307 citations · 2.2k across the 35 of their papers we have counts for
35 papers
My Chemical Harness: Evolutionary Molecular Design over Synthetic Pathways with Large Language Model Agents
César Ojeda, Darius A. Faroughy, Maryam Karimi +3
Designing molecules with target properties is most useful when candidate structures are accompanied by feasible synthetic routes. We introduce My Chemical Harness, a route-native e…
Neural Scaling Laws for Jet Generation
Oz Amram, Darius A. Faroughy, Tjarko Gerdes +5
Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compute, and model parameters -- ar…
Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction
Darius A. Faroughy, Sofia Palacios Schweitzer, Ian Pang +2
Autonomous language-model agents are increasingly evaluated on long-horizon tool-use tasks, but existing benchmarks rarely capture the complexity and nuance of real scientific work…
Prior-Fitted Functional Flow: In-Context Generative Models for Pharmacokinetics
César Ojeda, Niklas Hartung, Wilhelm Huisinga +6
We introduce Prior-Fitted Functional Flows, a generative foundation model for pharmacokinetics that enables zero-shot population synthesis and individual forecasting without manual…
SURFing to the Fundamental Limit of Jet Tagging
Ian Pang, Darius A. Faroughy, David Shih +2
Beyond the practical goal of improving search and measurement sensitivity through better jet tagging algorithms, there is a deeper question: what are their upper performance limits…
Multimodal Generative Flows for LHC Jets
Darius A. Faroughy, Manfred Opper, Cesar Ojeda
Generative modeling of high-energy collisions at the Large Hadron Collider (LHC) offers a data-driven route to simulations, anomaly detection, among other applications. A central c…
On the EFT validity for Drell-Yan tails at the LHC
Lukas Allwicher, Darius A. Faroughy, Matheus Martines +2
In this article, we examine the validity range of the Effective Field Theory (EFT) description of high-energy Drell-Yan processes at the LHC. To this purpose, we consider explicit…
Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics
Oz Amram, Luca Anzalone, Joschka Birk +7
Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrat…
Accessing CKM suppressed top decays at the LHC
Manuel Szewc
We present an strategy for measuring the off-diagonal elements of the third row of CKM matrix through the branching fractions of top quark decays , where i…
EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion
Erik Buhmann, Cedric Ewen, Darius A. Faroughy +7
Jets at the LHC, typically consisting of a large number of highly correlated particles, are a fascinating laboratory for deep generative modeling. In this paper, we present two nov…
Probing Lepton Flavor Violation in Meson Decays with LHC Data
Sébastien Descotes-Genon, Darius A. Faroughy, Ioannis Plakias +1
In this letter, we use LHC data from the Drell-Yan processes (with ) to derive model-independent upper limits on lepton-flavor-violating meson decays.…
Accessing CKM suppressed top decays at the LHC
Darius A. Faroughy, Jernej F. Kamenik, Manuel Szewc +1
We propose an extension of the existing experimental strategy for measuring branching fractions of top quark decays, targeting specifically , where is a light qua…
Semileptonics at High-
Darius A. Faroughy
We consider the Drell-Yan processes and at high- as probes of New Physics effects in semileptonic transitions. For this purpos…
HighPT: A Tool for high- Drell-Yan Tails Beyond the Standard Model
Lukas Allwicher, Darius. A. Faroughy, Florentin Jaffredo +2
HighPT is a Mathematica package for the analysis of high-energy data of semileptonic transitions at hadron colliders. It allows to compute high- tail observables for semilepto…
Drell-Yan Tails Beyond the Standard Model
Lukas Allwicher, Darius A. Faroughy, Florentin Jaffredo +2
We investigate the high- tails of the and Drell-Yan processes as probes of New Physics in semileptonic interactions with an arbitrary flavor…
On a model with two scalar leptoquarks -- and
Damir Bečirević, Ilja Doršner, Svjetlana Fajfer +4
We discuss a model that can accommodate the -physics anomalies, based on combining two scalar leptoquarks, and , of mass , and that we p…
Collider Signatures of Coannihilating Dark Matter in Light of the B-Physics Anomalies
Michael J. Baker, Darius A. Faroughy, Sokratis Trifinopoulos
Motivated by UV explanations of the -physics anomalies, we study a dark sector containing a Majorana dark matter candidate and a coloured coannihilation partner, connected to th…
Bayesian Probabilistic Modelling for Four-Tops at the LHC
Ezequiel Alvarez, Barry M. Dillon, Darius A. Faroughy +3
Monte Carlo (MC) generators are crucial for analyzing data in particle collider experiments. However, often even a small mismatch between the MC simulations and the measurements ca…
On the single leptoquark solutions to the -physics anomalies
Andrei Angelescu, Damir Bečirević, Darius A. Faroughy +2
We revisit the possibilities of accommodating the experimental indications of the lepton flavor universality violation in -hadron decays in the minimal scenarios in which the St…
Reading the footprints of the B-meson flavor anomalies
Claudia Cornella, Darius A. Faroughy, Javier Fuentes-Martin +2
Motivated by the recent LHCb announcement of a violation of lepton-flavor universality in the ratio , we present an updated, comprehen…
The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics
Gregor Kasieczka, Benjamin Nachman, David Shih +44
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. I…
Uncovering hidden patterns in collider events with Bayesian probabilistic models
Darius A. Faroughy
Individual events at high-energy colliders like the LHC can be represented by a sequence of measurements, or 'point patterns' in an observable space. Starting from this data repres…
Learning the latent structure of collider events
Barry M. Dillon, Darius A. Faroughy, Jernej F. Kamenik +1
We describe a technique to learn the underlying structure of collider events directly from the data, without having a particular theoretical model in mind. It allows to infer aspec…
Flavour symmetries in the SMEFT
Darius A. Faroughy, Gino Isidori, Felix Wilsch +1
We analyse how and flavour symmetries act on the Standard Model Effective Field Theory, providing an organising principle to classify the large number of dimensio…