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A formalism is developed to study certain five-term recursion relations by discrete phase integral (or Wentzel-Kramers-Brillouin) methods. Such recursion relations arise naturally in the study of the Schrodinger equation for certain spin…

Mathematical Physics · Physics 2007-05-23 Anupam Garg

Coherent diffractive imaging is a technique that recovers the sample image by numerically inverting its diffraction pattern. We propose a generalization of this method for the inversion of multi-wavelength data. Using this approach, we show…

Optics · Physics 2020-05-08 Erik Malm , Edwin Fohtung , Anders Mikkelsen

We present multiply subtractive Kramers-Kronig (MSKK) relations for the moments of arbitrary order harmonic generation susceptibility. Using experimental data on third-harmonic wave from polysilane, we show that singly subtractive…

Materials Science · Physics 2009-11-10 Valerio Lucarini , Jarkko J. Saarinen , Kei-Erik Peiponen

We improve the density-matrix renormalization group (DMRG) evaluation of the Kubo formula for the zero-temperature linear conductance of one-dimensional correlated systems.The dynamical DMRG is used to compute the linear response of a…

Strongly Correlated Electrons · Physics 2018-10-08 Jan-Moritz Bischoff , Eric Jeckelmann

We derive the divergence-kernel formula for the linear response of random dynamical systems. Specifically, the pathwise expression is for the parameter-derivative of the marginal or stationary density, not an averaged observable. Our…

Dynamical Systems · Mathematics 2025-12-30 Angxiu Ni

We introduce a driven diffusive model involving poly-dispersed hard k-mers on a one dimensional periodic ring and investigate the possibility of phase separation transition in such systems. The dynamics consists of a size dependent…

Statistical Mechanics · Physics 2015-06-23 Bijoy Daga , P. K. Mohanty

Dispersion lies at the heart of real-time signal processing systems across the entire electromagnetic spectrum from radio to optics. However, the performance and applicability of such systems have been severely plagued by distortions due to…

Optics · Physics 2016-01-08 Shulabh Gupta , Christophe Caloz

Quantum algorithms have the potential to revolutionize our understanding of open quantum systems in chemistry. In this work, we demonstrate that a repeated interaction model, which could serve as the foundation for a digital quantum…

Quantum Physics · Physics 2025-05-05 Lea K. Northcote , Matthew S. Teynor , Gemma C. Solomon

We present an alternative numerical reconstruction algorithm for direct tomographic reconstruction of a sample refractive indices from the measured intensities of its far-field coherent diffraction patterns. We formulate the well-known…

Computational Physics · Physics 2019-02-06 T. Ramos , Bastian E. Grønager , Martin Skovgaard Andersen , J. W. Andreasen

We present a novel approach to the regression of quantum mechanical energies based on a scattering transform of an intermediate electron density representation. A scattering transform is a deep convolution network computed with a cascade of…

Machine Learning · Computer Science 2016-05-23 Matthew Hirn , Nicolas Poilvert , Stéphane Mallat

In this paper, we present an analytical model for the diffusive molecular communication (MC) system with a reversible adsorption receiver in a fluid environment. The widely used concentration shift keying (CSK) is considered for modulation.…

Emerging Technologies · Computer Science 2016-06-23 Yansha Deng , Adam Noel , Maged Elkashlan , Arumugam Nallanathan , Karen C. Cheung

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-21 Maria Han Veiga , Xi Meng , Oleg Y. Gnedin , Nickolay Y. Gnedin , Xun Huan

In this article, we are interested in the asymptotic analysis of a finite volume scheme for one dimensional linear kinetic equations, with either Fokker-Planck or linearized BGK collision operator. Thanks to appropriate uniform estimates,…

Numerical Analysis · Mathematics 2019-11-12 Marianne Bessemoulin-Chatard , Maxime Herda , Thomas Rey

Diffusion models show promise for image restoration, but existing methods often struggle with inconsistent fidelity and undesirable artifacts. To address this, we introduce Kernel Density Steering (KDS), a novel inference-time framework…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Yuyang Hu , Kangfu Mei , Mojtaba Sahraee-Ardakan , Ulugbek S. Kamilov , Peyman Milanfar , Mauricio Delbracio

In phase retrieval, the goal is to recover a complex signal from the magnitude of its linear measurements. While many well-known algorithms guarantee deterministic recovery of the unknown signal using i.i.d. random measurement matrices,…

Information Theory · Computer Science 2017-03-24 Boshra Rajaei , Sylvain Gigan , Florent Krzakala , Laurent Daudet

Heat diffusion processes have found wide applications in modelling dynamical systems over graphs. In this paper, we consider the recovery of a $k$-bandlimited graph signal that is an initial signal of a heat diffusion process from its…

Information Theory · Computer Science 2021-10-05 Longxiu Huang , Deanna Needell , Sui Tang

It is well known that Maxwell equations can be expressed in a unitary Schrodinger-Dirac representation for homogeneous media. However, difficulties arise when considering inhomogeneous media. A Dyson map points to a unitary field qubit…

We present a resynchronization method for quantum key distribution (QKD) systems that enables rapid and reliable recovery from interruptions of the quantum channel and changes of its optical path length. By periodically transmitting short…

In this article we propose a dynamic approach to complex vector reconstruction in the context of quantum tomography. There are two underlying assumptions behind our reasoning. The first one claims that the evolution of a d-level pure…

Quantum Physics · Physics 2020-07-03 Artur Czerwiński

This work presents a distributed algorithm for nonlinear adaptive learning. In particular, a set of nodes obtain measurements, sequentially one per time step, which are related via a nonlinear function; their goal is to collectively…

Information Theory · Computer Science 2016-02-09 Symeon Chouvardas , Moez Draief