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It is shown that self-dual theories generalize to four dimensions both the conformal and analytic aspects of two-dimensional conformal field theories. In the harmonic space language there appear several ways to extend complex analyticity…

High Energy Physics - Theory · Physics 2009-10-22 V. Ogievetsky , F. Gursey , M. Evans

A strong analog classical simulation of general quantum evolution is proposed, which serves as a novel scheme in quantum computation and simulation. The scheme employs the approach of geometric quantum mechanics and quantum informational…

Quantum Physics · Physics 2017-03-16 Dong-Sheng Wang

We propose a measure based upon the fundamental theoretical concept in algorithmic information theory that provides a natural approach to the problem of evaluating $n$-dimensional complexity by using an $n$-dimensional deterministic Turing…

Computational Complexity · Computer Science 2015-08-27 Hector Zenil , Fernando Soler-Toscano , Jean-Paul Delahaye , Nicolas Gauvrit

Our goal is to establish existence with suitable initial data of solutions to general parabolic equation in one dimension, $u_t = L(u_x)_x$, where $L$ is merely a monotone function. We also expose the basic properties of solutions,…

Analysis of PDEs · Mathematics 2012-07-23 Piotr Bogusław Mucha , Piotr Rybka

In this article algebraic constructions are introduced in order to study the variety defined by a radical parametrization (a tuple of functions involving complex numbers, $n$ variables, the four field operations and radical extractions). We…

Algebraic Geometry · Mathematics 2017-02-02 J. Rafael Sendra , David Sevilla , Carlos Villarino

A novel method for extracting physical parameters from experimental and simulation data is presented. The method is based on statistical concepts and it relies on Monte Carlo simulation techniques. It identifies and determines with maximal…

High Energy Physics - Phenomenology · Physics 2012-05-31 C. N. Papanicolas , E. Stiliaris

Symbolic regression is a machine learning technique that can learn the governing formulas of data and thus has the potential to transform scientific discovery. However, symbolic regression is still limited in the complexity and…

Machine Learning · Computer Science 2023-05-30 Michael Zhang , Samuel Kim , Peter Y. Lu , Marin Soljačić

Complete analysis of quantum wave functions of linear systems in an arbitrary number of dimensions is given. It is shown how one can construct a complete set of stationary quantum states of an arbitrary linear system from purely classical…

Quantum Physics · Physics 2007-06-13 Tomasz Sowinski

Archetypal analysis represents a set of observations as convex combinations of pure patterns, or archetypes. The original geometric formulation of finding archetypes by approximating the convex hull of the observations assumes them to be…

Machine Learning · Statistics 2014-04-08 Sohan Seth , Manuel J. A. Eugster

Quantum theory expresses the observable relations between physical properties in terms of probabilities that depend on the specific context described by the "state" of a system. However, the laws of physics that emerge at the macroscopic…

Quantum Physics · Physics 2016-06-06 Holger F. Hofmann

As is known, factor analysis is a popular method to reduce dimension for high-dimensional data. For matrix data, the dimension reduction can be more effectively achieved through both row and column directions. In this paper, we introduce a…

Methodology · Statistics 2019-04-17 Xialu Liu , Elynn Chen

Classical Decision Theory provides a normative framework for representing and reasoning about complex preferences. Straightforward application of this theory to automate decision making is difficult due to high elicitation cost. In response…

Artificial Intelligence · Computer Science 2013-01-30 Vu A. Ha , Peter Haddawy

We study new Legendre transforms in classical mechanics and investigate some of their general properties. The behaviour of the new functions is analyzed under coordinate transformations.When invariance under different kinds of…

General Relativity and Quantum Cosmology · Physics 2013-10-23 Ginés R. Pérez Teruel

Qualitative Spatial and Temporal Reasoning (QSTR) is concerned with symbolic knowledge representation, typically over infinite domains. The motivations for employing QSTR techniques range from exploiting computational properties that allow…

Artificial Intelligence · Computer Science 2016-06-02 Frank Dylla , Jae Hee Lee , Till Mossakowski , Thomas Schneider , André Van Delden , Jasper Van De Ven , Diedrich Wolter

Variational analysis provides the theoretical foundations and practical tools for constructing optimization algorithms without being restricted to smooth or convex problems. We survey the central concepts in the context of a concrete but…

Optimization and Control · Mathematics 2025-04-08 Johannes O. Royset

The Dirac equation for an electron in two spatial dimensions in the Coulomb and homogeneous magnetic fields is discussed. For weak magnetic fields, the approximate energy values are obtained by semiclassical method. In the case with strong…

Quantum Physics · Physics 2009-11-06 Choon-Lin Ho , V. R. Khalilov

We propose some new uses of toric variety structures in the study of quantum computation for small radices. In particular, we observe the concurrence of the equivalence classes of quantum states under quantum measurement and the orbits of…

Predictive theory to geometrically engineer devices and materials in continuum systems to have desired topological-like effects is developed here by bridging the gap between quantum and continuum mechanical descriptions. A platonic crystal,…

Mesoscale and Nanoscale Physics · Physics 2018-12-05 Mehul Makwana , Richard Craster

We study the use of the Euler characteristic for multiparameter topological data analysis. Euler characteristic is a classical, well-understood topological invariant that has appeared in numerous applications, including in the context of…

Algebraic Topology · Mathematics 2021-02-17 Gabriele Beltramo , Rayna Andreeva , Ylenia Giarratano , Miguel O. Bernabeu , Rik Sarkar , Primoz Skraba

The traditional display of elements in the periodic table is convenient for the study of chemistry and physics. However, the atomic number alone is insufficient for training statistical machine learning models to describe and extract…

Materials Science · Physics 2023-08-25 Anthony Onwuli , Ashish V. Hegde , Kevin Nguyen , Keith T. Butler , Aron Walsh