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We propose a novel approach toward the general solution of the sign problem in real-time path-integral simulations. Using a recursive multilevel blocking strategy, this method circumvents the sign problem by synthesizing the phase…

Chemical Physics · Physics 2009-10-31 C. H. Mak , R. Egger

The sign problem is a major obstacle in quantum Monte Carlo simulations for many-body fermion systems. We examine this problem with a new perspective based on the Majorana reflection positivity and Majorana Kramers positivity. Two…

Strongly Correlated Electrons · Physics 2018-01-19 Z. C. Wei , Congjun Wu , Yi Li , Shiwei Zhang , T. Xiang

We consider the problem of adaptive stratified sampling for Monte Carlo integration of a noisy function, given a finite budget n of noisy evaluations to the function. We tackle in this paper the problem of adapting to the function at the…

Machine Learning · Statistics 2013-03-13 Alexandra Carpentier , Remi Munos

Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fundamental in many applications like diagnosis, natural…

Artificial Intelligence · Computer Science 2012-06-18 Hannaneh Hajishirzi , Eyal Amir

Monte-Carlo simulations are routinely used for estimating the scaling exponents of complex systems. However, due to finite-size effects, determining the exponent values is often difficult and not reliable. Here we present a novel technique…

Computational Physics · Physics 2013-03-05 Indrek Mandre , Jaan Kalda

Many random processes can be simulated as the output of a deterministic model accepting random inputs. Such a model usually describes a complex mathematical or physical stochastic system and the randomness is introduced in the input…

Machine Learning · Statistics 2012-11-21 A. Gokcen Mahmutoglu , Alper T. Erdogan , Alper Demir

The notorious sign problem severely limits the applicability of quantum Monte Carlo (QMC) simulations, as statistical errors grow exponentially with system size and inverse temperature. A recent proposal of a quantum-computing stochastic…

Quantum Physics · Physics 2026-03-11 Kwai-Kong Ng , Min-Fong Yang

The problem of optimising functions with intractable gradients frequently arise in machine learning and statistics, ranging from maximum marginal likelihood estimation procedures to fine-tuning of generative models. Stochastic approximation…

Machine Learning · Statistics 2026-01-30 James Cuin , Davide Carbone , Yanbo Tang , O. Deniz Akyildiz

The Monte Carlo shell model is a powerful technique for computational nuclear structure. Only a certain class of nuclear interactions, however, such as pairing and quadrupole, are free of the numerical noise known as the sign problem.This…

Nuclear Theory · Physics 2009-10-31 C. W. Johnson , D. J. Dean

Monte Carlo algorithms are barely considered in spin foam quantum gravity. Due to the quantum nature of spin foam amplitudes one cannot readily apply them, and the present sign problem is a threat to convergence and thus efficiency. Yet,…

General Relativity and Quantum Cosmology · Physics 2024-07-25 Sebastian Steinhaus

The computational cost of a Monte Carlo algorithm can only be meaningfully discussed when taking into account the magnitude of the resulting statistical error. Aiming for a fixed error per particle, we study the scaling behavior of the…

Computational Physics · Physics 2010-02-11 Norbert Nemec

Monte Carlo sampling methods often suffer from long correlation times. Consequently, these methods must be run for many steps to generate an independent sample. In this paper a method is proposed to overcome this difficulty. The method…

Computation · Statistics 2007-09-13 Jonathan Weare

A brief introduction to the technique of Monte Carlo simulations in statistical physics is presented. The topics covered include statistical ensembles random and pseudo random numbers, random sampling techniques, importance sampling, Markov…

Statistical Mechanics · Physics 2016-08-31 K. P. N. Murthy

The path integral formulation of quantum mechanical problems including fermions is often affected by a severe numerical sign problem. We show how such a sign problem can be alleviated by a judiciously chosen constant imaginary offset to the…

Strongly Correlated Electrons · Physics 2024-10-23 Christoph Gäntgen , Evan Berkowitz , Thomas Luu , Johann Ostmeyer , Marcel Rodekamp

Astronomers are often confronted with funky populations and distributions of objects: brighter objects are more likely to be detected; targets are selected based on colour cuts; imperfect classification yields impure samples. Failing to…

Cosmology and Nongalactic Astrophysics · Physics 2017-06-21 Samuel R. Hinton , Alex Kim , Tamara M. Davis

Monte Carlo simulations are widely used in many areas including particle accelerators. In this lecture, after a short introduction and reviewing of some statistical backgrounds, we will discuss methods such as direct inversion, rejection…

Computational Physics · Physics 2020-06-19 Ji Qiang

We study the hardness of classically simulating Gaussian boson sampling at nonzero photon distinguishability. We find that similar to regular boson sampling, distinguishability causes exponential attenuation of the many-photon interference…

Quantum Physics · Physics 2020-07-08 Jelmer J. Renema

A simulation method based on the RG blocking is shown to yield statistical errors smaller than that of the crude MC using absolute values of the original measures. The new method is particularly suitable to apply to the sign problem of…

High Energy Physics - Lattice · Physics 2007-05-23 J. F. Markham , T. D. Kieu

This work shows that the recently discovered operator contraction identity for solving the discreet Path Integral of the harmonic oscillator can be applied equally to fermions in any dimension. This then yields an exactly solvable model for…

Strongly Correlated Electrons · Physics 2026-04-21 Siu A. Chin

We study a diagnostic strategy which is based on the anticipation of the diagnostic process by simulation of the dynamical process starting from the initial findings. We show that such a strategy could result in more accurate diagnoses…

Biological Physics · Physics 2018-04-04 Alireza Mashaghi , Abolfazl Ramezanpour