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byAK and the research community

Oct 29

Pretrained Event Classification Model for High Energy Physics Analysis

We introduce a foundation model for event classification in high-energy physics, built on a Graph Neural Network architecture and trained on 120 million simulated proton-proton collision events spanning 12 distinct physics processes. The model is pretrained to learn a general and robust representation of collision data using challenging multiclass and multilabel classification tasks. Its performance is evaluated across seven event classification tasks, which include new physics processes not encountered during pretraining as well as ATLAS Open Data to demonstrate generalizability across different simulation frameworks, from Delphes fast simulation to full ATLAS detector simulation. Fine-tuning the pretrained model significantly improves classification performance, particularly in scenarios with limited training data, demonstrating gains in both accuracy and computational efficiency. To investigate the underlying mechanisms behind these performance improvements, we employ a representational similarity evaluation framework based on Centered Kernel Alignment. This analysis reveals that encoder-stage representations of the fine-tuned model remain similar to those of the baseline, while intermediate graph processing layers diverge substantially, indicating that fine-tuning preserves general-purpose encoders while developing fundamentally different message-passing pathways to arrive at superior task performance.

  • 4 authors
·
May 5

Chameleon Gravity with an Environmental Frequency Dependent on Density

Scalar field theories of modified gravity are strongly constrained by the absence of detectable long range fifth forces in laboratory and Solar System environments. The chameleon mechanism addresses this problem by making the equilibrium value and effective mass of the scalar field dependent on the ambient matter density. In this work, we investigate an effective phenomenological extension of the chameleon framework in which the scalar potential contains an additional quadratic environmental contribution characterized by a density dependent background frequency. This background frequency is distinct from the frequency of scalar perturbations and parametrizes unresolved environmental effects beyond the conventional matter coupling. For an inverse power law scalar potential, we derive the modified equilibrium configuration and identify a frequency dominated regime in which the environmental contribution controls the density dependence of the field. Linear perturbations about the environmental minimum obey a Klein Gordon dispersion relation with a density-dependent effective mass, and the absence of tachyonic instability requires a positive environmental coupling. We further derive analytical consistency conditions associated with frequency dominance, thin shell screening, fifth-force suppression, and the weak field approximation. Numerical illustrations for representative parameter choices demonstrate how the modified density scaling can enhance fifth-force suppression relative to the conventional chameleon case.

  • 2 authors
·
Oct 7

Objects in Generated Videos Are Slower Than They Appear: Models Suffer Sub-Earth Gravity and Don't Know Galileo's Principle...for now

Video generators are increasingly evaluated as potential world models, which requires them to encode and understand physical laws. We investigate their representation of a fundamental law: gravity. Out-of-the-box video generators consistently generate objects falling at an effectively slower acceleration. However, these physical tests are often confounded by ambiguous metric scale. We first investigate if observed physical errors are artifacts of these ambiguities (e.g., incorrect frame rate assumptions). We find that even temporal rescaling cannot correct the high-variance gravity artifacts. To rigorously isolate the underlying physical representation from these confounds, we introduce a unit-free, two-object protocol that tests the timing ratio t_1^2/t_2^2 = h_1/h_2, a relationship independent of g, focal length, and scale. This relative test reveals violations of Galileo's equivalence principle. We then demonstrate that this physical gap can be partially mitigated with targeted specialization. A lightweight low-rank adaptor fine-tuned on only 100 single-ball clips raises g_{eff} from 1.81,m/s^2 to 6.43,m/s^2 (reaching 65% of terrestrial gravity). This specialist adaptor also generalizes zero-shot to two-ball drops and inclined planes, offering initial evidence that specific physical laws can be corrected with minimal data.

  • 4 authors
·
Dec 1, 2025