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At least 289 records · Page 16

Azimuthal angular correlation of J/ψ plus jet production at the electron-ion collider

By investigating the soft gluon radiation in the J/ψ plus jet photoproduction at the electron-ion collider (EIC), we demonstrate that the azimuthal angular correlations between the leading jet and heavy quarkonium provide a unique probe to the production mechanism of the latter. In particular, a significant cos⁡(φ) asymmetry is found for the color-singlet channel, whereas it vanishes or has an opposite sign for color-octet production, depending on the jet transverse momentum. Numerical results of cos⁡(φ) and cos⁡(2⁢φ) asymmetries employing both the color-singlet model and the nonrelativistic QCD approach are presented for typical kinematics at the future EIC.

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TeV-scale particles and LHC events with dijet pairs

Scalar particles that couple to two up quarks may be produced at the LHC even if they are ultraheavy, in the 8 − 10 TeV mass range. A renormalizable theory that includes a diquark particle of this type (S uu ), two vectorlike quarks (χ 1 , χ 2 ), and a gauge-singlet pseudoscalar, predicts LHC signals involving four or more jets of very high p T . Two remarkable events observed by the CMS experiment, each involving four high-p T jets, may be due to an Suu of mass near 8.5 TeV, and a χ 2 mass of 2.1 TeV. A separate excess reported by CMS in the nonresonant dijet pair search is consistent with a χ 1 mass of 0.95 TeV. This hypothesis may be tested through CMS and ATLAS searches for signals with a pair of dijet resonances of masses clustered around 1 TeV, and separately around 2 TeV, which have 4j invariant masses in the 5 − 8 TeV range. These additional signals would arise from cascade decays of S uu → χ 2 χ 2 , which lead to 5j and 6j events with invariant masses around 8 TeV. Depending on the couplings of the heavy colored particles, additional signals are possible, involving for example highly-boosted top quarks.

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Cavity Based Searches for New Particles and Gravitational Waves

The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will focus mostly on Dark SRF and MAGO activities.

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Neutron Identification Capabilities in MicroBooNE Through the Application of Machine Learning with Blips

Neutrinos (ν) are subatomic particles first observed in 1956 by LANL physicists Clyde Cowan and Frederick Reines but first theorized by Wolfgang Pauli in 1930. Neutrinos are the least massive known particle and are classified as leptons with 3 flavors corresponding to their leptonic counterparts (electron, muon, and tau). We know that they are abundant, 65 billion neutrinos travel through your fingertip every second, and elusive, a single neutrino could fly through a lightyear of lead without interacting at all. Though, there is much still unknown and a better characterization of these “ghostly” particles can give us clues as to the matter/anti-matter asymmetry in the early universe and possible glimpses into new physics. To measure a particle that is extremely light and rarely interacting, physicists have developed an extremely sensitive detector known as a Liquid Argon Time Projection Chamber (LArTPC). The fiducial volume (or TPC) is bombarded with neutrinos, some of which interact with argon (Ar) atoms to produce particles that in turn excite and ionize the Ar. The products of these are free electrons which then drift through the TPC’s applied magnetic field towards a multi-plane wire readout system. The electrons’ charge is collected at this anode and the light from the initial interactions is collected by photomultiplier tubes (PMTs). In conjunction, these mechanisms allow LArTPCs to achieve millimeter spatial resolution and sub-MeV energy thresholds. The detector of interest in this study is the MicroBooNE Experiment at Fermilab. MicroBooNE is an above ground LArTPC with dimensions of approximately 10m × 2.5m × 2.3m, about the size of a school bus. Its purpose is to study neutrinos, so to improve rates of measured ν interactions, the detector is squarely in the path of the Booster Neutrino Beam (BNB) at Fermilab. A major challenge in neutrino studies is energy reconstruction, much of the neutrino’s original energy is lost in interactions that the detector is not sensitive to, often due to low-energy products. The initial goal of this analysis was to better identify neutrons, the main source of poor energy reconstruction in neutrino events. Because neutrons are neutral particles, like neutrinos, we can only directly measure the products of their interactions in LArTPCs. Most of these products are low-energy signals and while each one contributes a negligible amount of energy, collectively these signals make up most of the lost energy in each neutrino event. We define these signals as blips; point-like, isolated depositions of charge in the detector. Blips have MeV-scale energies and are the size of a single hit (charge deposition) or a cluster of a few hits on at least two wire planes. Blips are the principal detector features used to study low-energy physics; thus, they are the key to unlocking information not only about neutrons but gamma photons, supernova and solar neutrinos as well as helping us better identify certain particles. Therefore, this analysis strives to use blips for improved neutron identification (ID) and characterization.

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Warm Hawking relics from primordial black hole domination

We study the cosmological impact of warm, dark-sector relic particles produced as Hawkingradiation in a primordial-black-hole-dominated universe before big bang nucleosynthesis. If thesedark-sector particles are stable, they would survive to the present day as Hawking relicsand modify the growth of cosmological structure. We show that such relics are producedwith much larger momenta, but in smaller quantities than the familiar thermal relics considered instandard cosmology. Consequently, Hawking relics with keV–MeV masses affect the growth oflarge-scale structure in a similar way to eV-scale thermal relics like massive neutrinos. Wemodel their production and evolution, and show that their momentum distributions are broader thancomparable relics with thermal distributions. Warm Hawking relics affect the growth ofcosmological perturbations and we constrain their abundance to be less than 2% of the darkmatter over a broad range of their viable parameter space. Finally, we examine how futuremeasurements of the matter power spectrum can distinguish Hawking relics from thermal particles.

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Single Electron Self-coherence and Its Wave/Particle Duality in the Electron Microscope

Intensities in high-resolution phase-contrast images from electron microscopes build up discretely in time by detecting single electrons. A wave description of pulse-like coherent-inelastic interaction of an electron with matter implies a time-dependent coexistence of coherent partial waves. Their superposition forms a wave package by phase decoherence of 0.5 - 1 radian with Heisenbergs energy uncertainty ΔE H = $\hbar$/2 Δt -1 matching the energy loss ΔE of a coherent-inelastic interaction and sets the interaction time Δt. In these circumstances, the product of Planck's constant and the speed of light hc is given by the product of the expression for temporal coherence λ 2 /Δλ and the energy loss ΔE. Experimentally, the self-coherence length was measured by detecting the energy-dependent localization of scattered, plane matter waves in surface proximity exploiting the Goos–Hänchen shift. Chromatic-aberration Cc-corrected electron microscopy on boron nitride (BN) proves that the coherent crystal illumination and phase contrast are lost if the self-coherence length shrinks below the size of the crystal unit cell at ΔE > 200 eV. Finally, in perspective, the interaction time of any matter wave compares with the lifetime of a virtual particle of any elemental interaction, suggesting the present concept of coherent-inelastic interactions of matter waves might be generalizable.

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Peter Higgs (1929–2024)

Peter Ware Higgs, a particle physics icon, died on 8 April at the age of 94. Higgs illuminated the path to understanding how exact symmetries obeyed by the laws of nature might be masked by an asymmetric ground state that is an outcome of symmetrical laws. In 1964, he posited that a field filling all of space could be the agent that hides the underlying symmetries of the fundamental interactions. Additionally, when excited, the field reveals itself as a massive unstable particle. In the context of a joint theory of electromagnetism and the weak interaction, that particle—popularly called the Higgs boson—emerged as the keystone of the standard model of particle physics. The decades-long search for the boson engaged the passion of thousands of scientists and engineers and stirred the curiosity of the public the world over.

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Final Technical Report for GROWTH-MSI at Sonoma University

This final technical report describes the goals, activities, outcomes, and broader impacts of the GROWTH-MSI program, supported through the DOE RENEW Initiative in High Energy Physics. The program established a 1.5-year traineeship for undergraduate students from six Northern California Minority Serving Institutions, connected students with DOE laboratory research mentors, provided particle physics coursework and professional development, and advanced HEP research infrastructure at CSU Stanislaus and Sonoma State University.

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Non-universal SUSY models, $g_\mu -2$, $m_H$ and dark matter

We study the anomalous magnetic moment of the muon, g μ – 2 ≡ 2a μ , in the context of supersymmetric models beyond the CMSSM, where the unification of either the gaugino masses M 1,2,3 or sfermion and Higgs masses is relaxed, taking into account the measured mass of the Higgs boson, m H , the cosmological dark matter density and the direct detection rate. We find that the model with non-unified gaugino masses can make a contribution Δa μ ~ 20 x 10 –10 to the anomalous magnetic moment of the muon, for example if M 1,2 ~ 600 GeV and M 3 ~ 8 TeV. The model with non-universal sfermion and Higgs masses can provide even larger Δa μ ~ 24 x 10 –10 if the sfermion masses for the first and the second generations are ~400 GeV and that of the third is ~8 TeV. We discuss the prospects for collider searches for supersymmetric particles in specific benchmark scenarios illustrating these possibilities, focusing in particular on the prospects for detecting the lighter smuon and the lightest neutralino.

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Is infrared-collinear safe information all you need for jet classification?

Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this discriminating power, and whether jet observables that are tractable in perturbative QCD such as those obeying infrared-collinear (IRC) safety serve as sufficient inputs. In this article, we introduce a new classifier, Jet Flow Networks (JFNs), in an effort to address the question of whether IRC unsafe information provides additional discriminating power in jet classification. JFNs are permutation-invariant neural networks (deep sets) that take as input the kinematic information of reconstructed subjets. The subjet radius and a cut on the subjet’s transverse momenta serve as tunable hyperparameters enabling a controllable sensitivity to soft emissions and nonperturbative effects. We demonstrate the performance of JFNs for quark vs. gluon and Z vs. QCD jet tagging. For small subjet radii and transverse momentum cuts, the performance of JFNs is equivalent to the IRC-unsafe Particle Flow Networks (PFNs), demonstrating that infrared-collinear unsafe information is not necessary to achieve strong discrimination for both cases. As the subjet radius is increased, the performance of the JFNs remains essentially unchanged until physical thresholds that we identify are crossed. For relatively large subjet radii, we show that the JFNs may offer an increased model independence with a modest tradeoff in performance compared to classifiers that use the full particle information of the jet. These results shed new light on how machines learn patterns in high-energy physics data.

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Once-in-a-lifetime encounter models for neutrino media: From coherent oscillations to flavor equilibration

Collective neutrino oscillations are typically studied using the lowest-order quantum kinetic equation, also known as the mean-field approximation. However, some recent quantum many-body simulations suggest that quantum entanglement among neutrinos may be important and may result in flavor equilibration of the neutrino gas. In this work, we develop new quantum models for neutrino gases in which any pair of neutrinos can interact at most once in their lifetimes. A key parameter of our models is γ = μ Δ z , where μ is the neutrino coupling strength, which is proportional to the neutrino density, and Δ z is the duration over which a pair of neutrinos can interact each time. Our models reduce to the mean-field approach in the limit γ → 0 and achieve flavor equilibration in time t ≫ ( γ μ ) − 1 . These models demonstrate the emergence of coherent flavor oscillations from the particle perspective and may help elucidate the role of quantum entanglement in collective neutrino oscillations. Published by the American Physical Society 2024

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Contour deformations for nonholomorphic actions

We show how contour deformations may be used to control the sign problem of lattice Monte Carlo calculations with nonholomorphic Boltzmann factors. Such actions arise naturally in quantum mechanical scattering problems. The approach is demonstrated in conjunction with the holomorphic gradient flow. As our central example we compute the real-time evolution of a particle in a one-dimensional analog of the Yukawa potential. Published by the American Physical Society 2024

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Coherent spin states and emergent de Sitter quasinormal modes

As a toy model for the microscopic description of matter in de Sitter space, we consider a Hamiltonian acting on the spin-j representation of SU(2). This is a model with a finite-dimensional Hilbert space, from which quasinormal modes emerge in the large-spin limit. The path integral over coherent spin states can be evaluated at the semiclassical level and from it we find the single-particle de Sitter density of states, including 1/j corrections. Along the way, we discuss the use of quasinormal modes in quantum mechanics, starting from the paradigmatic upside-down harmonic oscillator.

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Dark sector searches with the CMS experiment

Astrophysical observations provide compelling evidence for gravitationally interacting dark matter in the universe that cannot be explained by the standard model of particle physics. The extraordinary amount of data from the CERN LHC presents a unique opportunity to shed light on the nature of dark matter at unprecedented collision energies. This Report comprehensively reviews the most recent searches with the CMS experiment for particles and interactions belonging to a dark sector and for dark-sector mediators. Models with invisible massive particles are probed by searches for signatures of missing transverse momentum recoiling against visible standard model particles. Searches for mediators are also conducted via fully visible final states. The results of these searches are compared with those obtained from direct-detection experiments. Searches for alternative scenarios predicting more complex dark sectors with multiple new particles and new forces are also presented. Many of these models include long-lived particles, which could manifest themselves with striking unconventional signatures with relatively small amounts of background. Searches for such particles are discussed and their impact on dark-sector scenarios is evaluated. Many results and interpretations have been newly obtained for this Report.

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Complete 6D Tracking of a Single Electron in the IOTA Ring

We present the results of the first experiments on 6-dimensional phase-space tracking of a single electron in a storage ring, using a linear multi-anode photomultiplier tube for simultaneously measuring transverse coordinates and arrival times of synchrotron-radiation pulses. This technology makes it possible to fully reconstruct turn-by-turn positions and momentums in all three planes for a single particle. Complete experimental particle tracking enables the first direct measurements of dynamical properties, including invariants, amplitude and energy dependence of tunes with exceptional precision, and chaotic behavior.

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Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

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Identifying Neutrino Final States and Energies in MicroBooNE with New Deep-Learning Based LArTPC Reconstruction Frameworks

MicroBooNE, a Liquid Argon Time Projection Chamber (LArTPC) located in the $\nu_{\mu}$-dominated Booster Neutrino Beam at Fermilab, has been studying $\nu_{e}$ charged-current (CC) interaction rates to shed light on the MiniBooNE low energy excess. The LArTPC technology employed by MicroBooNE provides the capability to image neutrino interactions with mm-scale precision. Computer vision and other machine learning techniques are promising tools for image processing that could boost efficiencies for selecting $\nu_{e}$-CC and other rare signals, reduce cosmic and beam-induced backgrounds, and improve the reconstruction of neutrino energies. The MicroBooNE experiment has been at the forefront of developing and testing such techniques for use in physics analyses. In this poster we overview deep-learning based reconstruction methods. We will showcase the use of a recurrent neural network to estimate neutrino energies and present a new reconstruction framework that uses convolutional neural networks to locate neutrino interaction vertices, tag pixels with track and shower labels, and perform particle identification on reconstructed clusters. We will present studies characterizing the performance of these new tools and demonstrate their effectiveness through their use in an inclusive $\nu_{e}$-CC event selection.

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Mu2e: Modeling Drift of Ionized Particles with ML

The Mu2e experiment searches for charged lepton flavor violation through muon-to-electron conversion in the field of a nucleus. The signal is a monoenergetic electron with an energy of 104.97 MeV. Its momentum is reconstructed using information from drifting ionized particles in a straw tracker detector. This project analyzes the drift of ionized particles with a deep neural network to help improve the momentum reconstruction process. The model yields a 20% improvement in resolution from a reference linear model.

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