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Standard cosmological data analyses typically constrain simple phenomenological dark-energy parameters, for example the present-day value of the equation of state parameter, $w_0$, and its variation with scale factor, $w_a$. However,…

Cosmology and Nongalactic Astrophysics · Physics 2022-03-30 Yuewei Wen , Eva Nesbit , Dragan Huterer , Scott Watson

The Standard Model of electroweak interactions has had great success in describing the observed data over the last three decades. The precision of experimental measurements affords tests of the Standard Model at the quantum loop level…

High Energy Physics - Experiment · Physics 2011-03-23 Douglas A. Glenzinski , Ulrich Heintz

At Run II of the Tevatron it will be possible to measure the W boson mass with a relative precision of about 2 times 10^-4, which will eventually represent the best measured observable beyond the input parameters of the SM. Proper…

High Energy Physics - Phenomenology · Physics 2007-05-23 Jens Erler

Measurements of the $W^\pm$ mass ($m_W$) provide an important consistency check of the Standard Model (SM) and constrain the possibility of physics beyond the SM. Precision measurements of $m_W$ at hadron colliders are inferred from…

High Energy Physics - Phenomenology · Physics 2016-10-07 Mikkel Bjørn , Michael Trott

In this letter, we test clipping effective field theory (EFT) simulations as a method of ensuring EFT validity. The procedure imposes that, at the level of the simulation, the invariant mass of a $W^+W^-$ pair $M_{WW}$ is less than the new…

High Energy Physics - Phenomenology · Physics 2026-01-28 Daniel Gillies , Andrea Banfi , Adam Martin

We present an update of the global fit of the Standard Model electroweak sector to latest experimental results. We include new kinematic top quark and $W$ boson mass measurements from the LHC, a $\sin^2\theta^{\ell}_{\mathrm{eff}}$ result…

High Energy Physics - Phenomenology · Physics 2019-12-16 Johannes Haller , Andreas Hoecker , Roman Kogler , Klaus Mönig , Thomas Peiffer , Jörg Stelzer

General formulas as well as leading asymptotics for corrections to Z- and W-boson parameters are derived. Experimental data fits in Standard Model and its extensions are discussed and results are presented.

High Energy Physics - Phenomenology · Physics 2008-12-16 M. I. Vysotsky

We present a comprehensive re-evaluation of the $ft$ values in superallowed nuclear $\beta$ decays crucial for the precise determination of $V_{ud}$ and low-energy tests of the electroweak Standard Model. It consists of the first, fully…

Nuclear Theory · Physics 2024-04-11 Chien-Yeah Seng , Mikhail Gorchtein

Semiconductor device models are essential to understand the charge transport in thin film transistors (TFTs). Using these TFT models to draw inference involves estimating parameters used to fit to the experimental data. These experimental…

Machine Learning · Computer Science 2021-11-29 Neel Chatterjee , Somya Sharma , Sarah Swisher , Snigdhansu Chatterjee

A recent EFT result from CMS is presented, combining differential cross section and direct EFT measurements performed by the CMS Collaboration across four branches of the Standard Model: top, Higgs, electroweak and QCD physics. To maximize…

High Energy Physics - Experiment · Physics 2026-02-04 Niels Van den Bossche

Earth observation (EO) is crucial for monitoring environmental changes, responding to disasters, and managing natural resources. In this context, foundation models facilitate remote sensing image analysis to retrieve relevant geoinformation…

Computer Vision and Pattern Recognition · Computer Science 2025-06-16 Francesc Marti-Escofet , Benedikt Blumenstiel , Linus Scheibenreif , Paolo Fraccaro , Konrad Schindler

Parameter-Efficient Fine-Tuning (PEFT) is a popular class of techniques that strive to adapt large models in a scalable and resource-efficient manner. Yet, the mechanisms underlying their training performance and generalization remain…

Machine Learning · Computer Science 2026-02-10 Zahra Rahimi Afzal , Tara Esmaeilbeig , Mojtaba Soltanalian , Mesrob I. Ohannessian

We investigate a failure mode that arises during the training of reasoning models, where the diversity of generations begins to collapse, leading to suboptimal test-time scaling. Notably, the Pass@1 rate reliably improves during supervised…

Machine Learning · Computer Science 2025-10-09 Xingyu Dang , Christina Baek , Kaiyue Wen , Zico Kolter , Aditi Raghunathan

We discuss the development of the theory of electroweak radiative corrections and its role in testing the Standard Model, predicting the top quark mass, constraining the Higgs boson mass, and searching for deviations that may signal the…

High Energy Physics - Phenomenology · Physics 2008-11-26 Alberto Sirlin

The Standard Model Effective Field Theory (SMEFT) offers a systematic approach to study potential deviations from the Standard Model (SM) through higher-dimensional operators that encapsulate new physics effects. In this work, we analyze…

High Energy Physics - Phenomenology · Physics 2025-03-06 Luca Mantani , Veronica Sanz

Mechanistic interpretability aims to break models into meaningful parts; verifying that two such parts implement the same computation is a prerequisite. Existing similarity measures evaluate either empirical behaviour, leaving them blind to…

Machine Learning · Computer Science 2026-05-15 ML Nissen Gonzalez , Melwina Albuquerque , Laurence Wroe , Jacob Meyer Cohen , Logan Riggs Smith , Thomas Dooms

The low-energy effective field theory is constructed by integrating out Standard Model states with masses proximate to the electroweak scale. We report the equations of motion for this theory, including corrections due to higher dimensional…

High Energy Physics - Phenomenology · Physics 2019-07-10 Andreas Helset , Michael Trott

We give a complete analysis of indirect determinations of the top quark mass in the Standard Model by introducing a systematic procedure to identify observables that receive quantum corrections enhanced by powers of $M_t$. We propose to use…

High Energy Physics - Phenomenology · Physics 2016-01-27 Gian F. Giudice , Paride Paradisi , Alessandro Strumia

The F-measure, also known as the F1-score, is widely used to assess the performance of classification algorithms. However, some researchers find it lacking in intuitive interpretation, questioning the appropriateness of combining two…

Machine Learning · Computer Science 2021-03-19 David J. Hand , Peter Christen , Nishadi Kirielle

How do we transfer the relevant knowledge from ever larger foundation models into small, task-specific downstream models that can run at much lower costs? Standard transfer learning using pre-trained weights as the initialization transfers…

Machine Learning · Computer Science 2024-06-12 Shikai Qiu , Boran Han , Danielle C. Maddix , Shuai Zhang , Yuyang Wang , Andrew Gordon Wilson