A Quantum Monte Carlo Approach to the Adiabatic Connection Method

نویسنده

  • Maziar Nekovee
چکیده

We present a new method for realizing the adiabatic connection approach in density functional theory, which is based on combining accurate variational quantum Monte Carlo calculations with a constrained optimization of the ground state many-body wavefunction for different values of the Coulomb coupling constant. We use the method to study an electron gas in the presence of a cosine-wave potential. For this system we present results for the exchange-correlation hole and exchange-correlation energy density, and compare our findings with those from the local density approximation and generalized gradient approximation.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Generalized valence bond wave functions in quantum Monte Carlo.

We present a technique for using quantum Monte Carlo (QMC) to obtain high quality energy differences. We use generalized valence bond (GVB) wave functions, for an intuitive approach to capturing the important sources of static correlation, without needing to optimize the orbitals with QMC. Using our modifications to Walker branching and Jastrows, we can then reliably use diffusion quantum Monte...

متن کامل

A quantum Monte Carlo calculation of the ground state energy of the hydrogen molecule

We have calculated the ground state energy of the hydrogen molecule using the quantum Monte Carlo (QMC) method of solving the Schrodinger equation, without the use of the Born-Oppenheimer or any other adiabatic approximations. The wave function sampling was carried out in the full 12-dimensional configuration space of the four particles (two electrons and two protons). Two different methods wer...

متن کامل

Between Classical and Quantum Monte Carlo Methods: “Variational” QMC

The variational Monte Carlo method is reviewed here. It is in essence a classical statistical mechanics approach, yet allows the calculation of quantum expectation values. We give an introductory exposition of the theoretical basis of the approach, including sampling methods and acceleration techniques; its connection with trial wavefunctions; and how in practice it is used to obtain high quali...

متن کامل

Training a Large Scale Classifier with the Quantum Adiabatic Algorithm

In a previous publication we proposed discrete global optimization as a method to train a strong binary classifier constructed as a thresholded sum over weak classifiers. Our motivation was to cast the training of a classifier into a format amenable to solution by the quantum adiabatic algorithm. Applying adiabatic quantum computing (AQC) promises to yield solutions that are superior to those w...

متن کامل

QBoost: Large Scale Classifier Training with Adiabatic Quantum Optimization

We introduce a novel discrete optimization method for training in the context of a boosting framework for large scale binary classifiers. The motivation is to cast the training problem into the format required by existing adiabatic quantum hardware. First we provide theoretical arguments concerning the transformation of an originally continuous optimization problem into one with discrete variab...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1998