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Due to lack of scientific understanding, some mechanisms may be missing in mathematical modeling of complex phenomena in science and engineering. These mathematical models thus contain some uncertainties such as uncertain parameters. One…

Probability · Mathematics 2012-04-05 Jinqiao Duan , Ting Gao , Guowei He

Due to their intuitive appeal, Bayesian methods of modeling and uncertainty quantification have become popular in modern machine and deep learning. When providing a prior distribution over the parameter space, it is straightforward to…

Machine Learning · Statistics 2025-06-05 Ivan Melev , Goeran Kauermann

The origin of the radiatively induced Lorentz and CPT violations, in perturbative evaluations, of an extended version of QED, is investigated. Using a very general calculational method, concerning the manipulations and calculations…

High Energy Physics - Theory · Physics 2011-07-19 O. A. Battistel , G. Dallabona

Interpretability research takes counterfactual theories of causality for granted. Most causal methods rely on counterfactual interventions to inputs or the activations of particular model components, followed by observations of the change…

Machine Learning · Computer Science 2024-07-08 Aaron Mueller

We investigate the influence of random errors in external control parameters on the stability of holonomic quantum computation in the case of arbitrary loops and adiabatic connections. A simple expression is obtained for the case of small…

Quantum Physics · Physics 2009-11-13 P. V. Buividovich , V. I. Kuvshinov

We present some informal remarks on aspects of relativistic quantum computing.

Quantum Physics · Physics 2007-05-23 S. Pakvasa , W. Simmons , X. Tata

Uncertainty quantification is a key part of astronomy and physics; scientific researchers attempt to model both statistical and systematic uncertainties in their data as best as possible, often using a Bayesian framework. Decisions might…

Instrumentation and Methods for Astrophysics · Physics 2022-07-29 Peter Hatfield

The goal of this Section is to formulate some of the basic results on the theory of integral equations and mention some of its applications. The literature of this subject is very large. Proofs are not given due to the space restriction.…

Classical Analysis and ODEs · Mathematics 2015-03-03 A. G. Ramm

Atomistic simulations often rely on interatomic potentials to access greater time- and length- scales than those accessible to first principles methods such as density functional theory (DFT). However, since a parameterised potential…

Materials Science · Physics 2024-10-08 I. R. Best , T. J. Sullivan , J. R. Kermode

Contraction coefficients give a quantitative strengthening of the data processing inequality. As such, they have many natural applications whenever closer analysis of information processing is required. However, it is often challenging to…

Quantum Physics · Physics 2024-05-24 Christoph Hirche

The homogeneous transform has many practical applications outside the realm of mathematics, for instance to represent the proportions of several chemical substances. We aim here to present results about the transformation of measures, which…

Functional Analysis · Mathematics 2016-10-10 Hubert Holin

We describe the difficulties that advanced undergraduate and graduate students have with quantum measurement within the standard interpretation of quantum mechanics. We explore the possible origins of these difficulties by analyzing student…

Physics Education · Physics 2016-04-05 Guangtian Zhu , Chandralekha Singh

It brings into attention briefly the genuine significance of uncertainty relations and of their extrapolations for which conventional(usual) doctrine promotes unjustified ideas.

Quantum Physics · Physics 2015-01-14 Spiridon Dumitru

Invariances in neural networks are useful and necessary for many tasks. However, the representation of the invariance of most neural network models has not been characterized. We propose measures to quantify the invariance of neural…

Machine Learning · Computer Science 2023-10-27 Facundo Manuel Quiroga , Jordina Torrents-Barrena , Laura Cristina Lanzarini , Domenec Puig-Valls

I give a brief overview of fault-tolerant quantum computation, with an emphasis on recent work and open questions.

Quantum Physics · Physics 2007-08-31 Daniel Gottesman

We propose the experimental test of the uncertainty principle. From sub-quantum models it follows that the uncertainty principle may be not true on short time intervals of the order of a picosecond. The positive result of this experiment…

Quantum Physics · Physics 2007-05-23 Jiri Soucek

Further formulas are presented involving quantum mechanics, thermodynamics, and integrable systems. Modifications of dispersionless theory are developed.

High Energy Physics - Theory · Physics 2007-05-23 Robert Carroll

Evaluated nuclear data uncertainties are often perceived as unrealistic, most often because they are thought to be too small. The impact of this issue in applied nuclear science has been discussed widely in recent years. Commonly suggested…

Data Analysis, Statistics and Probability · Physics 2020-04-28 R. Capote , S. Badikov , A. Carlson , I. Duran , F. Gunsing , D. Neudecker , V. G. Pronyaev , P. Schillebeeckx , G. Schnabel , D. L. Smith , A. Wallner

Statistical inferential results generally come with a measure of reliability for decision-making purposes. For a policy implementer, the value of implementing published policy research depends critically upon this reliability. For a policy…

Other Statistics · Statistics 2024-08-21 Duncan Ermini Leaf

The effects of any quantum measurement can be described by a collection of measurement operators {M_m} acting on the quantum state of the measured system. However, the Hilbert space formalism tends to obscure the relationship between the…

Quantum Physics · Physics 2009-11-07 Holger F. Hofmann