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Closed-system quantum annealing is expected to sometimes fail spectacularly in solving simple problems for which the gap becomes exponentially small in the problem size. Much less is known about whether this gap scaling also impedes…

Quantum Physics · Physics 2018-07-31 Anurag Mishra , Tameem Albash , Daniel A. Lidar

Quantum annealing provides a powerful platform for simulating magnetic materials and realizing statistical physics models, presenting a compelling alternative to classical Monte Carlo methods. We demonstrate that quantum annealers can…

We study the quantum relaxation of the two-dimensional transverse-field Ising model after global quenches with a real-time variational Monte Carlo method and address the question whether this non-integrable, two-dimensional system…

Statistical Mechanics · Physics 2017-01-18 Benjamin Blaß , Heiko Rieger

The shift of interest from general purpose quantum computers to adiabatic quantum computing or quantum annealing calls for a broadly applicable and easy to implement test to assess how quantum or adiabatic is a specific hardware. Here we…

Quantum Physics · Physics 2018-03-28 Bartłomiej Gardas , Jacek Dziarmaga , Wojciech H. Zurek , M. Zwolak

The ability to evaluate the outcomes of quantum annealers is essential for such devices to be used in complex computational tasks. We introduce a statistical test of the quality of Ising-based annealers' output based on the data only,…

Quantum Physics · Physics 2022-10-06 Krzysztof Domino , Mátyás Koniorczyk , Zbigniew Puchała

Quantum simulators and processors are rapidly improving nowadays, but they are still not able to solve complex and multidimensional tasks of practical value. However, certain numerical algorithms inspired by the physics of real quantum…

Quantum Physics · Physics 2019-12-19 Alexander E. Ulanov , Egor S. Tiunov , A. I. Lvovsky

Quantum annealing is a general strategy for solving difficult optimization problems with the aid of quantum adiabatic evolution. Both analytical and numerical evidence suggests that under idealized, closed system conditions, quantum…

Mapping finite-temperature dynamical phase diagrams of quantum many-body models is a necessary step towards establishing a framework of far-from-equilibrium quantum many-body universality. However, this is quite difficult due, in part, to…

Quantum Physics · Physics 2026-02-20 Lucas Katschke , Roland C. Farrell , Umberto Borla , Lode Pollet , Jad C. Halimeh

Quantum annealing is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. Quantum annealing in the transverse field Ising model, implemented on D-Wave…

Quantum Physics · Physics 2023-06-13 Elijah Pelofske

Quantum technology is maturing to the point where quantum devices, such as quantum communication systems, quantum random number generators and quantum simulators, may be built with capabilities exceeding classical computers. A quantum…

Relations of simulated annealing and quantum annealing are studied by a mapping from the transition matrix of classical Markovian dynamics of the Ising model to a quantum Hamiltonian and vice versa. It is shown that these two operators, the…

Quantum Physics · Physics 2015-01-08 Hidetoshi Nishimori , Junichi Tsuda , Sergey Knysh

Quantum devices are affected by intrinsic and environmental noises. An in-depth characterization of noise effects is essential for exploiting noisy quantum computing. To this end, we studied the energy dissipative behavior of a quantum…

Quantum Physics · Physics 2019-03-14 Tadashi Kadowaki , Masayuki Ohzeki

Quantum computation is a promising emerging technology, and by utilizing the principles of quantum mechanics, it is expected to achieve faster computations than classical computers for specific problems. There are two distinct architectures…

Quantum Physics · Physics 2025-03-13 Takashi Imoto , Yuki Susa , Ryoji Miyazaki , Yuichiro Matsuzaki

We study the effect of a thermal environment on the quantum annealing dynamics of a transverse-field Ising chain. The environment is modelled as a single Ohmic bath of quantum harmonic oscillators weakly interacting with the total…

Quantum Physics · Physics 2018-09-26 Luca Arceci , Simone Barbarino , Davide Rossini , Giuseppe E. Santoro

We provide a detailed description of the quantum interferometric thermometer, which is a device that estimates the temperature of a sample from the measurements of the optical phase. For the first time, we rigorously analyze the operation…

Quantum Physics · Physics 2015-09-15 Marcin Jarzyna , Marcin Zwierz

Drawing independent samples from high-dimensional probability distributions represents the major computational bottleneck for modern algorithms, including powerful machine learning frameworks such as deep learning. The quest for discovering…

Quantum Physics · Physics 2022-10-13 Marc Vuffray , Carleton Coffrin , Yaroslav A. Kharkov , Andrey Y. Lokhov

Recently, it was demonstrated both theoretically and experimentally on the D-Wave quantum annealer that transverse-field quantum annealing does not find all ground states with equal probability. In particular, it was proposed that more…

We design and implement a quantum laboratory to experimentally observe and study dynamical processes of quantum field theories. Our approach encodes the field theory as an Ising model, which is then solved by a quantum annealer. As a…

High Energy Physics - Theory · Physics 2021-03-31 Steven Abel , Michael Spannowsky

We face the problem of detecting and featuring footprints of quantum criticality in the finite-temperature behavior of quantum many-body systems. Our strategy is that of comparing the phase diagram of a system displaying a T=0 quantum phase…

Statistical Mechanics · Physics 2007-08-09 Alessandro Cuccoli , Alessio Taiti , Ruggero Vaia , Paola Verrucchi

Boltzmann machine is a powerful machine learning model with many real-world applications, for example by constructing deep belief networks. Statistical inference on a Boltzmann machine can be carried out by sampling from its posterior…

Quantum Physics · Physics 2023-11-23 Mārtiņš Kālis , Andris Locāns , Rolands Šikovs , Hassan Naseri , Andris Ambainis