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Gravity does not naturally fit well with canonical quantization. Affine quantization is an alternative procedure that is similar to canonical quantization but may offer a positive result when canonical quantization fails to offer a positive…

General Relativity and Quantum Cosmology · Physics 2019-10-22 John R. Klauder

The long-standing problem of time in canonical quantum gravity is the source of several conceptual and technical issues. Here, recent mathematical results are used to provide a consistent algebraic formulation of dynamical symplectic…

General Relativity and Quantum Cosmology · Physics 2023-01-04 Martin Bojowald , Artur Tsobanjan

Reduced density matrices are a powerful tool in the analysis of entanglement structure, approximate or coarse-grained dynamics, decoherence, and the emergence of classicality. It is straightforward to produce a reduced density matrix with…

Quantum Physics · Physics 2020-03-09 Oleg Kabernik , Jason Pollack , Ashmeet Singh

The paper puts together some loosely connected observations, old and new, on the concept of a quantum field and on the properties of Feynman amplitudes. We recall, in particular, the role of (exceptional) elementary induced representations…

Mathematical Physics · Physics 2013-12-02 Ivan Todorov

The concept of randomized measurements on individual particles has proven to be useful for analyzing quantum systems and is central for methods like shadow tomography of quantum states. We introduce $\textit{collective}$ randomized…

Quantum Physics · Physics 2024-08-12 Satoya Imai , Géza Tóth , Otfried Gühne

The advent of cloud quantum computing has led to the rapid development of quantum algorithms. In particular, it is necessary to study variational quantum-classical hybrid algorithms, which are executable on noisy intermediate-scale quantum…

Quantum Physics · Physics 2020-07-02 Ikko Hamamura , Takashi Imamichi

Graphs are a natural representation for systems based on relations between connected entities. Combinatorial optimization problems, which arise when considering an objective function related to a process of interest on discrete structures,…

Machine Learning · Computer Science 2024-08-21 Victor-Alexandru Darvariu , Stephen Hailes , Mirco Musolesi

We review the definition of geometric quantization, which begins with defining a mathematical framework for the algebra of observables that holds equally well for classical and quantum mechanics. We then discuss prequantization, and go into…

Mathematical Physics · Physics 2007-05-23 William Gordon Ritter

Current decision support systems address domains that are heterogeneous in nature and becoming progressively larger. Such systems often require the input of expert judgement about a variety of different fields and an intensive computational…

Other Statistics · Statistics 2017-07-10 Manuele Leonelli , Eva Riccomagno , Jim Q. Smith

Probabilistic predictions can be evaluated through comparisons with observed label frequencies, that is, through the lens of calibration. Recent scholarship on algorithmic fairness has started to look at a growing variety of…

Machine Learning · Computer Science 2023-05-16 Benedikt Höltgen , Robert C Williamson

The title refers to the area of research which studies infinite groups using measure-theoretic tools, and studies the restrictions that group structure imposes on ergodic theory of their actions. The paper is a survey of recent developments…

Dynamical Systems · Mathematics 2010-08-10 Alex Furman

Generative adversarial networks (GANs) have an enormous potential impact on digital content creation, e.g., photo-realistic digital avatars, semantic content editing, and quality enhancement of speech and images. However, the performance of…

Artificial Intelligence · Computer Science 2021-09-01 Pavel Andreev , Alexander Fritzler , Dmitry Vetrov

Deep neural networks are the state-of-the-art methods for many real-world tasks, such as computer vision, natural language processing and speech recognition. For all its popularity, deep neural networks are also criticized for consuming a…

Machine Learning · Computer Science 2018-12-18 Yunhui Guo

Several problems in physics, in particular the averaging problem in gravity, can be described in a formalism derived from the real-space Renormalization Group (RG) methods. It is shown that the RG flow is provided by the Ricci-Hamilton…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Kamilla Piotrkowska

A method of ``blocking'' triangulations that rests on the self-similarity feature of dynamically triangulated random manifolds is proposed. The method is used to define the renormalization group for random geometries. As an illustration,…

High Energy Physics - Lattice · Physics 2009-10-22 D. Johnston , J-P. Kownacki , A. Krzywicki

The development of randomized algorithms for numerical linear algebra, e.g. for computing approximate QR and SVD factorizations, has recently become an intense area of research. This paper studies one of the most frequently discussed…

Numerical Analysis · Computer Science 2013-08-28 Rafi Witten , Emmanuel Candes

Arithmetical properties of a finite group are properties of the group which are defined by its arithmetical parameters such as the order of the group, the element orders and so on. In this paper, we discuss a number of results on…

Group Theory · Mathematics 2025-04-22 Natalia V. Maslova

This is a survey article on some recent developments in the arithmetic theory of linear algebraic groups over higher-dimensional fields, written for the Notices of the AMS.

Number Theory · Mathematics 2021-01-26 Andrei S. Rapinchuk , Igor A. Rapinchuk

Randomized benchmarking is a widely used experimental technique to characterize the average error of quantum operations. Benchmarking procedures that scale to enable characterization of $n$-qubit circuits rely on efficient procedures for…

Quantum Physics · Physics 2016-05-20 Andrew W. Cross , Easwar Magesan , Lev S. Bishop , John A. Smolin , Jay M. Gambetta

Computer simulations are enabling researchers to investigate systems which are extremely difficult to handle analytically. In the particular case of General Relativity, numerical models have proved extremely valuable for investigations of…

General Relativity and Quantum Cosmology · Physics 2010-04-06 Luis Lehner
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