The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact $N$-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC method (IP-DMQMC) which overcomes the limitation of only sampling one inverse temperature point at a time, instead allowing for the sampling of a temperature range within a single calculation thereby reducing the computational cost. At the target inverse temperature, instead of ending the simulation, we incorporate a change of picture away from the interaction picture. The resulting equations of motion have piecewise functions and use the interaction picture in the first phase of a simulation, followed by the...
In this work, we present a method to build a first order reduced density matrix (1-RDM) of a molecul...
In this Letter we present a novel quantum Monte Carlo method for fermions, based on an exact decompo...
2noOver the past several decades, computational approaches to studying strongly-interacting systems ...
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples t...
We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-partic...
The density matrix quantum Monte Carlo (DMQMC) method is used to sample exact-on-average N-body dens...
Properties that are necessarily formulated within pure (symmetric) expectation values are difficult ...
We expand upon the recent semi-stochastic adaptation to full configuration interaction quantum Monte...
In this thesis we investigate the recently developed Full Configuration Interaction Quantum Monte Ca...
Building on the success of Quantum Monte Carlo techniques such as diffusion Monte Carlo, alternative...
Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full c...
With the development of peta-scale computers and exa-scale only a few years away, the quantum Monte ...
Quantum Monte Carlo (QMC) is an extremely powerful method to treat many-body systems. Usually quantu...
Quantum Monte Carlo (QMC) methods are among the most accurate for computing ground state properties ...
In this work, we present a method to build a first order reduced density matrix (1-RDM) of a molecul...
In this work, we present a method to build a first order reduced density matrix (1-RDM) of a molecul...
In this Letter we present a novel quantum Monte Carlo method for fermions, based on an exact decompo...
2noOver the past several decades, computational approaches to studying strongly-interacting systems ...
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples t...
We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-partic...
The density matrix quantum Monte Carlo (DMQMC) method is used to sample exact-on-average N-body dens...
Properties that are necessarily formulated within pure (symmetric) expectation values are difficult ...
We expand upon the recent semi-stochastic adaptation to full configuration interaction quantum Monte...
In this thesis we investigate the recently developed Full Configuration Interaction Quantum Monte Ca...
Building on the success of Quantum Monte Carlo techniques such as diffusion Monte Carlo, alternative...
Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full c...
With the development of peta-scale computers and exa-scale only a few years away, the quantum Monte ...
Quantum Monte Carlo (QMC) is an extremely powerful method to treat many-body systems. Usually quantu...
Quantum Monte Carlo (QMC) methods are among the most accurate for computing ground state properties ...
In this work, we present a method to build a first order reduced density matrix (1-RDM) of a molecul...
In this work, we present a method to build a first order reduced density matrix (1-RDM) of a molecul...
In this Letter we present a novel quantum Monte Carlo method for fermions, based on an exact decompo...
2noOver the past several decades, computational approaches to studying strongly-interacting systems ...