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At least 1,531 records · Page 85

Exploring J/ψ Production Mechanism at the Future Electron-Ion Collider

We propose to use transverse momentum p T distribution of J/ψ production at the future Electron Ion Collider (EIC) to explore the production mechanism of heavy quarkonia in high energy collisions. We apply QCD and QED collinear factorization to the production of a $c\bar{c}$ pair at high p T , and non-relativistic QCD factorization to the hadronization of the pair to a J/ψ. We evaluate J/ψ p T -distribution at both leading and next-to-leading order in strong coupling, and show that production rates for various color-spin channels of a $c\bar{c}$ pair in electron-hadron collisions are very different from that in hadron-hadron collisions, which provides a strong discriminative power to determine various transition rates for the pair to become a J/ψ. We predict that the J/ψ produced in electron-hadron collisions is likely unpolarized, and the production is an ideal probe for gluon distribution of colliding hadron (or nucleus). We find that the J/ψ production is dominated by the color-octet channel, providing an excellent probe to explore the gluon medium in large nuclei at the EIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Primordial Inflation Explorer (PIXIE): a nulling polarimeter for cosmic microwave background observations

The Primordial Inflation Explorer (PIXIE) is a concept for an Explorer-class mission to measure the gravity-wave signature of primordial inflation through its distinctive imprint on the linear polarization of the cosmic microwave background. The instrument consists of a polarizing Michelson interferometer configured as a nulling polarimeter to measure the difference spectrum between orthogonal linear polarizations from two co-aligned beams. Either input can view the sky or a temperature-controlled absolute reference blackbody calibrator. Rhe proposed instrument can map the absolute intensity and linear polarization (Stokes I, Q, and U parameters) over the full sky in 400 spectral channels spanning 2.5 decades in frequency from 30 GHz to 6 THz (1 cm to 50 μm wavelength). Multi-moded optics provide background-limited sensitivity using only 4 detectors, while the highly symmetric design and multiple signal modulations provide robust rejection of potential systematic errors. The principal science goal is the detection and characterization of linear polarization from an inflationary epoch in the early universe, with tensor-to-scalar ratio r < 10{sup −3} at 5 standard deviations. The rich PIXIE data set can also constrain physical processes ranging from Big Bang cosmology to the nature of the first stars to physical conditions within the interstellar medium of the Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring redshift-space distortions in large-scale structure

We explore and compare different ways large-scale structure observables in redshift-space and real space can be connected. These include direct computation in Lagrangian space, moment expansions and two formulations of the streaming model. Here we derive for the first time a Fourier space version of the streaming model, which yields an algebraic relation between the real- and redshift-space power spectra which can be compared to earlier, phenomenological models. By considering the redshift-space 2-point function in both configuration and Fourier space, we show how to generalize the Gaussian streaming model to higher orders in a systematic and computationally tractable way. We present a closed-form solution to the Zeldovich power spectrum in redshift space and use this as a framework for exploring convergence properties of different expansion approaches. While we use the Zeldovich approximation to illustrate these results, much of the formalism and many of the relations we derive hold beyond perturbation theory, and could be used with ingredients measured from N-body simulations or in other areas requiring decomposition of Cartesian tensors times plane waves. Lastly, we finish with a discussion of the redshift-space bispectrum, bias and stochasticity and terms in Lagrangian perturbation theory up to 1-loop order.

79 ASTRONOMY AND ASTROPHYSICS↗

The large scale polarization explorer (LSPE) for CMB measurements: performance forecast

The measurement of the polarization of the Cosmic Microwave Background (CMB) radiation is one of the current frontiers in cosmology. In particular, the detection of the divergence-free component of the polarization field, the B-mode component, reveals the presence of gravitational waves in the early Universe. The detection of such component is at the moment the most promising technique to probe the inflationary theory describing the very early evolution of the Universe. The measurement of the polarization of the Cosmic Microwave Background (CMB) radiation is one of the current frontiers in cosmology. In particular, the detection of the primordial divergence-free component of the polarization field, the B-mode, could reveal the presence of gravitational waves in the early Universe. The detection of such a component is at the moment the most promising technique to probe the inflationary theory describing the very early evolution of the Universe. We present the updated performance forecast of the Large Scale Polarization Explorer (LSPE), a program dedicated to the measurement of the CMB polarization. LSPE is composed of two instruments: LSPE-Strip, a radiometer-based telescope on the ground in Tenerife-Teide observatory, and LSPE-SWIPE (Short-Wavelength Instrument for the Polarization Explorer) a bolometer-based instrument designed to fly on a winter arctic stratospheric long-duration balloon. The program is among the few dedicated to observation of the Northern Hemisphere, while most of the international effort is focused into ground-based observation in the Southern Hemisphere. Measurements are currently scheduled in Winter 2022/23 for LSPE-SWIPE, with a flight duration up to 15 days, and in Summer 2022 with two years observations for LSPE-Strip. In this work, we describe the main features of the two instruments, identifying the most critical aspects of the design, in terms of impact on the performance forecast. We estimate the expected sensitivity of each instrument and propagate their combined observing power to the sensitivity to cosmological parameters, including the effect of scanning strategy, component separation, residual foregrounds and partial sky coverage. We also set requirements on the control of the most critical systematic effects and describe techniques to mitigate their impact. LSPE will reach a sensitivity in tensor-to-scalar ratio of σr < 0.01, set an upper limit r < 0.015 at 95% confidence level, and improve constraints on other cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring the effect of ELM and code-coupling frequencies on plasma and material modeling of dynamic recycling in divertors

Abstract Integrated modeling of plasma-surface interactions provides a comprehensive and self-consistent description of the system, moving the field closer to developing predictive and design capabilities for plasma facing components. One such workflow, including descriptions for the scrape-off-layer plasma, ion-surface interactions and the sub-surface evolution, was previously used to address steady-state scenarios and has recently been extended to incorporate time-dependence and two-way information flow. The new model can address dynamic recycling in transient scenarios, such as the application presented in this paper: the evolution of W samples pre-damaged by helium and exposed to ELMy H-mode plasmas in the DIII-D DiMES. A first set of simulations explored the effect of ELM frequency. This study was discussed in detail in this conference’s proceedings and is summarized here. The 2nd set of simulations, which is the focus of this paper, explores the effect of code-coupling frequency. These simulations include initial SOLPS solutions converged to the inter-ELM state, ion impact energy ( E in ) and angles ( A in ) calculated by hPIC2, and an improved heat transfer description in Xolotl. The model predicts increases in particle fluxes and decreases in heat fluxes by 10%–20% with the coupling time-step. Compared with the first set of simulations, the less shallow impact angle leads to smaller reflection rates and significant D implantation. The higher fraction of implanted flux (and deeper), in particular during ELMs, increases the accumulated D content in the W near-surface region. Future expansion of the workflow includes coupling to hPIC2 and GITR to ensure accurate descriptions of E in and A in , and W impurity transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring Two Approaches for an End-to-End Scientific Analysis Workflow

The advance of the scientific discovery process is accomplished by the integration of independently-developed programs run on disparate computing facilities into coherent workflows usable by scientists who are not experts in computing. For such advancement, we need a system which scientists can use to formulate analysis workflows, to integrate new components to these workflows, and to execute different components on resources that are best suited to run those components. In addition, we need to monitor the status of the workflow as components get scheduled and executed, and to access the intermediate and final output for visual exploration and analysis. Finally, it is important for scientists to be able to share their workflows with collaborators. Moreover we have explored two approaches for such an analysis framework for the Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC), the first one is based on the use and extension of Galaxy, a web-based portal for biomedical research, and the second one is based on a programming language, Python. In our paper, we present a brief description of the two approaches, describe the kinds of extensions to the Galaxy system we have found necessary in order to support the wide variety of scientific analysis in the cosmology community, and discuss how similar efforts might be of benefit to the HEP community.

97 MATHEMATICS AND COMPUTING↗

Exploring the environmental drivers of human blastomycosis cases in the Midwestern United States

Blastomycosis is a fungal infection endemic to the eastern United States (US) and Canada caused by the inhalation of the fungi Blastomyces spp. Currently, the environmental drivers of disease dynamics are poorly understood. The goal of our work was to explore what environmental conditions are associated with the annual presence of blastomycosis cases, and therefore are potentially explanatory of the ecological niche of Blastomyces. We examined the relationships between reported cases of blastomycosis in three Midwestern US states (Michigan, Minnesota, and Wisconsin) from 2007–2017 in relation to eleven hypothesized environmental conditions, including climate, stream and soil mineral content, and land cover variables. Then, we fit logistic regression models to explore the relationships between the environmental variables and yearly blastomycosis case occurrence. Mean soil moisture, stream sediment mercury content, percent of water within the county, and woody wetlands land cover were all positively associated with the presence of annual cases, with woody wetlands having the most consistent signal across the three states. We also found significant differences in the likelihood of case presence between US states that were not explained by the variables in our model, suggesting state-level differences in case reporting and disease awareness. Our results provide a perspective on potential biological hypotheses to further test regarding environmental controls on the life cycle and ecological niche of Blastomyces.

54 ENVIRONMENTAL SCIENCES↗

A unified exploration of the chronology of the Galaxy

The Milky Way has distinct structural stellar components linked to its formation and subsequent evolution, but disentangling them is non-trivial. With the recent availability of high-quality data for a large numbers of stars in the Milky Way, it is a natural next step for research in the evolution of the Galaxy to perform automated explorations with unsupervised methods of the structures hidden in the combination of large-scale spectroscopic, astrometric, and asteroseismic data sets. We determine precise stellar properties for 21 076 red giants, mainly spanning 2–15 kpc in Galactocentric radii, making it the largest sample of red giants with measured asteroseismic ages available to date. We explore the nature of different stellar structures in the Galactic disc by using Gaussian mixture models as an unsupervised clustering method to find substructure in the combined chemical, kinematic, and age subspace. The best-fitting mixture model yields four distinct physical Galactic components in the stellar disc: the thin disc, the kinematically heated thin disc, the thick disc, and the stellar halo. We find hints of an age asymmetry between the Northern and Southern hemisphere, and we measure the vertical and radial age gradient of the Galactic disc using the asteroseismic ages extended to further distances than previous studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring the origin of the distance bimodality of stars in the periphery of the Small Magellanic Cloud with APOGEE and Gaia

ABSTRACT The Magellanic Cloud system represents a unique laboratory for study of both interacting dwarf galaxies and the ongoing process of the formation of the Milky Way and its halo. We focus on one aspect of this complex, three-body interaction – the dynamical perturbation of the Small Magellanic Cloud (SMC) by the Large Magellanic Cloud (LMC), and specifically potential tidal effects on the SMC’s eastern side. Using Gaia astrometry and the precise radial velocities (RVs) and multielement chemical abundances from Apache Point Observatory Galactic Evolution Experiment (APOGEE-2) Data Release 17, we explore the well-known distance bimodality on the eastern side of the SMC. Through estimated stellar distances, proper motions, and RVs, we characterize the kinematics of the two populations in the bimodality and compare their properties with those of SMC populations elsewhere. Moreover, while all regions explored by APOGEE seem to show a single chemical enrichment history, the metallicity distribution function (MDF), of the ‘far’ stars on the eastern periphery of the SMC is found to resemble that for the more metal-poor fields of the western periphery, whereas the MDF for the ‘near’ stars on the eastern periphery resembles that for stars in the SMC Centre. The closer eastern periphery stars also show RVs (corrected for SMC rotation and bulk motion) that are, on average, approaching us relative to all other SMC populations sampled. We interpret these trends as evidence that the near stars on the eastern side of the SMC represent material pulled out of the central SMC as part of its tidal interaction with the LMC.

Almeida, Andres (ORCID:0009000007332479)↗

Extremes of the jet–accretion power relation of blazars, as explored by NuSTAR

Hard X-ray observations are crucial to study the non-thermal jet emission from high-redshift, powerful blazars. We observed two bright z > 2 flat spectrum radio quasars (FSRQs) in hard X-rays to explore the details of their relativistic jets and their possible variability. S5 0014+81 (at z = 3.366) and B0222+185 (at z=2.690) have been observed twice by the Nuclear Spectroscopic Telescope Array (NuSTAR) simultaneously with Swift /XRT, showing different variability behaviors. We found that NuSTAR is instrumental to explore the variability of powerful high-redshift blazars, even when no gamma-ray emission is detected. The two sources have proven to have respectively the most luminous accretion disk and the most powerful jet among known blazars. Furthermore, thanks to these properties, they are located at the extreme end of the jet-accretion disk relation previously found for gamma-ray detected blazars, to which they are consistent.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The interplay between chromosome stability and cell cycle control explored through gene–gene interaction and computational simulation

Chromosome stability models are usually qualitative models derived from molecular-genetic mechanisms for DNA repair, DNA synthesis, and cell division. While qualitative models are informative, they are also challenging to reformulate as precise quantitative models. In this report we explore how (A) laboratory experiments, (B) quantitative simulation, and (C) seriation algorithms can inform models of chromosome stability. Laboratory experiments were used to identify 19 genes that when over-expressed cause chromosome instability in the yeast Saccharomyces cerevisiae . To better understand the molecular mechanisms by which these genes act, we explored their genetic interactions with 18 deletion mutations known to cause chromosome instability. Quantitative simulations based on a mathematical model of the cell cycle were used to predict the consequences of several genetic interactions. These simulations lead us to suspect that the chromosome instability genes cause cell-cycle perturbations. Cell-cycle involvement was confirmed using a seriation algorithm, which was used to analyze the genetic interaction matrix to reveal an underlying cyclical pattern. The seriation algorithm searched over 10 14 possible arrangements of rows and columns to find one optimal arrangement, which correctly reflects events during cell cycle phases. To conclude, we illustrate how the molecular mechanisms behind these cell cycle events are consistent with established molecular interaction maps.

Biochemistry & Molecular Biology↗

Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms

Here, this study investigates the thermal properties of the repulsive Fermi-Hubbard model with chemical potential using variational quantum algorithms, crucial in comprehending particle behaviour within lattices at heightened temperatures in condensed matter systems. Conventional computational methods encounter challenges, especially in managing chemical potential, prompting exploration into Hamiltonian approaches. Despite the promise of quantum algorithms, their efficacy is hampered by coherence limitations when simulating extended imaginary time evolution sequences. To overcome these constraints, this research focuses on optimizing variational quantum algorithms to probe the thermal properties of the Fermi-Hubbard model. Physics-inspired circuit designs are tailored to alleviate coherence constraints, facilitating a more comprehensive exploration of materials at elevated temperatures. Our study demonstrates the potential of variational algorithms in simulating the thermal properties of the Fermi-Hubbard model while acknowledging limitations stemming from error sources in quantum devices and encountering barren plateaus.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring origins for correlations between flow harmonics and transverse momentum in small collision systems

High statistics data sets from experiments at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC) with small and large collision species have enabled a wealth of new flow measurements, including the event-by-event correlation between observables. One exciting such observable $ρ(v^2_n, [p_T])$ gauges the correlation between the mean transverse momentum of particles in an event and the various flow coefficients (v n ) in the same event [P. Bozek, Phys. Rev. C 93, 044908 (2016)]. Recently it has been proposed that very low multiplicity events may be sensitive to initial-state glasma correlations [G. Giacalone, B. Schenke, and C. Shen, Phys. Rev. Lett. 125, 192301 (2020)] rather than flow-related dynamics. We find utilizing the ip-jazma framework that the color domain explanation for the glasma results are incomplete. We then explore predictions from pythia8, and the version for including nuclear collisions called pythia-angantyr, which have only nonflow correlations, and from the ampt model which has both nonflow and flow-type correlations. We find that pythia-angantyr has nonflow contributions to $ρ(v^2_n, [p_T])$ in p + O, p + Pb, and O + O collisions that are positive at low multiplicity and comparable to the glasma correlations. It is striking that in pythia8 in p + p collisions there is actually a sign change from positive to negative $ρ(v^2_n, [p_T])$ as a function of multiplicity. The ampt results match the experimental data general trends in Pb+Pb collisions at the LHC, except at low multiplicity where ampt has the opposite sign. In p + Pb collisions, ampt has the opposite sign from experimental data and we explore this within the context of parton geometry. Predictions for p + O, O + O, and Xe + Xe are also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Graph reinforcement learning for exploring model spaces beyond the standard model

We present a methodology for performing scans of beyond the standard model (BSM) parameter spaces with reinforcement learning. We identify a novel procedure using graph neural networks that is capable of exploring spaces of models without the user specifying a fixed particle content, allowing broad classes of BSM models to be explored—in theory, the technique is applicable to nearly any model space with a prespecified gauge group. We provide a generic procedure by which a suitable graph grammar can be developed for any BSM model that features user-specified symmetry groups and a finite number of different possible particle species, the use of which is applicable to a variety of machine learning tasks over the actions of BSM theories beyond our particular reinforcement learning use case. As a proof of concept, we construct the graph grammar for theories with vectorlike leptons that may or may not be charged under a dark U ( 1 ) group, inspired by portal matter extensions of the sub-GeV vector portal/kinetic mixing simplified dark matter models. We then use this graph grammar to create a reinforcement learning environment tasked with creating models with these vectorlike leptons that are consistent with a list of a variety of precision observables. The reinforcement learning agent succeeds in developing models that can address the observed muon anomalous magnetic moment discrepancy while remaining consistent with flavor violation and electroweak precision observables, including both constructions that have previously been studied as well as new models that have not, to our knowledge, previously been identified. By inspecting the resulting ensembles of models that the agent produces and experimenting with different configurations for our reinforcement learning environment and graph grammar, we also infer various lessons about the development of these environments that can be transferable to reinforcement learning scans of more complicated model spaces and comment on future directions for the development of this technique into a more mature tool. Published by the American Physical Society 2025

Wojcik, George N.↗

Crystallographic map: A general lattice and basis formalism enabling efficient and discretized exploration of crystallographic phase space

Three-dimensional lattices are fundamental to solid-state physics. The description of a lattice with an atomic basis constitutes the necessary information to predict solid phase properties and evolution. Here, we present an algorithm for systematically exploring crystallographic phase space. Further, coupled with ab initio techniques, such as density functional theory, this algorithm offers an approach for exploring and tuning materials behavior, with a broad range of potential applications: particularly martensitic phase transformations and materials stability.

36 MATERIALS SCIENCE↗

NeuralCubes: Deep Representations for Visual Data Exploration

Visual exploration of large multi-dimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are some of the most promising approaches. However, these techniques usually require a large memory footprint for large datasets. To tackle this problem, we present NeuralCubes: neural networks that predict results for aggregate queries, similar to data cubes. NeuralCubes learns a function that takes as input a given query, for instance, a geographic region and temporal interval, and outputs the result of the query. The learned function serves as a real-time, low-memory approximator for aggregation queries. Our models are small enough to be sent to the client side (e.g. the web browser for a web-based application) for evaluation, enabling data exploration of large datasets without database/network connection. Here, we demonstrate the effectiveness of NeuralCubes through extensive experiments on a variety of datasets and discuss how NeuralCubes opens up opportunities for new types of visualization and interaction.

97 MATHEMATICS AND COMPUTING↗

Blending Machine Learning and Interaction Design in Audio Explorer

The results of machine learning models can often be difficult to interpret, especially for domain experts. Audio Explorer, the winning entry of the 2018 VAST Challenge, is an interactive data exploration tool that effectively communicates machine learning results, using coordinated geospatial, temporal, and auditory visualizations to promote information discovery.

Visual analytics, VAST Challenge↗

Interactive Streamline Exploration and Manipulation Using Deformation

Occlusion presents a major challenge in visualizing three-dimensional flow fields with streamlines. Displaying too many streamlines at once makes it difficult to locate interesting regions, but displaying too few streamlines risks missing important features. A more ideal streamline exploration model is to allow the viewer to freely move across the field that has been populated with interesting streamlines and pull away the streamlines that cause occlusion so that the viewer can inspect the hidden ones in detail. In this paper, we present a streamline deformation algorithm that supports such user-driven interaction with three-dimensional flow fields. We define a view-dependent focus+context technique that moves the streamlines occluding the focus area using a novel displacement model. To preserve the context surrounding the user-chosen focus area, we propose two shape models to define the transition zone for the surrounding streamlines, and the displacement of the contextual streamlines is solved interactively with a goal of preserving their shapes as much as possible. Based on our deformation model, we design an interactive streamline exploration tool using a lens metaphor. Our system runs interactively so that users can move their focus and examine the flow field freely.

flow visualization, focus+context, streamline, def↗