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I present a partly pedagogic discussion of the Gel'fand-Yaglom formula for the functional determinant of a one-dimensional, second order difference operator, in the simplest settings. The formula is a textbook one in discrete…

Mathematical Physics · Physics 2015-06-03 J. S. Dowker

We study the discrete logarithm problem for the multiplicative group and for elliptic curves over a finite field by using a lifting of the corresponding object to an algebraic number field and global duality. We introduce the…

Number Theory · Mathematics 2007-10-15 Ming-Deh Huang , Wayne Raskind

In 2007, A.I.Aptekarev and his collaborators discovered a sequence of rational approximations to Euler's constant $\gamma$ defined by a linear recurrence. In this paper, we generalize this result and present an explicit construction of…

Number Theory · Mathematics 2012-06-04 Khodabakhsh Hessami Pilehrood , Tatiana Hessami Pilehrood

In [5] I.P. Goulden, D.M. Jackson, and R. Vakil formulated a conjecture relating certain Hurwitz numbers (enumerating ramified coverings of the sphere) to the intersection theory on a conjectural Picard variety. We are going to use their…

Algebraic Geometry · Mathematics 2018-07-18 Sergey Shadrin , Dimitri Zvonkine

Given a rational function of degree at least two defined over a number field k, we study the cardinality of the set of rational iterated preimages. We prove bounds for the cardinality of this set as the rational function varies in certain…

Number Theory · Mathematics 2011-09-29 Aaron Levin

Numerical reasoning over text is a challenging task of Artificial Intelligence (AI), requiring reading comprehension and numerical reasoning abilities. Previous approaches use numerical reasoning programs to represent the reasoning process.…

Artificial Intelligence · Computer Science 2022-10-21 Jiaxin Zhang , Yashar Moshfeghi

We survey an area of recent development, relating dynamics to theoretical computer science. We discuss the theoretical limits of simulation and computation of interesting quantities in dynamical systems. We will focus on central objects of…

Dynamical Systems · Mathematics 2011-04-15 Stefano Galatolo , Mathieu Hoyrup , Cristóbal Rojas

Suppose $E$ is an elliptic curve over $\mathbb{Q}$ and $\chi$ is a Dirichlet character. We use statistical properties of modular symbols to estimate heuristically the probability that $L(E,\chi,1) = 0$. Via the Birch and Swinnerton-Dyer…

Number Theory · Mathematics 2020-08-10 Barry Mazur , Karl Rubin

Dirac's approach to gauge symmetries is discussed. We follow closely the steps that led him from his conjecture concerning the generators of gauge transformations {\it at a given time} --to be contrasted with the common view of gauge…

History and Philosophy of Physics · Physics 2007-05-23 Josep M. Pons

Many safety-critical scientific and engineering systems evolve according to differential-algebraic equations (DAEs), where dynamical behavior is constrained by physical laws and admissibility conditions. In practice, these systems operate…

Machine Learning · Computer Science 2026-04-14 Minxing Zheng , Zewei Deng , Liyan Xie , Shixiang Zhu

Interactive theorem provers, like Isabelle/HOL, Coq and Lean, have expressive languages that allow the formalization of general mathematical objects and proofs. In this context, an important goal is to reduce the time and effort needed to…

Symbolic Computation · Computer Science 2024-05-17 Marcus Rossel , Andrés Goens

Experimental mathematics is an experimental approach to mathematics in which programming and symbolic computation are used to investigate mathematical objects, identify properties and patterns, discover facts and formulas and even…

Combinatorics · Mathematics 2020-05-19 Yukun Yao

This paper discusses limitations of reflexive and diagonal arguments as methods of proof of limitative theorems (e.g. G\"odel's theorem on Entscheidungsproblem, Turing's halting problem or Chaitin-G\"odel's theorem). The fact, that a formal…

Logic in Computer Science · Computer Science 2015-03-19 Kajetan Młynarski

Reliable uncertainty estimation has become a crucial requirement for the industrial deployment of deep learning algorithms, particularly in high-risk applications such as autonomous driving and medical diagnosis. However, mainstream…

Machine Learning · Computer Science 2024-09-10 Junyu Gao , Mengyuan Chen , Liangyu Xiang , Changsheng Xu

We propose a new method based on machine learning to \emph{play the devil's advocate} and investigate the impact of unknown systematic effects in a quantitative way. This method proceeds by reversing the measurement process and using the…

High Energy Physics - Experiment · Physics 2023-09-11 Andrei Golutvin , Aleksandr Iniukhin , Andrea Mauri , Patrick Owen , Nicola Serra , Andrey Ustyuzhanin

We introduce Explanatory Learning (EL), a framework to let machines use existing knowledge buried in symbolic sequences -- e.g. explanations written in hieroglyphic -- by autonomously learning to interpret them. In EL, the burden of…

Provability logic concerns the study of modality $\Box$ as provability in formal systems such as Peano arithmetic. Natural, albeit quite surprising, topological interpretation of provability logic has been found in the 1970's by Harold…

Logic · Mathematics 2012-10-30 Lev Beklemishev , David Gabelaia

In 1987 Serre conjectured that any mod l ("ell", not "1") two-dimensional irreducible odd representation of the absolute Galois group of the rationals came from a modular form in a precise way. We present a generalisation of this conjecture…

Number Theory · Mathematics 2019-12-19 Kevin Buzzard , Fred Diamond , Frazer Jarvis

The set of special unipotent representations of a semisimple Lie group was defined by Barbasch and Vogan. According to predictions of Arthur (established by Adams, Barbasch, and Vogan), this set is an overlapping union of Arthur packets.…

Representation Theory · Mathematics 2011-06-22 Dan M. Barbasch , Peter E. Trapa

Researchers have demonstrated state-of-the-art performance in sequential decision making problems (e.g., robotics control, sequential prediction) with deep neural network models. One often has access to near-optimal oracles that achieve…

Machine Learning · Computer Science 2017-03-06 Wen Sun , Arun Venkatraman , Geoffrey J. Gordon , Byron Boots , J. Andrew Bagnell