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Randomness is an intrinsic feature of quantum theory. The outcome of any quantum measurement will be random, sampled from a probability distribution that is defined by the measured quantum state. The task of sampling from a prescribed…

Quantum Physics · Physics 2021-01-19 Dominik Hangleiter

Fermi gases in strongly coupled regimes, such as the unitary limit, are inherently challenging for many-body methods. Although much progress has been made with purely analytic methods, quantitative results require ab initio numerical…

Statistical Mechanics · Physics 2015-06-16 Dietrich Roscher , Jens Braun , Jiunn-Wei Chen , Joaquín E. Drut

Quantum Monte Carlo (QMC) methods are the gold standard for studying equilibrium properties of quantum many-body systems -- their phase transitions, ground and thermal state properties. However, in many interesting situations QMC methods…

Quantum Physics · Physics 2020-08-19 Dominik Hangleiter , Ingo Roth , Daniel Nagaj , Jens Eisert

We review recent attempts at dealing with the sign problem in Monte Carlo calculations by deforming the region of integration in the path integral from real to complex fields. We discuss the theoretical foundations, the algorithmic issues…

High Energy Physics - Lattice · Physics 2018-04-18 Paulo F. Bedaque

We present a new Monte Carlo algorithm for simulating quantum spin systems which is able to suppress the negative sign problem. This algorithm has only a linear complexity in the lattice size used for the simulation. A general description…

High Energy Physics - Lattice · Physics 2007-05-23 A. Galli

Monte Carlo simulations away from half-filling suffer from a sign problem that can be reduced by deforming the contour of integration. Such a transformation, which induces a Jacobian determinant in the Boltzmann weight, can be implemented…

Computational Physics · Physics 2022-09-30 Marcel Rodekamp , Evan Berkowitz , Christoph Gäntgen , Stefan Krieg , Thomas Luu , Johann Ostmeyer

We point out that Monte Carlo simulations of theories with severe sign problems can be profitably performed over manifolds in complex space different from the one with fixed imaginary part of the action. We describe a family of such…

High Energy Physics - Lattice · Physics 2016-03-22 Andrei Alexandru , Gokce Basar , Paulo F. Bedaque , Gregory W. Ridgway , Neill C. Warrington

We present a general technique for addressing sign problems that arise in Monte Carlo simulations of field theories. This method deforms the domain of the path integral to a manifold in complex field space that maximizes the average sign…

High Energy Physics - Lattice · Physics 2018-06-06 Andrei Alexandru , Paulo Bedaque , Henry Lamm , Scott Lawrence

Quantum Monte Carlo method is applied to fractional quantum Hall systems. The use of the linear programming method enables us to avoid the negative-sign problem in the Quantum Monte Carlo calculations. The formulation of this method and the…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Sei Suzuki , Tatsuya Nakajima

The numerical simulation of dynamical phenomena in interacting quantum systems is a notoriously hard problem. Although a number of promising numerical methods exist, they often have limited applicability due to the growth of entanglement or…

Quantum Physics · Physics 2021-09-08 Stefano De Nicola

Path integrals with complex actions are encountered for many physical systems ranging from spin- or mass-imbalanced atomic gases and graphene to quantum chromo-dynamics at finite density to the non-equilibrium evolution of quantum systems.…

High Energy Physics - Lattice · Physics 2022-09-01 Lukas Kades , Martin Gärttner , Thomas Gasenzer , Jan M. Pawlowski

We present a novel strategy to strongly reduce the severity of the sign problem, using line integrals along paths of changing imaginary action. Highly oscillating regions along these paths cancel out, decreasing their contributions. As a…

High Energy Physics - Lattice · Physics 2023-10-18 Rasmus N. Larsen

We propose a method for Monte Carlo simulations of systems with a complex action. The method has the advantages of being in principle applicable to any such system and provides a solution to the overlap problem. We apply it in random matrix…

High Energy Physics - Lattice · Physics 2017-08-23 Jan Ambjorn , Konstantinos N. Anagnostopoulos , Jun Nishimura , Jacobus J. M. Verbaarschot

We consider the numerical analysis of the inchworm Monte Carlo method, which is proposed recently to tackle the numerical sign problem for open quantum systems. We focus on the growth of the numerical error with respect to the simulation…

Numerical Analysis · Mathematics 2021-12-07 Zhenning Cai , Jianfeng Lu , Siyao Yang

Quantum Monte Carlo methods are sophisticated numerical techniques for simulating interacting quantum systems. In some cases, however, they suffer from the notorious "sign problem" and become too inefficient to be useful. A recent…

Strongly Correlated Electrons · Physics 2008-05-16 K. S. D. Beach , Matthieu Mambrini , Fabien Alet

We propose a method for Monte Carlo simulations of systems with a complex action. The method has the advantages of being in principle applicable to any such system and provides a solution to the overlap problem. In some cases, like in the…

High Energy Physics - Lattice · Physics 2009-11-10 J. Ambjorn , K. N. Anagnostopoulos , J. Nishimura , J. J. M. Verbaarschot

The multilevel blocking algorithm recently proposed as a possible solution to the sign problem in path-integral Monte Carlo simulations has been extended to systems with long-ranged interactions along the Trotter direction. As an…

Chemical Physics · Physics 2009-11-06 R. Egger , L. Muehlbacher , C. H. Mak

The infamous sign problem leads to an exponential complexity in Monte Carlo simulations of generic many-body quantum systems. Nevertheless, many phases of matter are known to admit a sign-problem-free representative, allowing efficient…

Strongly Correlated Electrons · Physics 2020-10-14 Omri Golan , Adam Smith , Zohar Ringel

In many real-world engineering systems, the performance or reliability of the system is characterised by a scalar parameter. The distribution of this performance parameter is important in many uncertainty quantification problems, ranging…

Methodology · Statistics 2022-10-03 Robert Millar , Jinglai Li , Hui Li

The partition function of a factor graph can sometimes be accurately estimated by Monte Carlo methods. In this paper, such methods are extended to factor graphs with negative and complex factors.

Computation · Statistics 2012-10-09 Mehdi Molkaraie , Hans-Andrea Loeliger