Related papers: Open Problems in Applying Random-Matrix Theory to …
Randomized clinical trials (RCTs) are ideal for estimating causal effects, because the distributions of background covariates are similar in expectation across treatment groups. When estimating causal effects using observational data,…
Classical random matrix ensembles were originally introduced in physics to approximate quantum many-particle nuclear interactions. However, there exists a plethora of quantum systems whose dynamics is explained in terms of few-particle…
We investigate the influence of the adjustment procedure and the set of measured observables on the properties and predictive power of relativistic self-consistent mean-field models for the nuclear ground state. These studies are performed…
Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two ways. We present a new theoretically tractable variant of…
The extraction of neutrino oscillation parameters often requires the unambiguous identification of the reaction mechanism to be used for the energy determination. The use of nuclear targets and of beams with broad energy distributions…
Some aspects of application of the Uncertainty Principle in the range of interaction radiation with matter surveyed. The procedure of adjustment is proposed at calculation of values of an electromagnetic energy in a quantum theory of a…
Quantum-matter theory (QMT), based on the Schr\"odinger or Dirac equations, is firmly established for both intra- and intermolecular interactions. However, there are two key issues with QMT. First, its applicability to large molecular…
The status of relativistic nuclear many-body calculations of nuclear systems to be built up in terms of protons and neutrons is reviewed. In detail, relativistic effects on several aspects of nuclear matter such as the effective mass,…
Neural networks have been used successfully in a variety of fields, which has led to a great deal of interest in developing a theoretical understanding of how they store the information needed to perform a particular task. We study the…
Results on the spectral behavior of random matrices as the dimension increases are applied to the problem of detecting the number of sources impinging on an array of sensors. A common strategy to solve this problem is to estimate the…
We analyze statistical properties of complex eigenvalues of random matrices $\hat{A}$ close to unitary. Such matrices appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with…
Random Matrix Theory (RMT) has successfully modeled diverse systems, from energy levels of heavy nuclei to zeros of $L$-functions. Many statistics in one can be interpreted in terms of quantities of the other; for example, zeros of…
The effect of autoionizing resonances in atomic systems and processes is reviewed. Theoretical framework for treating resonances in the coupled channel approximation using the R-matrix method, as well as approximations related to plasma…
Three- and four-nucleon reactions are discussed. The focus is on the notion of nuclear potentials, on conceptual and technical issues of calculations and on unresolved problems between existing theoretical predictions and experimental data.…
The R-matrix method is a fully-quantum time-independent scattering method, used to simulate nuclear, electron-atom, electron-ion, electron-molecule scattering and more. Here, a novel R-matrix method, RmatReact, is presented as applied to…
The interpretation of the nuclear cross sections measured using accelerator neutrino beams involve severe difficulties, arising primarily from the average over the incoming neutrino flux. The broad energy distribution of the beam particles…
We review basic theoretical concepts to describe nuclear collisions at ultrarelativistic energies. We discuss relativistic strings, Gribov--Regge theory (GRT) of hadronic interactions and string models based on GRT, and finally…
The automated inference of physically interpretable (bio)chemical reaction network models from measured experimental data is a challenging problem whose solution has significant commercial and academic ramifications. It is demonstrated,…
The treatment of nuclear effects in neutrino-nucleus interactions is one of the main sources of systematic uncertainty for the analysis and interpretation of data of neutrino oscillation experiments. Neutrinos interact with nuclei via…
Relativistic effects are investigated in nuclear matter calculations employing renormalized low-momentum nucleon-nucleon ($NN$) interactions. It is demonstrated that the relativistic effects cure a problem of non-relativistic low-momentum…