<?xml version="1.0" encoding="UTF-8"?>
<xml><records><RECORD><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><REFERENCE_TYPE>0</REFERENCE_TYPE><CONTRIBUTORS><AUTHORS><AUTHOR><style face="normal" font="default" size="100%">Tomasz Śmierzchalski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Łukasz Pawela</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Zbigniew Puchała</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Tomasz Trzciński</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></AUTHOR></AUTHORS></CONTRIBUTORS><TITLES><TITLE><style face="normal" font="default" size="100%">Post-Error Correction for Quantum Annealing Processor using Reinforcement Learning</style></TITLE></TITLES><KEYWORDS/><DATES/><AUTHORS><style face="normal" font="default" size="100%"/></AUTHORS><YEAR><style face="normal" font="default" size="100%">2022</style></YEAR><SECONDARY_TITLE><style face="normal" font="default" size="100%">International Conference on Computational Science (ICCS 2022): Lecture Notes in Computer Science </style></SECONDARY_TITLE><LANGUAGE><style face="normal" font="default" size="100%">eng</style></LANGUAGE><SECTION><style face="normal" font="default" size="100%">261–268</style></SECTION><DATE><style face="normal" font="default" size="100%">07/2022</style></DATE><URL><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-031-08760-8_22</style></URL><title><style face="normal" font="default" size="100%">Post-Error Correction for Quantum Annealing Processor using Reinforcement Learning</style></title></RECORD><RECORD><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><REFERENCE_TYPE>0</REFERENCE_TYPE><CONTRIBUTORS><AUTHORS><AUTHOR><style face="normal" font="default" size="100%">Tomasz Śmierzchalski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Jakub Pawłowski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Artur Przybysz</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Łukasz Pawela</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Zbigniew Puchała</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Mátyás Koniorczyk</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Sebastian Deffner</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Krzysztof Domino</style></AUTHOR></AUTHORS></CONTRIBUTORS><TITLES><TITLE><style face="normal" font="default" size="100%">Hybrid quantum-classical computation for automatic guided vehicles scheduling</style></TITLE></TITLES><KEYWORDS/><DATES/><AUTHORS><style face="normal" font="default" size="100%"/></AUTHORS><YEAR><style face="normal" font="default" size="100%">2024</style></YEAR><SECONDARY_TITLE><style face="normal" font="default" size="100%">Scientific Reports</style></SECONDARY_TITLE><LANGUAGE><style face="normal" font="default" size="100%">eng</style></LANGUAGE><VOLUME><style face="normal" font="default" size="100%">14</style></VOLUME><SECTION><style face="normal" font="default" size="100%">21809</style></SECTION><DATE><style face="normal" font="default" size="100%">09/2014</style></DATE><ABSTRACT><style face="normal" font="default" size="100%">&lt;p&gt;Motivated by recent efforts to develop quantum computing for practical, industrial-scale challenges, we demonstrate the effectiveness of state-of-the-art hybrid (not necessarily quantum) solvers in addressing the business-centric optimization problem of scheduling Automatic Guided Vehicles (AGVs). Some solvers can already leverage noisy intermediate-scale quantum (NISQ) devices. In our study, we utilize D-Wave hybrid solvers that implement classical heuristics with potential assistance from a quantum processing unit. This hybrid methodology performs comparably to existing classical solvers. However, due to the proprietary nature of the software, the precise contribution of quantum computation remains unclear. Our analysis focuses on a practical, business-oriented scenario: scheduling AGVs within a factory constrained by limited space, simulating a realistic production setting. Our approach maps a realistic AGVs problem onto one reminiscent of railway scheduling and demonstrates that the AGVs problem is better suited to quantum computing than its railway counterpart, the latter being denser in terms of the average number of constraints per variable. The main idea here is to highlight the potential usefulness of a hybrid approach for handling AGVs scheduling problems of practical sizes. We show that a scenario involving up to 21 AGVs, significant due to possible deadlocks, can be efficiently addressed by a hybrid solver in seconds.&lt;/p&gt;&#13;
</style></ABSTRACT><URL><style face="normal" font="default" size="100%">https://rdcu.be/dUkwi</style></URL><title><style face="normal" font="default" size="100%">Hybrid quantum-classical computation for automatic guided vehicles scheduling</style></title></RECORD><RECORD><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><REFERENCE_TYPE>0</REFERENCE_TYPE><CONTRIBUTORS><AUTHORS><AUTHOR><style face="normal" font="default" size="100%">Tomasz Śmierzchalski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Zakaria Mzaouali</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Sebastian Deffner</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></AUTHOR></AUTHORS></CONTRIBUTORS><TITLES><TITLE><style face="normal" font="default" size="100%">Efficiency Optimization in Quantum Computing: Balancing Thermodynamics and Computational Performance</style></TITLE></TITLES><KEYWORDS/><DATES/><AUTHORS><style face="normal" font="default" size="100%"/></AUTHORS><YEAR><style face="normal" font="default" size="100%">2024</style></YEAR><SECONDARY_TITLE><style face="normal" font="default" size="100%">Scientific Reports</style></SECONDARY_TITLE><LANGUAGE><style face="normal" font="default" size="100%">eng</style></LANGUAGE><VOLUME><style face="normal" font="default" size="100%">14</style></VOLUME><SECTION><style face="normal" font="default" size="100%">4555</style></SECTION><URL><style face="normal" font="default" size="100%">https://www.nature.com/articles/s41598-024-55314-z</style></URL><title><style face="normal" font="default" size="100%">Efficiency Optimization in Quantum Computing: Balancing Thermodynamics and Computational Performance</style></title></RECORD><RECORD><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><REFERENCE_TYPE>0</REFERENCE_TYPE><CONTRIBUTORS><AUTHORS><AUTHOR><style face="normal" font="default" size="100%">Anna Dziubyna</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Tomasz Śmierzchalski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Marek Rams</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Masoud Mohseni</style></AUTHOR></AUTHORS></CONTRIBUTORS><TITLES><TITLE><style face="normal" font="default" size="100%">Limitations of tensor-network approaches for optimization and sampling: A comparison to quantum and classical Ising machines</style></TITLE></TITLES><KEYWORDS/><DATES/><AUTHORS><style face="normal" font="default" size="100%"/></AUTHORS><YEAR><style face="normal" font="default" size="100%">2025</style></YEAR><SECONDARY_TITLE><style face="normal" font="default" size="100%">Physical Review Applied</style></SECONDARY_TITLE><LANGUAGE><style face="normal" font="default" size="100%">eng</style></LANGUAGE><VOLUME><style face="normal" font="default" size="100%">23</style></VOLUME><ISSUE><style face="normal" font="default" size="100%">5</style></ISSUE><DATE><style face="normal" font="default" size="100%">05/2025</style></DATE><ABSTRACT><style face="normal" font="default" size="100%">&lt;p&gt;Optimization problems pose challenges across various fields. In recent years, quantum annealers have emerged as a promising platform for tackling such challenges. Here, to provide an additional perspective, we develop a heuristic tensor-network-based algorithm to reveal the low-energy spectra of Ising spin-glass systems with interaction graphs relevant to present-day quantum annealers. Our deterministic approach combines a branch-and-bound search strategy with an approximate calculation of marginals via tensor-network contractions. Its application to quasi-two-dimensional lattices with large unit cells of up to 24 spins, realized in current quantum annealing processors, requires a dedicated approach that uses sparse structures in the tensor-network representation and GPU hardware acceleration. We benchmark our approach on random problems defined on Pegasus and Zephyr graphs with up to a few thousand spins, comparing it against the D-Wave Advantage quantum annealer and the simulated bifurcation algorithm, with the latter representing an emerging class of classical Ising solvers. In addition to examining the quality of the best solutions, we compare the diversity of low-energy states sampled by all the solvers. For the largest considered independent and identically distributed problems with over 5000 spins, the state-of-the-art tensor-network approaches lead to solutions that are 0.1% to 1% worse than the best solutions obtained by Ising machines while being 2 orders of magnitude slower. We attribute these results to approximate contraction failures. For embedded tile planting instances, our approach reaches approximately 0.1% from the planted ground state, a factor of 3 better than the Ising solvers. While all three methods can output diverse low-energy solutions—e.g., differing by at least a quarter of spins with energy error below 1%—our deterministic branch-and-bound approach finds sets of a few such states at most. In contrast, both Ising machines prove capable of sampling sets of thousands of such solutions.&lt;/p&gt;&#13;
</style></ABSTRACT><URL><style face="normal" font="default" size="100%">https://link.aps.org/doi/10.1103/PhysRevApplied.23.054049</style></URL><title><style face="normal" font="default" size="100%">Limitations of tensor-network approaches for optimization and sampling: A comparison to quantum and classical Ising machines</style></title></RECORD><RECORD><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><REFERENCE_TYPE>0</REFERENCE_TYPE><CONTRIBUTORS><AUTHORS><AUTHOR><style face="normal" font="default" size="100%">Tomasz Śmierzchalski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Anna Dziubyna</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Konrad Jałowiecki</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Zakaria Mzaouali</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Łukasz Pawela</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Marek Rams</style></AUTHOR></AUTHORS></CONTRIBUTORS><TITLES><TITLE><style face="normal" font="default" size="100%">SpinGlassPEPS.jl: Tensor-network package for Ising-like optimization on quasi-two-dimensional graphs</style></TITLE></TITLES><KEYWORDS/><DATES/><AUTHORS><style face="normal" font="default" size="100%"/></AUTHORS><YEAR><style face="normal" font="default" size="100%">2025</style></YEAR><SECONDARY_TITLE><style face="normal" font="default" size="100%">SoftwareX</style></SECONDARY_TITLE><LANGUAGE><style face="normal" font="default" size="100%">eng</style></LANGUAGE><VOLUME><style face="normal" font="default" size="100%">31</style></VOLUME><ABSTRACT><style face="normal" font="default" size="100%">&lt;p&gt;This work introduces SpinGlassPEPS.jl, a software package implemented in Julia, designed to find low-energy configurations of generalized Potts models, including Ising and QUBO problems, utilizing heuristic tensor network contraction algorithms on quasi-2D geometries. In particular, the package employs the Projected Entangled-Pairs States to approximate the Boltzmann distribution corresponding to the model’s cost function. This enables an efficient branch-and-bound search (within the probability space) that exploits the locality of the underlying problem’s topology. As a result, our software enables the discovery of low-energy configurations for problems on quasi-2D graphs, particularly those relevant to modern quantum annealing devices. The modular architecture of SpinGlassPEPS.jl supports various contraction schemes and hardware acceleration.&lt;/p&gt;&#13;
</style></ABSTRACT><URL><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S2352711025002249</style></URL><title><style face="normal" font="default" size="100%">SpinGlassPEPS.jl: Tensor-network package for Ising-like optimization on quasi-two-dimensional graphs</style></title></RECORD><RECORD><source-app name="Bibcite" version="8.x">Drupal-Bibcite</source-app><REFERENCE_TYPE>0</REFERENCE_TYPE><CONTRIBUTORS><AUTHORS><AUTHOR><style face="normal" font="default" size="100%">Jakub Pawlowski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Tomasz Śmierzchalski</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Fengping Jin</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Bartłomiej Gardas</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Sebastian Deffner</style></AUTHOR><AUTHOR><style face="normal" font="default" size="100%">Zakaria Mzaouali</style></AUTHOR></AUTHORS></CONTRIBUTORS><TITLES><TITLE><style face="normal" font="default" size="100%">Quantum annealers as programmable thermal machines</style></TITLE></TITLES><KEYWORDS/><DATES/><AUTHORS><style face="normal" font="default" size="100%"/></AUTHORS><YEAR><style face="normal" font="default" size="100%">2026</style></YEAR><SECONDARY_TITLE><style face="normal" font="default" size="100%">arxiv:2608.04564</style></SECONDARY_TITLE><URL><style face="normal" font="default" size="100%">https://arxiv.org/abs/2608.04564</style></URL><title><style face="normal" font="default" size="100%">Quantum annealers as programmable thermal machines</style></title></RECORD></records></xml>
