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Aerial transportation robots using suspended cables have emerged as versatile platforms for disaster response and rescue operations. To maximize the capabilities of these systems, robots need to aggressively fly through tightly constrained…

Robotics · Computer Science 2026-01-21 Mrunal Sarvaiya , Guanrui Li , Giuseppe Loianno

We introduce jet topics: a framework to identify underlying classes of jets from collider data. Because of a close mathematical relationship between distributions of observables in jets and emergent themes in sets of documents, we can apply…

High Energy Physics - Phenomenology · Physics 2018-06-20 Eric M. Metodiev , Jesse Thaler

In a recent paper we have shown how to optimally compute the differential and cumulative cross sections for massive event-shapes at $\mathcal{O}(\alpha_s)$ in full QCD. In the present article we complete our study by obtaining resummed…

High Energy Physics - Phenomenology · Physics 2020-10-28 Alejandro Bris , Vicent Mateu , Moritz Preisser

Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of…

High Energy Physics - Phenomenology · Physics 2026-03-27 Vinicius Mikuni , Benjamin Nachman

We introduce a novel end-to-end framework for jet reconstruction in high-energy collider events, leveraging the efficiency and long-range modeling capabilities of the Mamba architecture. Our model unifies instance segmentation,…

High Energy Physics - Phenomenology · Physics 2025-09-26 Jinmian Li , Peng Li , Bingwei Long , Rao Zhang

We introduce a new class of event shapes to characterize the jet-like structure of an event. Like traditional event shapes, our observables are infrared/collinear safe and involve a sum over all hadrons in an event, but like a jet…

High Energy Physics - Phenomenology · Physics 2015-06-17 Daniele Bertolini , Tucker Chan , Jesse Thaler

Unfolding, for example of distortions imparted by detectors, provides suitable and publishable representations of LHC data. Many methods for unbinned and high-dimensional unfolding using machine learning have been proposed, but no…

High Energy Physics - Phenomenology · Physics 2025-11-10 Antoine Petitjean , Anja Butter , Kevin Greif , Sofia Palacios Schweitzer , Tilman Plehn , Jonas Spinner , Daniel Whiteson

When are two collider events similar? Despite the simplicity and generality of this question, there is no established notion of the distance between two events. To address this question, we develop a metric for the space of collider events…

High Energy Physics - Phenomenology · Physics 2019-07-31 Patrick T. Komiske , Eric M. Metodiev , Jesse Thaler

We provide a general method to effectively compute differential and cumulative event-shape distributions to $\mathcal{O}(\alpha_s)$ precision for massive quarks produced primarily at an $e^+e^-$ collider. In particular, we show that at this…

High Energy Physics - Phenomenology · Physics 2020-03-17 Christopher Lepenik , Vicent Mateu

A key question for machine learning approaches in particle physics is how to best represent and learn from collider events. As an event is intrinsically a variable-length unordered set of particles, we build upon recent machine learning…

High Energy Physics - Phenomenology · Physics 2020-04-17 Patrick T. Komiske , Eric M. Metodiev , Jesse Thaler

Jets at high energy colliders are complicated objects to identify. Even if jets are widely separated, there is no reason for jets to have the same size. A single reconstruction, or interpretation, of each event can only extract a limited…

High Energy Physics - Phenomenology · Physics 2014-09-17 Yang-Ting Chien

How can one fully harness the power of physics encoded in relativistic $N$-body phase space? Topologically, phase space is isomorphic to the product space of a simplex and a hypersphere and can be equipped with explicit coordinates and a…

High Energy Physics - Phenomenology · Physics 2024-08-26 Tianji Cai , Junyi Cheng , Nathaniel Craig , Giacomo Koszegi , Andrew J. Larkoski

We present a scalable technique for the simulation of collider events with multi-jet final states, based on an improved parton-level event file format. The method is implemented for both leading- and next-to-leading order QCD calculations.…

High Energy Physics - Phenomenology · Physics 2023-11-09 Enrico Bothmann , Taylor Childers , Christian Guetschow , Stefan Höche , Paul Hovland , Joshua Isaacson , Max Knobbe , Robert Latham

The classification of events involving jets as signal-like or background-like can depend strongly on the jet algorithm used and its parameters. This is partly due to the fact that standard jet algorithms yield a single partition of the…

High Energy Physics - Phenomenology · Physics 2015-06-15 Dilani Kahawala , David Krohn , Matthew D. Schwartz

Collision-tolerant trajectory planning is the consideration that collisions, if they are planned appropriately, enable more effective path planning for robots capable of handling them. A mixed integer programming (MIP) optimization…

Robotics · Computer Science 2016-11-24 Mark L. Mote , Juan-Pablo Afman , Eric Feron

We discuss a method to obtain the true event-by-event net-charge multiplicity distributions from a corresponding measured distribution which is subjected to detector effects such as finite particle counting efficiency. The approach is based…

Nuclear Experiment · Physics 2015-06-12 P. Garg , D. K. Mishra , P. K. Netrakanti , A. K. Mohanty , B. Mohanty

One of the challenges of collider physics is to unambiguously associate detector based objects with the corresponding elementary physics objects. A particular example is the association of calorimeter-based objects such as "jets",…

High Energy Physics - Phenomenology · Physics 2013-05-30 Stephen D. Ellis , Tuhin S. Roy , Jakub Scholtz

Optimal transport provides a powerful framework for comparing measures while respecting the geometry of their support, but comes with an expensive computational cost, hindering its potential application to real world use cases. On…

Machine Learning · Computer Science 2026-05-20 Pierre Houédry , Iskander Legheraba , Léo Buecher , Nicolas Courty

An unfolding method, based on Bayes theorem is presented to obtain true event-by-event net-charge multiplicity distribution from a corresponding measured distribution, which is subjected to detector artifacts. The unfolding is demonstrated…

High Energy Physics - Phenomenology · Physics 2013-09-18 P. Garg , D. K. Mishra , P. K. Netrakanti , A. K. Mohanty , B. Mohanty