Cover Image

Symbolic Regression for Beyond the Standard Model Physics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	AbdusSalam, Shehu, Abel, Steve, Romao, Miguel Crispim
Format:	Preprint
Published:	2024
Subjects:	High Energy Physics - Phenomenology Artificial Intelligence Machine Learning High Energy Physics - Theory Computational Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Symbolic Regression and Differentiable Fits in Beyond the Standard Model Physics
by: AbdusSalam, Shehu, et al.
Published: (2025)

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits
by: AbdusSalam, Shehu
Published: (2026)

Coexisting Flux String Vacua from Numerical Kähler Moduli Stabilisation
by: AbdusSalam, Shehu, et al.
Published: (2025)

Systematic exploration of the non-geometric flux landscape
by: AbdusSalam, Shehu, et al.
Published: (2024)

Inferring Interpretable Models of Fragmentation Functions using Symbolic Regression
by: Makke, Nour, et al.
Published: (2025)

Experimental measurements outlasting MSSM-30 spectra
by: AbdusSalam, S., et al.
Published: (2024)

Modular Family Symmetry in Fluxed GUTs
by: Basiouris, Vasileios, et al.
Published: (2024)

Combining Evolutionary Strategies and Novelty Detection to go Beyond the Alignment Limit of the $Z_3$ 3HDM
by: Romão, Jorge Crispim, et al.
Published: (2024)

Fine-Tuning Small Reasoning Models for Quantum Field Theory
by: Woodward, Nathaniel S., et al.
Published: (2026)

A Perspective on Symbolic Machine Learning in Physical Sciences
by: Makke, Nour, et al.
Published: (2025)

Interpretable Scientific Discovery with Symbolic Regression: A Review
by: Makke, Nour, et al.
Published: (2022)

Uncovering Singularities in Feynman Integrals via Machine Learning
by: Liu, Yuanche, et al.
Published: (2025)

Axions, Photons and Physics Beyond the Standard Model
by: Paixão, Jefferson Mendes Aguiar
Published: (2024)

Iterated Agent for Symbolic Regression
by: Song, Zhuo-Yang, et al.
Published: (2025)

Uncertainty Quantification From Scaling Laws in Deep Neural Networks
by: Elsharkawy, Ibrahim, et al.
Published: (2025)

Learning to Unscramble: Simplifying Symbolic Expressions via Self-Supervised Oracle Trajectories
by: Shih, David
Published: (2026)

Vacuum Stability in the Standard Model and Beyond
by: Hiller, Gudrun, et al.
Published: (2024)

Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics
by: Chung, Daniel J. H., et al.
Published: (2025)

SMEFT ATLAS: The Landscape Beyond the Standard Model
by: Aebischer, Jason, et al.
Published: (2025)

Grand-unification Theory Atlas: Standard Model and Beyond
by: Cacciapaglia, Giacomo, et al.
Published: (2025)

Test-time Scaling Techniques in Theoretical Physics -- A Comparison of Methods on the TPBench Dataset
by: Gao, Zhiqi, et al.
Published: (2025)

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction
by: Faroughy, Darius A., et al.
Published: (2026)

Towards Beyond Standard Model Model-Building with Reinforcement Learning on Graphs
by: Wojcik, George N., et al.
Published: (2024)

Parisi-Wu Quantization, CP violation and Beyond the Standard Model
by: Kapoor, A. K.
Published: (2024)

TASI Lectures on Physics for Machine Learning
by: Halverson, Jim
Published: (2024)

Physics-informed neural networks viewpoint for solving the Dyson-Schwinger equations of quantum electrodynamics
by: Terin, Rodrigo Carmo
Published: (2024)

Spontaneous Symmetry Breaking: From the Effective Action to Cosmological Phase Transitions in the Standard Model and Beyond
by: Giovanakis, Apostolos
Published: (2024)

Learning Pole Structures of Hadronic States using Predictive Uncertainty Estimation
by: Frohnert, Felix, et al.
Published: (2025)

Improving Neutrino Oscillation Measurements through Event Classification
by: Ellis, Sebastian A. R., et al.
Published: (2025)

High-dimensional and Permutation Invariant Anomaly Detection
by: Mikuni, Vinicius, et al.
Published: (2023)

Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion
by: Shmakov, Alexander, et al.
Published: (2024)

When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning
by: Niarchos, Vasilis, et al.
Published: (2026)

Unearthing large pseudoscalar Yukawa couplings with Machine Learning
by: de Souza, Fernando Abreu, et al.
Published: (2025)

Flavour Physics Beyond the Standard Model
by: Altmannshofer, Wolfgang, et al.
Published: (2025)

Black String in the Standard Model
by: Hamada, Yu, et al.
Published: (2025)

Cambridge Lectures on The Standard Model
by: Quevedo, Fernando, et al.
Published: (2024)

Monopoles and Fermions in the Standard Model
by: Khoze, Valentin V.
Published: (2024)

Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation
by: Hashemi, Baran
Published: (2024)

Another Fit Bites the Dust: Conformal Prediction as a Calibration Standard for Machine Learning in High-Energy Physics
by: Araz, Jack Y., et al.
Published: (2025)

Weak scale supersymmetry emergent from the string landscape
by: Baer, Howard, et al.
Published: (2024)