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This paper shows that the problem of testing hypotheses in moment condition models without any assumptions about identification may be considered as a problem of testing with an infinite-dimensional nuisance parameter. We introduce a…

Statistics Theory · Mathematics 2014-09-24 Isaiah Andrews , Anna Mikusheva

Chronic disease progression models are governed by three main parameters: sensitivity, preclinical intensity, and sojourn time. The estimation of these parameters helps in optimizing screening programs and examine the improvement in…

Applications · Statistics 2020-01-22 Ayman Hijazy , András Zempléni

Motivated by the growing importance of fidelity in quantum critical phenomena, we establish a general relation between fidelity and structure factor of the driving term in a Hamiltonian through a newly introduced concept: fidelity…

Quantum Physics · Physics 2009-11-13 Wen-Long You , Ying-Wai Li , Shi-Jian Gu

High-dimensional predictive models, those with more measurements than observations, require regularization to be well defined, perform well empirically, and possess theoretical guarantees. The amount of regularization, often determined by…

Methodology · Statistics 2019-07-16 Darren Homrighausen , Daniel J. McDonald

Astrophysical observations suggest that the fine structure constant (alpha) may (or may not) be evolving over the cosmological time scale. This raises a much debated question: is alpha variation due to the variation of the speed of light…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. Yu. Ignatiev , B. J. Carson

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring…

Quantitative Methods · Quantitative Biology 2011-11-09 Ryan N. Gutenkunst , Joshua J. Waterfall , Fergal P. Casey , Kevin S. Brown , Christopher R. Myers , James P. Sethna

We address quantum critical systems as a resource in quantum estimation and derive the ultimate quantum limits to the precision of any estimator of the coupling parameters. In particular, if L denotes the size of a system and \lambda is the…

Quantum Physics · Physics 2009-11-13 Paolo Zanardi , Matteo G A Paris , Lorenzo Campos Venuti

Instrumental variables regression is a tool that is commonly used in the analysis of observational data. The instrumental variables are used to make causal inference about the effect of a certain exposure in the presence of unmeasured…

Methodology · Statistics 2023-09-07 Valentin Vancak , Arvid Sjölander

In practice, uncertainties in parameters and model structures always cause a gap between a model and the corresponding physical entity. Hence, to evaluate the performance of a model, the bounds of this gap must be assessed. In this paper,…

Optimization and Control · Mathematics 2021-02-08 Peng Wang , Shaobu Wang , Renke Huang , Zhenyu Huang

The quantum variables that can be accessed directly by experiments are described by observables. Therefore, physical parameters can only be evaluated indirectly, via estimations based on experimental measurement results. I show that the…

Quantum Physics · Physics 2012-12-12 B. M. Escher

It has long been recognized that the key to understand kinetic friction force $F_k$ is the analysis of microscopic instabilities that lead to sudden irreversible "pops" of certain degrees of freedom. In this Letter, the nature of such…

Materials Science · Physics 2016-08-16 Martin H. Müser

We study the dynamical response of a system to a sudden change of the tuning parameter $\lambda$ starting (or ending) at the quantum critical point. In particular we analyze the scaling of the excitation probability, number of excited…

Statistical Mechanics · Physics 2010-01-20 C. De Grandi , V. Gritsev , A. Polkovnikov

Many optimization problems in electrical engineering consider a large number of design parameters. A sensitivity analysis identifies the design parameters with the strongest influence on the problem of interest. This paper introduces the…

Computational Engineering, Finance, and Science · Computer Science 2023-07-07 M. Greta Ruppert , Yvonne Späck-Leigsnering , Julian Buschbaum , Herbert De Gersem

In the framework of an extended phenomenological approach to phase transitions, it is shown that existing nonlinear relation between local critical atomic parameters and phenomenological order parameter induces the corresponding nonlinear…

Statistical Mechanics · Physics 2015-06-23 Vladimir Dmitriev

Robustness analyzes the impact of small perturbations in the semantics of a model. This allows to model hardware imprecision and therefore it has been applied to determine implementability of timed automata. In a recent paper, we extend…

Software Engineering · Computer Science 2012-07-19 Louis-Marie Traonouez

In complex systems, external parameters often determine the phase in which the system operates, i.e., its macroscopic behavior. For nearly a century, statistical physics has extensively studied systems' transitions across phases,…

In order to investigate the evolutionary process of many deterministic Dynamical systems with unfixed parameter, a set of dynamical models with parameter changing continuously and the accumulation of this change might be large is introduced…

comp-gas · Physics 2008-02-03 H. P. Fang

This review article is devoted to application of precision molecular spectroscopy to studies of the possible spatial and temporal variations of the fundamental constants. Both astrophysical observations and laboratory experiments are…

Atomic Physics · Physics 2009-07-18 V. V. Flambaum , M. G. Kozlov

Many models of quintessence predict a time variation of the fundamental constants as well as a composition-dependent gravity like long-range force mediated by the cosmon. We present bounds for the cosmon coupling to matter and radiation…

High Energy Physics - Phenomenology · Physics 2009-11-07 C. Wetterich

Changes in parameters of a physical device can eventually lead to catastrophic failure. This paper discusses a parameter estimation method based on synchronization between a model and time series data. In particular, we examine the…

chao-dyn · Physics 2007-05-23 Justin Goodwin , Reggie Brown , Lutz Junge