In the past two decades, the simulated annealing technique has been considered as a powerful approach to handle many NP-hard optimization problems in VLSI designs. Recently, a new Monte Carlo and optimization technique, named simulated tempering, was invented and has been successfully applied to many scientific problems, from random field Ising modeling to the traveling salesman problem. It is ...

the aim of the present study was to investigate the effect of quenching and tempering temperatures on themicrostructure, mechanical properties and the wear characteristics of medium carbon-high chromium wear resistantsteel. in addition, the dominant wear mechanisms were studied. for this purpose, austenitizing and temperingtemperatures were selected in the ranges of 900- 1000 °c and 300- 500 °c...

Population annealing is a Monte Carlo algorithm that marries features from simulated-annealing and parallel-tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a Hamiltonian. Thus, population-annealing Monte Carlo can be used as a heuristic to solve combinatorial optimization problems. We illustrate the capabilities of popu...

Tail estimates are developed for power law probability distributions with exponential tempering using a conditional maximum likelihood approach based on the upper order statistics. The method is demonstrated on simulated data from a tempered stable distribution, and for several data sets from geophysics and finance that show a power law probability tail with some tempering.

The heat capacity and isomer distributions of the 38-atom Lennard-Jones cluster have been calculated in the canonical ensemble using parallel tempering Monte Carlo methods. A distinct region of temperature is identified that corresponds to equilibrium between the global minimum structure and the icosahedral basin of structures. This region of temperatures occurs below the melting peak of the he...

The free-energy landscape of the alpha-helix of protein G is studied by means of metadynamics coupled with a solute tempering algorithm. Metadynamics allows to overcome large energy barriers, whereas solute tempering improves the sampling with an affordable computational effort. From the sampled free-energy surface we are able to reproduce a number of experimental observations, such as the fact...

Restricted Boltzmann Machines (RBMs) are one of the fundamental building blocks of deep learning. Approximate maximum likelihood training of RBMs typically necessitates sampling from these models. In many training scenarios, computationally efficient Gibbs sampling procedures are crippled by poor mixing. In this work we propose a novel method of sampling from Boltzmann machines that demonstrate...

intermittent drying is a satisfactory technique for drying of heat sensitive grains especially rough rice. this method consists of two separate stages applied intermittently: drying and tempering. in this work, intermittent drying of rough rice is investigated both theoretically and experimentally. in order to characterize this process; a multi-scale model consisting of macroscopic and microsco...