Ultrafast dynamics in ferrimagnetic materials with a quantum Monte Carlo atomistic model
نویسندگان
چکیده
منابع مشابه
Iterative Monte Carlo for quantum dynamics.
We present a fully quantum mechanical methodology for calculating complex-time correlation functions by evaluating the discretized path integral expression iteratively on a grid selected by a Monte Carlo procedure. Both the grid points and the summations performed in each iteration utilize importance sampling, leading to favorable scaling with the number of particles, while the stepwise evaluat...
متن کاملQuantum Monte-Carlo for Non-Markovian dynamics
In fusion and fission processes, the reorganization of nucleons is fast with respect to the evolution of their relative distance and leads to dissipation in the motion of the nucleus. Thus, the internal degrees of freedom of the nucleus act as an environment which couples to the dynamics of the nucleus. One of the challenges in such an Open Quantum System is to incorporate non-Markovian effects...
متن کاملAb Initio Molecular Dynamics with Quantum Monte Carlo
Quantum Monte Carlo (QMC) is one of the most accurate electronic structure methods for ab initio many-body calculations in a broad range of electronic systems. Thanks to fast evolving massively parallel computers, much larger simulations of realistic systems become affordable. We have developed an ab initio simulation scheme at finite temperature based on molecular dynamics (MD) and QMC during ...
متن کاملAtomistic Monte Carlo Simulation of Lipid Membranes
Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sa...
متن کاملUltrafast Monte Carlo for Statistical Summations
Machine learning contains many computational bottlenecks in the form of nested summations over datasets. Computation of these summations is typically O(n) or higher, which severely limits application to large datasets. We present a multistage stratified Monte Carlo method for approximating such summations with probabilistic relative error control. The essential idea is fast approximation by sam...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review B
سال: 2017
ISSN: 2469-9950,2469-9969
DOI: 10.1103/physrevb.96.024441