79 citations · 514 across the 32 of their papers we have counts for
23 papers · 1 filter
Another Fit Bites the Dust: Conformal Prediction as a Calibration Standard for Machine Learning in High-Energy Physics
Jack Y. Araz, Michael Spannowsky
Machine-learning techniques are essential in modern collider research, yet their probabilistic outputs often lack calibrated uncertainty estimates and finite-sample guarantees, lim…
Deciphering compressed electroweakino excesses with MadAnalysis 5
Jack Y. Araz, Benjamin Fuks, Mark D. Goodsell +1
We present version 1.11 of MadAnalysis 5, which extends the software package in several major ways to improve the handling of efficiency tables, the computation of observables in d…
Graph theory inspired anomaly detection at the LHC
Jack Y. Araz, Dimitrios Athanasakos, Mateusz Ploskon +1
Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collide…
Point cloud-based diffusion models for the Electron-Ion Collider
Jack Y. Araz, Vinicius Mikuni, Felix Ringer +3
At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standar…
Les Houches guide to reusable ML models in LHC analyses
Jack Y. Araz, Andy Buckley, Gregor Kasieczka +10
With the increasing usage of machine-learning in high-energy physics analyses, the publication of the trained models in a reusable form has become a crucial question for analysis p…
Spey: smooth inference for reinterpretation studies
Jack Y. Araz
Statistical models serve as the cornerstone for hypothesis testing in empirical studies. This paper introduces a new cross-platform Python-based package designed to utilise differe…
Searches for new physics with boosted top quarks in the MadAnalysis 5 and Rivet frameworks
Jack Y. Araz, Andy Buckley, Benjamin Fuks
High-momentum top quarks are a natural physical system in collider experiments for testing models of new physics, and jet substructure methods are key both to exploiting their larg…
Strength in numbers: optimal and scalable combination of LHC new-physics searches
Jack Y. Araz, Andy Buckley, Benjamin Fuks +4
To gain a comprehensive view of what the LHC tells us about physics beyond the Standard Model (BSM), it is crucial that different BSM-sensitive analyses can be combined. But in gen…
Signal region combination with full and simplified likelihoods in MadAnalysis 5
Gaël Alguero, Jack Y. Araz, Benjamin Fuks +1
The statistical combination of disjoint signal regions in reinterpretation studies uses more of the data of an analysis and gives more robust results than the single signal region…
Recasting LHC searches for long-lived particles with MadAnalysis 5
Jack Y. Araz, Benjamin Fuks, Mark D. Goodsell +1
We present an extension of the simplified fast detector simulator of MadAnalysis 5 - the SFS framework - with methods making it suitable for the treatment of long-lived particles o…
Cross-fertilising extra gauge boson searches at the LHC
Jack Y. Araz, Mariana Frank, Benjamin Fuks +2
For the purpose of cross-fertilising currently separate experimental approaches, we connect results of LHC analyses attempting to access the properties of additional and…
Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States
Jack Y. Araz, Michael Spannowsky
Tensor Networks are non-trivial representations of high-dimensional tensors, originally designed to describe quantum many-body systems. We show that Tensor Networks are ideal vehic…
Combine and Conquer: Event Reconstruction with Bayesian Ensemble Neural Networks
Jack Y. Araz, Michael Spannowsky
Ensemble learning is a technique where multiple component learners are combined through a protocol. We propose an Ensemble Neural Network (ENN) that uses the combined latent-featur…
Proceedings of the second MadAnalysis 5 workshop on LHC recasting in Korea
Benjamin Fuks, Pyungwon Ko, Seung J. Lee +32
We document the activities performed during the second MadAnalysis 5 workshop on LHC recasting, that was organised in KIAS (Seoul, Korea) on February 12-20, 2020. We detail the imp…
Precision SMEFT bounds from the VBF Higgs at high transverse momentum
Jack Y. Araz, Shankha Banerjee, Rick S. Gupta +1
We study the production of Higgs bosons at high transverse momenta via vector-boson fusion (VBF) in the Standard Model Effective Field Theory (SMEFT). We find that contributions fr…
Simplified fast detector simulation in MadAnalysis 5
Jack Y. Araz, Benjamin Fuks, Georgios Polykratis
We introduce a new simplified fast detector simulator in the MadAnalysis 5 platform. The Python-like interpreter of the programme has been augmented by new commands allowing for a…
Leptophobic in supersymmetry and where to find them
Jack Y. Araz
This report presents possible loopholes in heavy searches which are concentrated around high mass resonances. We present a scenario where massive neutral vector boson $Z…
Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2
Waleed Abdallah, Shehu AbdusSalam, Azar Ahmadov +139
We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpret…
Les Houches 2019 Physics at TeV Colliders: New Physics Working Group Report
G. Brooijmans, A. Buckley, S. Caron +87
This report presents the activities of the `New Physics' working group for the `Physics at TeV Colliders' workshop (Les Houches, France, 10--28 June, 2019). These activities includ…
Reinterpreting the results of the LHC with MadAnalysis 5: uncertainties and higher-luminosity estimates
Jack Y. Araz, Mariana Frank, Benjamin Fuks
The MadAnalysis 5 framework can be used to assess the potential of various LHC analyses for unravelling any specific new physics signal. We present an extension of the LHC reinterp…
Exploring vector-like supersymmetric extensions of the Standard Model with dark matter and colliders
Jack Y. Araz, Shankha Banerjee, Mariana Frank +2
Motivated by grand unification considerations, we analyze a simple extension of the minimal supersymmetric standard model with additional pairs of vector-like chiral supermultiplet…
Loopholes in searches at the LHC: exploring supersymmetric and leptophobic scenarios
Jack Y. Araz, Gennaro Corcella, Mariana Frank +1
Searching for heavy vector bosons , predicted in models inspired by Grand Unification Theories, is among the challenging objectives of the LHC. The ATLAS and CMS collabor…
Differentiating supersymmetric models with right sneutrino and neutralino dark matter
Jack Y. Araz, Mariana Frank, Benjamin Fuks
We perform a detailed analysis of dark matter signals of supersymmetric models containing an extra gauge group. We investigate scenarios in which either the right sne…