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Related papers: Finetuned Cancellations and Improbable Theories

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Counterfactual reasoning -- envisioning hypothetical scenarios, or possible worlds, where some circumstances are different from what (f)actually occurred (counter-to-fact) -- is ubiquitous in human cognition. Conventionally,…

Artificial Intelligence · Computer Science 2023-05-31 Julius von Kügelgen , Abdirisak Mohamed , Sander Beckers

No physical measurement can be performed with infinite precision. This leaves a loophole in the standard no-go arguments against non-contextual hidden variables. All such arguments rely on choosing special sets of quantum-mechanical…

Quantum Physics · Physics 2009-10-31 Rob Clifton , Adrian Kent

A systematic program is developed for analyzing and cancelling local anomalies on networks of intersecting orbifold planes in the context of M-theory. Through a delicate balance of factors, it is discovered that local anomaly matching on…

High Energy Physics - Theory · Physics 2009-10-07 Michael Faux , Dieter Luest , Burt A. Ovrut

Superdeterminism - where the Measurement Independence assumption in Bell's Theorem is violated - is frequently assumed to imply implausibly conspiratorial correlations between properties $\lambda$ of particles being measured and measurement…

Quantum Physics · Physics 2024-01-09 Tim Palmer

In statistical inference, uncertainty is unknown and all models are wrong. That is to say, a person who makes a statistical model and a prior distribution is simultaneously aware that both are fictional candidates. To study such cases,…

Machine Learning · Computer Science 2023-02-13 Sumio Watanabe

The argument from naturalness is widely employed in contemporary quantum field theory. Essentially a formalized aesthetic criterion, it received a meaning in the debate on the Higgs mechanism, which goes beyond aesthetics. We follow the…

History and Philosophy of Physics · Physics 2017-01-23 Alexei Grinbaum

We derive a new lower bound on the success probability of the Pretty Good Measurement (PGM) for worst-case quantum state discrimination among $m$ pure states. Our bound is strictly tighter than the previously known Gram-matrix-based bound…

Quantum Physics · Physics 2026-02-27 Sergio Escobar , Austin Pechan

Constants of Nature that have nongeneric values pose a riddle often referred to as the finetuning problem. The conspicuous values assumed by many physical constants (e.g., the vanishing effective cosmological constant, the smallness of the…

High Energy Physics - Phenomenology · Physics 2008-02-03 D. L. Bennett , C. D. Froggatt , H. B. Nielsen

Time-symmetric cosmological theories, in which the initial and final states are arranged to have similar features or are independently fixed, have been quite extensively discussed in the literature. However, a more general and perhaps more…

General Relativity and Quantum Cosmology · Physics 2012-04-20 Adrian Kent

In order to find a physical axiomatization of quantum theory, physical theories are often considered as a special case of a much more general framework of generalized probabilistic theories. We first present a detailed introduction to…

Quantum Physics · Physics 2012-03-27 Corsin Pfister

We discuss conditionalisation for Accept-Desirability models in an abstract decision-making framework, where uncertain rewards live in a general linear space, and events are special projection operators on that linear space. This abstract…

Artificial Intelligence · Computer Science 2025-12-23 Kathelijne Coussement , Gert de Cooman , Keano De Vos

Melvin models with irrational twist parameter provide an interesting example of conformal field theories with non-compact target space, and localized states which are arbitrarily close to being delocalized. We study the torus partition sum…

High Energy Physics - Theory · Physics 2009-11-10 David Kutasov , Jens Marklof , Gregory W. Moore

The minimax risk is often considered as a gold standard against which we can compare specific statistical procedures. Nevertheless, as has been observed recently in robust and heavy-tailed estimation problems, the inherent reduction of the…

Statistics Theory · Mathematics 2024-07-08 Tianyi Ma , Kabir A. Verchand , Richard J. Samworth

The Higgs boson discovery stirred interest in next-to-minimal supersymmetric models, due to the apparent fine-tuning required to accommodate it in minimal theories. To assess their naturalness, we compare fine-tuning in a $\mathbb{Z}_3$…

High Energy Physics - Phenomenology · Physics 2017-11-10 Peter Athron , Csaba Balazs , Benjamin Farmer , Andrew Fowlie , Dylan Harries , Doyoun Kim

Evidence for fine-tuning of physical parameters suitable for life can perhaps be explained by almost any combination of providence, coincidence or multiverse. A multiverse usually includes parts unobservable to us, but if the theory for it…

High Energy Physics - Theory · Physics 2007-05-23 Don N. Page

With the increasing impact of algorithmic decision-making on human lives, the interpretability of models has become a critical issue in machine learning. Counterfactual explanation is an important method in the field of interpretable…

Machine Learning · Computer Science 2024-07-17 Ao Xu , Tieru Wu

The solution to fine tuning is one of the principal motivations for supersymmetry. However constraints on the parameter space of the Minimal Supersymmetric Standard Model (MSSM) suggest it may also require fine tuning (although to a much…

High Energy Physics - Phenomenology · Physics 2007-10-15 Peter Athron , D. J. Miller

We propose confidence regions for the parameters of incomplete models with exact coverage of the true parameter in finite samples. Our confidence region inverts a test, which generalizes Monte Carlo tests to incomplete models. The test…

Econometrics · Economics 2025-10-07 Lixiong Li , Marc Henry

The Cancellation Problem for Affine Spaces is settled affirmatively, that is, it is proved that : Let $ k $ be an algebraically closed field of characteristic zero and let $n, m \in \mathbb{N}$. If $R[Y_1,..., Y_m] \cong_k k[X_1,...,…

Commutative Algebra · Mathematics 2020-05-12 Susumu Oda

This paper presents a theoretical overview of a Neural Contraction Metric (NCM): a neural network model of an optimal contraction metric and corresponding differential Lyapunov function, the existence of which is a necessary and sufficient…

Machine Learning · Computer Science 2021-10-05 Hiroyasu Tsukamoto , Soon-Jo Chung , Jean-Jacques Slotine , Chuchu Fan