240 citations · 538 across the 12 of their papers we have counts for
12 papers
The Quantum Trellis: A classical algorithm for sampling the parton shower with interference effects
Sebastian Macaluso, Kyle Cranmer
Simulations of high-energy particle collisions, such as those used at the Large Hadron Collider, are based on quantum field theory; however, many approximations are made in practic…
Reframing Jet Physics with New Computational Methods
Kyle Cranmer, Matthew Drnevich, Sebastian Macaluso +1
We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element - parton shower matching for large jet multiplicity,…
Exact and Approximate Hierarchical Clustering Using A*
Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath +6
Hierarchical clustering is a critical task in numerous domains. Many approaches are based on heuristics and the properties of the resulting clusterings are studied post hoc. Howeve…
Hierarchical clustering in particle physics through reinforcement learning
Johann Brehmer, Sebastian Macaluso, Duccio Pappadopulo +1
Particle physics experiments often require the reconstruction of decay patterns through a hierarchical clustering of the observed final-state particles. We show that this task can…
Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath +5
Hierarchical clustering is a fundamental task often used to discover meaningful structures in data, such as phylogenetic trees, taxonomies of concepts, subtypes of cancer, and casc…
The Machine Learning Landscape of Top Taggers
G. Kasieczka, T. Plehn, A. Butter +24
Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range of modern machine learning approaches. Unlike most established metho…
Pulling Out All the Tops with Computer Vision and Deep Learning
Sebastian Macaluso, David Shih
We apply computer vision with deep learning -- in the form of a convolutional neural network (CNN) -- to build a highly effective boosted top tagger. Previous work (the "DeepTop" t…
Cornering Natural SUSY at LHC Run II and Beyond
Matthew R. Buckley, David Feld, Sebastian Macaluso +2
We derive the latest constraints on various simplified models of natural SUSY with light higgsinos, stops and gluinos, using a detailed and comprehensive reinterpretation of the mo…
Dark Matter and the Higgs in Natural SUSY
Aria Basirnia, Sebastian Macaluso, David Shih
Null results from dark matter (DM) direct detection experiments and the 125 GeV Higgs both pose serious challenges to minimal supersymmetry. In this paper, we propose a simple exte…
Revealing Compressed Stops Using High-Momentum Recoils
Sebastian Macaluso, Michael Park, David Shih +1
Searches for supersymmetric top quarks at the LHC have been making great progress in pushing sensitivity out to higher mass, but are famously plagued by gaps in coverage around low…
Deep inelastic scattering structure functions of holographic spin-1 hadrons with
Ezequiel Koile, Sebastian Macaluso, Martin Schvellinger
Two-point current correlation functions of the large limit of supersymmetric and non-supersymmetric Yang-Mills theories at strong coupling are investigated in terms of their st…
Deep Inelastic Scattering from Holographic Spin-One Hadrons
Ezequiel Koile, Sebastian Macaluso, Martin Schvellinger
We study deep inelastic scattering structure functions from hadrons using different holographic dual models which describe the strongly coupled regime of gauge theories in the larg…