An efficient Monte Carlo algorithm for determining the minimum energy structures of metallic grain boundaries
نویسندگان
چکیده
منابع مشابه
Quantum Monte Carlo calculations for minimum energy structures.
We present an efficient method to find minimum energy structures using energy estimates from accurate quantum Monte Carlo calculations. This method involves a stochastic process formed from the stochastic energy estimates from Monte Carlo calculations that can be averaged to find precise structural minima while using inexpensive calculations with moderate statistical uncertainty. We demonstrate...
متن کاملAlgorithm and Data Structures for Efficient Energy Maintenance during Monte Carlo Simulation of Proteins
Monte Carlo simulation (MCS) is a common methodology to compute pathways and thermodynamic properties of proteins. A simulation run is a series of random steps in conformation space, each perturbing some degrees of freedom of the molecule. A step is accepted with a probability that depends on the change in value of an energy function. Typical energy functions sum many terms. The most costly one...
متن کاملnano-rods zno as an efficient catalyst for the synthesis of chromene phosphonates, direct amidation and formylation of amines
چکیده ندارد.
An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering
We propose an efficient sequential Monte Carlo inference scheme for the recently proposed coalescent clustering model [1]. Our algorithm has a quadratic runtime while those in [1] is cubic. In experiments, we were surprised to find that in addition to being more efficient, it is also a better sequential Monte Carlo sampler than the best in [1], when measured in terms of variance of estimated li...
متن کاملAn Energy-efficient Mathematical Model for the Resource-constrained Project Scheduling Problem: An Evolutionary Algorithm
In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...
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: Computational Materials Science
سال: 2018
ISSN: 0927-0256
DOI: 10.1016/j.commatsci.2018.09.017