High Energy Particle Collisions Research Articles

Secondary vertex reconstruction with MaskFormers

In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by b- or c-quarks. Traditional methods, while effective, require extensive manual optimisation and struggle to perform consistently across wide regions of phase space. Meanwhile, recent advancements in machine learning have improved performance but are unable to fully reconstruct multiple vertices. In this work we propose a novel approach to secondary vertex reconstruction based on recent advancements in object detection and computer vision. Our method directly predicts the presence and properties of an arbitrary number of vertices in a single model. This approach overcomes the limitations of existing techniques. Applied to simulated proton-proton collision events, our approach demonstrates significant improvements in vertex finding efficiency, achieving a 10% improvement over an existing state-of-the-art method. Moreover, it enables vertex fitting, providing accurate estimates of key vertex properties such as transverse momentum, radial flight distance, and angular displacement from the jet axis. When integrated into a flavour tagging pipeline, our method yields a 50% improvement in light-jet rejection and a 15% improvement in c-jet rejection at a b-jet selection efficiency of 70%. These results demonstrate the potential of adapting advanced object detection techniques for particle physics, and pave the way for more powerful and flexible reconstruction tools in high-energy physics experiments.

Cosmic ray test of shashlik electromagnetic calorimeter modules for NICA-MPD

The electromagnetic calorimeter (ECal) plays a critical role in high-energy particle colliders, by measuring the energy of particles that interact primarily via the electromagnetic interaction such as electrons, positrons and photons. Fudan University has undertaken part of the mass production of ECal modules for the Multi-Purpose Detector (MPD) project of the Nuclotron-based Ion Collider fAcility (NICA). Preliminary tests on the ECal modules is an essential step in detector construction. This article introduces the cosmic ray testing of the ECal modules produced by Fudan University. We tested the cosmic ray under the conditions of horizontal and vertical placement of the module, calculated the average number of generated photons, and estimated the module’s energy resolution. Moreover we analyzed the time resolution performance of the device. The test results indicate that when cosmic rays vertically traverse the entire ECal, the number of photons produced can reach 834, with a potential energy resolution less than 5%/E. The time resolution is 189ps. Based on the comprehensive test results, the production of the ECal meets the design requirements.

Libepa — A C++/Python library for calculations of cross sections of ultraperipheral collisions

The library provides a set of C++/Python functions for computing cross sections of ultraperipheral collisions of high energy particles under the equivalent photons approximation. Cross sections are represented through multiple integrals over the phase space. The integrals are calculated through recurrent application of algorithms for one dimensional integration. The paper contains an introduction to the theory of ultraperipheral collisions, discusses the library approach and provides a few examples of calculations.

(Invited) There’s More to a Probabilistic Neuromorphic Computing System Than Noisy Devices

A range of computing problems require understanding uncertainty, such as climate modeling, or use statistics to model problems that are otherwise difficult to solve, such as high energy particle collisions. Currently, these computations are handled by hardware where significant energy is spent to suppress stochasticity in materials and devices, and then significant computational resources are expended to re-introduce stochasticisty in algorithms. Instead, we take inspiration from the brain, which features 1015 stochastic synapses. This talk focuses on understanding how to leverage fluctuations in devices to do efficient sampling, which is a fundamental operation in many statistical approaches to computation [1]. In the first part of this talk, we use bitstreams generated by magnetic tunnel junction and tunnel diode devices to generate samples from different distributions, an elementary operation in statistical approaches to modeling. We show how to use elementary operations on multiple bits to improve both the accuracy and complexity of sampling. While intuition motivates the asking which of the two devices is more efficient at generating a random bitstream, in the second part of this talk, we show that this consideration is a small contribution to the overall circuit required to do a complete calculation. To significantly accelerate applications requires devices that minimize the energy and area cost of the CMOS parts of the design, as the true challenge lies in holistic codesign [2].At the heart of statistical approaches to computation is sampling. Typically, a uniform random sample is generated using a pseudo-random number generator (PRNG), followed by a mathematical operation to sample an application-relevant distribution. This sample is then plugged into a sequence of deterministic calculations that comprise a model. We use magnetic tunnel junctions and tunnel diodes to generate a fair coinflip, having equal probability of each of two outscomes, from which we create a uniform random sample. We show how to relate the quality of the device bitstreams to the quality of random samples [3]. While these devices consume significantly less energy than the PRNG, the energy consumed by the PRNG is a fraction of the energy consumed by a complete calculation. We next focus on moving the entire process of sampling non-uniform distributions into hardware. We show that weighted coinflips can be used to sample any distribution with a well-defined probability distribution function using a tree. Simple logic operations can be used to combine many inaccurate fair physical coinflips to produce a single high-accuracy weighted logical coinflip, and high quality samples from non-uniform distributions. Overall, a simple implementation uses a few hundred physical coinflips, some simple logic operations (shift register, comparison, XOR extractor), and memory access to produce a sample. This success points to the potential for moving more of the model into increasingly sophisticated sampling schemes.Having established how the basic element of the computation are connected, we are now ready to examine its efficiency compared to a PRNG, whose cost is roughly nJ/operation. Thus far, we have ignored the analog signal transduction attached to the coinflip devices and the logic operations that tie them together. Coinflip devices which cannot be directly integrated with logic will suffer from a von Neumann bottleneck. Thus, the coinflip devices need to be intimately integrated with logic, requiring paying a per-device transduction penalty. We find the energy cost for even the simplest signal transduction – a stimulating pulse and a latching output – is in the 100 fJ – 1 pJ per device range, which is larger than the energy consumed by either magnetic tunnel junctions or tunnel diodes. Meanwhile, the most expensive component of the logic operations stem from the fine-grained integration of memory. While only 32 weighted coinflips are needed to draw a 32-bit non-uniform sample, there are ~232 possible weights needed. We discuss schemes to prune the values needed to avoid the situation where the weights occupy all of a 1 cm2 die. In sum, the energy and area cost of the coinflip device are less important than the energy cost of signal transduction, and the area taken by memory for storing weights of a sampling tree.We emphasize that none of our estimates represents a tight optimization of any part of an imagined probabilistic computer. Still, in a full-system implementation, the efficient management of signal transduction and memory clearly outweight the energy or space consumed by the coinflip devices themselves. These factors comprise the key variables for stochastic devices that need to be accounted for in holistic codesign for probabilistic computing.SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

Quantum pathways for charged track finding in high-energy collisions.

In high-energy particle collisions, charged track finding is a complex yet crucial endeavor. We propose a quantum algorithm, specifically quantum template matching, to enhance the accuracy and efficiency of track finding. Abstracting the Quantum Amplitude Amplification routine by introducing a data register, and utilizing a novel oracle construction, allows data to be parsed to the circuit and matched with a hit-pattern template, without prior knowledge of the input data. Furthermore, we address the challenges posed by missing hit data, demonstrating the ability of the quantum template matching algorithm to successfully identify charged-particle tracks from hit patterns with missing hits. Our findings therefore propose quantum methodologies tailored for real-world applications and underline the potential of quantum computing in collider physics.

The new physics case for beam-dump experiments with accelerated muon beams

As the field examines a future muon collider as a possible successor to the LHC, we must consider how to fully utilize not only the high-energy particle collisions, but also any lower-energy staging facilities necessary in the R&D process. An economical and efficient possibility is to use the accelerated muon beam from either the full experiment or from cooling and acceleration tests in beam-dump experiments. Beam-dump experiments are complementary to the main collider as they achieve sensitivity to very small couplings with minimal instrumentation. We demonstrate the utility of muon beam-dump experiments for new physics searches at energies from 10 GeV to 5 TeV. We find that, even at low energies like those accessible at staging or demonstrator facilities, it is possible to probe new regions of parameter space for a variety of generic BSM models, including muonphilic, leptophilic, Lμ − Lτ, and dark photon scenarios. Such experiments could therefore provide opportunities for discovery of new physics well before the completion of the full multi-TeV collider.

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks

Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as graph neural networks (GNNs), have been leveraged for various data analysis tasks in high-energy physics. One typical task is jet tagging, where jets are viewed as point clouds with distinct features and edge connections between their constituent particles. The increasing size and complexity of the LHC particle datasets, as well as the computational models used for their analysis, have greatly motivated the development of alternative fast and efficient computational paradigms such as quantum computation. In addition, to enhance the validity and robustness of deep networks, we can leverage the fundamental symmetries present in the data through the use of invariant inputs and equivariant layers. In this paper, we provide a fair and comprehensive comparison of classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks (QGNNs) and equivariant quantum graph neural networks (EQGNN). The four architectures were benchmarked on a binary classification task to classify the parton-level particle initiating the jet. Based on their area under the curve (AUC) scores, the quantum networks were found to outperform the classical networks. However, seeing the computational advantage of quantum networks in practice may have to wait for the further development of quantum technology and its associated application programming interfaces (APIs).

High-Energy Collision of Quarks and Mesons in the Schwinger Model: From Tensor Networks to Circuit QED.

With the aim of studying nonperturbative out-of-equilibrium dynamics of high-energy particle collisions on quantum simulators, we investigate the scattering dynamics of lattice quantum electrodynamics in 1+1 dimensions. Working in the bosonized formulation of the model and in the thermodynamic limit, we use uniform-matrix-product-state tensor networks to construct multiparticle wave-packet states, evolve them in time, and detect outgoing particles post collision. This facilitates the numerical simulation of scattering experiments in both confined and deconfined regimes of the model at different energies, giving rise to rich phenomenology, including inelastic production of quark and meson states, meson disintegration, and dynamical string formation and breaking. We obtain elastic and inelastic scattering cross sections, together with time-resolved momentum and position distributions of the outgoing particles. Furthermore, we propose an analog circuit-QED implementation of the scattering process that is native to the platform, requires minimal ingredients and approximations, and enables practical schemes for particle wave-packet preparation and evolution. This study highlights the role of classical and quantum simulation in enhancing our understanding of scattering processes in quantum field theories in real time.

Investigation of scalar and fermion dark matter in mono-photon production at high-energy colliders

Many theories about dark matter have emerged due to its strong theoretical appeal in explaining astrophysical phenomena. However, experimental and theoretical particle physics have yet not provided evidence that dark matter is part of the observable Universe. Our work aims to investigate the interaction between Standard Model (SM) fermions and different species of dark matter (DM) particles in high-energy collisions through interaction of a new massive vector mediator, Z′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Z^{\\prime }$$\\end{document}. The production of scalar and fermion DM pairs via fermion annihilation into the new vector boson is investigated near a resonance (mχ∼MZ′/2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(m_{\\chi }\\sim M_{Z^{\\prime }}/2)$$\\end{document}, where a SM signal from hard photon emission is considered as initial state radiation, namely a mono-photon production. Values of coupling constants between the DM and the SM particles are mapped in contrast to the Planck satellite data for thermal relic density DM computed in the correct framework for the relic density near a resonance, where a weaker suppression of the relic density is expected. We show for the CLIC and LHC kinematic regimes that certain mass ranges and coupling constants of these DM particles are in agreement with the expected relic density near a resonance and are not excluded by collider and astrophysical limits.

Commissioning of Pixel Sensor Telescope for Monolithic Active Pixel Sensor Characterization

The Monolithic Active Pixel Sensors (MAPS) have been promisingly demonstrated as a core part of tracking detectors used in many experiments. In order to obtain decent particle tracks generated after high-energy particle collision, it is especially important that the detector must consist of high-performance MAPS. A pixel sensor telescope is a tool employed to investigate the properties of MAPS using high-energy particle test beams. At the Synchrotron Light Research Institute (SLRI), the pixel sensor telescope assembled with five layers of 50-µm thick pixel sensors has been commissioned and tested both in the laboratory with a radioactive source and by a high-energy electron test beam produced at the SLRI Beam Test Facility. With sensor signal threshold ranging from 9.73 to 10.15 DAC and noises between 0.62 and 0.87 DAC, each plane of the pixel sensor telescope can detect particles decaying from the radioactive source. Moreover, the test beam profiles have been measured to be 4.00 - 4.56 mm and 1.15 - 2.29 mm in horizontal and vertical axes, respectively. Correlations between each plane have been observed and confirm the proper operation of the pixel sensor telescope. Consequently, the pixel sensor telescope can be used to characterize the pixel sensor prototype.

Future high energy colliders and options for the U.S.

The United States has a rich history in high energy particle accelerators and colliders — both lepton and hadron machines, which have enabled several major discoveries in elementary particle physics. To ensure continued progress in the field, U.S. leadership as a key partner in building next generation collider facilities abroad is essential; also critically important is to prepare to host an energy frontier collider in the U.S. once the construction of the LBNF/DUNE project is completed. In this paper, we briefly discuss the ongoing and potential U.S. engagement in proposed collider projects abroad and present a number of future collider options we have studied for hosting an energy frontier collider in the U.S. We also call for initiating an integrated national R&D program in the U.S. now, focused on future colliders.

On the Partition Temperature of Massless Particles in High-Energy Collisions

Although partition temperature derived using the Darwin–Fowler method is exact for simple scenarios, the derivation for complex systems might reside in specific approximations whose viability is not ensured if the thermodynamic limit is not attained. This work elaborates on a related problem relevant to relativistic high-energy collisions. On the one hand, it is simple enough that closed-form expressions can be obtained precisely for the one-particle distribution function. On the other hand, the resulting expression is not an exponential form, and therefore, it is not straightforward that the notion of partition function could be implied. Specifically, we derive the one-particle distribution function for massless particles where the phase-space integration is performed exactly for the underlying canonical ensemble consisting of a given number of particles. We discuss the viability of the partition temperature in this case. Possible implications of the obtained results regarding the observed Tsallis distribution in transverse momentum spectra in high-energy collisions are also addressed.

20 T Hybrid Nb3Sn-HTS Block-Coil Accelerator Dipole With Stress-Management

In the framework of studies for high energy particle colliders, design concepts for high field dipoles are being explored. In particular, relatively compact 20 T magnets can be achieved in a hybrid configuration, combining a High Temperature Superconductor (HTS) and a Low Temperature Superconductor (LTS). Preliminary concepts have been previously proposed using Bi2212 for the HTS and Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn for the LTS. One of the main difficulties of 20 T magnets is the management of the very high stresses developing during operation. The design concepts rely on a rectangular block-coil layout, which offers the advantage of aligning the conductors with the main magnetic field, therefore submitting the conductors to a perpendicular electromagnetic force for a better control of the stresses. In addition, the layout allows a specific stress management, with adequate horizontal and vertical plates to intercept the stresses. The paper presents the improvements provided to the initial concept. In terms of magnetic design, the field quality has been improved. In terms of mechanical design, the stress management has been optimized to provide a compact coil with a reduced peak stress on the HTS. Concepts for flared-end coils with joints in the coil-ends are finally presented.

Transverse Momentum Distribution of Secondary Particles in High-Energy Collisions of Protons and Nuclei and the Possibility of Detecting Dark Matter Particles in the Spectra of Soft Photons

Transverse Momentum Distribution of Secondary Particles in High-Energy Collisions of Protons and Nuclei and the Possibility of Detecting Dark Matter Particles in the Spectra of Soft Photons

CDF II W-mass anomaly faces first-order electroweak phase transition

We suggest an appealing strategy to probe a large class of scenarios beyond the Standard Model simultaneously explaining the recent CDF II measurement of the W boson mass and predicting first-order phase transitions (FOPT) testable in future gravitational-wave (GW) experiments. Our analysis deploys measurements from the GW channels and high energy particle colliders. We discuss this methodology focusing on the specific example provided by an extension of the Standard Model of particle physics that incorporates an additional scalar textrm{SU}(2)_textrm{L} triplet coupled to the Higgs boson. We show that within this scenario a strong electroweak FOPT is naturally realised consistently with the measured W boson mass-shift. Potentially observable GW signatures imply the triplet mass scale to be TeV-ish, consistently with the value preferred by the W mass anomaly. This model can be tested in future space-based interferometers such as LISA, DECIGO, BBO, TianQin, TAIJI projects and in future colliders such as FCC, ILC, CEPC.

Dark matter from primordial black holes would hold charge

We explore the possibility that primordial black holes (PBHs) contain electric charge down to the present day. We find that PBHs should hold a non-zero net charge at their formation, due to either Poisson fluctuations at horizon crossing or high-energy particle collisions. Although initial charge configurations are subject to fast discharge processes through particle accretion or quantum particle emission, we show that maximally rotating PBHs could produce magnetic fields able to shield them from discharge. Moreover, given that electrons are the lightest and fastest charge carriers, we show that the plasma within virialised dark matter haloes can endow PBHs with net negative charge. We report charge-to-mass ratios between 10-31 C/kg and 10-15 C/kg for PBHs within the mass windows that allow them to constitute the entirety of the dark matter in the Universe.

Collider events on a quantum computer

High-quality simulated data is crucial for particle physics discoveries. Therefore, parton shower algorithms are a major building block of the data synthesis in event generator programs. However, the core algorithms used to generate parton showers have barely changed since the 1980s. With quantum computers’ rapid and continuous development, dedicated algorithms are required to exploit the potential that quantum computers provide to address problems in high-energy physics. This paper presents a novel approach to synthesising parton showers using the Discrete QCD method. The algorithm benefits from an elegant quantum walk implementation which can be embedded into the classical toolchain. We use the ibm_algiers device to sample parton shower configurations and generate data that we compare against measurements taken at the ALEPH, DELPHI and OPAL experiments. This is the first time a Noisy Intermediate-Scale Quantum (NISQ) device has been used to simulate realistic high-energy particle collision events.

20 T Hybrid Nb3Sn-HTS Block-Coil Designs for a Future Particle Collider

Future high energy particle colliders are under study, with a first goal of 16 T dipoles, which is believed to be the practical limit of Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn magnets. Another more ambitious goal is to aim for 20 T dipoles. This very high field would require High Temperature Superconductors (HTS), such as Bi2212 or REBCO. Their substantially higher cost necessitate anyways the use of Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn for an affordable accelerator application. Therefore, hybrid designs can be proposed, where the HTS are used in the high field (16–20 T) area, and Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn are used in the low field (<16T) area. Rectangular block-coil designs are particularly well adapted to this concept, since the separation between high field and low field can be made parallel to the cable turns, inside each layer of the coil. However, the large forces accumulating on the cable turns generate a high transverse stress detrimental to the coil. The paper presents a conceptual Hybrid Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn-HTS design generating 20 T in the bore with margin, using a block-coil concept. Several conductor options are discussed. The design also proposes stress-management solutions to deal with the large stress developing in the coils.

Tau Lepton Identification With Graph Neural Networks at Future Electron–Positron Colliders

Efficient and accurate reconstruction and identification of tau lepton decays plays a crucial role in the program of measurements and searches under the study for the future high-energy particle colliders. Leveraging recent advances in machine learning algorithms, which have dramatically improved the state of the art in visual object recognition, we have developed novel tau identification methods that are able to classify tau decays in leptons and hadrons and to discriminate them against QCD jets. We present the methodology and the results of the application at the interesting use case of the IDEA dual-readout calorimeter detector concept proposed for the future FCC-ee electron–positron collider.

Measurement of splittings along a jet shower in $\sqrt{s} = 200$ GeV pp collisions at STAR

Jets are algorithmic proxies of hard scattered partons, i.e. quarks and gluons, in high energy particle collisions. The STAR collaboration presents the first measurements of substructure observables at the first, second and third splits in the jet clustering tree via the iterative SoftDrop procedure. For each of these splits, we measure the fully corrected groomed shared momentum fraction (z_gg) and groomed jet radius (R_gg). We discuss the evolution of jet substructure in both the angular and momentum scales which allows for a self-similarity test of the DGLAP splitting function. We compare the fully corrected data to Monte Carlo models, providing stringent constraints on model parameters related to the parton shower and non-perturbative effects such as hadronization.