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We study the random connection model driven by a stationary Poisson process. In the first part of the paper, we derive a lace expansion with remainder term in the continuum and bound the coefficients using a new version of the BK…

Probability · Mathematics 2023-12-20 Markus Heydenreich , Remco van der Hofstad , Günter Last , Kilian Matzke

We describe extensions to the siesta density functional theory (dft) code [30], for the simulation of isolated molecules and their absorption spectra. The extensions allow for: - Use of a multi-grid solver for the Poisson equation on a…

Computational Physics · Physics 2013-02-20 Olivier Coulaud , Patrice Bordat , Pierre Fayon , Vincent Lebris , Isabelle Baraille , Ross Brown

We revisit the question of how to calculate correlations of the curvature perturbation, $\zeta$, using the $\delta N$ formalism when one cannot employ a truncated Taylor expansion of $N$. This problem arises when one uses lattice…

Cosmology and Nongalactic Astrophysics · Physics 2018-08-28 Shailee V. Imrith , David J. Mulryne , Arttu Rajantie

A typical linear open system is often defined as a component of a larger conservative one. For instance, a dielectric medium, defined by its frequency dependent electric permittivity and magnetic permeability is a part of a conservative…

Mathematical Physics · Physics 2009-11-11 Alexander Figotin , Stephen P. Shipman

One of the main frameworks to analyze the effects of the environment in a quantum computer is that of pure dephasing, where the dynamics of qubits can be characterised in terms of a well-known dynamical map. In this work we present a…

Quantum Physics · Physics 2020-03-11 Inés de Vega

We have developed the {\it general method} for the description of {\it separatrix chaos}, basing on the analysis of the separatrix map dynamics. Matching it with the resonant Hamiltonian analysis, we show that, for a given amplitude of…

Chaotic Dynamics · Physics 2007-11-01 S. M. Soskin , R. Mannella , O. M. Yevtushenko

Dissipative phenomena manifest in multiple mechanical systems. In this dissertation, different geometric frameworks for modelling non-conservative dynamics are considered. The objective is to generalize several results from conservative…

Mathematical Physics · Physics 2024-09-19 Asier López-Gordón

For a singularly perturbed system of reaction--diffusion equations, assuming that the 0th order solutions in regular and singular regions are all stable, we construct matched asymptotic expansions for formal solutions to any desired order…

patt-sol · Physics 2008-02-03 Xiao-Biao Lin

The method of perturbative expansion of master equation is employed to study the dissipative properties of system and of atom in the two-photon Jaynes-Cummings model (JCM) with degenerate atomic levels. The numerical results show that the…

Quantum Physics · Physics 2016-09-08 Y. Q. Guo , L. Zhou , H. S. Song

We use a previously introduced mapping between the continuum percolation model and the Potts fluid (a system of interacting s-states spins which are free to move in the continuum) to derive the low density expansion of the pair…

Statistical Mechanics · Physics 2009-10-28 Alon Drory , Brian Berkowitz , Giorgio Parisi , I. Balberg

We study a system-bath description in the strong coupling regime where it is not possible to derive a master equation for the reduced density matrix by a direct expansion in the system-bath coupling. A particular example is a bath with…

Mesoscale and Nanoscale Physics · Physics 2016-10-18 Michael Marthaler , Juha Leppäkangas

There is a well-known series expansion (Neumann series) in functional analysis for perturbative inversion of specific operators on Banach spaces. However, operators that appear in signal processing (e.g. folding and convolution of…

Mathematical Physics · Physics 2007-05-23 András László

Diagrammatic techniques to compute perturbatively the spectral properties of Euclidean Random Matrices in the high-density regime are introduced and discussed in detail. Such techniques are developed in two alternative and very different…

Disordered Systems and Neural Networks · Physics 2011-08-31 T. S. Grigera , V. Martin-Mayor , G. Parisi , P. Urbani , P. Verrocchio

We theoretically investigate the correlation functions of the phase of a light wave propagating through a turbulent medium. We use an equation for the logarithm of a wave packet envelope, which includes a second-order nonlinear term. Based…

Optics · Physics 2026-01-14 I. V. Kolokolov , V. V. Lebedev

In this note we study a fractional Poisson-Nernst-Planck equation modeling a semiconductor device. We prove several decay estimates for the Lebesgue and Sobolev norms in one, two and three dimensions. We also provide the first term of the…

Analysis of PDEs · Mathematics 2016-11-23 Rafael Granero-Belinchón

We generate the perturbative expansion of the single-particle Green's function and related self-energy for a half-filled single-band Hubbard model on a square lattice. We invoke algorithmic Matsubara integration to evaluate single-particle…

Strongly Correlated Electrons · Physics 2021-09-15 Bradley D. E. McNiven , G. Todd Andrews , James P. F. LeBlanc

The three-state Majorana model in the presence of dissipation is considered. Different models of system-environment interaction are explored, ranging from situation where dissipation is the main effect to regimes where dephasing is mainly…

Quantum Physics · Physics 2019-11-13 Benedetto Militello , Nikolay V. Vitanov

The effect of diffusional relaxation on the random sequential deposition process is studied in the limit of fast deposition. Expression for the coverage as a function of time are analytically derived for both the short-time and long-time…

Statistical Mechanics · Physics 2009-10-28 Eli Eisenberg , Asher Baram

The dynamics of the nuclear-spin quantum computer with large number (L=1000) of qubits is considered using a perturbation approach, based on approximate diagonalization of exponentially large sparse matrices. Small parameters are introduced…

Quantum Physics · Physics 2007-05-23 G. P. Berman , D. I. Kamenev , V. I. Tsifrinovich

Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be…

Machine Learning · Statistics 2013-10-28 Manfred Opper , Ulrich Paquet , Ole Winther