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The inherent noise and complexity of quantum communication networks leads to challenges in designing quantum network protocols using classical methods. To address this issue, we develop a variational quantum optimization framework that…

Quantum Physics · Physics 2023-04-14 Brian Doolittle , Tom Bromley , Nathan Killoran , Eric Chitambar

Periodically driven quantum many-body systems exhibit novel nonequilibrium states such as prethermalization, discrete time crystals, and many-body localization. Recently, the general mechanism of fractional resonances has been proposed that…

Quantum Physics · Physics 2023-01-09 Ruben Peña , Thi Ha Kyaw , Guillermo Romero

Solving the Schr\"{o}dinger equation for interacting many-body quantum systems faces computational challenges due to exponential scaling with system size. This complexity limits the study of important phenomena in materials science and…

Materials Science · Physics 2024-05-27 Avishek Singh , Nirmal Ganguli

Motivated by the need for efficient estimation of conditional expectations, we consider a least-squares function approximation problem with heavily polluted data. Existing methods that are effective in the small-noise regime are suboptimal…

Machine Learning · Statistics 2026-05-26 Ben Adcock , Bernhard Hientzsch , Akil Narayan , Yiming Xu

The quench dynamics of the Hubbard model in tilted and harmonic potentials is discussed within the semiclassical picture. Applying the fermionic truncated Wigner approximation (fTWA), the dynamics of imbalances for charge and spin degrees…

Statistical Mechanics · Physics 2022-10-18 Aleksander Kaczmarek , Adam S. Sajna

We study Bosonic representation of spin Ising model with the application of simulating two level systems using continuous variable quantum processors. We decompose the time evolution of spin systems into a sequence of continuous variable…

Quantum Physics · Physics 2020-09-29 Razieh Annabestani , Brajesh Gupt , Bhaskar Roy Bardhan

Solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be complex. Here, based on energy variance, we propose a variational method for solving the…

Quantum Physics · Physics 2024-02-21 Xu-Dan Xie , Zheng-Yuan Xue , Dan-Bo Zhang

We propose a scheme for solving mixed-integer programming problems in which the optimization problem is translated to a ground-state preparation problem on a set of bosonic quantum field modes (qumodes). We perform numerical demonstrations…

Quantum Physics · Physics 2023-11-13 Farhad Khosravi , Artur Scherer , Pooya Ronagh

We study the problem of global maximization of a function f given a finite number of evaluations perturbed by noise. We consider a very weak assumption on the function, namely that it is locally smooth (in some precise sense) with respect…

Machine Learning · Computer Science 2026-04-28 Michal Valko , Alexandra Carpentier , Rémi Munos

In this work, the probability uncertainties related to a stationary quantum system with solitonic mass distribution when subjected to deformable hyperbolic potentials are studied. Shannon's entropy and Fisher's information of a…

Quantum Physics · Physics 2022-06-08 F. C. E. Lima

This paper studies the computational and statistical aspects of quantile and pseudo-Huber tensor decomposition. The integrated investigation of computational and statistical issues of robust tensor decomposition poses challenges due to the…

Statistics Theory · Mathematics 2023-09-07 Yinan Shen , Dong Xia

An essential component of many sophisticated metaheuristics for solving combinatorial optimization problems is some variation of a local search routine that iteratively searches for a better solution within a chosen set of immediate…

Quantum Physics · Physics 2025-02-05 M. Podobrii , V. Kuzmin , V. Voloshinov , M. Veshchezerova , M. R. Perelshtein

Learning the Hamiltonian underlying a quantum many-body system in thermal equilibrium is a fundamental task in quantum learning theory and experimental sciences. To learn the Gibbs state of local Hamiltonians at any inverse temperature…

Quantum Physics · Physics 2025-04-04 Chi-Fang Chen , Anurag Anshu , Quynh T. Nguyen

We analyze some crucial questions regarding the practical feasibility of quantum simulation for lattice gauge models. Our analysis focuses on two models suitable for the quantum simulation of the Schwinger Hamiltonian, or QED in 1+1…

Quantum Physics · Physics 2014-12-11 Stefan Kühn , J. Ignacio Cirac , Mari-Carmen Bañuls

Simulating high-weight Hamiltonians can convert local noise on the original Hamiltonian into undesirable nonlocal noise on the simulated Hamiltonian. Here we show how starting from two-local Hamiltonian in the presence of non-Markovian…

Quantum Physics · Physics 2017-11-29 Milad Marvian , Todd Brun , Daniel A. Lidar

Magnetic and superconducting instabilities in the two-dimensional t-t'-Hubbard model are discussed within a functional renormalization group approach. The fermionic four-point vertex is efficiently parametrized by means of partial…

Strongly Correlated Electrons · Physics 2013-05-29 S. Friederich , H. C. Krahl , C. Wetterich

The existence of topological zero modes in nontrivial phase of quantum Ising chain results in not only the Kramers-like degeneracy spectrum, but also dynamic response for non-Hermitian perturbation in the ordered phase (2021 Phys. Rev.…

Quantum Physics · Physics 2022-09-16 K. L. Zhang , Z. Song

Simulation of quantum systems is expected to be one of the most important applications of quantum computing, with much of the theoretical work so far having focused on fermionic and spin-$\frac{1}{2}$ systems. Here, we instead consider…

We consider nearly-integrable Hamiltonian systems defined over a non-resonant domain. In the neighborhood of resonances, we use Nekhoroshev-like estimates to provide effective stability bounds for the action variables over long time. The…

Dynamical Systems · Mathematics 2026-04-08 Alessandra Celletti , Anargyros Dogkas , Alessia Francesca Guido

Quadratic Unconstrained Binary Optimization (QUBO) problems are prevalent in various applications and are known to be NP-hard. The seminal work of Goemans and Williamson introduced a semidefinite programming (SDP) relaxation for such…

Quantum Physics · Physics 2025-10-10 Haomu Yuan , Daniel Stilck França , Ilia Luchnikov , Egor Tiunov , Tobias Haug , Leandro Aolita
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