Application
Quantum, variational and adiabatic genetic algorithms and their applications
Quantum Information Science and Technology (QUINST)
Group Description:
Quantum mechanics is at the heart of our technology and economy (laser and transistor are quantum devices), but its full potential is far from being realized. Recent technological advances in optics, nanoscience, and engineering enable experimenters to create artificial structures or subject microscopic and mesoscopic systems to new manipulable conditions where quantum phenomena play a fundamental role.
Quantum technologies exploit these effects for practical purposes. Quantum science aims to discover, study, and control quantum effects at a fundamental level. These are two sides of a virtuous circle: new technologies lead to the discovery and study of new phenomena that will lead to new technologies.
Our goal is to control and understand quantum phenomena at the multidisciplinary intersection of Quantum Information, Quantum Optics, Cold Atoms, Quantum Control, Spintronics, Quantum Metrology, Atomic Interferometry, Superconducting Qubits and Circuit QED, and Foundations of Quantum Mechanics.
The QUINST team comprises principal investigators Iñigo L. Egusquiza and Mikel Sanz, along with Xi Chen, Gonzalo Muga, Enrique Rico, and Liano Wu.
Activity description:
This activity focuses on the tasks necessary to characterize and improve quantum algorithms and processes and search for their applications in industrial processes, finance, logistics, AI, quantum chemistry, among others. It consists of the following tasks:
- Development of mathematical tools for the analysis of the properties of quantum algorithms. In particular, the use of operator theory will be studied to bound errors in approximate quantum algorithms, and quantum channel theory will be employed to analyze the convergence of heuristic algorithms, such as quantum genetic algorithms.
- Analyse alternative quantum computing paradigms in NISQ processors against control errors, coherence errors, cross-talk, etc. In this context, the development of new “self-protected” quantum algorithms like Shor or Grover will be studied, as well as simulations and quantum AI software more resilient to errors.
- Optimization and acceleration of adiabatic-type algorithms using quantum control techniques or “adiabatic shortcuts,” introducing iterative and adaptive methods that only use knowledge of the initial and final Hamiltonians, and artificial intelligence and machine learning techniques to optimize speed and robustness against errors.
- Development of industrial applications and use cases for quantum algorithms, particularly in finance, logistics, artificial intelligence, and quantum chemistry, among others.
- Application of quantum algorithms (free from sign problems and other difficulties of classical computing) to the simulation of models of interest in nuclear and high-energy physics. Specifically, problems of many strongly correlated bodies with dynamic abelian and non-abelian gauge degrees of freedom and their application to the study of gauge theories.
Results
García-Azorín, P.; Cárdenas-López, F. A.; Huber, H. B. P.; Romero, G.; Werninghaus, M.; Motzoi, F.; Filipp, S.; Sanz, M. (Ed.)
Robust multi-mode superconducting qubit designed with evolutionary algorithms Working paper
2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Robust multi-mode superconducting qubit designed with evolutionary algorithms},
editor = {García-Azorín, P. and Cárdenas-López, F.A. and Huber, H.B.P. and Romero, G. and Werninghaus, M. and Motzoi, F. and Filipp, S. and Sanz, M.},
url = {https://arxiv.org/abs/2407.18895},
doi = {doi.org/10.48550/arXiv.2407.18895},
year = {2025},
date = {2025-07-26},
abstract = {Multi-mode superconducting circuits offer a promising platform for engineering robust systems for quantum computation. Previous studies have shown that single-mode devices cannot simultaneously exhibit resilience against multiple decoherence sources due to conflicting protection requirements. In contrast, multi-mode systems offer increased flexibility and have proven capable of overcoming these fundamental limitations. Nevertheless, exploring multi-mode architectures is computationally demanding due to the exponential scaling of the Hilbert space dimension. Here, we present a multi-mode device designed using evolutionary optimization techniques, which have been shown to be effective for this computational task. The proposed device was optimized to feature an anharmonicity of a third of the qubit frequency and reduced energy dispersion caused by charge and magnetic flux fluctuations. It exhibits improvements over the fundamental errors limiting Transmon and Fluxonium coherence and manipulation, aiming for a balance between low depolarization error and fast manipulation; furthermore demonstrating robustness against fabrication errors, a major limitation in many proposed multi-mode devices. Overall, by striking a balance between coupling matrix elements and noise protection, we propose a device that paves the way towards finding proper characteristics for the construction of superconducting quantum processors.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
Multi-mode superconducting circuits offer a promising platform for engineering robust systems for quantum computation. Previous studies have shown that single-mode devices cannot simultaneously exhibit resilience against multiple decoherence sources due to conflicting protection requirements. In contrast, multi-mode systems offer increased flexibility and have proven capable of overcoming these fundamental limitations. Nevertheless, exploring multi-mode architectures is computationally demanding due to the exponential scaling of the Hilbert space dimension. Here, we present a multi-mode device designed using evolutionary optimization techniques, which have been shown to be effective for this computational task. The proposed device was optimized to feature an anharmonicity of a third of the qubit frequency and reduced energy dispersion caused by charge and magnetic flux fluctuations. It exhibits improvements over the fundamental errors limiting Transmon and Fluxonium coherence and manipulation, aiming for a balance between low depolarization error and fast manipulation; furthermore demonstrating robustness against fabrication errors, a major limitation in many proposed multi-mode devices. Overall, by striking a balance between coupling matrix elements and noise protection, we propose a device that paves the way towards finding proper characteristics for the construction of superconducting quantum processors.
Rodriguez-Grasa, P.; Ban, Y.; Sanz, M.
Neural quantum kernels: Training quantum kernels with quantum neural networks Journal Article
In: Physical Review Research, vol. 7, iss. 2, no. 23269 , 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Neural quantum kernels: Training quantum kernels with quantum neural networks},
author = {Rodriguez-Grasa, P. and Ban, Y. and Sanz, M.},
url = {https://journals.aps.org/prresearch/abstract/10.1103/xphb-x2g4},
doi = {doi.org/10.1103/xphb-x2g4},
year = {2025},
date = {2025-06-16},
urldate = {2025-06-16},
journal = {Physical Review Research},
volume = {7},
number = {23269 },
issue = {2},
abstract = {Quantum and classical machine learning have been naturally connected through kernel methods, which have also served as proof-of-concept for quantum advantage. Quantum embeddings encode classical data into quantum feature states, enabling the construction of embedding quantum kernels (EQKs) by measuring vector similarities and projected quantum kernels (PQKs) through projections of these states. However, in both approaches, the model is influenced by the choice of the embedding. In this work, we propose using the training of a quantum neural network (QNN) to construct neural quantum kernels, specifically neural EQKs and neural PQKs—problem-inspired kernel functions. Unlike previous approaches, our method requires the kernel matrix to be constructed only once, significantly reducing computational overhead. To achieve this, we introduce a scalable training method for an 𝑛-qubit data reuploading QNN. Furthermore, we demonstrate neural quantum kernels can alleviate exponential concentration and enhance generalization capabilities compared to problem-agnostic kernels, positioning them as a scalable and robust solution for quantum machine learning applications.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Quantum and classical machine learning have been naturally connected through kernel methods, which have also served as proof-of-concept for quantum advantage. Quantum embeddings encode classical data into quantum feature states, enabling the construction of embedding quantum kernels (EQKs) by measuring vector similarities and projected quantum kernels (PQKs) through projections of these states. However, in both approaches, the model is influenced by the choice of the embedding. In this work, we propose using the training of a quantum neural network (QNN) to construct neural quantum kernels, specifically neural EQKs and neural PQKs—problem-inspired kernel functions. Unlike previous approaches, our method requires the kernel matrix to be constructed only once, significantly reducing computational overhead. To achieve this, we introduce a scalable training method for an 𝑛-qubit data reuploading QNN. Furthermore, we demonstrate neural quantum kernels can alleviate exponential concentration and enhance generalization capabilities compared to problem-agnostic kernels, positioning them as a scalable and robust solution for quantum machine learning applications.
Gonzalez-Conde, J.; Lewis, D.; Bharadwaj, S. S.; Sanz, M.
Quantum Carleman linearization efficiency in nonlinear fluid dynamics Journal Article
In: Physical Review Research, vol. 7, iss. 2, no. 23254, 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Quantum Carleman linearization efficiency in nonlinear fluid dynamics},
author = {Gonzalez-Conde, J. and Lewis, D. and Bharadwaj, S.S. and Sanz, M. },
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.023254},
doi = {doi.org/10.1103/PhysRevResearch.7.023254},
year = {2025},
date = {2025-06-12},
urldate = {2025-06-12},
journal = {Physical Review Research},
volume = {7},
number = {23254},
issue = {2},
abstract = {Computational fluid dynamics (CFD) is a specialized branch of fluid mechanics that utilizes numerical methods and algorithms to solve and analyze fluid-flow problems. One promising avenue to enhance CFD is the use of quantum computing, which has the potential to resolve nonlinear differential equations more efficiently than classical computers. Here, we try to answer the question of which regimes of nonlinear partial differential equations for fluid dynamics can have an efficient quantum algorithm. We propose a connection between the numerical parameter 𝑅, which guarantees efficiency in the truncation of the Carleman linearization, and the physical parameters that describe the fluid flow. This link can be made thanks to the Kolmogorov scale, which determines the minimum size of the grid needed to properly resolve the energy cascade induced by the nonlinear term. Additionally, we introduce the formalism for vector field simulation in different spatial dimensions, providing the discretization of the operators and the boundary conditions.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Computational fluid dynamics (CFD) is a specialized branch of fluid mechanics that utilizes numerical methods and algorithms to solve and analyze fluid-flow problems. One promising avenue to enhance CFD is the use of quantum computing, which has the potential to resolve nonlinear differential equations more efficiently than classical computers. Here, we try to answer the question of which regimes of nonlinear partial differential equations for fluid dynamics can have an efficient quantum algorithm. We propose a connection between the numerical parameter 𝑅, which guarantees efficiency in the truncation of the Carleman linearization, and the physical parameters that describe the fluid flow. This link can be made thanks to the Kolmogorov scale, which determines the minimum size of the grid needed to properly resolve the energy cascade induced by the nonlinear term. Additionally, we introduce the formalism for vector field simulation in different spatial dimensions, providing the discretization of the operators and the boundary conditions.
Garcia-de-Andoin, M.; Álvarez-Ahedo, A.; Franco-Rubio, A.; Sanz, M.
Impact and mitigation of Hamiltonian characterization errors in digital-analog quantum computation Working paper
2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Impact and mitigation of Hamiltonian characterization errors in digital-analog quantum computation},
author = {Garcia-de-Andoin, M. and Álvarez-Ahedo, A. and Franco-Rubio, A. and Sanz, M. },
url = {https://arxiv.org/abs/2505.03642},
doi = {doi.org/10.48550/arXiv.2505.03642},
year = {2025},
date = {2025-05-06},
urldate = {2025-05-06},
abstract = {Digital-analog is a universal quantum computing paradigm which employs the natural entangling
Hamiltonian of the system and single-qubit gates as resources. Here, we study the stability of
these protocols against Hamiltonian characterization errors. For this, we bound the maximum
separation between the target and the implemented Hamiltonians. Additionally, we obtain an upper
bound for the deviation in the expected value of an observable. We further propose a protocol for
mitigating calibration errors which resembles dynamical-decoupling techniques. These results open
the possibility of scaling digital-analog to intermediate and large scale systems while having an
estimation on the errors committed.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
Digital-analog is a universal quantum computing paradigm which employs the natural entangling
Hamiltonian of the system and single-qubit gates as resources. Here, we study the stability of
these protocols against Hamiltonian characterization errors. For this, we bound the maximum
separation between the target and the implemented Hamiltonians. Additionally, we obtain an upper
bound for the deviation in the expected value of an observable. We further propose a protocol for
mitigating calibration errors which resembles dynamical-decoupling techniques. These results open
the possibility of scaling digital-analog to intermediate and large scale systems while having an
estimation on the errors committed.
Hamiltonian of the system and single-qubit gates as resources. Here, we study the stability of
these protocols against Hamiltonian characterization errors. For this, we bound the maximum
separation between the target and the implemented Hamiltonians. Additionally, we obtain an upper
bound for the deviation in the expected value of an observable. We further propose a protocol for
mitigating calibration errors which resembles dynamical-decoupling techniques. These results open
the possibility of scaling digital-analog to intermediate and large scale systems while having an
estimation on the errors committed.
S. Ding Romero, Y.; Chen, Xi.; Ban, Y.
Scrambling in the charging of quantum batteries Journal Article
In: High Energy Physics, vol. 2025, no. 21, 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Scrambling in the charging of quantum batteries},
author = {Romero, S. Ding, Y. and Chen, Xi. and Ban, Y.},
url = {https://link.springer.com/content/pdf/10.1007/JHEP05(2025)021.pdf},
doi = {doi.org/10.1007/JHEP05(2025)021},
year = {2025},
date = {2025-05-05},
journal = {High Energy Physics},
volume = {2025},
number = {21},
abstract = {Exponentially fast scrambling of an initial state characterizes quantum chaotic systems. Given the importance of quickly populating higher energy levels from low-energy states in quantum battery charging protocols, this work investigates the role of quantum scrambling in quantum batteries and its effect on optimal power and charging times by means of the Sachdev-Ye-Kitaev model, a maximally-chaotic black hole physics model that has been recently proposed as a quantum battery. We adopt a bare representation with normalized bandwidths to suppress system energy dependence. To our knowledge, this is the first in-depth exploration of quantum scrambling in the context of quantum batteries. By analyzing the dynamics of out-of-time-order correlators, our findings indicate that quantum scrambling does not necessarily lead to faster charging, despite its potential for accelerating the process.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Exponentially fast scrambling of an initial state characterizes quantum chaotic systems. Given the importance of quickly populating higher energy levels from low-energy states in quantum battery charging protocols, this work investigates the role of quantum scrambling in quantum batteries and its effect on optimal power and charging times by means of the Sachdev-Ye-Kitaev model, a maximally-chaotic black hole physics model that has been recently proposed as a quantum battery. We adopt a bare representation with normalized bandwidths to suppress system energy dependence. To our knowledge, this is the first in-depth exploration of quantum scrambling in the context of quantum batteries. By analyzing the dynamics of out-of-time-order correlators, our findings indicate that quantum scrambling does not necessarily lead to faster charging, despite its potential for accelerating the process.
Navarro, J.; Ravell Rodríguez, R.; Sanz, M.
Existence of unbiased estimators in discrete quantum systems Journal Article
In: Physical Review Research, vol. 7, 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Existence of unbiased estimators in discrete quantum systems},
author = {Navarro, J. and Ravell Rodríguez, R. and Sanz, M. },
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.023060},
doi = {doi.org/10.1103/PhysRevResearch.7.023060},
year = {2025},
date = {2025-04-16},
journal = {Physical Review Research},
volume = {7},
abstract = {The Cramér-Rao bound serves as a crucial lower limit for the mean square error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prior knowledge of the estimated parameter for constructing the optimal unbiased estimator. In contrast, Bhattacharyya bounds offer a more robust estimation framework with respect to prior accuracy by introducing additional constraints on the estimator. In this work, we examine divergences that arise in the computation of these bounds and establish the conditions under which they remain valid. Notably, we show that when the number of constraints exceeds the number of measurement outcomes, an estimator with finite variance typically does not exist. Furthermore, we systematically investigate the properties of these bounds using paradigmatic examples, comparing them to the Cramér-Rao and Bayesian approaches.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
The Cramér-Rao bound serves as a crucial lower limit for the mean square error of an estimator in frequentist parameter estimation. Paradoxically, it requires highly accurate prior knowledge of the estimated parameter for constructing the optimal unbiased estimator. In contrast, Bhattacharyya bounds offer a more robust estimation framework with respect to prior accuracy by introducing additional constraints on the estimator. In this work, we examine divergences that arise in the computation of these bounds and establish the conditions under which they remain valid. Notably, we show that when the number of constraints exceeds the number of measurement outcomes, an estimator with finite variance typically does not exist. Furthermore, we systematically investigate the properties of these bounds using paradigmatic examples, comparing them to the Cramér-Rao and Bayesian approaches.
Gonzalez-Raya, T.; Mena, A.; Lazo, M.; L., Leggio; Novoa, D.; Sanz, M.
Entanglement transfer during quantum frequency conversion in gas-filled hollow-core fibers Journal Article
In: APL Photonics, vol. 10, 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Entanglement transfer during quantum frequency conversion in gas-filled hollow-core fibers},
author = {Gonzalez-Raya, T. and Mena, A. and Lazo, M. and Leggio L. and Novoa, D. and Sanz, M. },
url = {https://pubs.aip.org/aip/app/article/10/4/041302/3341958/Entanglement-transfer-during-quantum-frequency},
doi = {doi.org/10.1063/5.0246782},
year = {2025},
date = {2025-04-02},
journal = {APL Photonics},
volume = {10},
abstract = {Quantum transduction is essential for the future hybrid quantum networks, connecting devices across different spectral ranges. In this regard, molecular modulation in hollow-core fibers has proven to be exceptional for efficient and tunable frequency conversion of arbitrary light fields down to the single-photon limit. However, insights into this conversion method for quantum light have remained elusive beyond standard semi-classical models. In this Letter, we employ a quantum Hamiltonian framework to characterize the behavior of entanglement during molecular modulation while describing the quantum dynamics of both molecules and photons in agreement with recent experiments. In particular, apart from obtaining analytical expressions for the final opto-molecular states, our model predicts a close correlation between the evolution of the average photon numbers and the transfer of entanglement between the interacting parties. These results will contribute to the development of new fiber-based strategies to tackle the challenges associated with the upcoming generation of lightwave quantum technologies.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Quantum transduction is essential for the future hybrid quantum networks, connecting devices across different spectral ranges. In this regard, molecular modulation in hollow-core fibers has proven to be exceptional for efficient and tunable frequency conversion of arbitrary light fields down to the single-photon limit. However, insights into this conversion method for quantum light have remained elusive beyond standard semi-classical models. In this Letter, we employ a quantum Hamiltonian framework to characterize the behavior of entanglement during molecular modulation while describing the quantum dynamics of both molecules and photons in agreement with recent experiments. In particular, apart from obtaining analytical expressions for the final opto-molecular states, our model predicts a close correlation between the evolution of the average photon numbers and the transfer of entanglement between the interacting parties. These results will contribute to the development of new fiber-based strategies to tackle the challenges associated with the upcoming generation of lightwave quantum technologies.
Biswas, S.; Rico, E.; Grass, T.
Ring-exchange physics in a chain of three-level ions Journal Article
In: Quantum , 2025.
Abstract | Links | BibTeX | Tags: 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.
Rodriguez-Grasa, P.; Ibarrondo, R.; Gonzalez-Conde, J.; Ban, Y.; Rebentrost, P.; Sanz, M.
Quantum approximated cloning-assisted density matrix exponentiation Journal Article
In: Physical Review Research, vol. 7, 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Quantum approximated cloning-assisted density matrix exponentiation},
author = {Rodriguez-Grasa, P. and Ibarrondo, R. and Gonzalez-Conde, J. and Ban, Y. and Rebentrost, P. and Sanz, M. },
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.7.013264},
doi = {doi.org/10.1103/PhysRevResearch.7.013264},
year = {2025},
date = {2025-03-12},
journal = {Physical Review Research},
volume = {7},
abstract = {Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the embedding techniques based on Hamiltonian simulation techniques enable the loading of matrices into quantum computers. A representative example of these methods is the Lloyd-Mohseni-Rebentrost (LMR) protocol, which efficiently implements matrix exponentiation when multiple copies of a quantum state are available. However, this is a quite ideal setup, and in a realistic scenario, the copies are limited and the noncloning theorem prevents one from producing more exact copies in order to increase the accuracy of the protocol. Here, we propose a method to circumvent this limitation by introducing imperfect quantum copies, which significantly improve the performance of the LMR when the eigenvectors are known.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the embedding techniques based on Hamiltonian simulation techniques enable the loading of matrices into quantum computers. A representative example of these methods is the Lloyd-Mohseni-Rebentrost (LMR) protocol, which efficiently implements matrix exponentiation when multiple copies of a quantum state are available. However, this is a quite ideal setup, and in a realistic scenario, the copies are limited and the noncloning theorem prevents one from producing more exact copies in order to increase the accuracy of the protocol. Here, we propose a method to circumvent this limitation by introducing imperfect quantum copies, which significantly improve the performance of the LMR when the eigenvectors are known.
Rodriguez-Grasa, P.; Farzan-Rodríguez, R.; Novelli, G.; Ban, Y.; Sanz, M.
Satellite image classification with neural quantum kernels Journal Article
In: Machine Learning: Science and Technology, vol. 6, no. 1, 2025.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Satellite image classification with neural quantum kernels},
author = {Rodriguez-Grasa, P. and Farzan-Rodríguez, R. and Novelli, G. and Ban, Y. and Sanz, M. },
url = {https://iopscience.iop.org/article/10.1088/2632-2153/ada86c/pdf},
doi = {10.1088/2632-2153/ada86c},
year = {2025},
date = {2025-02-18},
journal = {Machine Learning: Science and Technology},
volume = {6},
number = {1},
abstract = {Achieving practical applications of quantum machine learning (QML) for real-world scenarios
remains challenging despite significant theoretical progress. This paper proposes a novel approach
for classifying satellite images, a task of particular relevance to the earth observation industry, using
QML techniques. Specifically, we focus on classifying images that contain solar panels, addressing a
complex real-world classification problem. Our approach begins with classical pre-processing to
reduce the dimensionality of the satellite image dataset. We then apply neural quantum
kernels-quantum kernels derived from trained quantum neural networks-for classification. We
evaluate several strategies within this framework, demonstrating results that are competitive with
the best classical methods. Key findings include the robustness of or results and their scalability,
with successful performance achieved up to 8 qubits.
},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Achieving practical applications of quantum machine learning (QML) for real-world scenarios
remains challenging despite significant theoretical progress. This paper proposes a novel approach
for classifying satellite images, a task of particular relevance to the earth observation industry, using
QML techniques. Specifically, we focus on classifying images that contain solar panels, addressing a
complex real-world classification problem. Our approach begins with classical pre-processing to
reduce the dimensionality of the satellite image dataset. We then apply neural quantum
kernels-quantum kernels derived from trained quantum neural networks-for classification. We
evaluate several strategies within this framework, demonstrating results that are competitive with
the best classical methods. Key findings include the robustness of or results and their scalability,
with successful performance achieved up to 8 qubits.
remains challenging despite significant theoretical progress. This paper proposes a novel approach
for classifying satellite images, a task of particular relevance to the earth observation industry, using
QML techniques. Specifically, we focus on classifying images that contain solar panels, addressing a
complex real-world classification problem. Our approach begins with classical pre-processing to
reduce the dimensionality of the satellite image dataset. We then apply neural quantum
kernels-quantum kernels derived from trained quantum neural networks-for classification. We
evaluate several strategies within this framework, demonstrating results that are competitive with
the best classical methods. Key findings include the robustness of or results and their scalability,
with successful performance achieved up to 8 qubits.
Lazar, J.; Giner Olavarrieta, S.; Gatti, G.; Argüelles, C.; Sanz, M.
New Pathways in Neutrino Physics via Quantum-Encoded Data Analysis Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {New Pathways in Neutrino Physics via Quantum-Encoded Data Analysis},
author = {Lazar, J. and Giner Olavarrieta, S. and Gatti, G. and Argüelles, C. and Sanz, M. },
url = {https://arxiv.org/abs/2402.19306},
doi = {doi.org/10.48550/arXiv.2402.19306},
year = {2024},
date = {2024-12-11},
urldate = {2024-12-11},
abstract = {Ever-increasing amount of data is produced by particle detectors in their quest to unveil the laws of Nature. The large data rate requires the use of specialized triggers that promptly reduce the data rate to a manageable level; however, in doing so, unexpected new phenomena may escape detection. Additionally, the large data rate is increasingly difficult to analyze effectively, which has led to a recent revolution on machine learning techniques. Here, we present a methodology based on recent quantum compression techniques that has the capacity to store exponentially more amount of information than classically available methods. To demonstrate this, we encode the full neutrino telescope event information using parity observables in an IBM quantum processor using 8 qubits. Then we show that we can recover the information stored on the quantum computer with a fidelity of 84%. Finally, we illustrate the use of our protocol by performing a classification task that separates electron-neutrino events to muon-neutrinos events in a neutrino telescope. This new capability would eventually allow us to solve the street light effect in particle physics, where we only record signatures of particles with which we are familiar.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
Ever-increasing amount of data is produced by particle detectors in their quest to unveil the laws of Nature. The large data rate requires the use of specialized triggers that promptly reduce the data rate to a manageable level; however, in doing so, unexpected new phenomena may escape detection. Additionally, the large data rate is increasingly difficult to analyze effectively, which has led to a recent revolution on machine learning techniques. Here, we present a methodology based on recent quantum compression techniques that has the capacity to store exponentially more amount of information than classically available methods. To demonstrate this, we encode the full neutrino telescope event information using parity observables in an IBM quantum processor using 8 qubits. Then we show that we can recover the information stored on the quantum computer with a fidelity of 84%. Finally, we illustrate the use of our protocol by performing a classification task that separates electron-neutrino events to muon-neutrinos events in a neutrino telescope. This new capability would eventually allow us to solve the street light effect in particle physics, where we only record signatures of particles with which we are familiar.
Espinosa, E. M.; Wu, L. A.
Study on quantum thermalization from thermal initial states in a superconducting quantum computer Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{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},
urldate = {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.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
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 Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{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},
urldate = {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 = {workingpaper}
}
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 Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{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},
urldate = {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.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
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.
Mariella, N.; Murphy, T.; Di Marcantonio, F.; Najafi, K.; Vallecorsa, S.; Zhuk, S.; Rico, E.
Order Parameter Discovery for Quantum Many-Body Systems Working paper
Preprint, 2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{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},
urldate = {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 = {workingpaper}
}
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.
Tang, J.; Xu, R.; Ding, Y.; Xu, X.; Ban, Y.; Yung, M. H.; Pérez-Obiol, A.; G. Chen Platero, Xi.
Exploring ground states of Fermi-Hubbard model on honeycomb lattices with counterdiabaticity Journal Article
In: Quantum Materials , vol. 9, no. 87, 2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Exploring ground states of Fermi-Hubbard model on honeycomb lattices with counterdiabaticity},
author = {Tang, J. and Xu, R. and Ding, Y. and Xu, X. and Ban, Y. and Yung, M.H. and Pérez-Obiol, A. and Platero, G. Chen, Xi.},
url = {https://www.nature.com/articles/s41535-024-00697-5},
doi = {doi.org/10.1038/s41535-024-00697-5},
year = {2024},
date = {2024-11-07},
journal = {Quantum Materials },
volume = {9},
number = {87},
abstract = {Exploring the ground state properties of many-body quantum systems conventionally involves adiabatic processes, alongside exact diagonalization, in the context of quantum annealing or adiabatic quantum computation. Shortcuts to adiabaticity by counter-diabatic driving serve to accelerate these processes by suppressing energy excitations. Motivated by this, we develop variational quantum algorithms incorporating the auxiliary counter-diabatic interactions, comparing them with digitized adiabatic algorithms. These algorithms are then implemented on gate-based quantum circuits to explore the ground states of the Fermi-Hubbard model on honeycomb lattices, utilizing systems with up to 26 qubits. The comparison reveals that the counter-diabatic inspired ansatz is superior to traditional Hamiltonian variational ansatz. Furthermore, the number and duration of Trotter steps are analyzed to understand and mitigate errors. Given the model’s relevance to materials in condensed matter, our study paves the way for using variational quantum algorithms with counterdiabaticity to explore quantum materials in the noisy intermediate-scale quantum era.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
Exploring the ground state properties of many-body quantum systems conventionally involves adiabatic processes, alongside exact diagonalization, in the context of quantum annealing or adiabatic quantum computation. Shortcuts to adiabaticity by counter-diabatic driving serve to accelerate these processes by suppressing energy excitations. Motivated by this, we develop variational quantum algorithms incorporating the auxiliary counter-diabatic interactions, comparing them with digitized adiabatic algorithms. These algorithms are then implemented on gate-based quantum circuits to explore the ground states of the Fermi-Hubbard model on honeycomb lattices, utilizing systems with up to 26 qubits. The comparison reveals that the counter-diabatic inspired ansatz is superior to traditional Hamiltonian variational ansatz. Furthermore, the number and duration of Trotter steps are analyzed to understand and mitigate errors. Given the model’s relevance to materials in condensed matter, our study paves the way for using variational quantum algorithms with counterdiabaticity to explore quantum materials in the noisy intermediate-scale quantum era.
Bottarelli, A.; Garcia de Andoin, M.; Chandarana, P.; Paul, K.; Chen, X.; Sanz, M.; Hauke, P.
Symmetry-enhanced Counterdiabatic Quantum Algorithm for Qudits Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Symmetry-enhanced Counterdiabatic Quantum Algorithm for Qudits},
author = {Bottarelli, A. and Garcia de Andoin, M. and Chandarana, P. and Paul, K. and Chen, X. and Sanz, M. and Hauke, P.},
url = {https://arxiv.org/abs/2410.06710},
doi = {doi.org/10.48550/arXiv.2410.06710},
year = {2024},
date = {2024-10-18},
abstract = {Qubit-based variational quantum algorithms have undergone rapid development in recent years but still face several challenges. In this context, we propose a symmetry-enhanced digitized counterdiabatic quantum algorithm utilizing qudits instead of qubits. This approach offers three types of compression as compared to with respect to conventional variational circuits. First, compression in the circuit depth is achieved by counterdiabatic protocols. Second, information about the problem is compressed by replacing qubits with qudits, allowing for a more efficient representation of the problem. Lastly, the number of parameters is reduced by employing the symmetries of the system. We illustrate this approach by tackling a graph-based optimization problem Max-3-Cut and a highly-entangled state preparation, the qutrit W state. As our numerical results show, we achieve a better convergence with a lower circuit depth and less measurement overhead in all the cases considered. This work leads to a better design of shallow variational quantum circuits, improving the feasibility of their implementation on near-term qudit devices},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
Qubit-based variational quantum algorithms have undergone rapid development in recent years but still face several challenges. In this context, we propose a symmetry-enhanced digitized counterdiabatic quantum algorithm utilizing qudits instead of qubits. This approach offers three types of compression as compared to with respect to conventional variational circuits. First, compression in the circuit depth is achieved by counterdiabatic protocols. Second, information about the problem is compressed by replacing qubits with qudits, allowing for a more efficient representation of the problem. Lastly, the number of parameters is reduced by employing the symmetries of the system. We illustrate this approach by tackling a graph-based optimization problem Max-3-Cut and a highly-entangled state preparation, the qutrit W state. As our numerical results show, we achieve a better convergence with a lower circuit depth and less measurement overhead in all the cases considered. This work leads to a better design of shallow variational quantum circuits, improving the feasibility of their implementation on near-term qudit devices
Pranav, C.; Koushik, P.; Garcia-de-Andoin, M.; Ban, Y.; Sanz, M.; Chen, X.
Photonic counterdiabatic quantum optimization algorithm Journal Article
In: Communications Physics, no. 315, 2024, ISBN: 2399-3650.
Abstract | Links | BibTeX | Tags: 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.
P. Koushik Chandarana, P.; Kasturi Ranjan, S.; Chen, X.; Del Campo, A.
Lyapunov Controlled Counterdiabatic Quantum Optimization Working paper
Preprint, 2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Lyapunov Controlled Counterdiabatic Quantum Optimization},
author = {Chandarana, P. Koushik, P. and Kasturi Ranjan, S. and Chen, X. and Del Campo, A. },
url = {https://arxiv.org/pdf/2409.12525},
doi = {doi.org/10.48550/arXiv.2409.12525},
year = {2024},
date = {2024-09-19},
urldate = {2024-09-19},
abstract = {We introduce a quantum algorithm integrating counterdiabatic (CD) protocols with quantum Lyapunov control (QLC) to tackle combinatorial optimization problems. This approach offers versatility, allowing implementation as either a digital-analog or purely digital algorithm based on selected control strategies. By examining spin-glass Hamiltonians, we illustrate how the algorithm can explore alternative paths to enhance solution outcomes compared to conventional CD techniques. This method reduces the dependence on extensive higher-order CD terms and classical optimization techniques, rendering it more suitable for existing quantum computing platforms. The combination of digital compression via CD protocols and the adaptable nature of QLC methods positions this approach as a promising candidate for near-term quantum computing.},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
We introduce a quantum algorithm integrating counterdiabatic (CD) protocols with quantum Lyapunov control (QLC) to tackle combinatorial optimization problems. This approach offers versatility, allowing implementation as either a digital-analog or purely digital algorithm based on selected control strategies. By examining spin-glass Hamiltonians, we illustrate how the algorithm can explore alternative paths to enhance solution outcomes compared to conventional CD techniques. This method reduces the dependence on extensive higher-order CD terms and classical optimization techniques, rendering it more suitable for existing quantum computing platforms. The combination of digital compression via CD protocols and the adaptable nature of QLC methods positions this approach as a promising candidate for near-term quantum computing.
Ferreiro-Vélez, J.; Iriarte-Zendoia, I.; Ban, Y.; Chen, Xi.
Shortcuts for Adiabatic and Variational Algorithms in Molecular Simulation Working paper
Preprint, 2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Shortcuts for Adiabatic and Variational Algorithms in Molecular Simulation},
author = {Ferreiro-Vélez, J. and Iriarte-Zendoia, I. and Ban, Y. and Chen, Xi. },
url = {https://arxiv.org/pdf/2407.20957},
doi = {doi.org/10.48550/arXiv.2407.20957},
year = {2024},
date = {2024-07-30},
urldate = {2024-07-30},
abstract = {Quantum algorithms are prominent in the pursuit of achieving quantum advantage in various computational tasks. However, addressing challenges, such as limited qubit coherence and high error rate in near-term devices, requires extensive efforts. In this paper, we present a substantial stride in quantum chemistry by integrating shortcuts-to-adiabaticity techniques into adiabatic and variational algorithms for calculating the molecular ground state. Our approach includes the counter-diabatic driving that accelerates adiabatic evolution by mitigating adiabatic errors. Additionally, we introduce the counter-diabatic terms as the adiabatic gauge ansatz for the variational quantum eigensolver, which exhibits favorable convergence properties with a fewer number of parameters, thereby reducing the circuit depth. Our approach achieves comparable accuracy to other established ansatzes, while enhancing the potential for applications in material science, drug discovery, and molecular simulations.},
howpublished = {Preprint},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
Quantum algorithms are prominent in the pursuit of achieving quantum advantage in various computational tasks. However, addressing challenges, such as limited qubit coherence and high error rate in near-term devices, requires extensive efforts. In this paper, we present a substantial stride in quantum chemistry by integrating shortcuts-to-adiabaticity techniques into adiabatic and variational algorithms for calculating the molecular ground state. Our approach includes the counter-diabatic driving that accelerates adiabatic evolution by mitigating adiabatic errors. Additionally, we introduce the counter-diabatic terms as the adiabatic gauge ansatz for the variational quantum eigensolver, which exhibits favorable convergence properties with a fewer number of parameters, thereby reducing the circuit depth. Our approach achieves comparable accuracy to other established ansatzes, while enhancing the potential for applications in material science, drug discovery, and molecular simulations.
Acuaviva, A.; Aguirre, D.; Peña, R.; Sanz, M.
Benchmarking Quantum Computers: Towards a Standard Performance Evaluation Approach Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Benchmarking Quantum Computers: Towards a Standard Performance Evaluation Approach},
author = {Acuaviva, A. and Aguirre, D. and Peña, R. and Sanz, M. },
url = {https://arxiv.org/abs/2407.10941},
doi = {doi.org/10.48550/arXiv.2407.10941},
year = {2024},
date = {2024-07-17},
urldate = {2024-07-17},
abstract = {The technological development of increasingly larger quantum processors on different quantum platforms raises the problem of how to fairly compare their performance, known as quantum benchmarking of quantum processors. This is a challenge that computer scientists have already faced when comparing classical processors, leading to the development of various mathematical tools to address it, but also to the identification of the limits of this problem. In this work, we briefly review the most important aspects of both classical processor benchmarks and the metrics comprising them, providing precise definitions and analyzing the quality attributes that they should exhibit. Subsequently, we analyze the intrinsic properties that characterize the paradigm of quantum computing and hinder the naive transfer of strategies from classical benchmarking. However, we can still leverage some of the lessons learned such as the quality attributes of a textit{good} benchmark. Additionally, we review some of the most important metrics and benchmarks for quantum processors proposed in the literature, assessing what quality attributes they fulfill. Finally, we propose general guidelines for quantum benchmarking. These guidelines aim to pave the way for establishing a roadmap towards standardizing the performance evaluation of quantum devices, ultimately leading to the creation of an organization akin to the Standard Performance Evaluation Corporation (SPEC).},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
The technological development of increasingly larger quantum processors on different quantum platforms raises the problem of how to fairly compare their performance, known as quantum benchmarking of quantum processors. This is a challenge that computer scientists have already faced when comparing classical processors, leading to the development of various mathematical tools to address it, but also to the identification of the limits of this problem. In this work, we briefly review the most important aspects of both classical processor benchmarks and the metrics comprising them, providing precise definitions and analyzing the quality attributes that they should exhibit. Subsequently, we analyze the intrinsic properties that characterize the paradigm of quantum computing and hinder the naive transfer of strategies from classical benchmarking. However, we can still leverage some of the lessons learned such as the quality attributes of a textit{good} benchmark. Additionally, we review some of the most important metrics and benchmarks for quantum processors proposed in the literature, assessing what quality attributes they fulfill. Finally, we propose general guidelines for quantum benchmarking. These guidelines aim to pave the way for establishing a roadmap towards standardizing the performance evaluation of quantum devices, ultimately leading to the creation of an organization akin to the Standard Performance Evaluation Corporation (SPEC).
Ding, Y.; Ban, Y.; Sanz, M.; Martín-Guerrero, J. D.; Chen, X.
Quantum Active Learning Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{nokey,
title = {Quantum Active Learning},
author = {Ding, Y. and Ban, Y. and Sanz, M. and Martín-Guerrero, J.D. and Chen, X. },
url = {https://arxiv.org/abs/2405.18230},
doi = {doi.org/10.48550/arXiv.2405.18230},
year = {2024},
date = {2024-05-28},
urldate = {2024-05-28},
abstract = {Quantum machine learning, as an extension of classical machine learning that harnesses quantum mechanics, facilitates effiient learning from data encoded in quantum states. Training a quantum neural network typically demands a substantial labeled training set for supervised learning. Human annotators, often experts, provide labels for samples through additional experiments, adding to the training cost. To mitigate this expense, there is a quest for methods that maintain model performance over fully labeled datasets while requiring fewer labeled samples in practice, thereby extending few-shot learning to the quantum realm. Quantum active learning estimates the uncertainty of quantum data to select the most informative samples from a pool for labeling. Consequently, a QML model is supposed to accumulate maximal knowledge as the training set comprises labeled samples selected via sampling strategies. Notably, the QML models trained within the QAL framework are not restricted to specific types, enabling performance enhancement from the model architecture's perspective towards few-shot learning. Recognizing symmetry as a fundamental concept in physics ubiquitous across various domains, we leverage the symmetry inherent in quantum states induced by the embedding of classical data for model design. We employ an equivariant QNN capable of generalizing from fewer data with geometric priors. We benchmark the performance of QAL on two classification problems, observing both positive and negative results. QAL effectively trains the model, achieving performance comparable to that on fully labeled datasets by labeling less than 7% of the samples in the pool with unbiased sampling behavior. Furthermore, we elucidate the negative result of QAL being overtaken by random sampling baseline through miscellaneous numerical experiments. },
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
Quantum machine learning, as an extension of classical machine learning that harnesses quantum mechanics, facilitates effiient learning from data encoded in quantum states. Training a quantum neural network typically demands a substantial labeled training set for supervised learning. Human annotators, often experts, provide labels for samples through additional experiments, adding to the training cost. To mitigate this expense, there is a quest for methods that maintain model performance over fully labeled datasets while requiring fewer labeled samples in practice, thereby extending few-shot learning to the quantum realm. Quantum active learning estimates the uncertainty of quantum data to select the most informative samples from a pool for labeling. Consequently, a QML model is supposed to accumulate maximal knowledge as the training set comprises labeled samples selected via sampling strategies. Notably, the QML models trained within the QAL framework are not restricted to specific types, enabling performance enhancement from the model architecture's perspective towards few-shot learning. Recognizing symmetry as a fundamental concept in physics ubiquitous across various domains, we leverage the symmetry inherent in quantum states induced by the embedding of classical data for model design. We employ an equivariant QNN capable of generalizing from fewer data with geometric priors. We benchmark the performance of QAL on two classification problems, observing both positive and negative results. QAL effectively trains the model, achieving performance comparable to that on fully labeled datasets by labeling less than 7% of the samples in the pool with unbiased sampling behavior. Furthermore, we elucidate the negative result of QAL being overtaken by random sampling baseline through miscellaneous numerical experiments.
Gonzalez-Raya, T.; Pirandola, S.; Sanz, M.
Satellite-based entanglement distribution and quantum teleportation with continuous variables Journal Article
In: Communications Physics, vol. 7, no. 126, 2024, ISBN: 2399-3650.
Abstract | Links | BibTeX | Tags: 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.
Gonzalez-Conde, J.; Watts, T. W.; Rodriguez-Grasa, P.; Sanz, M.
Efficient quantum amplitude encoding of polynomial functions Journal Article
In: Quantum, vol. 8, pp. 1297, 2024, ISBN: 2521-327X.
Abstract | Links | BibTeX | Tags: 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 Journal Article
In: Physical Review Research, vol. 6, iss. 1, 2024, ISBN: 2643-1564.
Abstract | Links | BibTeX | Tags: 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.
Cea, M.; Grossi, M.; Monaco, S.; Rico, E.; Tagliacozzo, L.; Vallecorsa, S.
Exploring the Phase Diagram of the quantum one-dimensional ANNNI model Working paper
2024.
Abstract | Links | BibTeX | Tags: UPV/EHU
@workingpaper{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},
urldate = {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.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {workingpaper}
}
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.
Xu, R.; Tang, J.; Chandarana, P.; Paul, K.; Xu, X.; Yung, M.; Chen, X.
Benchmarking hybrid digitized-counterdiabatic quantum optimization Journal Article
In: Physical Review Research, vol. 6, iss. 1, 2024, ISBN: 2643-1564.
Abstract | Links | BibTeX | Tags: 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.
Ding, Y.; Chen, Xi.; Magdalena-Benedito, R.; J Martín-Guerrero, D.
Closed-loop control of a noisy qubit with reinforcement learning Journal Article
In: Machine Learning: Science and Technology, vol. 4, iss. 2, 2023, ISBN: 2632-2153.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Closed-loop control of a noisy qubit with reinforcement learning},
author = {Ding, Y. and Chen, Xi. and Magdalena-Benedito, R. and Martín-Guerrero, J,D.
},
url = {https://iopscience.iop.org/article/10.1088/2632-2153/acd048},
doi = {10.1088/2632-2153/acd048},
isbn = {2632-2153},
year = {2023},
date = {2023-05-05},
urldate = {2023-05-05},
journal = {Machine Learning: Science and Technology},
volume = {4},
issue = {2},
abstract = {The exotic nature of quantum mechanics differentiates machine learning applications in the quantum realm from classical ones. Stream learning is a powerful approach that can be applied to extract knowledge continuously from quantum systems in a wide range of tasks. In this paper, we propose a deep reinforcement learning method that uses streaming data from a continuously measured qubit in the presence of detuning, dephasing, and relaxation. The model receives streaming quantum information for learning and decision-making, providing instant feedback on the quantum system. We also explore the agent's adaptability to other quantum noise patterns through transfer learning. Our protocol offers insights into closed-loop quantum control, potentially advancing the development of quantum technologies.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
The exotic nature of quantum mechanics differentiates machine learning applications in the quantum realm from classical ones. Stream learning is a powerful approach that can be applied to extract knowledge continuously from quantum systems in a wide range of tasks. In this paper, we propose a deep reinforcement learning method that uses streaming data from a continuously measured qubit in the presence of detuning, dephasing, and relaxation. The model receives streaming quantum information for learning and decision-making, providing instant feedback on the quantum system. We also explore the agent's adaptability to other quantum noise patterns through transfer learning. Our protocol offers insights into closed-loop quantum control, potentially advancing the development of quantum technologies.
Ding, Y.; Gonzalez-Conde, J.; Lamata, L.; Martín-Guerrero, J. D.; Lizaso, E.; Mugel, S.; Chen, X.; Orús, R.; Solano, E.; Sanz, M.
Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer Journal Article
In: Entropy, vol. 25, no. 2, pp. 323, 2023, ISBN: 1099-4300.
Abstract | Links | BibTeX | Tags: UPV/EHU
@article{nokey,
title = {Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer},
author = {Ding, Y. and Gonzalez-Conde, J. and Lamata, L. and Martín-Guerrero, J.D. and Lizaso, E. and Mugel, S. and Chen, X. and Orús, R. and Solano, E. and Sanz, M. },
url = {https://www.mdpi.com/1099-4300/25/2/323},
doi = {doi.org/10.3390/e25020323},
isbn = {1099-4300},
year = {2023},
date = {2023-02-10},
journal = {Entropy},
volume = {25},
number = {2},
pages = {323},
abstract = {The prediction of financial crashes in a complex financial network is known to be an NP-hard problem, which means that no known algorithm can efficiently find optimal solutions. We experimentally explore a novel approach to this problem by using a D-Wave quantum annealer, benchmarking its performance for attaining a financial equilibrium. To be specific, the equilibrium condition of a nonlinear financial model is embedded into a higher-order unconstrained binary optimization (HUBO) problem, which is then transformed into a spin-1/2 Hamiltonian with at most, two-qubit interactions. The problem is thus equivalent to finding the ground state of an interacting spin Hamiltonian, which can be approximated with a quantum annealer. The size of the simulation is mainly constrained by the necessity of a large number of physical qubits representing a logical qubit with the correct connectivity. Our experiment paves the way for the codification of this quantitative macroeconomics problem in quantum annealers.},
keywords = {UPV/EHU},
pubstate = {published},
tppubtype = {article}
}
The prediction of financial crashes in a complex financial network is known to be an NP-hard problem, which means that no known algorithm can efficiently find optimal solutions. We experimentally explore a novel approach to this problem by using a D-Wave quantum annealer, benchmarking its performance for attaining a financial equilibrium. To be specific, the equilibrium condition of a nonlinear financial model is embedded into a higher-order unconstrained binary optimization (HUBO) problem, which is then transformed into a spin-1/2 Hamiltonian with at most, two-qubit interactions. The problem is thus equivalent to finding the ground state of an interacting spin Hamiltonian, which can be approximated with a quantum annealer. The size of the simulation is mainly constrained by the necessity of a large number of physical qubits representing a logical qubit with the correct connectivity. Our experiment paves the way for the codification of this quantitative macroeconomics problem in quantum annealers.
