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Diffusion models enable the synthesis of highly accurate samples from complex distributions and have become foundational in generative modeling. Recently, they have demonstrated significant potential for solving Bayesian inverse problems by…

Machine Learning · Computer Science 2025-10-17 Yazid Janati , Alain Durmus , Jimmy Olsson , Eric Moulines

Herein, we present a new method to efficiently calculate electronically excited states in large molecular assemblies, consisting of hundreds of molecules. For this purpose, we combine the long-range corrected tight-binding…

Chemical Physics · Physics 2023-02-08 Richard Einsele , Joscha Hoche , Roland Mitric

Recently developed neural network-based \emph{ab-initio} solutions (Pfau et. al arxiv:1909.02487v2) for finding ground states of fermionic systems can generate state-of-the-art results on a broad class of systems. In this work, we improve…

Chemical Physics · Physics 2021-03-26 Max Wilson , Nicholas Gao , Filip Wudarski , Eleanor Rieffel , Norm M. Tubman

A diffusion Monte Carlo simulation of superfluid $^4$He at zero temperature and pressures up to 275 bar is presented. Increasing the pressure beyond freezing ($\sim$ 25 bar), the liquid enters the overpressurized phase in a metastable…

Other Condensed Matter · Physics 2009-11-11 L. Vranjes , J. Boronat , J. Casulleras , C. Cazorla

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real, nonnegative amplitudes. This raises the question of whether classical Monte Carlo algorithms…

Quantum Physics · Physics 2018-02-21 Jacob Bringewatt , William Dorland , Stephen P. Jordan , Alan Mink

Normal states of the attractive Hubbard model, especially in two dimension, are studied in the light of a transition from a Fermi liquid to an insulating or gapped state. A series of variational Monte Carlo calculations with better…

Strongly Correlated Electrons · Physics 2009-11-07 Hisatoshi Yokoyama

We introduce a Monte Carlo algorithm to efficiently compute transport properties of chaotic dynamical systems. Our method exploits the importance sampling technique that favors trajectories in the tail of the distribution of displacements,…

Statistical Mechanics · Physics 2018-05-25 Diego Tapias , David P. Sanders , Eduardo G. Altmann

We study the coupled two-species non-equilibrium reaction-controlled diffusion model introduced by Trimper et al. [Phys. Rev. E 62, 6071 (2000)] by means of detailed Monte Carlo simulations in one and two dimensions. Particles of type A may…

Statistical Mechanics · Physics 2009-11-10 Beth A. Reid , Jason C. Brunson , Uwe C. Tauber

Multi-dimensional density of states provides a useful description of complex frustrated systems. Recent advances in Monte Carlo methods enable efficient calculation of the density of states and related quantities, which renew the interest…

Disordered Systems and Neural Networks · Physics 2009-11-10 Yukito Iba , Hisanao Takahashi

We propose a novel Monte-Carlo based ab-initio algorithm for directly computing the statistics for quantities of interest in an immiscible two-phase compressible flow. Our algorithm samples the underlying probability space and evolves these…

Numerical Analysis · Mathematics 2023-03-30 Marco Petrella , Remi Abgrall , Siddhartha Mishra

A Monte Carlo method is presented to evaluate quantum states with many particles moving in the continuum. The scattering state is generated at each time by a Monte Carlo random sampling algorithm. The same calculation are repeated until the…

Nuclear Theory · Physics 2013-06-06 Zhen-Xiang Xu , Chong Qi

A Quadratic Diffusion Monte Carlo method has been used to obtain the equation of state of liquid $^4$He including the negative pressure region down to the spinodal point. The atomic interaction used is a renewed version (HFD-B(HE)) of the…

Condensed Matter · Physics 2009-10-22 J. Boronat , J. Casulleras , J. Navarro

The computation of free energies is a common issue in statistical physics. A natural technique to compute such high dimensional integrals is to resort to Monte Carlo simulations. However these techniques generally suffer from a high…

Statistical Mechanics · Physics 2021-05-17 Grégoire Ferré , Tobias Grafke

The possibility of using quantum computers for electronic structure calculations has opened up a promising avenue for computational chemistry. Towards this direction, numerous algorithmic advances have been made in the last five years. The…

We independently develop a simulation code following the previous dynamical Monte Carlo simulation of the diffusive shock acceleration under the isotropic scattering law during the scattering process, and the same results are obtained.…

Earth and Planetary Astrophysics · Physics 2015-05-20 Xin Wang , Yihua Yan

We investigate ways of accurately simulating the propagation of energetic charged particles over small times where the standard Monte Carlo approximation to diffusive transport breaks down. We find that a small-angle scattering procedure…

Astrophysics · Physics 2009-11-07 R. J. Protheroe , A. Meli , A. -C Donea

We calculate the efficiency of a rejection-free dynamic Monte Carlo method for $d$-dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential $r^{-p}$. Theoretically we find the algorithmic efficiency…

Statistical Mechanics · Physics 2009-11-13 Marta L. Guerra , M. A. Novotny , Hiroshi Watanabe , Nobuyasu Ito

We investigate energy transport in several two-level atom or spin-1/2 models by a direct coupling to heat baths of different temperatures. The analysis is carried out on the basis of a recently derived quantum master equation which…

Quantum Physics · Physics 2009-11-13 Mathias Michel , Ortwin Hess , Hannu Wichterich , Jochen Gemmer

The correlation energy of the homogeneous three-dimensional interacting electron gas is calculated using the variational and fixed-node diffusion Monte Carlo methods, with trial functions that include backflow and three-body correlations.…

Strongly Correlated Electrons · Physics 2009-10-31 Yongkyung Kwon , D. M. Ceperley , Richard M. Martin

The essence of atomic structure theory, quantum chemistry, and computational materials science is solving the multi-electron stationary Schr\"odinger equation. The Quantum Monte Carlo-based neural network wave function method has surpassed…

Atomic Physics · Physics 2023-12-27 JinDe Liu , Chenglong Qin , Xi He , Gang Jiang
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