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We study the exact solution for a two-mode model describing coherent coupling between atomic and molecular Bose-Einstein condensates (BEC), in the context of the Bethe ansatz. By combining an asymptotic and numerical analysis, we identify…

Statistical Mechanics · Physics 2009-11-07 Huan-Qiang Zhou , Jon Links , Ross H. McKenzie

This article unveils a new relation between the Nishimori temperature parametrizing a distribution P and the Bethe free energy on random Erdos-Renyi graphs with edge weights distributed according to P. Estimating the Nishimori temperature…

Machine Learning · Statistics 2021-09-27 Lorenzo Dall'Amico , Romain Couillet , Nicolas Tremblay

Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a given discrete objective function. An interpretation of such a function as the energy of a classical system allows us to reduce the…

Quantum Physics · Physics 2015-06-22 Sergio Boixo , Gerardo Ortiz , Rolando Somma

By instantaneously changing a global parameter in an extended quantum system, an initially equilibrated state will afterwards undergo a complex non-equilibrium unitary evolution whose description is extremely challenging. A non-perturbative…

Strongly Correlated Electrons · Physics 2010-05-11 Alexandre Faribault , Pasquale Calabrese , Jean-Sébastien Caux

We define and study an inference algorithm based on "belief propagation" (BP) and the Bethe approximation. The idea is to encode into a graph an a priori information composed of correlations or marginal probabilities of variables, and to…

Physics and Society · Physics 2007-05-23 Cyril Furtlehner , Jean-Marc Lasgouttes , Arnaud De La Fortelle

Concise and reliable modeling for aggregating power flexibility of distributed energy resources in active distribution networks (ADNs) is a crucial technique for coordinating transmission and distribution networks. Our recent research has…

Systems and Control · Electrical Eng. & Systems 2023-12-11 Yilin Wen , Zechun Hu , Jinhua He , Yi Guo

Bayesian methods which utilize Bayes' theorem to update the knowledge of desired parameters after each measurement, are used in a wide range of quantum science. For various applications in quantum science, efficiently and accurately…

Quantum Physics · Physics 2021-07-02 Chengyin Han , Jiahao Huang , Xunda Jiang , Ruihuan Fang , Yuxiang Qiu , Bo Lu , Chaohong Lee

An exact method to compute the entire equilibrium reduced density matrix for systems characterized by a system-bath Hamiltonian is presented. The approach is based upon a stochastic unraveling of the influence functional that appears in the…

Mesoscale and Nanoscale Physics · Physics 2015-06-04 Jeremy M. Moix , Yang Zhao , Jianshu Cao

The tomographic reconstruction of the state of a quantum-mechanical system is an essential component in the development of quantum technologies. We present an overview of different tomographic methods for determining the quantum-mechanical…

Quantum Physics · Physics 2016-02-09 Roman Schmied

In the framework of noisy quantum homodyne tomography with efficiency parameter $1/2 < \eta \leq 1$, we propose a novel estimator of a quantum state whose density matrix elements $\rho_{m,n}$ decrease like $Ce^{-B(m+n)^{r/ 2}}$, for fixed…

Statistics Theory · Mathematics 2014-02-11 P Alquier , K Meziani , G Peyré

Recently a novel approach to find approximate exchange-correlation functionals in density-functional theory (DFT) was presented (U. Mordovina et. al., JCTC 15, 5209 (2019)), which relies on approximations to the interacting wave function…

Chemical Physics · Physics 2021-03-04 Iris Theophilou , Teresa E. Reinhard , Angel Rubio , Michael Ruggenthaler

We prove that the lowest free energy of a classical interacting system at temperature $T$ with a prescribed density profile $\rho(x)$ can be approximated by the local free energy $\int f_T(\rho(x))dx$, provided that $\rho$ varies slowly…

Mathematical Physics · Physics 2024-08-28 Michal Jex , Mathieu Lewin , Peter Madsen

We propose an energy-driven stochastic master equation for the density matrix as a dynamical model for quantum state reduction. In contrast, most previous studies of state reduction have considered stochastic extensions of the Schr\"odinger…

Quantum Physics · Physics 2016-12-30 Dorje C. Brody , Lane P. Hughston

Most methods for estimating configurational entropy from molecular simulation data yield upper limits except for harmonic systems where they are exact. Problems arise at diffusive systems and the presence of conformational transitions.…

Chemical Physics · Physics 2019-10-22 Jürgen Schlitter , Matthias Massarczyk

High precision measurements are essential to solve major scientific and technological challenges, from gravitational wave detection to healthcare diagnostics. Quantum sensing delivers greater precision, but an in-depth optimisation of…

In this work, we show how to parameterize a density matrix that has an arbitrary symmetry, knowing the generators of the Lie algebra (if the symmetry group is a connected Lie group) or the generators of its underlying group (in case it is…

Quantum Physics · Physics 2023-01-25 Inés Corte , Marcelo Losada , Diego Tielas , Federico Holik , Lorena Rebón

The likelihood-free sequential Approximate Bayesian Computation (ABC) algorithms, are increasingly popular inference tools for complex biological models. Such algorithms proceed by constructing a succession of probability distributions over…

Computation · Statistics 2012-10-12 Daniel Silk , Saran Filippi , Michael P. H. Stumpf

Properties that are necessarily formulated within pure (symmetric) expectation values are difficult to calculate for projector quantum Monte Carlo approaches, but are critical in order to compute many of the important observable properties…

Computational Physics · Physics 2015-06-23 Catherine Overy , George H. Booth , N. S. Blunt , James Shepherd , Deidre Cleland , Ali Alavi

The achievement of Bose-Einstein condensation (BEC) in ultracold vapors of alkali atoms has given enormous impulse to the theoretical and experimental study of dilute atomic gases in condensed quantum states inside magnetic traps and…

Mathematical Physics · Physics 2017-11-21 Weizhu Bao

We present new algorithms and fast implementations to find efficient approximations for modelling stochastic processes. For many numerical computations it is essential to develop finite approximations for stochastic processes. While the…

Optimization and Control · Mathematics 2020-12-03 Kipngeno Benard Kirui , Georg Ch. Pflug , Alois Pichler
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