21,638 research outputs found
Geometric ergodicity for some space-time max-stable Markov chains
Max-stable processes are central models for spatial extremes. In this paper,
we focus on some space-time max-stable models introduced in Embrechts et al.
(2016). The processes considered induce discrete-time Markov chains taking
values in the space of continuous functions from the unit sphere of
to . We show that these Markov chains are
geometrically ergodic. An interesting feature lies in the fact that the state
space is not locally compact, making the classical methodology inapplicable.
Instead, we use the fact that the state space is Polish and apply results
presented in Hairer (2010)
Resummation for Nonequilibrium Perturbation Theory and Application to Open Quantum Lattices
Lattice models of fermions, bosons, and spins have long served to elucidate
the essential physics of quantum phase transitions in a variety of systems.
Generalizing such models to incorporate driving and dissipation has opened new
vistas to investigate nonequilibrium phenomena and dissipative phase
transitions in interacting many-body systems. We present a framework for the
treatment of such open quantum lattices based on a resummation scheme for the
Lindblad perturbation series. Employing a convenient diagrammatic
representation, we utilize this method to obtain relevant observables for the
open Jaynes-Cummings lattice, a model of special interest for open-system
quantum simulation. We demonstrate that the resummation framework allows us to
reliably predict observables for both finite and infinite Jaynes-Cummings
lattices with different lattice geometries. The resummation of the Lindblad
perturbation series can thus serve as a valuable tool in validating open
quantum simulators, such as circuit-QED lattices, currently being investigated
experimentally.Comment: 15 pages, 9 figure
Dilepton from Disoriented Chiral Condensates
Disoriented chiral condensates are manifested as long wavelength pionic
oscillations and their interaction with the thermal environment can be a
significant source of dileptons. We calculate the yield of such dilepton
production within the linear sigma model and illustrate the basic features of
the dilepton spectrum in a schematic model. We find that the dilepton yield
with invariant mass near and below due to the soft pion modes can be
up to two orders of magnitude larger than the corresponding equilibrium yield.
We conclude with a discussion on how this enhancement can be detected by
present dilepton experiments.Comment: 15 pages, 9 figs, uses epsf and sprocl style files Contribution to
Proceedings, International Workshop on Astro Hadron Physics `Hadrons in Dense
Matter', APCTP, Seoul, Korea, October 199
High-Accuracy Calculations of the Critical Exponents of Dyson's Hierarchical Model
We calculate the critical exponent gamma of Dyson's hierarchical model by
direct fits of the zero momentum two-point function, calculated with an Ising
and a Landau-Ginzburg measure, and by linearization about the Koch-Wittwer
fixed point. We find gamma= 1.299140730159 plus or minus 10^(-12). We extract
three types of subleading corrections (in other words, a parametrization of the
way the two-point function depends on the cutoff) from the fits and check the
value of the first subleading exponent from the linearized procedure. We
suggest that all the non-universal quantities entering the subleading
corrections can be calculated systematically from the non-linear contributions
about the fixed point and that this procedure would provide an alternative way
to introduce the bare parameters in a field theory model.Comment: 15 pages, 9 figures, uses revte
A Guide to Precision Calculations in Dyson's Hierarchical Scalar Field Theory
The goal of this article is to provide a practical method to calculate, in a
scalar theory, accurate numerical values of the renormalized quantities which
could be used to test any kind of approximate calculation. We use finite
truncations of the Fourier transform of the recursion formula for Dyson's
hierarchical model in the symmetric phase to perform high-precision
calculations of the unsubtracted Green's functions at zero momentum in
dimension 3, 4, and 5. We use the well-known correspondence between statistical
mechanics and field theory in which the large cut-off limit is obtained by
letting beta reach a critical value beta_c (with up to 16 significant digits in
our actual calculations). We show that the round-off errors on the magnetic
susceptibility grow like (beta_c -beta)^{-1} near criticality. We show that the
systematic errors (finite truncations and volume) can be controlled with an
exponential precision and reduced to a level lower than the numerical errors.
We justify the use of the truncation for calculations of the high-temperature
expansion. We calculate the dimensionless renormalized coupling constant
corresponding to the 4-point function and show that when beta -> beta_c, this
quantity tends to a fixed value which can be determined accurately when D=3
(hyperscaling holds), and goes to zero like (Ln(beta_c -beta))^{-1} when D=4.Comment: Uses revtex with psfig, 31 pages including 15 figure
A Two-Parameter Recursion Formula For Scalar Field Theory
We present a two-parameter family of recursion formulas for scalar field
theory. The first parameter is the dimension . The second parameter
() allows one to continuously extrapolate between Wilson's approximate
recursion formula and the recursion formula of Dyson's hierarchical model. We
show numerically that at fixed , the critical exponent depends
continuously on . We suggest the use of the independence as a
guide to construct improved recursion formulas.Comment: 7 pages, uses Revtex, one Postcript figur
Understanding molecular representations in machine learning: The role of uniqueness and target similarity
The predictive accuracy of Machine Learning (ML) models of molecular
properties depends on the choice of the molecular representation. Based on the
postulates of quantum mechanics, we introduce a hierarchy of representations
which meet uniqueness and target similarity criteria. To systematically control
target similarity, we rely on interatomic many body expansions, as implemented
in universal force-fields, including Bonding, Angular, and higher order terms
(BA). Addition of higher order contributions systematically increases
similarity to the true potential energy and predictive accuracy of the
resulting ML models. We report numerical evidence for the performance of BAML
models trained on molecular properties pre-calculated at electron-correlated
and density functional theory level of theory for thousands of small organic
molecules. Properties studied include enthalpies and free energies of
atomization, heatcapacity, zero-point vibrational energies, dipole-moment,
polarizability, HOMO/LUMO energies and gap, ionization potential, electron
affinity, and electronic excitations. After training, BAML predicts energies or
electronic properties of out-of-sample molecules with unprecedented accuracy
and speed
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