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A new method for nonperturbative investigations of quantum gravity is presented in which the simplicial path integral is approximated by the partition function of a spin system. This facilitates analytical and numerical computations…

High Energy Physics - Lattice · Physics 2009-10-28 W. Beirl , P. Homolka , B. Krishnan , H. Markum , J. Riedler

Some elementary rigorous remark about the replica formalism in the Statistical Physics' approach to threshold phenomena in Computational Complexity Theory is presented.

Mathematical Physics · Physics 2007-05-23 Gavriel Segre

We revisit Coincident General Relativity (CGR) in the gauge approach to gravity based on Symmetric Teleparallel Equivalent to General Relativity (STEGR) in the {\it internal-space formulation}, which one of the authors recently proposed in…

General Relativity and Quantum Cosmology · Physics 2025-09-22 Kyosuke Tomonari , Taishi Katsuragawa , Shin'ichi Nojiri

Community News: - Center for Gravitational Wave Physics, by Sam Finn - Perimeter Institute for Theoretical Physics, by Lee Smolin Research Briefs: - Detector and Data Developments within GEO 600, by Alicia Sintes - The Virtual Data Grid and…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Jorge Pullin

Background: This invited paper is the result of an invitation to write a retrospective article on a "TSE most influential paper" as part of the journal's 50th anniversary. Objective: To reflect on the progress of software engineering…

Software Engineering · Computer Science 2025-01-31 Martin Shepperd

In this PhD thesis I make use of the "Effective Field Theory of Gravity for Extended Objects" by Goldberger and Rothstein in order to investigate theories of gravity and to take a different point of view on the physical information that can…

General Relativity and Quantum Cosmology · Physics 2015-03-19 Umberto Cannella

General relativity (GR) characterizes gravity as a geometric properly exhibited as curvature on spacetime. Teleprallelism describes gravity through torsional properties, and can reproduce GR at the level of equations. Similar to f(R)…

General Relativity and Quantum Cosmology · Physics 2017-12-21 Jackson Levi Said

The goal of this paper is to provide a theory linear regression based entirely on approximations. It will be argued that the standard linear regression model based theory whether frequentist or Bayesian has failed and that this failure is…

Methodology · Statistics 2024-02-16 Laurie Davies

Einstein's goal of producing an advanced gravitational model that was independent of special relativity's "non-gravitational" derivations has arguably still not been achieved. The author produced a paper in 1998 outlining a possible method…

General Physics · Physics 2007-05-23 Eric Baird

Reinforcement learning has long struggled with poor sample efficiency. One promising approach to mitigate this problem is leveraging group-invariant Markov Decision Processes ($G$-invariant MDPs). Existing works in this direction have…

Machine Learning · Computer Science 2026-05-25 Shuai Zhen , Yifan Zhang , Yuling Wang , Yanhua Yu

This paper has been withdrawn by the author because similar published work on the topic was overlooked. See S. Deser and A. Waldron, Nucl. Phys. B 631, 369-387 (2002).

High Energy Physics - Theory · Physics 2007-12-15 Teymour Darkhosh

In the present paper we will investigate the relation between scalar-tensor theory and $f(R)$ theories of gravity. Such studies have been performed in the past for the metric formalism of $f(R)$ gravity; here we will consider mainly the…

General Relativity and Quantum Cosmology · Physics 2010-04-06 Thomas P. Sotiriou

We present a detailed mathematical study of the Monte Carlo replica method as applied in the global fitting literature from the high-energy physics theory community. For the first time, we provide a rigorous derivation of the parameter…

High Energy Physics - Phenomenology · Physics 2024-04-17 Mark N. Costantini , Maeve Madigan , Luca Mantani , James M. Moore

Linear regression with normally distributed errors - including particular cases such as ANOVA, Student's t-test or location-scale inference - is a widely used statistical procedure. In this case the ordinary least squares estimator…

Methodology · Statistics 2019-09-18 Alain Desgagné

Resampling methods such as the bootstrap have proven invaluable in the field of machine learning. However, the applicability of traditional bootstrap methods is limited when dealing with large streams of dependent data, such as time series…

Machine Learning · Statistics 2024-02-28 Nicolai Palm , Thomas Nagler

We use 1-dimensional numerical simulations to study spherical collapse in the f(R) gravity models. We include the nonlinear coupling of the gravitational potential to the scalar field in the theory and use a relaxation scheme to follow the…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-27 Alex Borisov , Bhuvnesh Jain , Pengjie Zhang

Experimental reproducibility and replicability are critical topics in machine learning. Authors have often raised concerns about their lack in scientific publications to improve the quality of the field. Recently, the graph representation…

Machine Learning · Computer Science 2022-02-21 Federico Errica , Marco Podda , Davide Bacciu , Alessio Micheli

News: - APS Prize on gravitation, by Cliff Will - TGG elections, by David Garfinkle - We hear that... by Jorge Pullin Research Briefs: - Experimental Unruh radiation?, by Matt Visser - Why is the universe accelerating?, by Beverly Berger -…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Jorge Pullin

Theory of general relativity (GR) has been scrutinized by experts for almost a century and describes accurately all gravitational phenomena ranging from the solar system to the universe. However, this success is achieved provided one admits…

General Physics · Physics 2013-07-02 Ram Gopal Vishwakarma

Bayesian inference with computationally expensive likelihood evaluations remains a significant challenge in many scientific domains. We propose normalizing flow regression (NFR), a novel offline inference method for approximating posterior…

Machine Learning · Statistics 2025-04-17 Chengkun Li , Bobby Huggins , Petrus Mikkola , Luigi Acerbi
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