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Related papers: Naturalness, Extra-Empirical Theory Assessments, a…

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Finetuning and Naturalness are extra-empirical theory assessments that reflect our expectation how scientific theories should provide an intuitive understanding about the foundations underlying the observed phenomena. Recently, the absence…

History and Philosophy of Physics · Physics 2019-05-16 Heinrich Päs

Fine-tuning criteria are frequently used to place upper limits on the masses of superpartners in supersymmetric extensions of the standard model. However, commonly used prescriptions for quantifying naturalness have some important…

High Energy Physics - Phenomenology · Physics 2009-09-25 Greg Anderson , Diego Castano

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

A well-known topic within the philosophy of physics is the problem of fine-tuning: the fact that the universal constants seem to take non-arbitrary values in order for live to thrive in our Universe. In this paper we will talk about this…

History and Philosophy of Physics · Physics 2024-09-06 Julian De Vuyst

The sensitivity criterion is widely used in measuring the level of fine-tuning, although many examples show it doesn't work under certain circumstances. We discuss the mathematics behind the fine-tuning problems, explain the mathematical…

High Energy Physics - Phenomenology · Physics 2007-05-23 Su Yan

Metaphysics is traditionally conceived as aiming at the truth -- indeed, the most fundamental truths about the most general features of reality. Philosophical naturalists, urging that philosophical claims be grounded on science, have often…

History and Philosophy of Physics · Physics 2024-10-28 Raoni Arroyo , Matteo Morganti

We review recent results that provide a new approach to the old problem of naturalness in supersymmetric models, without relying on subjective definitions for the fine-tuning associated with {\it fixing} the EW scale (to its measured value)…

High Energy Physics - Phenomenology · Physics 2013-08-12 D. M. Ghilencea

Background: Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health…

I assess various proposals for the source of the intuition that there is something problematic about contextuality, ultimately concluding that contextuality is best thought of in terms of fine-tuning. I then argue that as with other…

Quantum Physics · Physics 2021-11-24 Emily Adlam

Fine-tuning in physics and cosmology is often used as evidence that a theory is incomplete. For example, the parameters of the standard model of particle physics are "unnaturally" small (in various technical senses), which has driven much…

History and Philosophy of Physics · Physics 2017-07-14 Luke A. Barnes

We consider the bounds imposed by naturalness on the masses of superpartners for arbitrary points in nonminimal supersymmetric extensions of the standard model and for arbitrary messenger scales. This constitutes a significant…

High Energy Physics - Phenomenology · Physics 2007-05-23 David Wright

We critically analyze the rationale of arguments from finetuning and naturalness in particle physics and cosmology. Some other numerological coincidences are also discussed.

History and Philosophy of Physics · Physics 2019-12-02 S. Hossenfelder

When a physicist says that a theory is fine-tuned, they mean that it must make a suspiciously precise assumption in order to explain a certain observation. This is evidence that the theory is deficient or incomplete. One particular case of…

History and Philosophy of Physics · Physics 2021-10-18 Luke A. Barnes

Natural revision seems so natural: it changes beliefs as little as possible to incorporate new information. Yet, some counterexamples show it wrong. It is so conservative that it never fully believes. It only believes in the current…

Artificial Intelligence · Computer Science 2025-05-27 Paolo Liberatore

We report an inconsistency found in probability theory (also referred to as measure-theoretic probability). For probability measures induced by real-valued random variables, we deduce an "equality" such that one side of the "equality" is a…

General Mathematics · Mathematics 2017-03-01 Guang-Liang Li , Victor O. K. Li

In recent work, Nina Emery has defended the view that, in the context of naturalistic metaphysics, one should maintain the same epistemic attitude towards science and metaphysics. That is, naturalists who are scientific realists ought to be…

History and Philosophy of Physics · Physics 2025-05-13 Raoni Arroyo , Matteo Morganti

It is a well-known empirical phenomenon that natural axiomatic theories are pre-well-ordered by consistency strength. Without a precise mathematical definition of "natural," it is unclear how to study this phenomenon mathematically. We will…

Logic · Mathematics 2026-03-04 James Walsh

There have been numerous publications on the advantages and disadvantages of estimating natural (pure) effects compared to controlled effects. One of the main criticisms of natural effects is that it requires an additional assumption for…

Methodology · Statistics 2024-03-01 Ian Shrier

The ideas of aleatoric and epistemic uncertainty are widely used to reason about the probabilistic predictions of machine-learning models. We identify incoherence in existing discussions of these ideas and suggest this stems from the…

Machine Learning · Computer Science 2025-08-19 Freddie Bickford Smith , Jannik Kossen , Eleanor Trollope , Mark van der Wilk , Adam Foster , Tom Rainforth

The quantification of aleatoric and epistemic uncertainty in terms of conditional entropy and mutual information, respectively, has recently become quite common in machine learning. While the properties of these measures, which are rooted…

Machine Learning · Computer Science 2023-06-27 Lisa Wimmer , Yusuf Sale , Paul Hofman , Bern Bischl , Eyke Hüllermeier
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