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Charged particle reconstruction or track reconstruction is one of the most crucial components of pattern recognition in high-energy collider physics. It is known to entail enormous consumption of computing resources, especially when the…

Quantum Physics · Physics 2024-09-02 Hideki Okawa , Qing-Guo Zeng , Xian-Zhe Tao , Man-Hong Yung

Accurate determination of particle track reconstruction parameters will be a major challenge for the High Luminosity Large Hadron Collider (HL-LHC) experiments. The expected increase in the number of simultaneous collisions at the HL-LHC…

One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction. Its main part is the track reconstruction procedure which consists in looking for all tracks that elementary particles…

Machine Learning · Computer Science 2019-10-02 Dmitriy Baranov , Sergey Mitsyn , Pavel Goncharov , Gennady Ososkov

Quantum Computing is a rapidly developing field with the potential to tackle the increasing computational challenges faced in high-energy physics. In this work, we explore the potential and limitations of variational quantum algorithms in…

At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for analysis are expected to face challenges due to scaling with track density. Quantum annealing has shown promise in its…

In high-energy particle collisions, charged track finding is a complex yet crucial endeavour. We propose a quantum algorithm, specifically quantum template matching, to enhance the accuracy and efficiency of track finding. Abstracting the…

High Energy Physics - Phenomenology · Physics 2025-09-03 Christopher Brown , Michael Spannowsky , Alexander Tapper , Simon Williams , Ioannis Xiotidis

In high energy physics (HEP) experiments, the reconstruction of charged particle trajectories is one of the most fundamental yet computationally expensive parts of event processing. At future hadron colliders such as the High-Luminosity…

Instrumentation and Detectors · Physics 2020-07-03 Xiaocong Ai

Collider experiments are equipped with trigger systems that rapidly inspect the physics content emerging from collisions to decide whether the resulting products are worth saving for later analysis. One crucial aspect for analyzing the…

High Energy Physics - Experiment · Physics 2026-04-14 Andrea Coccaro , Carlo Schiavi , Alessandro Zaio

The reconstruction of charged particle trajectories is a crucial challenge of particle physics experiments as it directly impacts particle reconstruction and physics performances. To reconstruct these trajectories, different reconstruction…

Reconstructing charged particle tracks is a fundamental task in modern collider experiments. The unprecedented particle multiplicities expected at the High-Luminosity Large Hadron Collider (HL-LHC) pose significant challenges for track…

High Energy Physics - Experiment · Physics 2025-12-16 Samuel Van Stroud , Philippa Duckett , Max Hart , Nikita Pond , Sébastien Rettie , Gabriel Facini , Tim Scanlon

Reconstructing the trajectories of charged particles from the collection of hits they leave in the detectors of collider experiments like those at the Large Hadron Collider (LHC) is a challenging combinatorics problem and computationally…

High Energy Physics - Experiment · Physics 2024-03-15 Philippa Duckett , Gabriel Facini , Marcin Jastrzebski , Sarah Malik , Sebastien Rettie , Tim Scanlon

Particle tracking in biological imaging is concerned with reconstructing the trajectories, locations, or velocities of the targeting particles. The standard approach of particle tracking consists of two steps: first reconstructing…

Signal Processing · Electrical Eng. & Systems 2022-04-11 Ping Liu , Habib Ammari

Quantum algorithms can potentially solve a handful of problems more efficiently than their classical counterparts. In that context, it has been discussed that Markov chains problems could be solved significantly faster using quantum…

Quantum Physics · Physics 2025-12-01 Baptiste Claudon , Jean-Philip Piquemal , Pierre Monmarché

Pattern recognition algorithms are commonly employed to simplify the challenging and necessary step of track reconstruction in sub-atomic physics experiments. Aiding in the discrimination of relevant interactions, pattern recognition seeks…

Quantum Physics · Physics 2021-07-14 Gregory Quiroz , Lauren Ice , Andrea Delgado , Travis S. Humble

Usage of cutting-edge artificial intelligence will be the baseline at future high energy colliders such as the High Luminosity Large Hadron Collider, to cope with the enormously increasing demand of the computing resources. The rapid…

Quantum Physics · Physics 2024-03-01 Hideki Okawa

Involving only the measurements of commuting observables - the problem-setting and the corresponding solution - quantum algorithms should be subject to classical logic. This would allow flanking their customary quantum description with a…

Quantum Physics · Physics 2025-07-08 Giuseppe Castagnoli

Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms…

Fast 4$\pi$ solid angle particle track recognition has been a challenge in particle physics for a long time, especially in using nuclear emulsion detectors. The recent advances in computing technology opened the way for its realization. A…

Instrumentation and Detectors · Physics 2015-06-18 A. Ariga , T. Ariga

Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup expected from the High-Luminosity LHC, the computational…

One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction. Its main part is the track reconstruction procedure which consists in looking for all tracks that elementary particles…

Machine Learning · Computer Science 2019-02-20 Dmitriy Baranov , Gennady Ososkov , Pavel Goncharov , Andrei Tsytrinov
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