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We have developed a technique to accelerate the acquisition of effectively uncorrelated configurations for off-lattice models of dense polymer melts which makes use of both parallel tempering and large scale Monte Carlo moves. The method is…

Soft Condensed Matter · Physics 2009-10-31 Alex Bunker , Burkhard Duenweg

We introduce the 'smooth gate', an entangling method for trapped-ion qubits where residual spin-motion entanglement errors are adiabatically eliminated by ramping the gate detuning. We demonstrate electronically controlled two-qubit gates…

Markov chain Monte Carlo algorithms have important applications in counting problems and in machine learning problems, settings that involve estimating quantities that are difficult to compute exactly. How much can quantum computers speed…

Quantum Physics · Physics 2020-02-10 Aram W. Harrow , Annie Y. Wei

Parallel tempering is a generic Markov chain Monte Carlo sampling method which allows good mixing with multimodal target distributions, where conventional Metropolis-Hastings algorithms often fail. The mixing properties of the sampler…

Computation · Statistics 2012-05-08 Blazej Miasojedow , Eric Moulines , Matti Vihola

One of the most fundamental problems in quantum many-body physics is the characterization of correlations among thermal states. Of particular relevance is the thermal area law, which justifies the tensor network approximations to thermal…

Quantum Physics · Physics 2021-03-12 Tomotaka Kuwahara , Álvaro M. Alhambra , Anurag Anshu

We take advantage of recent improvements in the grand canonical Hybrid Monte Carlo (HMC) algorithm, to perform a precision study of the single-particle gap in the hexagonal Hubbard model, with on-site electron-electron interactions. After…

Strongly Correlated Electrons · Physics 2021-11-01 Johann Ostmeyer

As has been shown elsewhere, a reasonable model of the loss of entanglement or correlation that occurs in quantum computations is one which assumes that they can effectively be predicted by a framework that presupposes the presence of…

A complex but important challenge in understanding quantum mechanical phenomena is the simulation of quantum many-body dynamics. Although quantum computers offer significant potential to accelerate these simulations, their practical…

Quantum Physics · Physics 2025-09-26 Gian Gentinetta , Friederike Metz , Giuseppe Carleo

The Markov entropy decomposition (MED) is a recently-proposed, cluster-based simulation method for finite temperature quantum systems with arbitrary geometry. In this paper, we detail numerical algorithms for performing the required steps…

Statistical Mechanics · Physics 2013-05-29 Andrew J. Ferris , David Poulin

We are concerned with the computation of the mean-time-to-absorption (MTTA) for a large system of loosely interconnected components, modeled as continuous time Markov chains. In particular, we show that splitting the local and…

Numerical Analysis · Mathematics 2019-07-05 Leonardo Robol , Giulio Masetti

Thermoelectric coolers (TECs) offer a promising solution for direct cooling of local hotspots and active thermal management in advanced electronic systems. However, TECs present significant trade-offs among spatial cooling, heating and…

Applied Physics · Physics 2024-07-17 Jiajian Luo , Jaeho Lee

We extend the formalism of pure state thermodynamics to matrix product states. In pure state thermodynamics finite temperature properties of quantum systems are derived without the need of statistical mechanics ensembles, but instead using…

Quantum Physics · Physics 2013-10-31 Silvano Garnerone

We introduce a tensor network method for approximating thermal equilibrium states of quantum many-body systems at low temperatures. Whereas the usual approach starts from infinite temperature and evolves the state in imaginary time (toward…

Quantum Physics · Physics 2025-10-23 Denise Cocchiarella , Mari Carmen Bañuls

We present a protocol to experimentally measure the infinite-temperature out-of-time-ordered correlation (OTOC) -- which is a probe of quantum information scrambling in a system -- for systems with a Hamiltonian which has either a chiral…

Quantum Physics · Physics 2020-06-29 Bhuvanesh Sundar

The Hubbard model is a longstanding problem in the theory of strongly correlated electrons and a very active one in the experiments with ultracold fermionic atoms. Motivated by current and prospective quantum simulations, we apply a…

Strongly Correlated Electrons · Physics 2022-11-07 Aritra Sinha , Marek M. Rams , Piotr Czarnik , Jacek Dziarmaga

In the microcanonical thermal pure quantum (mTPQ) method, the canonical ensemble is derived using Taylor series expansions. We prove that the truncation error decreases exponentially with system size when the effective temperature of the…

Statistical Mechanics · Physics 2024-11-06 Atsushi Iwaki

Precise determination of thermodynamic parameters in ultracold Bose gases remains challenging due to the destructive nature of conventional measurement techniques and inherent experimental uncertainties. We demonstrate a machine learning…

Quantum Gases · Physics 2025-10-29 Jack Griffiths , Steven A. Wrathmall , Simon A. Gardiner

Path-integral techniques are a powerful tool used in open quantum systems to provide an exact solution for the non-Markovian dynamics. However, the exponential scaling of the tensor size with quantum memory length of these techniques limits…

Quantum Physics · Physics 2025-08-25 L. M. J. Hall , A. Gisdakis , E. A. Muljarov

We report the quantum process tomography of a M$\o$lmer-S$\o$rensen entangling gate. The tomographic protocol relies on a single discriminatory transition, exploiting excess micromotion in the trap to realize all operations required to…

Quantum Physics · Physics 2015-06-17 Nir Navon , Nitzan Akerman , Shlomi Kotler , Yinnon Glickman , Roee Ozeri

The adaptive variational quantum dynamics simulation (AVQDS) method performs real-time evolution of quantum states using automatically generated parameterized quantum circuits that often contain substantially fewer gates than Trotter…

Quantum Physics · Physics 2025-06-23 Feng Zhang , Cai-Zhuang Wang , Thomas Iadecola , Peter P. Orth , Yong-Xin Yao
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