Results 101 to 110 of about 926,631 (217)
Quantum Monte Carlo calculations of the potential energy curve of the helium dimer [PDF]
arXiv, 2010 We report results of both the Diffusion Quantum Monte Carlo (DMC) and Reptation Quantum Monte Carlo (RMC) methods on the potential energy curve of the helium dimer. We show that it is possible to obtain a highly accurate description of the helium dimer. An improved stochastic reconfiguration technique is employed to optimize the many-body wave function,
arxiv
Quantum Monte Carlo calculations of light nuclei [PDF]
Exotic nuclei and atomic masses (ENAM 98), 1998 Variational Monte Carlo and Green's function Monte Carlo are powerful tools for calculations of properties of light nuclei using realistic two-nucleon and three-nucleon potentials. Recently the GFMC method has been extended to multiple states with the same quantum numbers.
openaire +6 more sources
Scaling analysis and instantons for thermally assisted tunneling and quantum Monte Carlo simulations [PDF]
, 2016 We develop an instantonic calculus to derive an analytical expression for the thermally-assisted tunneling decay rate of a metastable state in a fully connected quantum spin model. The tunneling decay problem can be mapped onto the Kramers escape problem
Zhang Jiang +6 more
semanticscholar +1 more source
Inkjet Printed Multifunctional Graphene Sensors for Flexible and Wearable Electronics
Advanced Electronic Materials, EarlyView.The sensitivity of electrical properties of graphene to external stimuli are used to demonstrate multifunctional inkjet‐printed graphene sensors for the detection of pressure, temperature, humidity, and magnetic field. By combining the design freedom of inkjet printing with the unique properties of graphene, multifunctional devices are achieved ...
Feiran Wang +10 more
wiley +1 more source
MontePython: Implementing Quantum Monte Carlo using Python [PDF]
, 2006 We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and diffusion Monte Carlo and we describe how to implement theses methods in pure C++ and C++/Python.
arxiv +1 more source
Boosting the accuracy and speed of quantum Monte Carlo: Size consistency and time step [PDF]
, 2016 Diffusion Monte Carlo (DMC) simulations for fermions are becoming the standard for providing high-quality reference data in systems that are too large to be investigated via quantum chemical approaches.
Andrea Zen +4 more
semanticscholar +1 more source
Advanced Electronic Materials, EarlyView.A compact model for ferroelectric thin‐film capacitors operating under different electric fields and temperatures is reported. The model can reproduce polarization switching down to 4 K, making them suitable for quantum computing and space technologies.
Ella Paasio +2 more
wiley +1 more source
Analytic Continuation of Quantum Monte Carlo Data by Stochastic Analytical Inference [PDF]
, 2009 We present an algorithm for the analytic continuation of imaginary-time quantum Monte Carlo data which is strictly based on principles of Bayesian statistical inference. Within this framework we are able to obtain an explicit expression for the calculation of a weighted average over possible energy spectra, which can be evaluated by standard Monte ...
arxiv +1 more source
Using Dopants as Agents to Probe Key Electronic Properties of Organic Semiconductors
Advanced Electronic Materials, EarlyView.Dopants are typically used in organic electronics to enhance conductivity, but here their potential is demonstrated as probes for fundamental material properties. By integrating experimental data and multiscale simulations, it is shown how dopant ionization and conductivity measurements enable accurate extraction of ionization potential and Coulomb ...
Artem Fediai +3 more
wiley +1 more source
The Lognormal Distribution and Quantum Monte Carlo Data [PDF]
arXiv, 2003 Quantum Monte Carlo data are often afflicted with distributions that resemble lognormal probability distributions and consequently their statistical analysis can not be based on simple Gaussian assumptions. To this extent a method is introduced to estimate these distributions and thus give better estimates to errors associated with them. This method is
arxiv