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1. Parallelized domain decomposition for multi-dimensional Lagrangian random walk mass-transfer particle tracking schemes

   https://doi.org/10.5194/gmd-16-833-2023  

   Schauer, Lucas; Schmidt, Michael J.; Engdahl, Nicholas B.; Pankavich, Stephen D.; Benson, David A.; Bolster, Diogo (January 2023, Geoscientific Model Development)

   Abstract. Lagrangian particle tracking schemes allow a wide range of flow and transport processes to be simulated accurately, but a major challenge is numerically implementing the inter-particle interactions in an efficient manner. This article develops a multi-dimensional, parallelized domain decomposition (DDC) strategy for mass-transfer particle tracking (MTPT) methods in which particles exchange mass dynamically. We show that this can be efficiently parallelized by employing large numbers of CPU cores to accelerate run times. In order to validate the approach and our theoretical predictions we focus our efforts on a well-known benchmark problem with pure diffusion, where analytical solutions in any number of dimensions are well established. In this work, we investigate different procedures for “tiling” the domain in two and three dimensions (2-D and 3-D), as this type of formal DDC construction is currently limited to 1-D. An optimal tiling is prescribed based on physical problem parameters and the number of available CPU cores, as each tiling provides distinct results in both accuracy and run time. We further extend the most efficient technique to 3-D for comparison, leading to an analytical discussion of the effect of dimensionality on strategies for implementing DDC schemes. Increasing computational resources (cores) within the DDC method produces a trade-off between inter-node communication and on-node work.For an optimally subdivided diffusion problem, the 2-D parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to around 2700 cores, reducing a 5 h simulation to 8 s, while the 3-D algorithm maintains appreciable speedup up to 1700 cores. 

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2. Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations.

   https://doi.org/10.1007/978-3-031-20047-2_13  

   Wen, S.; Wang, H.; Metaxas, D. (January 2022, Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science)

   Avidan, S.; Brostow, G.; Cissé, M.; Farinella, G.M.; Hassner, T. (Ed.)

   Wen, S., Wang, H., Metaxas, D. (2022). Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13682. Springer, Cham. https://doi.org/10.1007/978-3-031-20047-2_13 Multi-agent trajectory forecasting has recently attracted a lot of attention due to its widespread applications including autonomous driving. Most previous methods use RNNs or Transformers to model agent dynamics in the temporal dimension and social pooling or GNNs to model interactions with other agents; these approaches usually fail to learn the underlying continuous temporal dynamics and agent interactions explicitly. To address these problems, we propose Social ODE which explicitly models temporal agent dynamics and agent interactions. Our approach leverages Neural ODEs to model continuous temporal dynamics, and incorporates distance, interaction intensity, and aggressiveness estimation into agent interaction modeling in latent space. We show in extensive experiments that our Social ODE approach compares favorably with state-of-the-art, and more importantly, can successfully avoid sudden obstacles and effectively control the motion of the agent, while previous methods often fail in such cases. 

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3. A compendium of distances to molecular clouds in the Star Formation Handbook

   https://doi.org/10.1051/0004-6361/201936145  

   Zucker, Catherine; Speagle, Joshua S.; Schlafly, Edward F.; Green, Gregory M.; Finkbeiner, Douglas P.; Goodman, Alyssa; Alves, João (January 2020, Astronomy & Astrophysics)

   Accurate distances to local molecular clouds are critical for understanding the star and planet formation process, yet distance measurements are often obtained inhomogeneously on a cloud-by-cloud basis. We have recently developed a method that combines stellar photometric data with Gaia DR2 parallax measurements in a Bayesian framework to infer the distances of nearby dust clouds to a typical accuracy of ∼5%. After refining the technique to target lower latitudes and incorporating deep optical data from DECam in the southern Galactic plane, we have derived a catalog of distances to molecular clouds in Reipurth (2008, Star Formation Handbook, Vols. I and II) which contains a large fraction of the molecular material in the solar neighborhood. Comparison with distances derived from maser parallax measurements towards the same clouds shows our method produces consistent distances with ≲10% scatter for clouds across our entire distance spectrum (150 pc−2.5 kpc). We hope this catalog of homogeneous distances will serve as a baseline for future work. 

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4. The Galactic bulge exploration: IV. RR Lyrae stars as tracers of the Galactic bar: 3D and 5D analysis and extinction variation

   https://doi.org/10.1051/0004-6361/202450620  

   Prudil, Z; Kunder, A; Beraldo_e_Silva, L; Gough-Kelly, S; Rejkuba, M; Anderson, S R; Debattista, V P; Gerhard, O; Rich, R M; Nataf, D M; et al (March 2025, Astronomy & Astrophysics)

   RR Lyrae stars toward the Galactic bulge are used to investigate whether this old stellar population traces the Galactic bar. Although the bar is known to dominate the mass in the inner Galaxy, there is no consensus on whether the RR Lyrae star population, which constitutes some of the most ancient stars in the bulge and thus traces the earliest epochs of star formation, contributes to the barred bulge. We create new reddening maps and derive new extinction laws from visual to near-infrared passbands using improved RR Lyrae period-absolute magnitude-metallicity relations, enabling distance estimates for individual bulge RR Lyrae variables. The extinction law is most uniform inR_IKsandR_JKsand the distances to individual RR Lyrae based on these colors are determined with an accuracy of 6 and 4%, respectively. Using only the near-infrared passbands for distance estimation, we infer the distance to the Galactic center equal tod^cen_JKs= 8217 ± 1(stat) ± 528(sys) pc after geometrical correction. We show that variations in the extinction law toward the Galactic bulge can mimic a barred spatial distribution in the bulge RR Lyrae star population in visual passbands. This arises from a gradient in extinction differences along Galactic longitudes and latitudes, which can create the perception of the Galactic bar, particularly when using visual passband-based distances. A barred angle in the RR Lyrae spatial distribution disappears when near-infrared passband-based distances are used, as well as when reddening law variations are incorporated in visual passband-based distances. The prominence of the bar, traced by RR Lyrae stars, depends on their metallicity, with metal-poor RR Lyrae stars ([Fe/H] < −1.0 dex) showing little to no tilt with respect to the bar. Metal-rich ([Fe/H] > −1.0 dex) RR Lyrae stars do show a barred bulge signature in spatial properties derived using near-infrared distances, with an angle ofι= 18 ± 5 deg, consistent with previous bar measurements from the literature. This also hints at a younger age for this RR Lyrae subgroup. The 5D kinematic analysis, primarily based on transverse velocities, indicates a rotational lag in RR Lyrae stars compared to red clump giants. Despite variations in the extinction law, our kinematic conclusions are robust across different distance estimation methods. 

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5. TDCOSMO: VI. Distance measurements in time-delay cosmography under the mass-sheet transformation

   https://doi.org/10.1051/0004-6361/202039895  

   Chen, Geoff C.-F.; Fassnacht, Christopher D.; Suyu, Sherry H.; Yıldırım, Akın; Komatsu, Eiichiro; Luis Bernal, José (August 2021, Astronomy & Astrophysics)

   null (Ed.)

   Time-delay cosmography with gravitationally lensed quasars plays an important role in anchoring the absolute distance scale and hence measuring the Hubble constant, H 0 , independent of traditional distance ladder methodology. A current potential limitation of time-delay distance measurements is the mass-sheet transformation (MST), which leaves the lensed imaging unchanged but changes the distance measurements and the derived value of H 0 . In this work we show that the standard method of addressing the MST in time-delay cosmography, through a combination of high-resolution imaging and the measurement of the stellar velocity dispersion of the lensing galaxy, depends on the assumption that the ratio, D s / D ds , of angular diameter distances to the background quasar and between the lensing galaxy and the quasar can be constrained. This is typically achieved through the assumption of a particular cosmological model. Previous work (TDCOSMO IV) addressed the mass-sheet degeneracy and derived H 0 under the assumption of the ΛCDM model. In this paper we show that the mass-sheet degeneracy can be broken without relying on a specific cosmological model by combining lensing with relative distance indicators such as supernovae Type Ia and baryon acoustic oscillations, which constrain the shape of the expansion history and hence D s / D ds . With this approach, we demonstrate that the mass-sheet degeneracy can be constrained in a cosmological model-independent way. Hence model-independent distance measurements in time-delay cosmography under MSTs can be obtained. 

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