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At least 19 records

Method to simultaneously facilitate all jet physics tasks

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 jet physics are proceeding in parallel. We show that specially constructed machine learning models trained for a specific jet classification task can improve the accuracy, precision, or speed of all other jet physics tasks. This is demonstrated by training on a particular multiclass generation and classification task and then using the learned representation for different generation and classification tasks, for datasets with a different (full) detector simulation, for jets from a different collision system ($pp$ versus $ep$), for generative models, for likelihood ratio estimation, and for anomaly detection. We consider our omnilearn approach thus as a jet-physics foundation model. It is made publicly available for use in any area where state-of-the-art precision is required for analyses involving jets and their substructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Foundation model framework for all tasks involving jet physics

Foundation models use large datasets to build an effective representation of data that can be deployed on diverse downstream tasks. Previous research developed the omnilearn foundation model for jet physics, using unique properties of particle physics, and showed that it could significantly advance discovery potential across collider experiments. This paper introduces a major upgrade, resulting in the omnilearned framework. This framework has three new elements: (1) updates to the model architecture and training, (2) using over 1 × 10 9 jets used for training, and (3) providing well-documented software for accessing all datasets and models. We demonstrate omnilearned with three representative tasks: top-quark jet tagging with the community delphes-based benchmark dataset, b tagging with ATLAS full simulation, and anomaly detection with CMS experimental data. In each case, omnilearned is the state of the art, further expanding the discovery potential of past, current, and future collider experiments.

Bhimji, Wahid [Lawrence Berkeley National Laborato

Learning about jet physics from gamma-ray blazars

The spectral properties of the MeV radiation-dominated blazars are used to place constraints on the physical parameters of relativistic jets in quasars. The luminosities and positions of high energy and low energy spectral components are used to derive constraints on the jet speeds, magnetic fields and the distances at which most of the nonthermal radiation is produced. By comparing the theoretically predicted bulk-Compton radiation with the observed soft X-ray luminosities, upper limits on the optical thickness and lower limits on the distance where the relativistic jet is formed and collimated, are identified. The results show that these jets should be Thomson optically thin and, in the case of gamma ray production dominated by the external radiation Compton process, favor proton-electron jets. Weaker constraints on the pair production are provided if the gamma ray production is dominated by the synchrotron self Compton (SSC) process. The values of the jet Lorentz factors predicted by the SSC models are smaller than those observed in quasars.

Sikora, M.

Numerical Simulation of Screech Tones from Supersonic Jets: Physics and Prediction

The objectives of this project are to: (1) perform a numerical simulation of the jet screech phenomenon; and (2) use the data of the simulations to obtain a better understanding of the physics of jet screech. The original grant period was for three years. This was extended at no cost for an extra year to allow the principal investigator time to publish the results. We would like to report that our research work and results (supported by this grant) have fulfilled both objectives of the grant. The following is a summary of the important accomplishments: (1) We have now demonstrated that it is possible to perform accurate numerical simulations of the jet screech phenomenon. Both the axisymmetric case and the fully three-dimensional case were carried out successfully. It is worthwhile to note that this is the first time the screech tone phenomenon has been successfully simulated numerically; (2) All four screech modes were reproduced in the simulation. The computed screech frequencies and intensities were in good agreement with the NASA Langley Research Center data; (3) The staging phenomenon was reproduced in the simulation; (4) The effects of nozzle lip thickness and jet temperature were studied. Simulated tone frequencies at various nozzle lip thickness and jet temperature were found to agree well with experiments; (5) The simulated data were used to explain, for the first time, why there are two axisymmetric screech modes and two helical/flapping screech modes; (6) The simulated data were used to show that when two tones are observed, they co-exist rather than switching from one mode to the other, back and forth, as some previous investigators have suggested; and (7) Some resources of the grant were used to support the development of new computational aeroacoustics (CAA) methodology. (Our screech tone simulations have benefited because of the availability of these improved methods.)

Tam, Christopher K. W.

Implicit quantile networks for emulation in jet physics

Abstract The ability to model and sample from conditional densities is important in many physics applications. Implicit quantile networks (IQN) have been successfully applied to this task in domains outside physics. In this work, we illustrate the potential of IQNs as components of emulators using the simulation of jets as an example. Specifically, we use an IQN to map jets described by their 4-momenta at the generation level to jets at the event reconstruction level. The conditional densities emulated by our model closely match those generated by Delphes , while also enabling faster jet simulation.

Kronheim, Braden (ORCID:0000000307040972)

Search for New Physics in Jet Multiplicity Patterns of Multilepton Events at $\sqrt{s}$ = 13 TeV

A first search for beyond the standard model physics in jet multiplicity patterns of multilepton events is presented, using a data sample corresponding to an integrated luminosity of 138 fb −1 of 13 TeV proton-proton collisions recorded by the CMS detector at the LHC. The search uses observed jet multiplicity distributions in one-, two-, and four-lepton events to explore possible enhancements in jet production rate in three-lepton events with and without bottom quarks. The data are found to be consistent with the standard model expectation. The results are interpreted in terms of supersymmetric production of electroweak chargino-neutralino superpartners with cascade decays terminating in prompt hadronic 𝑅-parity violating interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Jet Noise Physics and Modeling Using First-principles Simulations

An extensive analysis of our jet DNS database has provided for the first time the complex correlations that are the core of many statistical jet noise models, including MGBK. We have also for the first time explicitly computed the noise from different components of a commonly used noise source as proposed in many modeling approaches. Key findings are: (1) While two-point (space and time) velocity statistics are well-fitted by decaying exponentials, even for our low-Reynolds-number jet, spatially integrated fourth-order space/retarded-time correlations, which constitute the noise "source" in MGBK, are instead well-fitted by Gaussians. The width of these Gaussians depends (by a factor of 2) on which components are considered. This is counter to current modeling practice, (2) A standard decomposition of the Lighthill source is shown by direct evaluation to be somewhat artificial since the noise from these nominally separate components is in fact highly correlated. We anticipate that the same will be the case for the Lilley source, and (3) The far-field sound is computed in a way that explicitly includes all quadrupole cancellations, yet evaluating the Lighthill integral for only a small part of the jet yields a far-field noise far louder than that from the whole jet due to missing nonquadrupole cancellations. Details of this study are discussed in a draft of a paper included as appendix A.

Freund, Jonathan B.

CAA for Jet Noise Physics

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.

Mankbadi, Reda

CAA for Jet Noise Physics: Issues and Recent Progress

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.

Mankbadi, Reda

Is tokenization needed for masked particle modeling?

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.

conditional generative models

Phenomenological opportunities at the EIC

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.

Electron–Ion collider

Probing Blazar Structure Through Multiwavelength Variability

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.

Urry, C. Megan

Fundamental limit of jet tagging

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.

Artificial intelligence

A Universal Scaling for the Energetics of Relativistic Jets From Black Hole Systems

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.

Nemmen, R. S.

Wasserstein normalized autoencoder for anomaly detection

A novel anomaly detection algorithm is presented. The Wasserstein normalized autoencoder (WNAE) is a normalized probabilistic model that minimizes the Wasserstein distance between the learned probability distribution—a Boltzmann distribution where the energy is the reconstruction error of the autoencoder (AE)—and the distribution of the training data. This algorithm has been developed and applied to the identification of semivisible jets—conical sprays of visible standard model (SM) particles and invisible dark matter states—with the CMS experiment at the CERN LHC. Trained on jets of particles from simulated SM processes, the WNAE is shown to learn the probability distribution of the input data in a fully unsupervised fashion, such that it effectively identifies new physics jets as anomalies. The model exhibits stable, convergent training and recovers strong classification performance for a wide range of signals against the selected background process, for which a standard AE fails because of outlier reconstruction. In addition, the model improves upon standard normalized autoencoders while remaining fully agnostic to the signal. The WNAE directly tackles the problem of outlier reconstruction, a common failure mode of autoencoders in anomaly detection tasks.

Hayrapetyan, Aram [Yerevan Phys. Inst.]

Spectral Energy Distribution Models for Low-Luminosity Active Galactic Nuclei in LINERs

Low-luminosity active galactic nuclei (LLAGNs) represent the bulk of the AGN population in the present-day universe and they trace the low-level accreting supermassive black holes. In order to probe the accretion and jet physical properties in LLAGNs as a class, we model the broadband radio to X-rays spectral energy distributions (SEDs) of 21 LLAGNs in low-ionization nuclear emission-line regions (LINERs) with a coupled accretion-jet model. The accretion flow is modeled as an inner ADAF outside of which there is a truncated standard thin disk. We find that the radio emission is severely underpredicted by ADAF models and is explained by the relativistic jet. The origin of the X-ray radiation in most sources can be explained by three distinct scenarios: the X-rays can be dominated by emission from the ADAF, or the jet, or the X-rays can arise from a jet-ADAF combination in which both components contribute to the emission with similar importance. For 3 objects both the jet and ADAF fit equally well the X-ray spectrum and can be the dominant source of X-rays whereas for 11 LLAGNs a jet-dominated model accounts better than the ADAF-dominated model for the data. The individual and average SED models that we computed can be useful for different studies of the nuclear emission of LLAGNs. From the model fits, we estimate important parameters of the central engine powering LLAGNs in LINERs, such as the mass accretion rate and the mass-loss rate in the jet and the jet power - relevant for studies of the kinetic feedback from jets.

Nemmen, Rodrigo S.

Simulation of Flow Through Breach in Leading Edge at Mach 24

A baseline solution for CFD Point 1 (Mach 24) in the STS-107 accident investigation was modified to include effects of holes through the leading edge into a vented cavity. The simulations were generated relatively quickly and early in the investigation by making simplifications to the leading edge cavity geometry. These simplifications in the breach simulations enabled: 1) A very quick grid generation procedure; 2) High fidelity corroboration of jet physics with internal surface impingements ensuing from a breach through the leading edge, fully coupled to the external shock layer flow at flight conditions. These simulations provided early evidence that the flow through a 2 inch diameter (or larger) breach enters the cavity with significant retention of external flow directionality. A normal jet directed into the cavity was not an appropriate model for these conditions at CFD Point 1 (Mach 24). The breach diameters were of the same order or larger than the local, external boundary-layer thickness. High impingement heating and pressures on the downstream lip of the breach were computed. It is likely that hole shape would evolve as a slot cut in the direction of the external streamlines. In the case of the 6 inch diameter breach the boundary layer is fully ingested.

Gnoffo, Peter A.

Effects of Wing Leading Edge Penetration with Venting and Exhaust Flow from Wheel Well at Mach 24 in Flight

A baseline solution for CFD Point 1 (Mach 24) in the STS-107 accident investigation was modified to include effects of: (1) holes through the leading edge into a vented cavity; and (2) a scarfed, conical nozzle directed toward the centerline of the vehicle from the forward, inboard corner of the landing gear door. The simulations were generated relatively quickly and early in the investigation because simplifications were made to the leading edge cavity geometry and an existing utility to merge scarfed nozzle grid domains with structured baseline external domains was implemented. These simplifications in the breach simulations enabled: (1) a very quick grid generation procedure; and (2) high fidelity corroboration of jet physics with internal surface impingements ensuing from a breach through the leading edge, fully coupled to the external shock layer flow at flight conditions. These simulations provided early evidence that the flow through a two-inch diameter (or larger) breach enters the cavity with significant retention of external flow directionality. A normal jet directed into the cavity was not an appropriate model for these conditions at CFD Point 1 (Mach 24). The breach diameters were of the same order or larger than the local, external boundary-layer thickness. High impingement heating and pressures on the downstream lip of the breach were computed. It is likely that hole shape would evolve as a slot cut in the direction of the external streamlines. In the case of the six-inch diameter breach the boundary layer is fully ingested. The intent of externally directed jet simulations in the second scenario was to approximately model aerodynamic effects of a relatively large internal wing pressure, fueled by combusting aluminum, which deforms the corner of the landing gear door and directs a jet across the windside surface. These jet interactions, in and of themselves, were not sufficiently large to explain observed aerodynamic behavior.

Gnoffo, Peter A.