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Related papers: Efficient Calculation of Energy Spectra Using Path…

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A recently developed method, introduced in Phys. Rev. Lett. 94 (2005) 180403, Phys. Rev. B 72 (2005) 064302, Phys. Lett. A 344 (2005) 84, systematically improved the convergence of generic path integrals for transition amplitudes. This was…

Statistical Mechanics · Physics 2011-08-08 Jelena Grujic , Aleksandar Bogojevic , Antun Balaz

We generalize a recently developed method for accelerated Monte Carlo calculation of path integrals to the physically relevant case of generic many-body systems. This is done by developing an analytic procedure for constructing a hierarchy…

Statistical Mechanics · Physics 2011-08-08 Aleksandar Bogojevic , Ivana Vidanovic , Antun Balaz , Aleksandar Belic

We investigate the properties of two standard energy estimators used in path-integral Monte Carlo simulations. By disentangling the variance of the estimators and their autocorrelation times we analyse the dependence of the performance on…

Condensed Matter · Physics 2009-10-30 Wolfhard Janke , Tilman Sauer

Path integral Monte Carlo with Green's function analysis allows the sampling of quantum mechanical properties of molecules at finite temperature. While a high-precision computation of the energy of the Born-Oppenheimer surface from path…

Quantum Physics · Physics 2007-05-23 Daejin Shin , Ming-Chak Ho , J. Shumway

We present and discuss a detailed derivation of a new analytical method that systematically improves the convergence of path integrals of a generic $N$-fold discretized theory. We develop an explicit procedure for calculating a set of…

Statistical Mechanics · Physics 2011-08-08 Aleksandar Bogojevic , Antun Balaz , Aleksandar Belic

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

Path integral Monte Carlo (PIMC) simulations are used to calculate the momentum distribution of the homogeneous electron gas at finite temperature. This is done by calculating the off-diagonal elements of the real-space density matrix,…

Statistical Mechanics · Physics 2007-05-23 B. Militzer , E. L. Pollock , D. M. Ceperley

Accurate path integral Monte Carlo or molecular dynamics calculations of isotope effects have until recently been expensive because of the necessity to reduce three types of errors present in such calculations: statistical errors due to…

Chemical Physics · Physics 2017-05-10 Konstantin Karandashev , Jiri Vanicek

We perform a thorough analysis on the choice of estimators for random series path integral methods. In particular, we show that both the thermodynamic (T-method) and the direct (H-method) energy estimators have finite variances and are…

Statistical Mechanics · Physics 2009-11-10 Cristian Predescu , Dubravko Sabo , J. D. Doll , David L. Freeman

We present full quantum statistical energetics of some electron-light nuclei systems. This is accomplished with the path integral Monte Carlo method. The effects on energetics arising from the change in the nuclear mass are studied. The…

Chemical Physics · Physics 2013-05-30 Ilkka Kylänpää , Tapio T. Rantala , David M. Ceperley

We present a methodology for accelerating the estimation of the free energy from path integral Monte Carlo simulations by considering an intermediate artificial reference system where interactions are inexpensive to evaluate numerically.…

We present Path Integral Monte Carlo C code for calculation of quantum mechanical transition amplitudes for 1D models. The SPEEDUP C code is based on the use of higher-order short-time effective actions and implemented to the maximal order…

Perturbation theory of large-scale structures of the Universe at next-to-leading order and next-to-next-to-leading order provides us with predictions of cosmological statistics at sub-percent level in the mildly non-linear regime. Its use…

Cosmology and Nongalactic Astrophysics · Physics 2021-11-08 Ken Osato , Takahiro Nishimichi , Atsushi Taruya , Francis Bernardeau

Accurately and efficiently estimating system performance under uncertainty is paramount in power system planning and operation. Monte Carlo simulation is often used for this purpose, but convergence may be slow, especially when detailed…

Computation · Statistics 2020-10-23 Simon Tindemans , Goran Strbac

The subject of the present study is the Monte Carlo path-integral evaluation of the moments of spectral functions. Such moments can be computed by formal differentiation of certain estimating functionals that are infinitely-differentiable…

Statistical Mechanics · Physics 2009-11-11 Cristian Predescu

This chapter is devoted to the computation of equilibrium (thermodynamic) properties of quantum systems. In particular, we will be interested in the situation where the interaction between particles is so strong that it cannot be treated as…

Mesoscale and Nanoscale Physics · Physics 2016-02-03 Alexei Filinov , Jens Böning , Michael Bonitz

This paper proposes several explicit and implicit multistep frequency response optimized integrators considering first or second order derivative. A prediction-based method aiming at accelerating a novel power system transient simulation…

Systems and Control · Electrical Eng. & Systems 2021-02-16 Sheng Lei , Alexander Flueck

A general method for computing kinetic isotope effects is described. The method uses the quantum-instanton approximation and is based on the thermodynamic integration with respect to the mass of the isotopes and on the path-integral…

Chemical Physics · Physics 2007-05-23 Jiri Vanicek , William H. Miller

We describe a path-integral ground-state quantum Monte Carlo method for light nuclei in continuous space. We show how to efficiently update and sample the paths with spin-isospin dependent and spin-orbit interactions. We apply the method to…

Nuclear Theory · Physics 2022-10-28 Rong Chen , Kevin E. Schmidt

The efficient evaluation of high-dimensional integrals is of importance in both theoretical and practical fields of science, such as data science, statistical physics, and machine learning. However, exact computation methods suffer from the…

Statistics Theory · Mathematics 2017-12-15 Radislav Vaisman , Robert Salomone , Dirk P. Kroese
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