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Related papers: Reducing the Sign Problem with Line Integrals

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A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

Monte Carlo methods play a central role in particle physics, where they are indispensable for simulating scattering processes, modeling detector responses, and performing multi-dimensional integrals. However, traditional Monte Carlo methods…

Quantum Physics · Physics 2025-10-14 Heechan Yi , Kayoung Ban , Myeonghun Park , Kyoungchul Kong

The Feynman path integral has revolutionized modern approaches to quantum physics. Although the path integral formalism has proven very successful and spawned several approximation schemes, the direct evaluation of real-time path integrals…

Quantum Physics · Physics 2025-01-28 Job Feldbrugge , Joshua Y. L. Jones

We present a strategy to alleviate the sign problem in continuous-time quantum Monte Carlo (CTQMC) simulations of the dynamical-mean-field-theory (DMFT) equations for the spin-orbit-coupled multiorbital Hubbard model. We first identify the…

Strongly Correlated Electrons · Physics 2020-01-22 Aaram J. Kim , Philipp Werner , Roser Valentí

The Hubbard model at finite chemical potential is a cornerstone for understanding doped correlated systems, but simulations are severely limited by the sign problem. In the auxiliary-field formulation, the spin basis mitigates the sign…

Strongly Correlated Electrons · Physics 2026-03-20 Dominic Schuh , Lena Funcke , Janik Kreit , Thomas Luu , Simran Singh

Despite the versatility of generalized linear mixed models in handling complex experimental designs, they often suffer from misspecification and convergence problems. This makes inference on the values of coefficients problematic. To…

Methodology · Statistics 2025-03-31 Angela Andreella , Jelle Goeman , Jesse Hemerik , Livio Finos

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

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 2009-10-30 J. F. Markham , T. D. Kieu

Path integrals describing quantum many-body systems can be calculated with Monte Carlo sampling techniques, but average quantities are often subject to signal-to-noise ratios that degrade exponentially with time. A phase-reweighting…

High Energy Physics - Lattice · Physics 2017-07-12 Michael L. Wagman , Martin J. Savage

The fermion sign problem remains the primary obstacle in simulating the thermodynamic properties of various fermionic systems. In this work, we present a sign-blocking method to mitigate the numerical instability inherent in the sign…

Computational Physics · Physics 2026-04-14 Yunuo Xiong , Hongwei Xiong

The reduction of a large number of scalar integrals to a small set of master integrals via Laporta's algorithm is common practice in multi-loop calculations. It is also a major bottleneck in terms of running time and memory consumption. It…

High Energy Physics - Phenomenology · Physics 2015-06-17 Philipp Kant

Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought to be estimated. In this paper, we survey the literature for…

We present methods for the numerical evaluation of the master integrals that appear in the calculation of scattering amplitudes at higher order in perturbative quantum field theory. We follow the general strategy of solving first-order…

High Energy Physics - Phenomenology · Physics 2025-01-06 Renato Maria Prisco , Jonathan Ronca , Francesco Tramontano

Over-parameterized deep models usually over-fit to a given training distribution, which makes them sensitive to small changes and out-of-distribution samples at inference time, leading to low generalization performance. To this end, several…

Computer Vision and Pattern Recognition · Computer Science 2019-12-12 Saeid Asgari Taghanaki , Kumar Abhishek , Ghassan Hamarneh

The problem of sampling according to the probability distribution minimizing a given free energy, using interacting particles unadjusted kinetic Langevin Monte Carlo, is addressed. In this setting, three sources of error arise, related to…

Probability · Mathematics 2024-12-05 Pierre Monmarché , Katharina Schuh

We solve numerically exactly a simple toy model to quantum general relativity or more properly to path integral on a curved space. We consider the thermal equilibrium of a quantum many body problem on the sphere, the surface of constant…

Quantum Gases · Physics 2026-03-25 Riccardo Fantoni

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

In a recent paper, Lucco Castello et al. [arXiv:2107.03537] provided an accurate parametrization of classical one-component plasma bridge functions that was embedded in a novel dielectric scheme for strongly coupled electron liquids. Here,…

Statistical Mechanics · Physics 2021-10-11 P. Tolias , F. Lucco Castello , T. Dornheim

We present a guiding principle for designing fermionic Hamiltonians and quantum Monte Carlo (QMC) methods that are free from the infamous sign problem by exploiting the Lie groups and Lie algebras that appear naturally in the Monte Carlo…

Strongly Correlated Electrons · Physics 2015-12-23 Lei Wang , Ye-Hua Liu , Mauro Iazzi , Matthias Troyer , Gergely Harcos

This paper focuses on signal processing tasks in which the signal is transformed from the signal space to a higher dimensional coefficient space (also called phase space) using a continuous frame, processed in the coefficient space, and…

Numerical Analysis · Mathematics 2021-09-14 Ron Levie , Haim Avron
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