Creating simple, interpretable anomaly detectors for new physics in jet substructure
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Dr. Mankbadi summarized recent CAA results. Examples of the effect of various boundary condition schemes on the computed acoustic field, for a point source in a uniform flow, were shown. Solutions showing the impact of inflow excitations on the result were also shown. Results from a large eddy simulation, using a fourth-order MacCormack scheme with a Smagorinsky sub-grid turbulence model, were shown for a Mach 2.1 unheated jet. The results showed that the results were free from spurious modes. Results were shown for a Mach 1.4 jet using LES in the near field and the Kirchhoff method for the far field. Predicted flow field characteristics were shown to be in good agreement with data and predicted far field directivities were shown to be in qualitative agree with experimental measurements.
Dr. Mankbadi summarized recent CAA results. Examples of the effect of various boundary condition schemes on the computed acoustic field, for a point source in a uniform flow, were shown. Solutions showing the impact of inflow excitations on the result were also shown. Results from a large eddy simulation, using a fourth-order MacCormack scheme with a Smagorinsky sub-grid turbulence model, were shown for a Mach 2.1 unheated jet. The results showed that the results were free from spurious modes. Results were shown for a Mach 1.4 jet using LES in the near field and the Kirchhoff method for the far field. Predicted flow field characteristics were shown to be in good agreement with data and predicted far field directivities were shown to be in qualitative agree with experimental measurements.
In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a model is trained to recover the missing elements of a set, a learning objective that requires no labels and can be applied directly to experimental data. We achieve significant performance improvements over previous work on MPM by addressing inefficiencies in the implementation and incorporating a more powerful decoder. We compare several pre-training tasks and introduce new reconstruction methods that utilize conditional generative models without data tokenization or discretization. We show that these new methods outperform the tokenized learning objective from the original MPM on a new test bed for foundation models for jets, which includes using a wide variety of downstream tasks relevant to jet physics, such as classification, secondary vertex finding, and track identification.
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This review presents a comprehensive overview of key phenomenological opportunities at the future Electron–Ion Collider (EIC), synthesizing discussions and collaborative research efforts developed within the Korean EIC community and the EICφ collaboration. We explore a diverse range of physics topics central to the EIC scientific program, including the multidimensional tomography of nucleon and nuclear structure, precision Quantum Chromodynamics studies through jet physics and event-shape observables, heavy quarkonium production as a probe of partonic dynamics, and the spectroscopy of exotic hadrons. Furthermore, we discuss the transformative potential of emerging technologies—specifically Machine Learning and Quantum Computing—as essential tools for addressing the computational challenges and maximizing the scientific discovery potential of the EIC era.
The goal of this project was to create, maintain, and strengthen a world-class, nationally and internationally recognized experimental high energy physics group at Louisiana Tech University, focusing on research at the energy frontier of collider-based particle physics, first on the DØ experiment and then with the ATLAS experiment, and providing leadership within the US high energy physics community in the areas of jet physics, top quark and charged Higgs decays involving tau leptons, as well as developing leadership in high performance computing.
This was a project to understand the multiwavelength variability of blazars, via monitoring with the XTE satellite and many other space- and ground-based observatories. Blazars are dominated by strong nonthermal emission, we now know, due to relativistic beaming in an aligned jet. Thus they are ideal laboratories for studying jet physics. The physical scales of the inner, energetically dominant jets are generally too small to resolve with current or next-generation instruments, so we used variability to probe the balance between acceleration/injection of energetic particles and radiative/other losses, and to infer jet structure. Our work has shown that the radio through UV-X-ray emission is produced via synchrotron radiation, and that at the peak frequency and above, the emission region is approximately homogeneous. A separate gamma-ray component, which is often energetically dominant, varies in a correlated way but with larger amplitude, suggesting it is produced when the synchrotron-emitting electrons Compton scatter soft photons (though other possibilities remain viable). With RXTE we carried out two intensive monitoring campaigns on the blazar PKS2155-304, in May 1996 and November 1996. Analysis and interpretation of these data constituted the main activities under this grant. The results have been presented at several meetings, and a number of publications have resulted from this work. In addition, a final paper for a refereed publication is in final draft form, as are companion papers based on simultaneous Rosat and EUVE results.
Identifying the origin of high-energy hadronic jets (jet tagging) has been a critical benchmark problem for machine learning in particle physics. Jets are ubiquitous at colliders and are complex objects that serve as prototypical examples of collections of particles to be categorized. Over the last decade, machine learning-based classifiers have replaced classical observables as the state of the art in jet tagging. Increasingly complex machine learning models are leading to increasingly more effective tagger performance. Our goal is to address the question of convergence—are we getting close to the fundamental limit on jet tagging or is there still potential for computational, statistical, and physical insights for further improvements? We address this question using state-of-the-art generative models to create a realistic, synthetic dataset with a known jet tagging optimum. Various state-of-the-art taggers are deployed on this dataset, showing that there is a significant gap between their performance and the optimum. Our dataset and software are made public to provide a benchmark task for future developments in jet tagging and other areas of particle physics.
The PHENIX collaboration is planning a detector upgrade, sPHENIX, which consists of large acceptance calorimetry and tracking detectors built around the superconducting solenoid recently shipped to Brookhaven from the decommissioned BaBar experiment at SLAC. The sPHENIX calorimeter system includes three radial layers of samplingcalorimeters, a tungsten-scintillating fiber electromagnetic calorimeter, and two longitudinally segmented samplinghadron calorimeters that are made of scintillator tiles and steel plates. Together, they provide hermetic coverage in n < 1 for calorimetry based jet measurements as well as minimal bias jet trigger capability, which coupled with high resolution tracking, enable an extremely rich jet physics program at RHIC.
Black holes generate collimated, relativistic jets which have been observed in gamma-ray bursts (GRBs), microquasars, and at the center of some galaxies (active galactic nuclei; AGN). How jet physics scales from stellar black holes in GRBs to the supermassive ones in AGNs is still unknown. Here we show that jets produced by AGNs and GRBs exhibit the same correlation between the kinetic power carried by accelerated particles and the gamma-ray luminosity, with AGNs and GRBs lying at the low and high-luminosity ends, respectively, of the correlation. This result implies that the efficiency of energy dissipation in jets produced in black hole systems is similar over 10 orders of magnitude in jet power, establishing a physical analogy between AGN and GRBs.
Hall physics is often neglected in high energy density plasma jets due to the relatively high electron density of such jets (n{sub e} ∼ 10{sup 19} cm{sup −3}). However, the vacuum region surrounding the jet has much lower densities and is dominated by Hall electric field. This electric field redirects plasma flows towards or away from the axis, depending on the radial current direction. A resulting change in the jet density has been observed experimentally. Furthermore, if an axial field is applied on the jet, the Hall effect is enhanced and ignoring it leads to serious discrepancies between experimental results and numerical simulations. By combining high currents (∼1 MA) and magnetic field helicity (15° angle) in a pulsed power generator such as COBRA, plasma jets can be magnetized with a 10 T axial field. The resulting field enhances the impact of the Hall effect by altering the density profile of current-free plasma jets and the stability of current-carrying plasma jets (e.g., Z-pinches)
Jet physics is an exciting and rapidly growing branch of particle physics, particularly relevant to the energy frontier. Just a few years ago, jets were universally treated as structureless objects, representing the momentum of an underlying quark or gluon. Nowadays, jets are understood to be intricate, dynamical objects with interesting hidden properties worthy of investigation and relevant for understanding quantum field theory.
We provide a novel development in jet physics by predicting the energy profiles of light-quark and gluon jets in the framework of perturbative QCD. Resumming large logarithmic contributions to all orders in the coupling constant, our predictions are shown to agree well with Tevatron CDF and Large Hadron Collider CMS data. We also extend our resummation formalism to the invariant mass distributions of light-quark and gluon jets produced in hadron collisions. The predicted peak positions and heights in jet mass distributions are consistent with CDF data within uncertainties induced by parton distribution functions.
The correlation between the kinetic power P {sub jet} and intrinsic bolometric luminosity L {sub jet} of jets may reveal the underlying jet physics in various black hole systems. Based on the recent work by Nemmen et al., we re-investigate this correlation with additional sources of black hole X-ray binaries (BXBs) in hard/quiescent states and low-luminosity active galactic nuclei (LLAGNs). The new sample includes 29 sets of data from 7 BXBs and 20 LLAGNs, with P {sub jet} and L {sub jet} being derived from spectral modeling of the quasi-simultaneous multi-band spectra under the accretion jet scenario. Compared to previous works, the range of luminosity is now enlarged to more than 20 decades, i.e., from ∼10{sup 31} erg s{sup –1} to ∼10{sup 52} erg s{sup –1}, which allows for better constraining of the correlation. One notable result is that the jets in BXBs and LLAGNs almost follow the same P {sub jet}-L {sub jet} correlation that was obtained from blazars and gamma-ray bursts. The slope indices we derived are 1.03 ± 0.01 for the whole sample, 0.85 ± 0.06 for the BXB subsample, 0.71 ± 0.11 for the LLAGN subsample, and 1.01 ± 0.05 for the LLAGN-blazar subsample, respectively. The correlation index around unit implies the independence of jet efficiency on the luminosity or kinetic power. Our results may further support the hypothesis that similar physical processes exist in the jets of various black hole systems.
We explore jet physics in hadron collisions using the parton shower event generator Deductor. Of particular interest is the one jet inclusive cross section $d{\sigma}/d{P}_{\mathrm{T}}$ for jets of very high ${P}_{\mathrm{T}}$. Compared to the Born level, the cross section decreases substantially because of ${P}_{\mathrm{T}}$ loss from the jet during showering. We compare to the same effect in Pythia and Dire. The cross section then increases substantially because of the summation of threshold logarithms included in Deductor. We also study the cross section to have a gap with no jets between two hard jets that are widely separated in rapidity. Here we compare Atlas data to Deductor with virtuality based ordering and to Deductor with ${k}_{\mathrm{T}}$ ordering. We also compare with perturbation theory. In both cases, we check whether adding an underlying event and hadronization has a significant effect beyond that found with just a parton shower.