English
Related papers

Related papers: Goodstein revisited

200 papers

We investigate the theory PAI (Peano Arithmetic with Indiscernibles). Models of PAI are of the form (M, I), where M is a model of PA, I is an unbounded set of order indiscernibles over M, and (M, I) satisfies the extended induction scheme…

Logic · Mathematics 2022-12-19 Ali Enayat

The consistency of posterior distributions in density estimation is at the core of Bayesian statistical theory. Classical work established sufficient conditions, typically combining KL support with complexity bounds on sieves of high prior…

Statistics Theory · Mathematics 2025-10-22 Nicola Bariletto , Stephen G. Walker

Bayesian inference and uncertainty quantification in a general class of non-linear inverse regression models is considered. Analytic conditions on the regression model $\{\mathscr G(\theta): \theta \in \Theta\}$ and on Gaussian process…

Statistics Theory · Mathematics 2021-04-16 François Monard , Richard Nickl , Gabriel P. Paternain

In Commutative Algebra structure results on minimal free resolutions of Gorenstein modules are of classical interest. We define Gorenstein modules of finite length over the weighted polynomial ring via symmetric matrices in divided powers.…

Commutative Algebra · Mathematics 2008-07-21 Michael Kunte

We present an elementary and explicit proof of the separability criterion for continuous variable two-party Gaussian systems. Our proof is based on an elementary formulation of uncertainty relations and an explicit determination of…

Quantum Physics · Physics 2008-07-19 Kazuo Fujikawa

A famous conjecture of Graham asserts that every set $A \subseteq \mathbb{Z}_p \setminus \{0\}$ can be ordered so that all partial sums are distinct. Although this conjecture was recently proved for sufficiently large primes by Pham and…

Combinatorics · Mathematics 2026-02-24 Simone Costa , Stefano Della Fiore

We give a survey on the general effective reduction theory of integral polynomials and its applications. We concentrate on results providing the finiteness for the number of `$\mathbb{Z}$-equivalence classes' and…

Number Theory · Mathematics 2025-12-01 Jan-Hendrik Evertse , Kálmán Győry

We obtain a uniform stability of recovering entire functions of a special form from their zeros. To this form, one can reduce the characteristic determinants of strongly regular differential operators and pencils of the first and the second…

Spectral Theory · Mathematics 2021-10-04 Sergey Buterin

We use techniques of proof mining to extract a uniform rate of metastability (in the sense of Tao) for the strong convergence of approximants to fixed points of uniformly continuous pseudocontractive mappings in Banach spaces which are…

Functional Analysis · Mathematics 2020-01-17 Ulrich Kohlenbach , Andrei Sipos

In physics, all dynamical equations that describe fundamental interactions are second order ordinary differential equations in the time derivatives. In the literature, this property is traced back to a result obtained by Ostrogradski in the…

General Relativity and Quantum Cosmology · Physics 2025-03-03 Aaron Collavini , Stefano Ansoldi

Gaussian Process regression is a kernel method successfully adopted in many real-life applications. Recently, there is a growing interest on extending this method to non-Euclidean input spaces, like the one considered in this paper,…

Machine Learning · Computer Science 2022-12-05 Antonio Candelieri , Andrea Ponti , Francesco Archetti

We introduce a new concept, the APN-defect, which can be thought of as measuring the distance of a given function $G:\mathbb{F}_{2^n} \rightarrow \mathbb{F}_{2^n}$ to the set of almost perfect nonlinear (APN) functions. This concept is…

Information Theory · Computer Science 2024-06-12 Nurdagül Anbar , Tekgül Kalaycı , Alev Topuzoğlu

We study reflection principles of Peano Arithmetic PA which are based on both proof and provability. Any such reflection principle in PA is equivalent to either $\Box P\!\rightarrow\! P$ ($\Box P$ stands for `$P$ is provable') or $\Box^k…

Logic · Mathematics 2014-05-13 Elena Nogina

Measuring dependence between random variables is a fundamental problem in Statistics, with applications across diverse fields. While classical measures such as Pearson's correlation have been widely used for over a century, they have…

Statistics Theory · Mathematics 2025-10-08 Marta Catalano , Hugo Lavenant

The question of optimally approximating an arbitrary probability measure in the Wasserstein distance by a discrete one with uniform weights is considered. Estimates are obtained for the optimal approximation distance, with an explicit rate…

Probability · Mathematics 2026-04-14 Benjamin Seeger

This Comment argues that two assumptions, which are presented as basic assumptions of Bell's theorem in [J. Handsteiner et al., Phys. Rev. Lett. 118, 060401 (2017)] and elsewhere, in fact follow from more basic premises. Measurement…

Quantum Physics · Physics 2017-05-12 Nathan Argaman

In classical physics, events follow a definite causal order: the past influences the future, but not the reverse. Quantum theory, however, permits superpositions of causal orders -- so-called indefinite causal orders -- which can provide…

Quantum Physics · Physics 2026-04-29 Carla M. D. Richter , Michael Antesberger , Huan Cao , Philip Walther , Lee A. Rozema

In 1977, Malament proved a certain uniqueness theorem about standard synchrony, also known as Poincar\'e-Einstein simultaneity, which has generated many commentaries over the years, some of them contradictory. We think that the situation…

Mathematical Physics · Physics 2012-10-09 Fabien Besnard

In his Autobiographical Notes, Einstein mentioned that on his road to the final theory of general relativity it was a major difficulty to accustom himself to the idea that coordinates need not possess an immediate physical meaning in terms…

History and Philosophy of Physics · Physics 2018-01-30 Dennis Dieks

This paper considers the problem of regression over distributions, which is becoming increasingly important in machine learning. Existing approaches often ignore the geometry of the probability space or are computationally expensive. To…

Machine Learning · Computer Science 2025-10-31 Maksim Maslov , Alexander Kugaevskikh , Matthew Ivanov