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Related papers: Types, equations, dimensions and the Pi theorem

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Measures of similarity (or dissimilarity) are a key ingredient to many machine learning algorithms. We introduce DID, a pairwise dissimilarity measure applicable to a wide range of data spaces, which leverages the data's internal structure…

Machine Learning · Statistics 2022-03-08 Théophile Cantelobre , Carlo Ciliberto , Benjamin Guedj , Alessandro Rudi

We investigate the connection between the two major mathematical frameworks for modeling interactive beliefs: Harsanyi type spaces and possible-worlds style probability frames. While translating the former into the latter is…

Logic in Computer Science · Computer Science 2017-07-28 Adam Bjorndahl , Joseph Y. Halpern

For the right application, the use of programming paradigms such as functional or logic programming can enormously increase productivity in software development. But these powerful paradigms are tied to exotic programming languages, while…

Software Engineering · Computer Science 2007-05-23 M. H. van Emden , S. C. Somosan

Optimization in large language models (LLMs) unfolds over high-dimensional parameter spaces with non-Euclidean structure. Information geometry frames this landscape using the Fisher information metric, enabling more principled learning via…

Computation and Language · Computer Science 2025-12-09 Riccardo Di Sipio

This paper introduces a new notion of dimensionality of probabilistic models from an information-theoretic view point. We call it the "descriptive dimension"(Ddim). We show that Ddim coincides with the number of independent parameters for…

Machine Learning · Computer Science 2019-10-28 Kenji Yamanishi

The class of Basic Feasible Functionals BFF$_2$ is the type-2 counterpart of the class FP of type-1 functions computable in polynomial time. Several characterizations have been suggested in the literature, but none of these present a…

Logic in Computer Science · Computer Science 2023-06-22 Emmanuel Hainry , Bruce M. Kapron , Jean-Yves Marion , Romain Péchoux

We describe a method for deepening a student's understanding of basic physics by asking the student to express physical ideas in a functional programming language. The method is implemented in a second-year course in computational physics…

Computers and Society · Computer Science 2014-12-17 Scott N. Walck

Heisenberg's uncertainty principle is often cited as an example of a "purely quantum" relation with no analogue in the classical limit where $\hbar \to 0$. However, this formulation of the classical limit is problematic for many reasons,…

Quantum Physics · Physics 2021-02-23 Viola Gattus , Sotirios Karamitsos

A group of dimensionless numbers, termed DLV (Density-Length-Velocity) system, is put forward to represent the scaled behavior of structures under impact loads. It is obtained by means of the Buckingham Pi theorem with an alternative basis.…

Classical Physics · Physics 2021-07-02 Shuai Wang , Fei Xu , Zhen Dai

The binary radix expansion of a real number can be used to code the outcome of any series of coin tosses, a fact that provides an intriguing link between number theory, measure theory and statistical physics. Inspired by this fact, a…

Mathematical Physics · Physics 2020-03-11 Vladimir García-Morales , Javier Cervera , José A. Manzanares

Currently it is widely accepted that the language of science is mathematics. This book explores an alternative idea where the future of science is based on the language of algorithms and programs. How such a language can actually be…

Logic in Computer Science · Computer Science 2020-11-06 Garry Pantelis

We present an open-source computer program written in Python language for quantum measurement and related issues. In our program, quantum states and operators, including quantum gates, can be developed into a quantum-object function…

Quantum Physics · Physics 2021-03-17 Le Bin Ho , Kieu Quang Tuan , Hung Q. Nguyen

We show that the dimension of the geometric shape formed by the phenomenologically valid points inside a multi-dimensional parameter space can be used to characterise different new physics models and to define a quantitative measure for the…

High Energy Physics - Phenomenology · Physics 2015-05-20 Thorsten Feldmann , Christoph Promberger , Stefan Recksiegel

Classically domain theory is a rigourous mathematical structure to describe denotational semantics for programming languages and to study the computability of partial functions. Recently, the application of domain theory has also been…

Quantum Physics · Physics 2007-05-23 Elham Kashefi

Patterns provide a concise, syntactic way of describing a set of strings, but their expressive power comes at a price: a number of fundamental decision problems concerning (erasing) pattern languages, such as the membership problem and…

Formal Languages and Automata Theory · Computer Science 2019-05-21 Ziyuan Gao

We give an overview of our philosophy of pictures in mathematics. We emphasize a bi-directional process between picture language and mathematical concepts: abstraction and simulation. This motivates a program to understand different…

History and Overview · Mathematics 2018-03-13 Arthur Jaffe , Zhengwei Liu

If a one-phrase summary of the subject of this thesis were required, it would be something like: miscellaneous large (but finite) dimensional phenomena in quantum information theory. That said, it could nonetheless be helpful to briefly…

Quantum Physics · Physics 2016-07-26 Cécilia Lancien

In order for language models to aid physics research, they must first encode representations of mathematical and natural language discourse which lead to coherent explanations, with correct ordering and relevance of statements. We present a…

Computation and Language · Computer Science 2023-06-05 Jordan Meadows , Zili Zhou , Andre Freitas

A generalized form of Wien's displacement law and the blackbody radiation laws of (a) Rayleigh and Jeans, (b) Rayleigh, (c) Wien and Paschen, (d) Thiesen and (e) Planck are derived using principles of dimensional analysis. This kind of…

Mathematical Physics · Physics 2008-03-22 Gerhard Kramm , Fritz Herbert

Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both…