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In this paper, we develop a new method to estimate the parameters of a deteriorating system under perfect condition-based maintenance. This method is based on the asymptotical behavior of the system, which is studied by using the renewal…

Statistics Theory · Mathematics 2013-07-15 Philippe Briand , Edwige Idée , Céline Labart

We present parametrizations of the $\gamma^\ast N \to N(1535)1/2^-$, $\gamma^\ast N \to N(1520)3/2^-$ and $\gamma^\ast N \to \Delta(1232)3/2^+$ transition amplitudes that are compatible with the analytic constraints at the pseudothreshold…

Nuclear Theory · Physics 2017-03-08 G. Ramalho

Latent feature models (LFM)s are widely employed for extracting latent structures of data. While offering high, parameter estimation is difficult with LFMs because of the combinational nature of latent features, and non-identifiability is a…

Machine Learning · Computer Science 2018-09-27 Ryota Suzuki , Shingo Takahashi , Murtuza Petladwala , Shigeru Kohmoto

Much of mechanistic interpretability has focused on understanding the activation spaces of large neural networks. However, activation space-based approaches reveal little about the underlying circuitry used to compute features. To better…

Machine Learning · Computer Science 2025-04-02 Brianna Chrisman , Lucius Bushnaq , Lee Sharkey

We propose a new strategy to systematically search for new physics processes in particle collisions at the energy frontier. An examination of all possible topologies which give identifiable resonant features in a specific final state leads…

In order to arrive at ultimately accurate results available with the LMTO method in the local density approximation, the stability of full-potential LMTO predictions for off-center displacements in KNbO3, as depending on the choice of basis…

Materials Science · Physics 2008-02-03 A. V. Postnikov , G. Borstel

We present and discuss predictions for a cross section of bulk and single-particle properties in symmetric nuclear matter based on recent high-quality nucleon-nucleon potentials at N3LO and including all subleading three-nucleon forces. We…

Nuclear Theory · Physics 2022-01-05 Francesca Sammarruca , Randy Millerson

In this work, we consider the problem of estimating the parameters of polynomially damped sinusoidal signals, commonly encountered in, for instance, spectroscopy. Generally, finding the parameter values of such signals constitutes a…

Signal Processing · Electrical Eng. & Systems 2019-06-27 Filip Elvander , Johan Swärd , Andreas Jakobsson

We consider a tagged particle in mean field interaction with a free gas of density N at equilibrium. In dimensions $d\geq4$, we prove the convergence of its trajectory, as N goes to infinity, to the one of a diffusion process associated…

Probability · Mathematics 2026-02-20 Thierry Bodineau , Pierre Le Bris

Point defects play a key role in determining semiconductor properties, such as electrical conductivity and photoluminescence, and often enable functional behavior. Accurate first-principles supercell simulations of point defects require…

Materials Science · Physics 2026-05-26 Abdul M. Reyes , Sebastian E. Reyes-Lillo , Eduardo Menéndez-Proupin

Spontaneous scalarization phenomenon in scalar-tensor gravity is known to be a form of phase transition, and it was recently shown that the order of this transition changes depending on the parameters of the theory. There exists a…

General Relativity and Quantum Cosmology · Physics 2026-04-29 Murat Özinan , Kıvanç İ. Ünlütürk , Fethi M. Ramazanoğlu

Fix an algebraically closed field $\F$ and an integer $d \geq 3$. Let $V$ be a vector space over $\F$ with dimension $d+1$. A Leonard pair on $V$ is a pair of diagonalizable linear transformations $A: V \to V$ and $A^* : V \to V$, each…

Rings and Algebras · Mathematics 2014-08-26 Kazumasa Nomura

In a finite volume, resonances and multi-hadron states are identified by discrete energy levels. When comparing the results of lattice QCD calculations to scattering experiments, it is important to have a way of associating the energy…

High Energy Physics - Lattice · Physics 2015-03-20 J. M. M. Hall , A. C. -P. Hsu , D. B. Leinweber , A. W. Thomas , R. D. Young

We investigate the intertwining of Laguerre processes of parameter $\alpha$ in different dimensions. We introduce a Feller kernel that depends on $\alpha $ and intertwines the $\alpha$-Laguerre process in $N+1$ dimensions and that in $N$…

Probability · Mathematics 2024-03-19 Alexander I. Bufetov , Yosuke Kawamoto

In porous media physics, calibrating model parameters through experiments is a challenge. This process is plagued with errors that come from modelling, measurement and computation of the macroscopic observables through random homogenization…

Optimization and Control · Mathematics 2014-02-06 F. Legoll , W. Minvielle , A. Obliger , M. Simon

We introduce a recipe to estimate the low-energy scattering parameters of a quantum few-body system - scattering length, effective range, and shape parameter - by using only discrete state calculations. We place the system in an artificial…

Nuclear Theory · Physics 2025-08-12 D. V. Fedorov , A. M. Pedersen

We discuss unitarity constraints on the dynamics of a system of three interacting particles. We show how the short-range interaction that describes three-body resonances can be separated from the long-range exchange processes, in particular…

High Energy Physics - Phenomenology · Physics 2019-09-04 M. Mikhasenko , Y. Wunderlich , A. Jackura , V. Mathieu , A. Pilloni , B. Ketzer , A. P. Szczepaniak

Detection of effects of the parameters of the synthetic process on the microstructure of materials is an important, yet elusive goal of materials science. We develop a method for detecting effects based on copula theory, high dimensional…

Materials Science · Physics 2023-04-04 Alex Hagen , Shane Jackson

The unexpected emergence of ferroelectricity in HfO2 at reduced dimensions has attracted considerable attention, as it provides a pathway toward the realization of ultrasmall ferroelectric devices. Ab initio calculations suggest that this…

Materials Science · Physics 2025-12-19 Yusuke Tamura , Kairi Masuda , Yu Kumagai

Tensor decomposition methods allow us to learn the parameters of latent variable models through decomposition of low-order moments of data. A significant limitation of these algorithms is that there exists no general method to regularize…

Machine Learning · Statistics 2019-05-28 Omer Gottesman , Weiwei Pan , Finale Doshi-Velez
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