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The dependence of the nuclear level density on intrinsic deformation is an important input to dynamical nuclear processes such as fission. Auxiliary-field Monte Carlo (AFMC) method is a powerful method for computing nuclear level densities.…

Nuclear Theory · Physics 2018-09-26 M. T. Mustonen , C. N. Gilbreth , Y. Alhassid , G. F. Bertsch

We present experimental results demonstrating controllable dispersion in a ring laser by monitoring the lasing-frequency response to cavity-length variations. Pumping on an N-type level configuration in ${}^{87}$Rb, we tailor the…

We present a technique for entropy optimization to calculate a distribution from its moments. The technique is based upon maximizing a discretized form of the Shannon entropy functional by mapping the problem onto a dual space where an…

Disordered Systems and Neural Networks · Physics 2009-11-10 K. Bandyopadhyay , A. K. Bhattacharya , Parthapratim Biswas , D. A. Drabold

Fisher information, Shannon information entropy and Statistical Complexity are calculated for the interface of a normal metal and a superconductor, as a function of the temperature for several materials. The order parameter $\Psi({\bf r})$…

Quantum Physics · Physics 2018-06-05 Ch. C. Moustakidis , C. P. Panos

Estimation of Shannon and R\'enyi entropies of unknown discrete distributions is a fundamental problem in statistical property testing and an active research topic in both theoretical computer science and information theory. Tight bounds on…

Quantum Physics · Physics 2023-07-19 Tongyang Li , Xiaodi Wu

We present intensity-resolved above threshold ionization (ATI) spectra of xenon using an intensity scanning and deconvolution technique. Experimental data were obtained with laser pulses of 58 fs and central wavelength of 800 nm from a…

We study the Shannon entropy of the probability distribution resulting from the ground-state wave function of a one-dimensional quantum model. This entropy is related to the entanglement entropy of a Rokhsar-Kivelson-type wave function…

Strongly Correlated Electrons · Physics 2009-11-25 Jean-Marie Stéphan , Shunsuke Furukawa , Grégoire Misguich , Vincent Pasquier

Inverse Compton scattering of an ultra-relativistic electron in the field of a high-intensity laser produces photon beams with angular and spectral distributions that are strongly dependent on the laser intensity. Here, we show that the…

Plasma Physics · Physics 2024-07-17 K. Fleck , T. Blackburn , E. Gerstmayr , M. Bruschi , P. Grutta , M. Morandin , G. Sarri

We present a numerical study of the application of the Shannon entropy technique to the planar restricted three-body problem in the vicinity of first-order interior mean-motion resonances with the perturber. We estimate the diffusion…

Chaotic Dynamics · Physics 2020-01-08 C. Beaugé , P. M. Cincotta

Scenario-based probabilistic forecasts have become vital for decision-makers in handling intermittent renewable energies. This paper presents a recent promising deep learning generative approach called denoising diffusion probabilistic…

Machine Learning · Computer Science 2023-08-22 Esteban Hernandez Capel , Jonathan Dumas

This paper investigates what can be inferred about an arbitrary continuous probability distribution from a finite sample of $N$ observations drawn from it. The central finding is that the $N$ sorted sample points partition the real line…

Machine Learning · Statistics 2025-07-30 Urban Eriksson

Estimating entropies from limited data series is known to be a non-trivial task. Naive estimations are plagued with both systematic (bias) and statistical errors. Here, we present a new 'balanced estimator' for entropy functionals Shannon,…

Statistical Mechanics · Physics 2008-04-30 Juan A. Bonachela , Haye Hinrichsen , Miguel A. Munoz

Gamma distributions, which contain the exponential as a special case, have a distinguished place in the representation of near-Poisson randomness for statistical processes; typically, they represent distributions of spacings between events…

Mathematical Physics · Physics 2009-05-22 C. T. J. Dodson

In information theory, Fisher information and Shannon information (entropy) are respectively used to quantify the uncertainty associated with the distribution modeling and the uncertainty in specifying the outcome of given variables. These…

Machine Learning · Statistics 2018-09-27 Huangjie Zheng , Jiangchao Yao , Ya Zhang , Ivor W. Tsang , Jia Wang

Lepton polarization asymmetries for the flavor-changing neutral current (FCNC) dileptonic decays of {\Lambda}b baryons are calculated using single-component analytic (SCA) and multicomponent numerical (MCN) form factors. We show that these…

Nuclear Theory · Physics 2015-06-11 L. Mott , W. Roberts

Probabilistic constellation shaping has been used in long-haul optically amplified coherent systems for its capability to approach the Shannon limit and realize fine rate granularity. The availability of high-bandwidth optical-electronic…

Signal Processing · Electrical Eng. & Systems 2023-03-31 Md Sabbir-Bin Hossain , Georg Bocherer , Talha Rahman , Tom Wettlin , Nebojsa Stojanovic , Stefano Calabro , Stephan Pachnicke

Physical Unclonable Functions (PUFs) leverage signal variations that occur within the device as a source of entropy. On-chip instrumentation is utilized by some PUF architectures to measure and digitize these variations, which are then…

Cryptography and Security · Computer Science 2024-09-04 Jim Plusquellic , Jennifer Howard , Ross MacKinnon , Kristianna Hoffman , Eirini Eleni Tsiropoulou , Calvin Chan

The Shannon entropy, the desequilibrium and their generalizations (R\'enyi and Tsallis entropies) of the three-dimensional single-particle systems in a spherically-symmetric potential $V(r)$ can be decomposed into angular and radial parts.…

Quantum Physics · Physics 2017-01-17 J. S. Dehesa , I. V. Toranzo , D. Puertas-Centeno

In this work, we investigate the reliability of information-theoretic measures based on the electron-density and shape-function, specifically Shannon and R\'enyi entropies, as descriptors of electronic correlation. By establishing a…

Quantum Physics · Physics 2026-05-21 Diogo J. L. Rodrigues , Evelio Francisco , Ángel Martín Pendás

In a world where more decisions are made using artificial intelligence, it is of utmost importance to ensure these decisions are well-grounded. Neural networks are the modern building blocks for artificial intelligence. Modern neural…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Mohamad Al Shaar , Nils Ekström , Gustav Gille , Reza Rezvan , Ivan Wely