19,361 research outputs found
Rigorous wave function embedding with dynamical fluctuations
The dynamical fluctuations in approaches such as dynamical mean-field theory
(DMFT) allow for the self-consistent optimization of a local fragment,
hybridized with a true correlated environment. We show that these correlated
environmental fluctuations can instead be efficiently captured in a wave
function perspective in a computationally cheap, frequency-independent,
zero-temperature approach. This allows for a systematically improvable,
short-time wave function analogue to DMFT, which entails a number of
computational and numerical benefits. We demonstrate this approach to solve the
correlated dynamics of the paradigmatic Bethe lattice Hubbard model, as well as
detailing cluster extensions in the one-dimensional Hubbard chain where we
clearly show the benefits of this rapidly convergent description of correlated
environmental fluctuations
Thermal pump-compressor for space use Patent
Thermal pump-compressor for converting solar energ
Hadron masses from dynamical, non-perturbatively O(a) improved Wilson fermions
We present results on light hadron masses from simulations of full QCD and
report on experiences in running such simulations on a Hitachi SR8000-F1
supercomputer.Comment: Lattice 2000 (Spectrum), 4 pages, 6 eps figure
Spectral functions of strongly correlated extended systems via an exact quantum embedding
Density matrix embedding theory (DMET) [Phys. Rev. Lett., 109, 186404
(2012)], introduced a new approach to quantum cluster embedding methods,
whereby the mapping of strongly correlated bulk problems to an impurity with
finite set of bath states was rigorously formulated to exactly reproduce the
entanglement of the ground state. The formalism provided similar physics to
dynamical mean-field theory at a tiny fraction of the cost, but was inherently
limited by the construction of a bath designed to reproduce ground state,
static properties. Here, we generalize the concept of quantum embedding to
dynamic properties and demonstrate accurate bulk spectral functions at
similarly small computational cost. The proposed spectral DMET utilizes the
Schmidt decomposition of a response vector, mapping the bulk dynamic
correlation functions to that of a quantum impurity cluster coupled to a set of
frequency dependent bath states. The resultant spectral functions are obtained
on the real-frequency axis, without bath discretization error, and allows for
the construction of arbitrary dynamic correlation functions. We demonstrate the
method on the 1D and 2D Hubbard model, where we obtain zero temperature,
thermodynamic limit spectral functions, and show the trivial extension to
two-particle Green functions. This advance therefore extends the scope and
applicability of DMET in condensed matter problems as a computationally
tractable route to correlated spectral functions of extended systems, and
provides a competitive alternative to dynamical mean-field theory for dynamic
quantities.Comment: 6 pages, 6 figure
Non-linear biases, stochastically-sampled effective Hamiltonians and spectral functions in quantum Monte Carlo methods
In this article we study examples of systematic biases that can occur in
quantum Monte Carlo methods due to the accumulation of non-linear expectation
values, and approaches by which these errors can be corrected. We begin with a
study of the Krylov-projected FCIQMC (KP-FCIQMC) approach, which was recently
introduced to allow efficient, stochastic calculation of dynamical properties.
This requires the solution of a sampled effective Hamiltonian, resulting in a
non-linear operation on these stochastic variables. We investigate the
probability distribution of this eigenvalue problem to study both stochastic
errors and systematic biases in the approach, and demonstrate that such errors
can be significantly corrected by moving to a more appropriate basis. This is
lastly expanded to include consideration of the correlation function QMC
approach of Ceperley and Bernu, showing how such an approach can be taken in
the FCIQMC framework.Comment: 12 pages, 7 figure
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