, and we provide three novel algorithms to calculate the neighbour list under several hypotheses which take into account a-priori information of the system. We also describe a decision methodology for the actual use of the proposed quantum algorithms. The performance of the algorithms is tested with a statistical simulation of the oracle, where a fixed number of pairs of bodies are set as neighbours. A statistical analysis of the number of oracle queries is carried out. The results obtained with our simulations indicate that when the density of bodies is low, our algorithms clearly outperform the best classical algorithm in terms of oracle queries.},
keywords = {UNIOVI},
pubstate = {published},
tppubtype = {article}
}
One of the strategies to reduce the complexity of N-body simulations is the computation of the neighbour list. However, this list needs to be updated from time to time, with a high computational cost. This paper focuses on the use of quantum computing to accelerate such a computation. Our proposal is based on a well-known oracular quantum algorithm (Grover). We introduce an efficient quantum circuit to build the oracle that marks pairs of closed bodies, and we provide three novel algorithms to calculate the neighbour list under several hypotheses which take into account a-priori information of the system. We also describe a decision methodology for the actual use of the proposed quantum algorithms. The performance of the algorithms is tested with a statistical simulation of the oracle, where a fixed number of pairs of bodies are set as neighbours. A statistical analysis of the number of oracle queries is carried out. The results obtained with our simulations indicate that when the density of bodies is low, our algorithms clearly outperform the best classical algorithm in terms of oracle queries.
García-Beni, J.; Giorgi, G. L.; Soriano, M. C.; Zambrini, R.
Squeezing as a resource for time series processing in quantum reservoir computing Artículo de revista
En: Optics Express, vol. 32, iss. 4, pp. 6733-6747, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: csic1
@article{nokey,
title = {Squeezing as a resource for time series processing in quantum reservoir computing},
author = {García-Beni, J. and Giorgi, G.L. and Soriano, M.C. and Zambrini, R.},
url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-4-6733&id=546462},
doi = {doi.org/10.1364/OE.507684},
year = {2024},
date = {2024-02-09},
journal = {Optics Express},
volume = {32},
issue = {4},
pages = { 6733-6747},
abstract = {Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time-series processing. In particular, we consider a loop-based photonic architecture for reservoir computing and address the effect of squeezing in the reservoir, considering a Hamiltonian with both active and passive coupling terms. Interestingly, squeezing can be either detrimental or beneficial for quantum reservoir computing when moving from ideal to realistic models, accounting for experimental noise. We demonstrate that multimode squeezing enhances its accessible memory, which improves the performance in several benchmark temporal tasks. The origin of this improvement is traced back to the robustness of the reservoir to readout noise, which is increased with squeezing.},
keywords = {csic1},
pubstate = {published},
tppubtype = {article}
}
Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time-series processing. In particular, we consider a loop-based photonic architecture for reservoir computing and address the effect of squeezing in the reservoir, considering a Hamiltonian with both active and passive coupling terms. Interestingly, squeezing can be either detrimental or beneficial for quantum reservoir computing when moving from ideal to realistic models, accounting for experimental noise. We demonstrate that multimode squeezing enhances its accessible memory, which improves the performance in several benchmark temporal tasks. The origin of this improvement is traced back to the robustness of the reservoir to readout noise, which is increased with squeezing.
García-Beni, J.; Giorgi, G. L.; Soriano, M. C.; Zambrini, R.
Squeezing as a resource for time series processing in quantum reservoir computing Artículo de revista
En: Optics Express, vol. 32, iss. 4, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: uib
@article{nokey,
title = {Squeezing as a resource for time series processing in quantum reservoir computing},
author = {García-Beni, J. and Giorgi, G.L. and Soriano, M.C. and Zambrini, R.},
url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-4-6733&id=546462},
doi = {doi.org/10.1364/OE.507684},
year = {2024},
date = {2024-02-09},
journal = {Optics Express},
volume = {32},
issue = {4},
abstract = {Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time-series processing. In particular, we consider a loop-based photonic architecture for reservoir computing and address the effect of squeezing in the reservoir, considering a Hamiltonian with both active and passive coupling terms. Interestingly, squeezing can be either detrimental or beneficial for quantum reservoir computing when moving from ideal to realistic models, accounting for experimental noise. We demonstrate that multimode squeezing enhances its accessible memory, which improves the performance in several benchmark temporal tasks. The origin of this improvement is traced back to the robustness of the reservoir to readout noise, which is increased with squeezing.},
keywords = {uib},
pubstate = {published},
tppubtype = {article}
}
Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time-series processing. In particular, we consider a loop-based photonic architecture for reservoir computing and address the effect of squeezing in the reservoir, considering a Hamiltonian with both active and passive coupling terms. Interestingly, squeezing can be either detrimental or beneficial for quantum reservoir computing when moving from ideal to realistic models, accounting for experimental noise. We demonstrate that multimode squeezing enhances its accessible memory, which improves the performance in several benchmark temporal tasks. The origin of this improvement is traced back to the robustness of the reservoir to readout noise, which is increased with squeezing.
García-Beni, J.; Giorgi, G. L.; Soriano, M. C.; Zambrini, R.
Squeezing as a resource for time series processing in quantum reservoir computing Artículo de revista
En: Optics Express, vol. 32, iss. 4, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: uib
@article{nokey,
title = {Squeezing as a resource for time series processing in quantum reservoir computing},
author = {García-Beni, J. and Giorgi, G.L. and Soriano, M.C. and Zambrini, R. },
url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-4-6733&id=546462},
doi = {doi.org/10.1364/OE.507684},
year = {2024},
date = {2024-02-09},
urldate = {2024-02-09},
journal = {Optics Express},
volume = {32},
issue = {4},
abstract = {Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time-series processing. In particular, we consider a loop-based photonic architecture for reservoir computing and address the effect of squeezing in the reservoir, considering a Hamiltonian with both active and passive coupling terms. Interestingly, squeezing can be either detrimental or beneficial for quantum reservoir computing when moving from ideal to realistic models, accounting for experimental noise. We demonstrate that multimode squeezing enhances its accessible memory, which improves the performance in several benchmark temporal tasks. The origin of this improvement is traced back to the robustness of the reservoir to readout noise, which is increased with squeezing.},
keywords = {uib},
pubstate = {published},
tppubtype = {article}
}
Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time-series processing. In particular, we consider a loop-based photonic architecture for reservoir computing and address the effect of squeezing in the reservoir, considering a Hamiltonian with both active and passive coupling terms. Interestingly, squeezing can be either detrimental or beneficial for quantum reservoir computing when moving from ideal to realistic models, accounting for experimental noise. We demonstrate that multimode squeezing enhances its accessible memory, which improves the performance in several benchmark temporal tasks. The origin of this improvement is traced back to the robustness of the reservoir to readout noise, which is increased with squeezing.
Xu, R.; Tang, J.; Chandarana, P.; Paul, K.; Xu, X.; Yung, M.; Chen, X.
Benchmarking hybrid digitized-counterdiabatic quantum optimization Artículo de revista
En: Physical Review Research, vol. 6, iss. 1, 2024, ISBN: 2643-1564.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Benchmarking hybrid digitized-counterdiabatic quantum optimization},
author = {Xu, R. and Tang, J. and Chandarana, P. and Paul, K. and Xu, X. and Yung, M. and Chen, X. },
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.6.013147},
doi = {doi.org/10.1103/PhysRevResearch.6.013147},
isbn = {2643-1564},
year = {2024},
date = {2024-02-07},
journal = {Physical Review Research},
volume = {6},
issue = {1},
abstract = {Hybrid digitized-counterdiabatic quantum computing (DCQC) is a promising approach for leveraging the capabilities of nearterm quantum computers, utilizing parameterized quantum circuits designed with counterdiabatic protocols. However, the classical aspect of this approach has received limited attention. In this study, we systematically analyze the convergence behavior and solution quality of various classical optimizers when used in conjunction with the digitized-counterdiabatic approach. We demonstrate the effectiveness of this hybrid algorithm by comparing its performance to the traditional QAOA on systems containing up to 28 qubits. Furthermore, we employ principal component analysis to investigate the cost landscape and explore the crucial influence of parametrization on the performance of the counterdiabatic ansatz. Our findings indicate that fewer iterations are required when local cost landscape minima are present, and the SPSA-based BFGS optimizer emerges as a standout choice for the hybrid DCQC paradigm.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Hybrid digitized-counterdiabatic quantum computing (DCQC) is a promising approach for leveraging the capabilities of nearterm quantum computers, utilizing parameterized quantum circuits designed with counterdiabatic protocols. However, the classical aspect of this approach has received limited attention. In this study, we systematically analyze the convergence behavior and solution quality of various classical optimizers when used in conjunction with the digitized-counterdiabatic approach. We demonstrate the effectiveness of this hybrid algorithm by comparing its performance to the traditional QAOA on systems containing up to 28 qubits. Furthermore, we employ principal component analysis to investigate the cost landscape and explore the crucial influence of parametrization on the performance of the counterdiabatic ansatz. Our findings indicate that fewer iterations are required when local cost landscape minima are present, and the SPSA-based BFGS optimizer emerges as a standout choice for the hybrid DCQC paradigm.
Xu, R.; Tang, J.; Chandarana, P.; Paul, K.; Xu, X.; Yung, M.; Chen, X.
Benchmarking hybrid digitized-counterdiabatic quantum optimization Artículo de revista
En: Physical Review Research, vol. 6, iss. 1, 2024, ISBN: 2643-1564.
Resumen | Enlaces | BibTeX | Etiquetas: UPV/EHU
@article{nokey,
title = {Benchmarking hybrid digitized-counterdiabatic quantum optimization},
author = {Xu, R. and Tang, J. and Chandarana, P. and Paul, K. and Xu, X. and Yung, M. and Chen, X. },
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.6.013147},
doi = {doi.org/10.1103/PhysRevResearch.6.013147},
isbn = {2643-1564},
year = {2024},
date = {2024-02-07},
journal = {Physical Review Research},
volume = {6},
issue = {1},
abstract = {Hybrid digitized-counterdiabatic quantum computing (DCQC) is a promising approach for leveraging the capabilities of nearterm quantum computers, utilizing parameterized quantum circuits designed with counterdiabatic protocols. However, the classical aspect of this approach has received limited attention. In this study, we systematically analyze the convergence behavior and solution quality of various classical optimizers when used in conjunction with the digitized-counterdiabatic approach. We demonstrate the effectiveness of this hybrid algorithm by comparing its performance to the traditional QAOA on systems containing up to 28 qubits. Furthermore, we employ principal component analysis to investigate the cost landscape and explore the crucial influence of parametrization on the performance of the counterdiabatic ansatz. Our findings indicate that fewer iterations are required when local cost landscape minima are present, and the SPSA-based BFGS optimizer emerges as a standout choice for the hybrid DCQC paradigm.
},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Hybrid digitized-counterdiabatic quantum computing (DCQC) is a promising approach for leveraging the capabilities of nearterm quantum computers, utilizing parameterized quantum circuits designed with counterdiabatic protocols. However, the classical aspect of this approach has received limited attention. In this study, we systematically analyze the convergence behavior and solution quality of various classical optimizers when used in conjunction with the digitized-counterdiabatic approach. We demonstrate the effectiveness of this hybrid algorithm by comparing its performance to the traditional QAOA on systems containing up to 28 qubits. Furthermore, we employ principal component analysis to investigate the cost landscape and explore the crucial influence of parametrization on the performance of the counterdiabatic ansatz. Our findings indicate that fewer iterations are required when local cost landscape minima are present, and the SPSA-based BFGS optimizer emerges as a standout choice for the hybrid DCQC paradigm.
Anglés-Castillo, A.; Pérez, A.; Roldán, E.
Bright and dark solitons in a photonic nonlinear quantum walk: lessons from the continuum Artículo de revista
En: New Journal of Physics, vol. 26, 2024.
Resumen | Enlaces | BibTeX | Etiquetas: UV
@article{nokey,
title = {Bright and dark solitons in a photonic nonlinear quantum walk: lessons from the continuum},
author = {Anglés-Castillo, A. and Pérez, A. and Roldán, E. },
url = {https://iopscience.iop.org/article/10.1088/1367-2630/ad1e24},
doi = {10.1088/1367-2630/ad1e24},
year = {2024},
date = {2024-02-05},
journal = {New Journal of Physics},
volume = {26},
abstract = {We propose a nonlinear quantum walk model inspired in a photonic implementation in which the polarization state of the light field plays the role of the coin-qubit. In particular, we take profit of the nonlinear polarization rotation occurring in optical media with Kerr nonlinearity, which allows to implement a nonlinear coin operator, one that depends on the state of the coin-qubit. We consider the space-time continuum limit of the evolution equation, which takes the form of a nonlinear Dirac equation. The analysis of this continuum limit allows us to gain some insight into the existence of different solitonic structures, such as bright and dark solitons. We illustrate several properties of these solitons with numerical calculations, including the effect on them of an additional phase simulating an external electric field.},
keywords = {UV},
pubstate = {published},
tppubtype = {article}
}
We propose a nonlinear quantum walk model inspired in a photonic implementation in which the polarization state of the light field plays the role of the coin-qubit. In particular, we take profit of the nonlinear polarization rotation occurring in optical media with Kerr nonlinearity, which allows to implement a nonlinear coin operator, one that depends on the state of the coin-qubit. We consider the space-time continuum limit of the evolution equation, which takes the form of a nonlinear Dirac equation. The analysis of this continuum limit allows us to gain some insight into the existence of different solitonic structures, such as bright and dark solitons. We illustrate several properties of these solitons with numerical calculations, including the effect on them of an additional phase simulating an external electric field.
Olivera-Atencio, M. L.; Lamata, L.; Casado-Pascual, J.
Benefits of Open Quantum Systems for Quantum Machine Learning Artículo de revista
En: Adv Quantum Technologies, 2023, ISBN: 2511-9044.
Resumen | Enlaces | BibTeX | Etiquetas: artificial intelligence, Quantum algorithms, quantum machine learning, US
@article{nokey,
title = {Benefits of Open Quantum Systems for Quantum Machine Learning},
author = {Olivera-Atencio, M.L. and Lamata, L. and Casado-Pascual, J.
},
url = {https://quantumspain-project.es/wp-content/uploads/2023/12/Adv-Quantum-Tech-2023-Olivera‐Atencio-Benefits-of-Open-Quantum-Systems-for-Quantum-Machine-Learning.pdf},
doi = {10.1002/qute.202300247},
isbn = {2511-9044},
year = {2023},
date = {2023-12-10},
urldate = {2023-12-10},
journal = {Adv Quantum Technologies},
abstract = {Quantum machine learning (QML) is a discipline that holds the promise ofrevolutionizing data processing and problem-solving. However, dissipationand noise arising from the coupling with the environment are commonlyperceived as major obstacles to its practical exploitation, as they impact thecoherence and performance of the utilized quantum devices. Significantefforts have been dedicated to mitigating and controlling their negative effectson these devices. This perspective takes a different approach, aiming toharness the potential of noise and dissipation instead of combating them.Surprisingly, it is shown that these seemingly detrimental factors can providesubstantial advantages in the operation of QML algorithms under certaincircumstances. Exploring and understanding the implications of adaptingQML algorithms to open quantum systems opens up pathways for devisingstrategies that effectively leverage noise and dissipation. The recent worksanalyzed in this perspective represent only initial steps toward uncoveringother potential hidden benefits that dissipation and noise may offer. Asexploration in this field continues, significant discoveries are anticipated thatcould reshape the future of quantum computing.},
keywords = {artificial intelligence, Quantum algorithms, quantum machine learning, US},
pubstate = {published},
tppubtype = {article}
}
Quantum machine learning (QML) is a discipline that holds the promise ofrevolutionizing data processing and problem-solving. However, dissipationand noise arising from the coupling with the environment are commonlyperceived as major obstacles to its practical exploitation, as they impact thecoherence and performance of the utilized quantum devices. Significantefforts have been dedicated to mitigating and controlling their negative effectson these devices. This perspective takes a different approach, aiming toharness the potential of noise and dissipation instead of combating them.Surprisingly, it is shown that these seemingly detrimental factors can providesubstantial advantages in the operation of QML algorithms under certaincircumstances. Exploring and understanding the implications of adaptingQML algorithms to open quantum systems opens up pathways for devisingstrategies that effectively leverage noise and dissipation. The recent worksanalyzed in this perspective represent only initial steps toward uncoveringother potential hidden benefits that dissipation and noise may offer. Asexploration in this field continues, significant discoveries are anticipated thatcould reshape the future of quantum computing.
Ding, Y.; Martín-Guerrero, J. D.; Vives-Gilabert, Y.; Chen, X.
Active Learning in Physics: From 101, to Progress, and Perspective Bachelor Thesis
2023.
Resumen | Enlaces | BibTeX | Etiquetas: UV
@bachelorthesis{nokey,
title = {Active Learning in Physics: From 101, to Progress, and Perspective},
author = {Ding, Y. and Martín-Guerrero, J.D. and Vives-Gilabert, Y. and Chen, X. },
url = {https://onlinelibrary.wiley.com/doi/10.1002/qute.202300208},
doi = {doi.org/10.1002/qute.202300208},
year = {2023},
date = {2023-11-30},
urldate = {2023-11-30},
journal = {Advanced Quantum Technologies},
abstract = {Active learning (AL) is a family of machine learning (ML) algorithms that predates the current era of artificial intelligence. Unlike traditional approaches that require labeled samples for training, AL iteratively selects unlabeled samples to be annotated by an expert. This protocol aims to prioritize the most informative samples, leading to improved model performance compared to training with all labeled samples. In recent years, AL has gained increasing attention, particularly in the field of physics. This paper presents a comprehensive and accessible introduction to the theory of AL reviewing the latest advancements across various domains. Additionally, the potential integration of AL is explored with quantum ML, envisioning a synergistic fusion of these two fields rather than viewing AL as a mere extension of classical ML into the quantum realm.},
keywords = {UV},
pubstate = {published},
tppubtype = {bachelorthesis}
}
Active learning (AL) is a family of machine learning (ML) algorithms that predates the current era of artificial intelligence. Unlike traditional approaches that require labeled samples for training, AL iteratively selects unlabeled samples to be annotated by an expert. This protocol aims to prioritize the most informative samples, leading to improved model performance compared to training with all labeled samples. In recent years, AL has gained increasing attention, particularly in the field of physics. This paper presents a comprehensive and accessible introduction to the theory of AL reviewing the latest advancements across various domains. Additionally, the potential integration of AL is explored with quantum ML, envisioning a synergistic fusion of these two fields rather than viewing AL as a mere extension of classical ML into the quantum realm.
Clemente, G.; Crippa, A.; Jansen, K.; Ramírez-Uribe, S.; Rentería-Olivo, A. E.; Rodrigo, G.; Sborlini Germán Rodrigo, G.; Silva, L. V.
Variational quantum eigensolver for causal loop Feynman diagrams and directed acyclic graphs Artículo de revista
En: Physical Review D, vol. 108, iss. 9, 2023.
Resumen | Enlaces | BibTeX | Etiquetas: UV
@article{nokey,
title = {Variational quantum eigensolver for causal loop Feynman diagrams and directed acyclic graphs},
author = {Clemente, G. and Crippa, A. and Jansen, K. and Ramírez-Uribe, S. and Rentería-Olivo, A.E. and Rodrigo, G. and Germán Rodrigo, Sborlini, G. and Silva, L.V. },
url = {https://journals.aps.org/prd/abstract/10.1103/PhysRevD.108.096035},
doi = {doi.org/10.1103/PhysRevD.108.096035},
year = {2023},
date = {2023-11-29},
urldate = {2023-11-29},
journal = {Physical Review D},
volume = {108},
issue = {9},
abstract = {We present a variational quantum eigensolver (VQE) algorithm for the efficient bootstrapping of the causal representation of multiloop Feynman diagrams in the loop-tree duality or, equivalently, the selection of acyclic configurations in directed graphs. A loop Hamiltonian based on the adjacency matrix describing a multiloop topology, and whose different energy levels correspond to the number of cycles, is minimized by VQE to identify the causal or acyclic configurations. The algorithm has been adapted to select multiple degenerated minima and thus achieves higher detection rates. A performance comparison with a Grover’s based algorithm is discussed in detail. The VQE approach requires, in general, fewer qubits and shorter circuits for its implementation, albeit with lesser success rates.},
keywords = {UV},
pubstate = {published},
tppubtype = {article}
}
We present a variational quantum eigensolver (VQE) algorithm for the efficient bootstrapping of the causal representation of multiloop Feynman diagrams in the loop-tree duality or, equivalently, the selection of acyclic configurations in directed graphs. A loop Hamiltonian based on the adjacency matrix describing a multiloop topology, and whose different energy levels correspond to the number of cycles, is minimized by VQE to identify the causal or acyclic configurations. The algorithm has been adapted to select multiple degenerated minima and thus achieves higher detection rates. A performance comparison with a Grover’s based algorithm is discussed in detail. The VQE approach requires, in general, fewer qubits and shorter circuits for its implementation, albeit with lesser success rates.
Martín-Guerrero, J. D.; Lamata, L.; Villmann, T.
Quantum Artificial Intelligence: A tutorial Conferencia
2023, ISBN: 978-2-87587-088-9.
Resumen | Enlaces | BibTeX | Etiquetas: artificial intelligence, machine learning, US
@conference{nokey,
title = {Quantum Artificial Intelligence: A tutorial},
author = {Martín-Guerrero, J. D. and Lamata, L. and Villmann, T.},
url = {https://quantumspain-project.es/wp-content/uploads/2023/09/ES2023-2.pdf},
doi = {10.14428/esann/2023.ES2023-2},
isbn = {978-2-87587-088-9},
year = {2023},
date = {2023-10-06},
urldate = {2023-10-06},
abstract = {This special session includes five high-quality papers on relevant topics, like quantum reinforcement learning, parallelization of quantum calculations, quantum feature selection and quantum vector quantization, thus capturing the richness and variability of approaches within QAI.},
keywords = {artificial intelligence, machine learning, US},
pubstate = {published},
tppubtype = {conference}
}
This special session includes five high-quality papers on relevant topics, like quantum reinforcement learning, parallelization of quantum calculations, quantum feature selection and quantum vector quantization, thus capturing the richness and variability of approaches within QAI.
Etxezarreta Martinez, J.; deMarti iOlius, A.; Crespo, P. M.
Superadditivity effects of quantum capacity decrease with the dimension for qudit depolarizing channels Artículo de revista
En: Physical Review A, vol. 108, iss. 3, 2023.
Resumen | Enlaces | BibTeX | Etiquetas: tecnun
@article{nokey,
title = {Superadditivity effects of quantum capacity decrease with the dimension for qudit depolarizing channels},
author = {Etxezarreta Martinez, J. and deMarti iOlius, A. and Crespo, P. M. },
url = {https://quantumspain-project.es/wp-content/uploads/2023/10/2301.10132-2.pdf},
doi = {doi.org/10.48550/arXiv.2301.10132},
year = {2023},
date = {2023-09-12},
urldate = {2023-09-12},
journal = {Physical Review A},
volume = {108},
issue = {3},
abstract = {Quantum channel capacity is a fundamental quantity in order to understand how well quantum information can be transmitted or corrected when subjected to noise. However, it is generally not known how to compute such quantities since the quantum channel coherent information is not additive for all channels, implying that it must be maximized over an unbounded number of channel uses. This leads to the phenomenon known as superadditivity, which refers to the fact that the regularized coherent information of n channel uses exceeds one-shot coherent information. In this article, we study how the gain in quantum capacity of qudit depolarizing channels relates to the dimension of the considered systems. We make use of an argument based on the no-cloning bound in order to prove that the possible superadditive effects decrease as a function of the dimension for such family of channels. In addition, we prove that the capacity of the qudit depolarizing channel coincides with the coherent information when d→∞. We also discuss the private classical capacity and obtain similar results. We conclude that when high-dimensional qudits experiencing depolarizing noise are considered, the coherent information of the channel is not only an achievable rate, but essentially the maximum possible rate for any quantum block code.},
keywords = {tecnun},
pubstate = {published},
tppubtype = {article}
}
Quantum channel capacity is a fundamental quantity in order to understand how well quantum information can be transmitted or corrected when subjected to noise. However, it is generally not known how to compute such quantities since the quantum channel coherent information is not additive for all channels, implying that it must be maximized over an unbounded number of channel uses. This leads to the phenomenon known as superadditivity, which refers to the fact that the regularized coherent information of n channel uses exceeds one-shot coherent information. In this article, we study how the gain in quantum capacity of qudit depolarizing channels relates to the dimension of the considered systems. We make use of an argument based on the no-cloning bound in order to prove that the possible superadditive effects decrease as a function of the dimension for such family of channels. In addition, we prove that the capacity of the qudit depolarizing channel coincides with the coherent information when d→∞. We also discuss the private classical capacity and obtain similar results. We conclude that when high-dimensional qudits experiencing depolarizing noise are considered, the coherent information of the channel is not only an achievable rate, but essentially the maximum possible rate for any quantum block code.
Hernani-Morales, C.; Alvarado, G.; Albarrán-Arriagada, F.; Vives-Gilabert, Y.; Solano, E.; Martín-Guerrero, J. D.
Machine Learning for maximizing the memristivity of single and coupled quantum memristors pre-print
2023.
Resumen | Enlaces | BibTeX | Etiquetas: machine learning, UV
@pre-print{nokey,
title = {Machine Learning for maximizing the memristivity of single and coupled quantum memristors},
author = {Hernani-Morales, C. and Alvarado, G. and Albarrán-Arriagada, F. and Vives-Gilabert, Y. and Solano, E. and Martín-Guerrero, J.D. },
url = {https://quantumspain-project.es/wp-content/uploads/2023/09/2309.05062.pdf},
doi = { https://doi.org/10.48550/arXiv.2309.05062},
year = {2023},
date = {2023-09-10},
urldate = {2023-09-10},
abstract = {We propose machine learning (ML) methods to characterize the memristive properties of single and coupled quantum memristors. We show that maximizing the memristivity leads to large values in the degree of entanglement of two quantum memristors, unveiling the close relationship between quantum correlations and memory. Our results strengthen the possibility of using quantum memristors as key components of neuromorphic quantum computing.
},
keywords = {machine learning, UV},
pubstate = {published},
tppubtype = {pre-print}
}
We propose machine learning (ML) methods to characterize the memristive properties of single and coupled quantum memristors. We show that maximizing the memristivity leads to large values in the degree of entanglement of two quantum memristors, unveiling the close relationship between quantum correlations and memory. Our results strengthen the possibility of using quantum memristors as key components of neuromorphic quantum computing.
Ferrer-Sánchez, A.; Flores-Garrigós, C.; Hernani-Morales, C.; Orquín-Marqués, J. J.; Hegade, N. N.; A.G. Cadavid, Montalban; Solano, E.; Vives-Gilabert, Y.; Martín-Guerrero, J. D.
Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation pre-print
2023.
Resumen | Enlaces | BibTeX | Etiquetas: UV
@pre-print{nokey,
title = {Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation},
author = {Ferrer-Sánchez, A. and Flores-Garrigós, C. and Hernani-Morales, C. and Orquín-Marqués, J.J. and Hegade, N.N. and Cadavid, A.G., Montalban, I. and Solano, E. and Vives-Gilabert, Y. and Martín-Guerrero, J.D. },
url = {https://quantumspain-project.es/wp-content/uploads/2023/09/2309.04434.pdf},
doi = { https://doi.org/10.48550/arXiv.2309.04434},
year = {2023},
date = {2023-09-08},
abstract = {We introduce a novel methodology that leverages the strength of Physics-Informed Neural Networks (PINNs) to address the counterdiabatic (CD) protocol in the optimization of quantum circuits comprised of systems with NQ qubits. The primary objective is to utilize physics-inspired deep learning techniques to accurately solve the time evolution of the different physical observables within the quantum system. To accomplish this objective, we embed the necessary physical information into an underlying neural network to effectively tackle the problem. In particular, we impose the hermiticity condition on all physical observables and make use of the principle of least action, guaranteeing the acquisition of the most appropriate counterdiabatic terms based on the underlying physics. The proposed approach offers a dependable alternative to address the CD driving problem, free from the constraints typically encountered in previous methodologies relying on classical numerical approximations. Our method provides a general framework to obtain optimal results from the physical observables relevant to the problem, including the external parameterization in time known as scheduling function, the gauge potential or operator involving the non-adiabatic terms, as well as the temporal evolution of the energy levels of the system, among others. The main applications of this methodology have been the H2 and LiH molecules, represented by a 2-qubit and 4-qubit systems employing the STO-3G basis. The presented results demonstrate the successful derivation of a desirable decomposition for the non-adiabatic terms, achieved through a linear combination utilizing Pauli operators. This attribute confers significant advantages to its practical implementation within quantum computing algorithms.},
keywords = {UV},
pubstate = {published},
tppubtype = {pre-print}
}
We introduce a novel methodology that leverages the strength of Physics-Informed Neural Networks (PINNs) to address the counterdiabatic (CD) protocol in the optimization of quantum circuits comprised of systems with NQ qubits. The primary objective is to utilize physics-inspired deep learning techniques to accurately solve the time evolution of the different physical observables within the quantum system. To accomplish this objective, we embed the necessary physical information into an underlying neural network to effectively tackle the problem. In particular, we impose the hermiticity condition on all physical observables and make use of the principle of least action, guaranteeing the acquisition of the most appropriate counterdiabatic terms based on the underlying physics. The proposed approach offers a dependable alternative to address the CD driving problem, free from the constraints typically encountered in previous methodologies relying on classical numerical approximations. Our method provides a general framework to obtain optimal results from the physical observables relevant to the problem, including the external parameterization in time known as scheduling function, the gauge potential or operator involving the non-adiabatic terms, as well as the temporal evolution of the energy levels of the system, among others. The main applications of this methodology have been the H2 and LiH molecules, represented by a 2-qubit and 4-qubit systems employing the STO-3G basis. The presented results demonstrate the successful derivation of a desirable decomposition for the non-adiabatic terms, achieved through a linear combination utilizing Pauli operators. This attribute confers significant advantages to its practical implementation within quantum computing algorithms.
De Marti i Olius, A.; Etxezarreta Martinez, J.; Fuentes, P.; Crespo, P. M.
Performance enhancement of surface codes via recursive minimum-weight perfect-match decoding Artículo de revista
En: Physical Review A, vol. 108, iss. 2, 2023, ISBN: 2469-9934.
Resumen | Enlaces | BibTeX | Etiquetas: tecnun
@article{,
title = {Performance enhancement of surface codes via recursive minimum-weight perfect-match decoding},
author = {De Marti i Olius, A. and Etxezarreta Martinez, J. and Fuentes, P. and Crespo, P. M.},
url = {https://quantumspain-project.es/wp-content/uploads/2023/10/2212.11632.pdf},
doi = {doi.org/10.1103/PhysRevA.108.022401},
isbn = {2469-9934},
year = {2023},
date = {2023-08-03},
urldate = {2023-08-03},
journal = {Physical Review A},
volume = {108},
issue = {2},
abstract = {The minimum weight perfect matching (MWPM) decoder is the standard decoding strategy for quantum surface codes. However, it suffers a harsh decrease in performance when subjected to biased or nonidentical quantum noise. In this work, we modify the conventional MWPM decoder so that it considers the biases, the nonuniformities, and the relationship between X, Y, and Z errors of the constituent qubits of a given surface code. Our modified approach, which we refer to as the recursive MWPM decoder, obtains an 18% improvement in the probability threshold pth under depolarizing noise. We also obtain significant performance improvements when considering biased noise and independent nonidentically distributed (i.ni.d.) error models derived from measurements performed on state-of-the-art quantum processors. In fact, when subjected to i.ni.d. noise, the recursive MWPM decoder yields a performance improvement of 105.5% over the conventional MWPM strategy, and in some cases, it even surpasses the performance obtained over the well-known depolarizing channel.},
keywords = {tecnun},
pubstate = {published},
tppubtype = {article}
}
The minimum weight perfect matching (MWPM) decoder is the standard decoding strategy for quantum surface codes. However, it suffers a harsh decrease in performance when subjected to biased or nonidentical quantum noise. In this work, we modify the conventional MWPM decoder so that it considers the biases, the nonuniformities, and the relationship between X, Y, and Z errors of the constituent qubits of a given surface code. Our modified approach, which we refer to as the recursive MWPM decoder, obtains an 18% improvement in the probability threshold pth under depolarizing noise. We also obtain significant performance improvements when considering biased noise and independent nonidentically distributed (i.ni.d.) error models derived from measurements performed on state-of-the-art quantum processors. In fact, when subjected to i.ni.d. noise, the recursive MWPM decoder yields a performance improvement of 105.5% over the conventional MWPM strategy, and in some cases, it even surpasses the performance obtained over the well-known depolarizing channel.
Pérez-Obiol, A.; Romero, A. M.; Menéndez, J.; Rios, A.; García-Sáez, A.; Juliá-Díaz, B.
Nuclear shell-model simulation in digital quantum computers Artículo de revista
En: Scientific Reports, vol. 13, 2023.
Resumen | Enlaces | BibTeX | Etiquetas: algorithms, quantic, quantum computing, simulations
@article{nokey,
title = {Nuclear shell-model simulation in digital quantum computers},
author = {Pérez-Obiol, A. and Romero, A. M. and Menéndez, J. and Rios, A. and García-Sáez, A. and Juliá-Díaz, B. },
url = {https://www.nature.com/articles/s41598-023-39263-7},
doi = {doi.org/10.1038/s41598-023-39263-7},
year = {2023},
date = {2023-07-29},
urldate = {2023-02-07},
journal = {Scientific Reports},
volume = {13},
abstract = {The nuclear shell model is one of the prime many-body methods to study the structure of atomic nuclei, but it is hampered by an exponential scaling on the basis size as the number of particles increases. We present a shell-model quantum circuit design strategy to find nuclear ground states that circumvents this limitation by exploiting an adaptive variational quantum eigensolver algorithm. Our circuit implementation is in excellent agreement with classical shell-model simulations for a dozen of light and medium-mass nuclei, including neon and calcium isotopes. We quantify the circuit depth, width and number of gates to encode realistic shell-model wavefunctions. Our strategy also addresses explicitly energy measurements and the required number of circuits to perform them. Our simulated circuits approach the benchmark results exponentially with a polynomial scaling in quantum resources for each nucleus and configuration space. Our work paves the way for quantum computing shell-model studies across the nuclear chart.},
keywords = {algorithms, quantic, quantum computing, simulations},
pubstate = {published},
tppubtype = {article}
}
The nuclear shell model is one of the prime many-body methods to study the structure of atomic nuclei, but it is hampered by an exponential scaling on the basis size as the number of particles increases. We present a shell-model quantum circuit design strategy to find nuclear ground states that circumvents this limitation by exploiting an adaptive variational quantum eigensolver algorithm. Our circuit implementation is in excellent agreement with classical shell-model simulations for a dozen of light and medium-mass nuclei, including neon and calcium isotopes. We quantify the circuit depth, width and number of gates to encode realistic shell-model wavefunctions. Our strategy also addresses explicitly energy measurements and the required number of circuits to perform them. Our simulated circuits approach the benchmark results exponentially with a polynomial scaling in quantum resources for each nucleus and configuration space. Our work paves the way for quantum computing shell-model studies across the nuclear chart.
Etxezarreta Martinez, J.; Fuentes, P.; deMarti iOlius, A.; Garcia-Frias, J.; Rodríguez Fonollosa, J.; Crespo, P. M.
Multiqubit time-varying quantum channels for NISQ-era superconducting quantum processors Artículo de revista
En: Physical Review Research, vol. 5, iss. 3, 2023, ISBN: 2643-1564.
Resumen | Enlaces | BibTeX | Etiquetas: tecnun
@article{nokey,
title = {Multiqubit time-varying quantum channels for NISQ-era superconducting quantum processors},
author = {Etxezarreta Martinez, J. and Fuentes, P. and deMarti iOlius, A. and Garcia-Frias, J. and Rodríguez Fonollosa, J. and Crespo, P.M.},
url = {https://journals.aps.org/prresearch/pdf/10.1103/PhysRevResearch.5.033055},
doi = {doi.org/10.1103/PhysRevResearch.5.033055},
isbn = {2643-1564},
year = {2023},
date = {2023-07-26},
journal = {Physical Review Research},
volume = {5},
issue = {3},
abstract = {Time-varying quantum channels (TVQCs) have been proposed as a model to include fluctuations of the relaxation (𝑇1) and dephasing times (𝑇2). In previous works, realizations of multiqubit TVQCs have been assumed to be equal for all the qubits of an error correction block, implying that the random variables that describe the fluctuations of 𝑇1 and 𝑇2 are block-to-block uncorrelated but qubit-wise perfectly correlated for the same block. In this article, we perform a correlation analysis of the fluctuations of the relaxation times of five multiqubit quantum processors. Our results show that it is reasonable to assume that the fluctuations of the relaxation and dephasing times of superconducting qubits are local to each of the qubits of the system. Based on these results, we discuss the multiqubit TVQCs when the fluctuations of the decoherence parameters for an error correction block are qubit-wise uncorrelated (as well as from block-to-block), a scenario we have named the fast time-varying quantum channel (FTVQC). Furthermore, we lower-bound the quantum capacity of general FTVQCs based on a quantity we refer to as the ergodic quantum capacity. Finally, we use numerical simulations to study the performance of quantum error correction codes when they operate over FTVQCs.},
keywords = {tecnun},
pubstate = {published},
tppubtype = {article}
}
Time-varying quantum channels (TVQCs) have been proposed as a model to include fluctuations of the relaxation (𝑇1) and dephasing times (𝑇2). In previous works, realizations of multiqubit TVQCs have been assumed to be equal for all the qubits of an error correction block, implying that the random variables that describe the fluctuations of 𝑇1 and 𝑇2 are block-to-block uncorrelated but qubit-wise perfectly correlated for the same block. In this article, we perform a correlation analysis of the fluctuations of the relaxation times of five multiqubit quantum processors. Our results show that it is reasonable to assume that the fluctuations of the relaxation and dephasing times of superconducting qubits are local to each of the qubits of the system. Based on these results, we discuss the multiqubit TVQCs when the fluctuations of the decoherence parameters for an error correction block are qubit-wise uncorrelated (as well as from block-to-block), a scenario we have named the fast time-varying quantum channel (FTVQC). Furthermore, we lower-bound the quantum capacity of general FTVQCs based on a quantity we refer to as the ergodic quantum capacity. Finally, we use numerical simulations to study the performance of quantum error correction codes when they operate over FTVQCs.
Combarro, E. F.; Pérez-Fernández, R.; Ranilla, J.; De Baets, B.
Solving the Kemeny ranking aggregation problem with quantum optimization algorithms Artículo de revista
En: Mathematical Methods in the Applied Sciences, vol. 46, iss. 16, 2023, ISBN: 0170-4214.
Resumen | Enlaces | BibTeX | Etiquetas: UNIOVI
@article{nokey,
title = {Solving the Kemeny ranking aggregation problem with quantum optimization algorithms},
author = {Combarro, E.F. and Pérez-Fernández, R. and Ranilla, J. and De Baets, B. },
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/mma.9489},
doi = {doi.org/10.1002/mma.9489},
isbn = {0170-4214},
year = {2023},
date = {2023-07-13},
journal = {Mathematical Methods in the Applied Sciences},
volume = {46},
issue = {16},
abstract = {The aim of a ranking aggregation problem is to combine several rankings into a single one that best represents them. A common method for solving this problem is due to Kemeny and selects as the aggregated ranking the one that minimizes the sum of the Kendall distances to the rankings to be aggregated. Unfortunately, the identification of the said ranking—called the Kemeny ranking—is known to be a computationally expensive task. In this paper, we study different ways of computing the Kemeny ranking with quantum optimization algorithms, and in particular, we provide some alternative formulations for the search for the Kemeny ranking as an optimization problem. To the best of our knowledge, this is the first time that this problem is addressed with quantum techniques. We propose four different ways of formulating the problem, one novel to this work. Two different quantum optimization algorithms—Quantum Approximate Optimization Algorithm and Quantum Adiabatic Computing—are used to evaluate each of the different formulations. The experimental results show that the choice of the formulation plays a big role on the performance of the quantum optimization algorithms.},
keywords = {UNIOVI},
pubstate = {published},
tppubtype = {article}
}
The aim of a ranking aggregation problem is to combine several rankings into a single one that best represents them. A common method for solving this problem is due to Kemeny and selects as the aggregated ranking the one that minimizes the sum of the Kendall distances to the rankings to be aggregated. Unfortunately, the identification of the said ranking—called the Kemeny ranking—is known to be a computationally expensive task. In this paper, we study different ways of computing the Kemeny ranking with quantum optimization algorithms, and in particular, we provide some alternative formulations for the search for the Kemeny ranking as an optimization problem. To the best of our knowledge, this is the first time that this problem is addressed with quantum techniques. We propose four different ways of formulating the problem, one novel to this work. Two different quantum optimization algorithms—Quantum Approximate Optimization Algorithm and Quantum Adiabatic Computing—are used to evaluate each of the different formulations. The experimental results show that the choice of the formulation plays a big role on the performance of the quantum optimization algorithms.
