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We develop a new framework of uncertainty variables to model uncertainty. An uncertainty variable is characterized by an uncertainty set, in which its realization is bound to lie, while the conditional uncertainty is characterized by a set…

Machine Learning · Statistics 2019-12-10 Rajat Talak , Sertac Karaman , Eytan Modiano

Using a new Bayesian method for solving inverse quantum problems, potentials of quantum systems are reconstructed from coordinate measurements in non-stationary states. The approach is based on two basic inputs: 1. a likelihood model,…

Quantum Physics · Physics 2007-05-23 J. C. Lemm

We show that the quantum-mechanical probability distribution involving complex probability amplitudes can be derived from three natural conditions imposed on a relativistically invariant probability function describing the motion of a…

Quantum Physics · Physics 2025-12-12 Karol Sajnok , Kacper Dębski , Andrzej Dragan

This paper is concerned with the study of the consistency of a variational method for probability measure quantization, deterministically realized by means of a minimizing principle, balancing power repulsion and attraction potentials. The…

Functional Analysis · Mathematics 2013-10-07 Massimo Fornasier , Jan-Christian Hütter

We propose a generalization of the Poincar\'e-Birkhoff Theorem on area-preserving twist maps to area-preserving twist maps that are random with respect to an ergodic probability measure. The classical theory is a particular instance of the…

Dynamical Systems · Mathematics 2014-12-09 Álvaro Pelayo , Fraydoun Rezakhanlou

A variational Perturbation theory based on the functional integral approach is formulated for many-particle systems. Using the variational action obtained through Jensen-Peierls' inequality, a perturbative expansion scheme for the…

Strongly Correlated Electrons · Physics 2009-10-31 Sang Koo You , Chul Koo Kim , Kyun Nahm , Hyun Sik Noh

Probabilistic regression techniques in control and robotics applications have to fulfill different criteria of data-driven adaptability, computational efficiency, scalability to high dimensions, and the capacity to deal with different…

Machine Learning · Computer Science 2021-03-31 Hany Abdulsamad , Peter Nickl , Pascal Klink , Jan Peters

Using connection with quantum field theory, the infinitesimal covariant abelian gauge transformation laws of relativistic two-particle constraint theory wave functions and potentials are established and weak invariance of the corresponding…

High Energy Physics - Theory · Physics 2009-10-30 H. Jallouli , H. Sazdjian

A program invariant is a property that holds for every execution of the program. Recent work suggest to infer likely-only invariants, via dynamic analysis. A likely invariant is a property that holds for some executions but is not…

Software Engineering · Computer Science 2007-05-23 Tristan Denmat , Arnaud Gotlieb , Mireille Ducasse

We seek to establish qualitative convergence results to a general class of evolution PDEs described by gradient flows in optimal transportation distances. These qualitative convergence results come from dynamical systems under the general…

Analysis of PDEs · Mathematics 2020-10-02 J. A. Carrillo , R. S. Gvalani , J. Wu

The concept of gauge invariance can be considered one of the most subtle and useful concept in theoretical physics since it can permit the comprehension of difficult systems in physics with an arbitrary choice of a reference frame at every…

High Energy Physics - Theory · Physics 2010-01-19 E. M. C. Abreu , J. Ananias Neto , A. C. R. Mendes , C. Neves , W. Oliveira

We present a first-principles implementation of spatial scale invariance as a local gauge symmetry in geometry dynamics using the method of best matching . In addition to the 3-metric, the proposed scale invariant theory also contains a…

General Relativity and Quantum Cosmology · Physics 2009-10-12 Hans F. Westman

It is often claimed that Bayesian methods, in particular Bayes factor methods for hypothesis testing, can deal with optional stopping. We first give an overview, using elementary probability theory, of three different mathematical meanings…

Statistics Theory · Mathematics 2021-03-24 Allard Hendriksen , Rianne de Heide , Peter Grünwald

We propose a path integral formulation for scale invariant quantum field theories. We do it by modifying the functional integration measure in such a way that the partition function is always exactly scale invariant, at the cost of having…

High Energy Physics - Theory · Physics 2020-07-10 Mario Herrero-Valea

The dynamical properties of the gauge theory of Born-Infeld type action, which is expected as the high-energy effective theory, are investigated by adding a complex scalar field to this gauge system. Especially the Coleman-Weinberg…

High Energy Physics - Theory · Physics 2007-05-23 Kazuo Ghoroku , Kazunari Kaneko

The aim of this note is to introduce a notion of dynamical entropy, which we call infinite-product entropy, for probability measures on (countable) infinite cartesian product of any measurable space with itself. The idea behind the…

Probability · Mathematics 2024-10-29 Maysam Maysami Sadr , Mina Shahrestani , Danial Bouzarjomehri Amnieh

In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the…

Optimization and Control · Mathematics 2018-01-09 Randa Herzallah

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions can be seen as a special case when the density matrix is restricted to be…

Quantum Physics · Physics 2009-01-12 Manfred K Warmuth , Dima Kuzmin

We propose that a quantum particle in a potential in one space dimension can be described by a probabilistic cellular automaton. While the simple updating rule of the automaton is deterministic, the probabilistic description is introduced…

Quantum Physics · Physics 2022-12-01 C. Wetterich

New integral formulas involving the Meijer $G$-function are derived using recent results concerning distributional characterisations and distributional transformations in probability theory.

Classical Analysis and ODEs · Mathematics 2018-01-16 Robert E. Gaunt