Descubriendo el potencial de la computación cuántica

@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}

}

@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 = {CSIC-4.7},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@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}

}

@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 = {US},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{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://advanced.onlinelibrary.wiley.com/doi/full/10.1002/qute.202300208},

doi = {doi.org/10.1002/qute.202300208},

year  = {2023},

date = {2023-10-24},

urldate = {2023-11-30},

journal = {Advanced Quantum Technologies},

volume = {6},

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 = {article}

}

@article{nokey,

title = {Frustrated magnets without geometrical frustration in bosonic flux ladders},

author = {Barbiero, L. and Cabedo, J. and Lewenstein, M. and Tarruell, L. and Celi, A.},

url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.L042008},

doi = {doi.org/10.1103/PhysRevResearch.5.L042008},

year  = {2023},

date = {2023-10-06},

volume = {5},

issue = {4},

pages = {42008},

abstract = {We propose a scheme to realize a frustrated Bose-Hubbard model with ultracold atoms in an optical lattice that comprises the frustrated spin-1/2 quantum 𝑋𝑋 model. Our approach is based on a square ladder of magnetic flux ∼𝜋 with one real and one synthetic spin dimension. Although this system does not have geometrical frustration, we show that at low energies it maps into an effective triangular ladder with staggered fluxes for specific values of the synthetic tunneling. We numerically investigate its rich phase diagram and show that it contains bond-ordered-wave and chiral superfluid phases. Our scheme gives access to minimal instances of frustrated magnets without the need for real geometrical frustration, in a setup of minimal experimental complexity.},

keywords = {ICFO-4.16},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@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}

}

@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 = {BSC},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@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}

}

@article{nokey,

title = {Quantum entanglement patterns in the structure of atomic nuclei within the nuclear shell model},

author = {Pérez-Obiol, A. and Masot-Llima, S. and Romero, A. M. and Menéndez, J. and Rios, A. and García-Sáez, A. and Juliá-Díaz, B. },

url = {https://link.springer.com/article/10.1140/epja/s10050-023-01151-z},

doi = {doi.org/10.1140/epja/s10050-023-01151-z},

isbn = {1434-601X},

year  = {2023},

date = {2023-07-11},

urldate = {2023-07-11},

journal = {The European Physical Journal A},

volume = {59},

number = {240},

abstract = {Quantum entanglement offers a unique perspective into the underlying structure of strongly-correlated systems such as atomic nuclei. In this paper, we use quantum information tools to analyze the structure of light and medium-mass berillyum, oxygen, neon and calcium isotopes within the nuclear shell model. We use different entanglement metrics, including single-orbital entanglement, mutual information, and von Neumann entropies for different equipartitions of the shell-model valence space and identify mode-entanglement patterns related to the energy, angular momentum and isospin of the nuclear single-particle orbitals. We observe that the single-orbital entanglement is directly related to the number of valence nucleons and the energy structure of the shell, while the mutual information highlights signatures of proton–proton and neutron–neutron pairing, as well as nuclear deformation. Proton and neutron orbitals are weakly entangled by all measures, and in fact have the lowest von Neumann entropies among all possible equipartitions of the valence space. In contrast, orbitals with opposite angular momentum projection have relatively large entropies, especially in spherical nuclei. This analysis provides a guide for designing more efficient quantum algorithms for the noisy intermediate-scale quantum era.},

keywords = {BSC},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Quantum circuits for discrete-time quantum walks with position-dependent coin operator},

author = {Nzongani, U. and Zylberman, J. and Doncecchi, C.E. and Pérez, A. and Debbasch, F. and Arnault, P. },

url = {https://link.springer.com/article/10.1007/s11128-023-03957-8},

doi = {doi.org/10.1007/s11128-023-03957-8},

year  = {2023},

date = {2023-07-01},

abstract = {The aim of this paper is to build quantum circuits that implement discrete-time quantum walks having an arbitrary position-dependent coin operator. The position of the walker is encoded in base 2: with n wires, each corresponding to one qubit, we encode position states. The data necessary to define an arbitrary position-dependent coin operator is therefore exponential in n. Hence, the exponentiality will necessarily appear somewhere in our circuits. We first propose a circuit implementing the position-dependent coin operator, that is naive, in the sense that it has exponential depth and implements sequentially all appropriate position-dependent coin operators. We then propose a circuit that “transfers” all the depth into ancillae, yielding a final depth that is linear in n at the cost of an exponential number of ancillae. The main idea of this linear-depth circuit is to implement in parallel all coin operators at the different positions. Reducing the depth exponentially at the cost of having an exponential number of ancillae is a goal which has already been achieved for the problem of loading classical data on a quantum circuit (Araujo in Sci Rep 11:6329, 2021) (notice that such a circuit can be used to load the initial state of the walker). Here, we achieve this goal for the problem of applying a position-dependent coin operator in a discrete-time quantum walk. Finally, we extend the result of Welch (New J Phys 16:033040, 2014) from position-dependent unitaries which are diagonal in the position basis to position-dependent -block-diagonal unitaries: indeed, we show that for a position dependence of the coin operator (the block-diagonal unitary) which is smooth enough, one can find an efficient quantum-circuit implementation approximating the coin operator up to an error  (in terms of the spectral norm), the depth and size of which scale as. A typical application of the efficient implementation would be the quantum simulation of a relativistic spin-1/2 particle on a lattice, coupled to a smooth external gauge field; notice that recently, quantum spatial-search schemes have been developed which use gauge fields as the oracle, to mark the vertex to be found (Zylberman in Entropy 23:1441, 2021), (Fredon arXiv:2210.13920). A typical application of the linear-depth circuit would be when there is spatial noise on the coin operator (and hence a non-smooth dependence in the position).},

keywords = {UV},

pubstate = {published},

tppubtype = {article}

}

@article{,

title = {Multi-dimensional Fourier series with quantum circuits},

author = {Casas, B. and Cervera-Lierta, A.},

url = {https://journals.aps.org/pra/abstract/10.1103/PhysRevA.107.062612

Preprint version: https://arxiv.org/abs/2302.03389



},

doi = {10.1103/PhysRevA.107.062612},

year  = {2023},

date = {2023-06-29},

urldate = {2023-06-29},

journal = {Physical Review A},

volume = {107},

issue = {5},

pages = {15},

abstract = {Quantum machine learning is the field that aims to integrate machine learning with quantum computation. In recent years, the field has emerged as an active research area with the potential to bring new insights to classical machine learning problems. One of the challenges in the field is to explore the expressibility of parametrized quantum circuits and their ability to be universal function approximators, as classical neural networks are. Recent works have shown that, with a quantum supervised learning model, we can fit any one-dimensional Fourier series, proving their universality. However, models for multidimensional functions have not been explored in the same level of detail. In this work, we study the expressibility of various types of circuit Ansätze that generate multidimensional Fourier series. We found that, for some Ansätze, the degrees of freedom required for fitting such functions grow faster than the available degrees in the Hilbert space generated by the circuits. For example, single-qudit models have limited power to represent arbitrary multidimensional Fourier series. Despite this, we show that we can enlarge the Hilbert space of the circuit by using more qudits or higher local dimensions to meet the degrees of freedom requirements, thus ensuring the universality of the models.},

keywords = {BSC},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{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://advanced.onlinelibrary.wiley.com/doi/10.1002/qute.202300294},

doi = {doi.org/10.1002/qute.202300294},

year  = {2023},

date = {2023-04-14},

urldate = {2023-09-10},

journal = {Advanced Quantum Technologies},

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 = {UV},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Quantum-enhanced multiparameter estimation and compressed sensing of a field},

author = {Baamara, Y. and Gessner, M. and Sinatra, A. },

url = {https://scipost.org/10.21468/SciPostPhys.14.3.050},

doi = {10.21468/SciPostPhys.14.3.050},

year  = {2023},

date = {2023-03-27},

journal = {SciPost Physics},

volume = {14},

issue = {3},

pages = {50},

abstract = {We show that a significant quantum gain corresponding to squeezed or over-squeezed spin states can be obtained in multiparameter estimation by measuring the Hadamard coefficients of a 1D or 2D signal. The physical platform we consider consists of two-level atoms in an optical lattice in a squeezed-Mott configuration, or more generally by correlated spins distributed in spatially separated modes. Our protocol requires the possibility to locally flip the spins, but relies on collective measurements. We give examples of applications to scalar or vector field mapping and compressed sensing.},

keywords = {ICFO-4.16},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{nokey,

title = {Quantum Brain Networks: A Perspective},

author = {Miranda, E. R. and Martín-Guerrero, J. D. and Venkatesh, S. and Hernani-Morales, C. and Lamata, L. and Solano, E. },

editor = {Durdu Guney},

url = {https://www.mdpi.com/2079-9292/11/10/1528/htm},

doi = {10.3390/electronics11101528},

year  = {2022},

date = {2022-05-11},

urldate = {2022-05-11},

journal = {Electronics },

volume = {11},

number = {10},

pages = {1528},

abstract = {We propose Quantum Brain Networks (QBraiNs) as a new interdisciplinary field integrating knowledge and methods from neurotechnology, artificial intelligence, and quantum computing. The objective is to develop an enhanced connectivity between the human brain and quantum computers for a variety of disruptive applications. We foresee the emergence of hybrid classical-quantum networks of wetware and hardware nodes, mediated by machine learning techniques and brain–machine interfaces. QBraiNs will harness and transform in unprecedented ways arts, science, technologies, and entrepreneurship, in particular activities related to medicine, Internet of Humans, intelligent devices, sensorial experience, gaming, Internet of Things, crypto trading, and business. },

keywords = {UV},

pubstate = {published},

tppubtype = {article}

}