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1. AGEL: Is the Conflict Real? Investigating Galaxy Evolution Models Using Strong Lensing at 0.3 < z < 0.9

   https://doi.org/10.3847/1538-4357/ad4ce3  

   Sahu, Nandini; Tran, Kim-Vy; Suyu, Sherry_H; Shajib, Anowar_J; Ertl, Sebastian; Kacprzak, Glenn_G; Glazebrook, Karl; Jones, Tucker; G_C, Keerthi_Vasan; Barone, Tania_M; et al (July 2024, The Astrophysical Journal)

   Abstract Observed evolution of the total mass distribution with redshift is crucial to testing galaxy evolution theories. To measure the total mass distribution, strong gravitational lenses complement the resolved dynamical observations that are currently limited toz≲ 0.5. Here we present the lens models for a pilot sample of seven galaxy-scale lenses from theASTRO3DGalaxy Evolution with Lenses (AGEL) survey. TheAGELlenses, modeled using HST/WFC3-F140W images with Gravitational Lens Efficient Explorer (GLEE) software, have deflector redshifts in the range 0.3 <z_defl< 0.9. Assuming a power-law density profile with slopeγ, we measure the total density profile for the deflector galaxies via lens modeling. We also measure the stellar velocity dispersions (σ_obs) for four lenses and obtainσ_obsfromSDSS-BOSSfor the remaining lenses to test our lens models by comparing observed and model-predicted velocity dispersions. For the sevenAGELlenses, we measure an average density profile slope of −1.95 ± 0.09 and aγ–zrelation that does not evolve with redshift atz< 1. Although our result is consistent with some observations and simulations, it differs from other studies atz< 1 that suggest theγ–zrelation evolves with redshift. The apparent conflicts among observations and simulations may be due to a combination of (1) systematics in the lensing and dynamical modeling; (2) challenges in comparing observations with simulations; and (3) assuming a simple power law for the total mass distribution. By providing more lenses atz_defl> 0.5, theAGELsurvey will provide stronger constraints on whether the mass profiles evolve with redshift as predicted by current theoretical models. 

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2. Toward Ubiquitous Interaction-Attentive and Extreme-Aware Crowd Activity Level Prediction

   https://doi.org/10.1145/3682063  

   Huang, Huiqun; Yang, Xi; He, Suining; Tabatabaie, Mahan (July 2024, ACM Transactions on Intelligent Systems and Technology)

   Accurate prediction of citywide crowd activity levels (CALs),i.e., the numbers of participants of citywide crowd activities under different venue categories at certain time and locations, is essential for the city management, the personal service applications, and the entrepreneurs in commercial strategic planning. Existing studies have not thoroughly taken into account the complex spatial and temporal interactions among different categories of CALs and their extreme occurrences, leading to lowered adaptivity and accuracy of their models. To address above concerns, we have proposedIE-CALP, a novel spatio-temporalInteractive attention-based andExtreme-aware model forCrowdActivityLevelPrediction. The tasks ofIE-CALPconsist of(a)forecasting the spatial distributions of various CALs at different city regions (spatial CALs), and(b)predicting the number of participants per category of the CALs (categorical CALs). To realize above, we have designed a novel spatial CAL-POI interaction-attentive learning component inIE-CALPto model the spatial interactions across different CAL categories, as well as those among the spatial urban regions and CALs. In addition,IE-CALPincorporate the multi-level trends (e.g., daily and weekly levels of temporal granularity) of CALs through a multi-level temporal feature learning component. Furthermore, to enhance the model adaptivity to extreme CALs (e.g., during extreme urban events or weather conditions), we further take into account theextreme value theoryand model the impacts of historical CALs upon the occurrences of extreme CALs. Extensive experiments upon a total of 738,715 CAL records and 246,660 POIs in New York City (NYC), Los Angeles (LA), and Tokyo have further validated the accuracy, adaptivity, and effectiveness ofIE-CALP’s interaction-attentive and extreme-aware CAL predictions. 

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3. Modeling Dense Star Clusters in the Milky Way and beyond with the Cluster Monte Carlo Code

   https://doi.org/10.3847/1538-4365/ac2edf  

   Rodriguez, Carl L.; Weatherford, Newlin C.; Coughlin, Scott C.; Amaro-Seoane, Pau; Breivik, Katelyn; Chatterjee, Sourav; Fragione, Giacomo; Kıroğlu, Fulya; Kremer, Kyle; Rui, Nicholas Z.; et al (January 2022, The Astrophysical Journal Supplement Series)

   Abstract We describe the public release of the Cluster Monte Carlo (CMC) code, a parallel, star-by-starN-body code for modeling dense star clusters.CMCtreats collisional stellar dynamics using Hénon’s method, where the cumulative effect of many two-body encounters is statistically reproduced as a single effective encounter between nearest-neighbor particles on a relaxation timescale. The star-by-star approach allows for the inclusion of additional physics, including strong gravitational three- and four-body encounters, two-body tidal and gravitational-wave captures, mass loss in arbitrary galactic tidal fields, and stellar evolution for both single and binary stars. The public release ofCMCis pinned directly to theCOSMICpopulation synthesis code, allowing dynamical star cluster simulations and population synthesis studies to be performed using identical assumptions about the stellar physics and initial conditions. As a demonstration, we present two examples of star cluster modeling: first, we perform the largest (N= 10⁸) star-by-starN-body simulation of a Plummer sphere evolving to core collapse, reproducing the expected self-similar density profile over more than 15 orders of magnitude; second, we generate realistic models for typical globular clusters, and we show that their dynamical evolution can produce significant numbers of black hole mergers with masses greater than those produced from isolated binary evolution (such as GW190521, a recently reported merger with component masses in the pulsational pair-instability mass gap). 

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4. A Fast Algorithm for Aperiodic Linear Stencil Computation using Fast Fourier Transforms

   https://doi.org/10.1145/3606338  

   Ahmad, Zafar; Chowdhury, Rezaul; Das, Rathish; Ganapathi, Pramod; Gregory, Aaron; Zhu, Yimin (December 2023, ACM Transactions on Parallel Computing)

   Stencil computations are widely used to simulate the change of state of physical systems across a multidimensional grid over multiple timesteps. The state-of-the-art techniques in this area fall into three groups: cache-aware tiled looping algorithms, cache-oblivious divide-and-conquer trapezoidal algorithms, and Krylov subspace methods. In this article, we present two efficient parallel algorithms for performing linear stencil computations. Current direct solvers in this domain are computationally inefficient, and Krylov methods require manual labor and mathematical training. We solve these problems for linear stencils by using discrete Fourier transforms preconditioning on a Krylov method to achieve a direct solver that is both fast and general. Indeed, while all currently available algorithms for solving general linear stencils perform Θ(NT) work, whereNis the size of the spatial grid andTis the number of timesteps, our algorithms performo(NT) work. To the best of our knowledge, we give the first algorithms that use fast Fourier transforms to compute final grid data by evolving the initial data for many timesteps at once. Our algorithms handle both periodic and aperiodic boundary conditions and achieve polynomially better performance bounds (i.e., computational complexity and parallel runtime) than all other existing solutions. Initial experimental results show that implementations of our algorithms that evolve grids of roughly 10⁷cells for around 10⁵timesteps run orders of magnitude faster than state-of-the-art implementations for periodic stencil problems, and 1.3× to 8.5× faster for aperiodic stencil problems. Code Repository:https://github.com/TEAlab/FFTStencils 

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5. Primordial Black Hole Dark Matter Simulations Using PopSyCLE

   https://doi.org/10.3847/1538-4357/ad3df0  

   Pruett, Kerianne; Dawson, William; Medford, Michael S; Lu, Jessica R; Lam, Casey; Perkins, Scott; McGill, Peter; Golovich, Nathan; Chapline, George (July 2024, The Astrophysical Journal)

   Abstract Primordial black holes (PBHs), theorized to have originated in the early Universe, are speculated to be a viable form of dark matter. If they exist, they should be detectable through photometric and astrometric signals resulting from gravitational microlensing of stars in the Milky Way. Population Synthesis for Compact-object Lensing Events, orPopSyCLE, is a simulation code that enables users to simulate microlensing surveys, and is the first of its kind to include both photometric and astrometric microlensing effects, which are important for potential PBH detection and characterization. To estimate the number of observable PBH microlensing events, we modifyPopSyCLEto include a dark matter halo consisting of PBHs. We detail our PBH population model, and demonstrate ourPopSyCLE+ PBH results through simulations of the Optical Gravitational Lensing Experiment-IV (OGLE-IV) and Nancy Grace Roman Space Telescope (Roman) microlensing surveys. We provide a proof-of-concept analysis for adding PBHs intoPopSyCLE, and thus include many simplifying assumptions, such asf_DM, the fraction of dark matter composed of PBHs, and ${\overline{m}}_{\mathrm{PBH}}$, mean PBH mass. Assuming ${\overline{m}}_{\mathrm{PBH}}=30$M_⊙, we find ∼3.6f_DMtimes as many PBH microlensing events than stellar evolved black hole events, a PBH average peak Einstein crossing time of ∼91.5 days, estimate on order of 10²f_DMPBH events within the 8 yr OGLE-IV results, and estimate Roman to detect ∼1000f_DMPBH microlensing events throughout its planned microlensing survey. 

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