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We present a theoretical investigation of thermal fluctuation statistics in a molecular motor. Energy transfer in the motor is described using a multidimensional discrete master equation with nearest-neighbor hopping. In this theory, energy…

Statistical Mechanics · Physics 2014-01-07 K. J. Challis , M. W. Jack

We present here a generalization of the thermal discrete dipole approximation (TDDA) that allows us to describe the near-field radiative heat transfer between finite objects of arbitrary shape that exhibit magneto-optical (MO) activity. We…

A diathermal wall between two heat baths at different temperatures can be mimicked by a layer of independent spin pairs with some internal energy and where each spin $\sigma_a$ is flipped by thermostat $a$ ($a=1,2$). The transition rates…

Statistical Mechanics · Physics 2015-05-06 Françoise Cornu , Michel Bauer

The one-dimensional (1D) Stefan problem is a prototypical heat and mass transfer problem that analyzes the temperature distribution in a material undergoing phase change. In addition, it describes the evolution of the phase change front…

Fluid Dynamics · Physics 2026-02-10 Mehran Soleimani , Kimmo Koponen , Nils Tilton , Amneet Pal Singh Bhalla

In this paper, we present an approach to enhance interpolation and approximation error estimates. Based on a previously derived first-order Taylor-like formula, we demonstrate its applicability in improving the $P_1$-interpolation error…

Numerical Analysis · Mathematics 2023-10-31 Joel Chaskalovic , Franck Assous

Let $\Delta(x)$ be the error term of the Dirichlet divisor problem. An asymptotic formula with the error term $O(T^{53/28+\epsilon})$ is established for the integral $\int_1^T\Delta^4(x)dx.$ Similar results are also established for some…

Number Theory · Mathematics 2008-05-13 Wenguang Zhai

In this paper, an improved thermal lattice Boltzmann (LB) model is proposed for simulating liquid-vapor phase change, which is aimed at improving an existing thermal LB model for liquid-vapor phase change [S. Gong and P. Cheng, Int. J. Heat…

Computational Physics · Physics 2017-12-13 Qing Li , P. Zhou , H. J. Yan

A number of improvements have been added to the existing analytical model of hysteresis loop defined in parametric form. In particular, three phase shifts are included in the model, which permits to tilt the hysteresis loop smoothly by the…

Optimization and Control · Mathematics 2020-06-11 Rostislav V. Lapshin

We introduce a systematic analysis of density functional approximation errors in solids by separating functional-driven from density-driven contributions using quantum Monte Carlo densities of silicon, sodium chloride, and copper as…

Materials Science · Physics 2026-05-15 Ayoub Aouina , Nicolas Tancogne-Dejean , Silvana Botti

The classical Density Functional Theory (DFT) is introduced as an application of entropic inference for inhomogeneous fluids at thermal equilibrium. It is shown that entropic inference reproduces the variational principle of DFT when…

Statistical Mechanics · Physics 2021-09-14 Ahmad Yousefi , Ariel Caticha

We determine universal critical exponents that describe the continuous phase transitions in different dimensions of space. We use continued functions without any external unknown parameters to obtain analytic continuation for the recently…

Statistical Mechanics · Physics 2021-03-26 Venkat Abhignan , R. Sankaranarayanan

A systematically improvable wave function is proposed for the numerical solution of strongly correlated systems. With a stochastic optimization method, based on the auxiliary field quantum Monte Carlo technique, an effective temperature…

Strongly Correlated Electrons · Physics 2022-03-22 Sandro Sorella

We have varied the disorder in a two-dimensional electron system in silicon by applying substrate bias. When the disorder becomes sufficiently low, we observe the emergence of the metallic phase, and find evidence for a metal-insulator…

Strongly Correlated Electrons · Physics 2009-10-30 Dragana Popovic , A. B. Fowler , S. Washburn

This paper presents results for the sampled-data boundary feedback control to the Stefan problem. The Stefan problem represents a liquid-solid phase change phenomenon which describes the time evolution of a material's temperature profile…

Optimization and Control · Mathematics 2019-06-05 Shumon Koga , Iasson Karafyllis , Miroslav Krstic

High-temperature series are computed for a generalized $3d$ Ising model with arbitrary potential. Two specific ``improved'' potentials (suppressing leading scaling corrections) are selected by Monte Carlo computation. Critical exponents are…

Statistical Mechanics · Physics 2009-10-31 Massimo Campostrini , Andrea Pelissetto , Paolo Rossi , Ettore Vicari

The functional delta-method provides a convenient tool for deriving bootstrap consistency of a sequence of plug-in estimators w.r.t. a given functional from bootstrap consistency of the underlying sequence of estimators. It has recently…

Statistics Theory · Mathematics 2016-09-21 Eric Beutner , Henryk Zähle

This research deals with massive multiple hypothesis testing. First regarding multiple tests as an estimation problem under a proper population model, an error measurement called Erroneous Rejection Ratio (ERR) is introduced and related to…

Statistics Theory · Mathematics 2007-06-13 Cheng Cheng

We consider the dunking problem: a solid body at uniform temperature $T_{\text i}$ is placed in a environment characterized by farfield temperature $T_\infty$ and spatially uniform time-independent heat transfer coefficient. We permit…

Numerical Analysis · Mathematics 2024-12-17 Kento Kaneko , Claude Le Bris , Anthony T. Patera

Measurement error is an important problem that has not been very well studied in the context of Functional Data Analysis. To the best of our knowledge, there are no existing methods that address the presence of functional measurement errors…

Statistics Theory · Mathematics 2018-09-19 Sneha Jadhav , Shuangge Ma

A conventional linear model for functional data involves expressing a response variable $Y$ in terms of the explanatory function $X(t)$, via the model: $Y=a+\int_I b(t)X(t)dt+\hbox{error}$, where $a$ is a scalar, $b$ is an unknown function…

Methodology · Statistics 2014-07-01 Peter Hall , Giles Hooker
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