arXiv subjects

Antonin Vacheret

Publications and source records attributed to Antonin Vacheret.

3 recordsLinked to original sources

arXiv2026

JetParticle-JEPA: An Efficient Self-Supervised Representation Learning method for Jet Tagging in High-Energy Physics

Jet tagging at the Large Hadron Collider increasingly relies on deep learning models trained on massive simulated datasets, leading to high computational costs and limited robustness to detector mismodeling. We introduce JetParticle-JEPA (JP-JEPA), a self-supervised Joint-Embedding Predictive Architecture that learns physically meaningful jet representations directly from continuous particle clouds without tokenization or reconstruction of raw inputs. Built on a Particle Transformer backbone, JP-JEPA predicts latent representations of masked particles while preserving fine-grained kinematic correlations. On the JetClass benchmark, JP-JEPA achieves performance comparable to fully supervised state-of-the-art methods on the full dataset, surpasses supervised baselines in low-label regimes, and significantly outperforms existing SSL approaches. On Top Quark and Quark-Gluon Tagging benchmarks, it remains on par with supervised methods. The learned representations also exhibit strong robustness to missing detector information and improved uncertainty behavior, highlighting JP-JEPA as a promising foundation-model framework for robust and data-efficient jet physics at the LHC.

hep-ph↗

arXiv2026

Neutrino Oscillation Parameter Estimation Using Structured Hierarchical Transformers

Neutrino oscillations encode fundamental information about neutrino masses and mixing parameters, offering a unique window into physics beyond the Standard Model. Estimating these parameters from oscillation probability maps is, however, computationally challenging due to the maps' high dimensionality and nonlinear dependence on the underlying physics. Traditional inference methods, such as likelihood-based or Monte Carlo sampling approaches, require extensive simulations to explore the parameter space, creating major bottlenecks for large-scale analyses. In this work, we introduce a data-driven framework that reformulates atmospheric neutrino oscillation parameter inference as a supervised regression task over structured oscillation maps. We propose a hierarchical transformer architecture that explicitly models the two-dimensional structure of these maps, capturing angular dependencies at fixed energies and global correlations across the energy spectrum. To improve physical consistency, the model is trained using a surrogate simulation constraint that enforces agreement between the predicted parameters and the reconstructed oscillation patterns. Furthermore, we introduce a neural network-based uncertainty quantification mechanism that produces distribution-free prediction intervals with formal coverage guarantees. Experiments on simulated oscillation maps under Earth-matter conditions demonstrate that the proposed method is comparable to a Markov Chain Monte Carlo baseline in estimation accuracy, with substantial improvements in computational cost (around 240$\times$ fewer FLOPs and 33$\times$ faster in average processing time). Moreover, the conformally calibrated prediction intervals remain narrow while achieving the target nominal coverage of 90%, confirming both the reliability and efficiency of our approach.

hep-ph↗

arXiv2019

Neutrino-based tools for nuclear verification and diplomacy in North Korea

We present neutrino-based options for verifying that the nuclear reactors at North Korea's Yongbyon Nuclear Research Center are no longer operating or that they are operating in an agreed manner, precluding weapons production. Neutrino detectors may be a mutually agreeable complement to traditional verification protocols because they do not require access inside reactor buildings, could be installed collaboratively, and provide persistent and specific observations. At Yongbyon, neutrino detectors could passively verify reactor shutdowns or monitor power levels and plutonium contents, all from outside the reactor buildings. The monitoring options presented here build on recent successes in basic particle physics. Following a dedicated design study, these tools could be deployed in as little as one year at a reasonable cost. In North Korea, cooperative deployment of neutrino detectors could help redirect a limited number of scientists and engineers from military applications to peaceful technical work in an international community. Opportunities for scientific collaboration with South Korea are especially strong. We encourage policymakers to consider collaborative neutrino projects within a broader program of action toward stability and security on the Korean Peninsula.

physics.soc-ph↗