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We show that, by using the quantum orthogonal functions invariant, we are able to solve a coupled of time dependent harmonic oscillators where all the time dependent frequencies are arbitrary. We do so, by transforming the time dependent…

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To…

Computing accurate estimates of the Fourier transform of analog signals from discrete data points is important in many fields of science and engineering. The conventional approach of performing the discrete Fourier transform of the data…

Machine Learning · Statistics 2017-12-08 Luca Ambrogioni , Eric Maris

Any pure quantum state can be equivalently represented by means of its wave function psi(q) or of the Fermi function g_F(q,p), with q and p coordinates and conjugate momenta of the system under investigation.We show that a Gaussian wave…

Quantum Physics · Physics 2009-05-14 Giuliano Benenti , Giuliano Strini

We introduce a formalism for time-dependent correlation functions for systems whose evolutions are governed by non-Hermitian Hamiltonians of general type. It turns out that one can define two different types of time correlation functions.…

Quantum Physics · Physics 2016-10-21 Alessandro Sergi , Konstantin G. Zloshchastiev

The unitary operator which transforms a harmonic oscillator system of time-dependent frequency into that of a simple harmonic oscillator of different time-scale is found, with and without an inverse-square potential. It is shown that for…

Quantum Physics · Physics 2009-11-06 Dae-Yup Song

In this article we wish to present a new method to obtain spectral functions at finite temperature and density from the Functional Renormalization Group (FRG). The FRG offers a powerful non-perturbative tool to deal with phase transitions…

High Energy Physics - Phenomenology · Physics 2014-09-17 Jochen Wambach , Ralf-Arno Tripolt , Nils Strodthoff , Lorenz von Smekal

We evaluate an adaptive gaussian quadrature integration scheme that will be suitable for the numerical evaluation of generalized redistribution in frequency functions. The latter are indispensable ingredients for "full non-LTE" radiation…

Instrumentation and Methods for Astrophysics · Physics 2020-01-29 F. Paletou , C. Peymirat , E. Anterrieu , T. Böhm

We solve the problem of resonance statistics in systems with broken time-reversal invariance by deriving the joint probability density of all resonances in the framework of a random matrix approach and calculating explicitly all n-point…

Condensed Matter · Physics 2009-10-31 Yan V. Fyodorov , B. A. Khoruzhenko

An efficient algorithm for time propagation of the time-dependent Kohn-Sham equations is presented. The algorithm is based on dividing the Hamiltonian into small time steps and assuming that it is constant over these steps. This allows for…

Computational Physics · Physics 2014-12-03 J. K. Dewhurst , K. Krieger , S. Sharma , E. K. U. Gross

Analysis of ac electrical systems can be performed via frame transformations in the time-domain or via harmonic transfer functions (HTFs) in the frequency-domain. The two approaches each have unique advantages but are hard to reconcile…

Signal Processing · Electrical Eng. & Systems 2020-03-11 Yunjie Gu , Yitong Li , Timothy C. Green

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It…

Computation · Statistics 2023-05-19 Viktor Witkovský

Objective: We present a technique for identification and statistical analysis of quasiperiodic spatiotemporal pressure signals recorded from multiple closely spaced sensors in the human colon. Methods: Identification is achieved by…

Applications · Statistics 2019-12-06 Lukasz Wiklendt , Marcello Costa , Simon Brookes , Phil G. Dinning

We show how frequency fluctuations of a vibrational mode can be separated from other sources of phase noise. The method is based on the analysis of the time dependence of the complex amplitude of forced vibrations. The moments of the…

Mesoscale and Nanoscale Physics · Physics 2015-06-03 Z. A. Maizelis , M. L. Roukes , M. I. Dykman

Time-frequency analysis has been applied successfully in many fields. However, the traditional methods, like short time Fourier transform and Cohen distribution, suffer from the low resolution or the interference of the cross terms. To…

Signal Processing · Electrical Eng. & Systems 2018-04-17 Yingpin Chen , Zhenming Peng , Ali Gholami , Jingwen Yan , Shu Li

The Gaussian process is a powerful and flexible technique for interpolating spatiotemporal data, especially with its ability to capture complex trends and uncertainty from the input signal. This chapter describes Gaussian processes as an…

Machine Learning · Statistics 2021-10-11 Kien Nguyen , John Krumm , Cyrus Shahabi

Time-frequency transforms represent a signal as a mixture of its time domain representation and its frequency domain representation. We present efficient algorithms for the quantum Zak transform and quantum Weyl-Heisenberg transform.

Quantum Physics · Physics 2007-05-23 J. Mark Ettinger

Quantum-classical correspondence for the average shape of eigenfunctions and the local spectral density of states are well-known facts. In this paper, the fluctuations that quantum mechanical wave functions present around the classical…

Chaotic Dynamics · Physics 2008-11-26 L. Benet , J. Flores , H. Hernandez-Saldaña , F. M. Izrailev , F. Leyvraz , T. H. Seligman

We study the statistics of wave functions in a ballistic chaotic system. The statistical ensemble is generated by adding weak smooth disorder. The conjecture of Gaussian fluctuations of wave functions put forward by Berry and generalized by…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 I. V. Gornyi , A. D. Mirlin

Gaussian Process state-space models capture complex temporal dependencies in a principled manner by placing a Gaussian Process prior on the transition function. These models have a natural interpretation as discretized stochastic…

Machine Learning · Computer Science 2022-02-24 Krista Longi , Jakob Lindinger , Olaf Duennbier , Melih Kandemir , Arto Klami , Barbara Rakitsch
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