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Related papers: Determining QMC simulability with geometric phases

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A recent preprint by Mazzola and Carleo numerically investigates exponential challenges that can arise for the QC-QMC algorithm introduced in our work, "Unbiasing fermionic quantum Monte Carlo with a quantum computer." As discussed in our…

The "sign problem" (SP) is the fundamental limitation to simulations of strongly correlated materials in condensed matter physics, solving quantum chromodynamics at finite baryon density, and computational studies of nuclear matter. As a…

Strongly Correlated Electrons · Physics 2022-03-09 Rubem Mondaini , Sabyasachi Tarat , Richard T. Scalettar

The Fermi-Hubbard model, a fundamental framework for studying strongly correlated phenomena could significantly benefit from quantum simulations when exploring non-trivial settings. However, simulating this problem requires twice as many…

Quantum Physics · Physics 2024-02-05 Arian Vezvaee , Nathan Earnest-Noble , Khadijeh Najafi

Nonadiabatic geometric quantum computation (NGQC) has emerged as an excellent proposal for achieving fast and robust quantum control against control errors. However, previous NGQC protocols could not be strongly resilient against the noise…

Quantum Physics · Physics 2023-07-12 Tian-Xiang Hou , Wei Li

Monte Carlo simulations are a powerful tool for elucidating the properties of complex systems across many disciplines. Not requiring any a priori knowledge, they are particularly well suited for exploring new phenomena. However, when…

Strongly Correlated Electrons · Physics 2016-03-02 Mauro Iazzi , Alexey A. Soluyanov , Matthias Troyer

The quantum theory of antiferromagnetism in metals is necessary for our understanding of numerous intermetallic compounds of widespread interest. In these systems, a quantum critical point emerges as external parameters (such as chemical…

Strongly Correlated Electrons · Physics 2012-12-24 Erez Berg , Max A. Metlitski , Subir Sachdev

We discuss encodings of fermionic many-body systems by qubits in the presence of symmetries. Such encodings eliminate redundant degrees of freedom in a way that preserves a simple structure of the system Hamiltonian enabling quantum…

Quantum Physics · Physics 2017-01-31 Sergey Bravyi , Jay M. Gambetta , Antonio Mezzacapo , Kristan Temme

The phase diagram of a material is of central importance to describe the properties and behaviour of a condensed matter system. We prove that the general task of determining the quantum phase diagram of a many-body Hamiltonian is…

Quantum Physics · Physics 2021-02-03 Johannes Bausch , Toby S. Cubitt , James D. Watson

We consider the one-dimensional quantum-statistical problem of interacting spin-less particles in an infinite deep potential valley and on a ring. Several limits for the applicability of the Quantum Monte Carlo (QMC) methods were revealed…

Statistical Mechanics · Physics 2007-05-23 Z. Neda , Z. Dezso

We propose a new projector quantum Monte-Carlo method to investigate the ground state of ultracold fermionic atoms modeled by a lattice Hamiltonian with on-site interaction. The many-body state is reconstructed from Slater determinants that…

Other Condensed Matter · Physics 2007-07-26 Olivier Juillet

Recent years have seen unprecedented advance in the design and control of quantum computers. Nonetheless, their applicability is still restricted and access remains expensive. Therefore, a substantial amount of quantum algorithms research…

Quantum Physics · Physics 2020-12-11 Thomas Grurl , Richard Kueng , Jürgen Fuß , Robert Wille

In recent years, the Hamiltonian Monte Carlo (HMC) algorithm has been found to work more efficiently compared to other popular Markov Chain Monte Carlo (MCMC) methods (such as random walk Metropolis-Hastings) in generating samples from a…

Computation · Statistics 2014-02-18 Andrew L. Beam , Sujit K. Ghosh , Jon Doyle

We establish general conditions under which Markov chains produced by the Hamiltonian Monte Carlo method will and will not be geometrically ergodic. We consider implementations with both position-independent and position-dependent…

Computation · Statistics 2018-11-19 Samuel Livingstone , Michael Betancourt , Simon Byrne , Mark Girolami

We introduce the adiabatic quantum Monte Carlo (AQMC) method, where we gradually crank up the interaction strength, as an amelioration of the sign problem. It is motivated by the adiabatic theorem and will approach the true ground-state if…

Strongly Correlated Electrons · Physics 2021-11-18 Mohammad-Sadegh Vaezi , Amir-Reza Negari , Amin Moharramipour , Abolhassan Vaezi

Hamiltonian Monte Carlo is typically based on the assumption of an underlying canonical symplectic structure. Numerical integrators designed for the canonical structure are incompatible with motion generated by non-canonical dynamics. These…

Machine Learning · Statistics 2020-08-20 James A. Brofos , Roy R. Lederman

Quantum computers are expected to help us to achieve accurate simulation of the dynamics of many-body quantum systems. However, the limitations of current NISQ devices prevents us from realising this goal today. Recently an algorithm for…

Quantum Physics · Physics 2021-08-17 Jonathan Wei Zhong Lau , Kishor Bharti , Tobias Haug , Leong Chuan Kwek

The negative sign problem in quantum Monte Carlo (QMC) simulations of cluster impurity problems is the major bottleneck in cluster dynamical mean field calculations. In this paper we systematically investigate the dependence of the sign…

Strongly Correlated Electrons · Physics 2015-11-18 Hiroshi Shinaoka , Yusuke Nomura , Silke Biermann , Matthias Troyer , Philipp Werner

A powerful way to guarantee the absence of a sign problem in determinantal quantum Monte Carlo simulations is imposing a particular type of anti-unitary symmetries. It is shown that these same symmetries give rise to constraints on…

Strongly Correlated Electrons · Physics 2025-09-08 Xu Zhang , Nick Bultinck

We introduce a family of Hamiltonian systems for measurement-based quantum computation with continuous variables. The Hamiltonians (i) are quadratic, and therefore two body, (ii) are of short range, (iii) are frustration-free, and (iv)…

Quantum Physics · Physics 2011-03-01 Leandro Aolita , Augusto J. Roncaglia , Alessandro Ferraro , Antonio Acín

Sampling-based inference has seen a surge of interest in recent years. Hamiltonian Monte Carlo (HMC) has emerged as a powerful algorithm that leverages concepts from Hamiltonian dynamics to efficiently explore complex target distributions.…

Computation · Statistics 2026-04-07 Arghya Mukherjee , Dootika Vats
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