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The baryonic physics shaping galaxy formation and evolution are complex, spanning a vast range of scales and making them challenging to model. Cosmological simulations rely on subgrid models that produce significantly different predictions. Understanding how models of stellar and active galactic nucleus (AGN) feedback affect baryon behavior across different halo masses and redshifts is essential. Using the SIMBA and IllustrisTNG suites from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, we explore the effect of parameters governing the subgrid implementation of stellar and AGN feedback. We find that while IllustrisTNG shows higher cumulative feedback energy across all halos, SIMBA demonstrates a greater spread of baryons, quantified by the closure radius and circumgalactic medium (CGM) gas fraction. This suggests that feedback in SIMBA couples more effectively to baryons and drives them more efficiently within the host halo. There is evidence that the different feedback modes are highly interrelated in these subgrid models. The parameters controlling the stellar feedback efficiency significantly impact AGN feedback, as seen in the suppression of black hole mass growth and delayed activation of AGN feedback to higher-mass halos with increasing stellar feedback efficiency in both simulations. Additionally, the AGN feedback efficiency parameters affect the CGM gas fraction at low halo masses in SIMBA, hinting at complex, nonlinear interactions between the AGN and supernova feedback modes. Overall, we demonstrate that stellar and AGN feedback are intimately interwoven, especially at low redshift, due to subgrid implementation, resulting in halo property effects that might initially seem counterintuitive. 

One of the most surprising gamma-ray burst (GRB) features discovered with theSwiftX-ray telescope (XRT) is a plateau phase in the early X-ray afterglow light curves. These plateaus are observed in the majority of long GRBs, while their incidence in short GRBs (SGRBs) is still uncertain due to their fainter X-ray afterglow luminosity with respect to long GRBs. An accurate estimate of the fraction of SGRBs with plateaus is of utmost relevance given the implications that the plateau may have for our understanding of the jet structure and possibly of the nature of the binary neutron star (BNS) merger remnant. This work presents the results of an extensive data analysis of the largest and most up-to-date sample of SGRBs observed with the XRT, and for which the redshift has been measured. We find a plateau incidence of 18–37% in SGRBs, which is a significantly lower fraction than that measured in long GRBs (> 50%). Although still debated, the plateau phase could be explained as energy injection from the spin-down power of a newly born magnetized neutron star (NS; magnetar). We show that this scenario can nicely reproduce the observed short GRB (SGRBs) plateaus, while at the same time providing a natural explanation for the different plateau fractions between short and long GRBs. In particular, our findings may imply that only a minority of BNS mergers generating SGRBs leave behind a sufficiently stable or long-lived NS to form a plateau. From the probability distribution of the BNS remnant mass, a fraction 18–37% of short GRB plateaus implies a maximum NS mass in the range ∼2.3 − 2.35 M_⊙. 

Most diffuse baryons, including the circumgalactic medium (CGM) surrounding galaxies and the intergalactic medium (IGM) in the cosmic web, remain unmeasured and unconstrained. Fast radio bursts (FRBs) offer an unparalleled method to measure the electron dispersion measures (DMs) of ionized baryons. Their distribution can resolve the missing baryon problem and constrain the history of feedback theorized to impart significant energy to the CGM and IGM. We analyze the Cosmology and Astrophysics with Machine Learning Simulations using three suites, IllustrisTNG, SIMBA, and Astrid, each varying six parameters (two cosmological and four astrophysical feedback), for a total of 183 distinct simulation models. We find significantly different predictions between the fiducial models of the suites owing to their different implementations of feedback. SIMBA exhibits the strongest feedback, leading to the smoothest distribution of baryons and reducing the sight-line-to-sight-line variance in DMs between z = 0 and 1. Astrid has the weakest feedback and the largest variance. We calculate FRB CGM measurements as a function of galaxy impact parameter, with SIMBA showing the weakest DMs due to aggressive active galactic nucleus (AGN) feedback and Astrid the strongest. Within each suite, the largest differences are due to varying AGN feedback. IllustrisTNG shows the most sensitivity to supernova feedback, but this is due to the change in the AGN feedback strengths, demonstrating that black holes, not stars, are most capable of redistributing baryons in the IGM and CGM. We compare our statistics directly to recent observations, paving the way for the use of FRBs to constrain the physics of galaxy formation and evolution. 

Today's robotic laboratories for drones are housed in a large room. At times, they are the size of a warehouse. These spaces are typically equipped with permanent devices to localize the drones, e.g., Vicon Infrared cameras. Significant time is invested to fine-tune the localization apparatus to compute and control the position of the drones. One may use these laboratories to develop a 3D multimedia system with miniature sized drones configured with light sources. As an alternative, this brave new idea paper envisions shrinking these room-sized laboratories to the size of a cube or cuboid that sits on a desk and costs less than 10K dollars. The resulting Dronevision (DV) will be the size of a 1990s Television. In addition to light sources, its Flying Light Specks (FLSs) will be network-enabled drones with storage and processing capability to implement decentralized algorithms. The DV will include a localization technique to expedite development of 3D displays. It will act as a haptic interface for a user to interact with and manipulate the 3D virtual illuminations. It will empower an experimenter to design, implement, test, debug, and maintain software and hardware that realize novel algorithms in the comfort of their office without having to reserve a laboratory. In addition to enhancing productivity, it will improve safety of the experimenter by minimizing the likelihood of accidents. This paper introduces the concept of a DV, the research agenda one may pursue using this device, and our plans to realize one. 

Abstract The existence of a secondary (in addition to compact object mergers) source of heavy element (r-process) nucleosynthesis, the core-collapse of rapidly rotating and highly magnetized massive stars, has been suggested by both simulations and indirect observational evidence. Here, we probe a predicted signature ofr-process enrichment, a late-time (≳40 days post-burst) distinct red color, in observations of gamma-ray burst supernovae (GRB-SNe), which are linked to these massive star progenitors. We present optical to near-IR color measurements of four GRB-SNe atz≲ 0.4, extending out to >500 days post-burst, obtained with the Hubble Space Telescope and large-aperture ground-based telescopes. Comparison of our observations to models indicates that GRBs 030329, 100316D, and 130427A are consistent with both no enrichment and producing 0.01–0.15M_⊙ofr-process material if there is a low amount of mixing between the innerr-process ejecta and outer supernova (SN) layers. GRB 190829A is not consistent with any models withr-process enrichment ≥0.01M_⊙. Taken together the sample of GRB-SNe indicates color diversity at late times. Our derived yields from GRB-SNe may be underestimated due tor-process material hidden in the SN ejecta (potentially due to low mixing fractions) or the limits of current models in measuringr-process mass. We conclude with recommendations for future search strategies to observe and probe the full distribution ofr-process produced by GRB-SNe. 

Abstract The resistance to oxidizing environments exhibited by some M n+1 AX n (MAX) phases stems from the formation of stable and protective oxide layers at high operating temperatures. The MAX phases are hexagonally arranged layered nitrides or carbides with general formula M n +1 AX n , n  = 1, 2, 3, where M is early transition elements, A is A block elements, and X is C/N. Previous attempts to model and assess oxide phase stability in these systems has been limited in scope due to higher computational costs. To address the issue, we developed a machine-learning driven high-throughput framework for the fast assessment of phase stability and oxygen reactivity of 211 chemistry MAX phase M 2 AX. The proposed scheme combines a sure independence screening sparsifying operator-based machine-learning model in combination with grand-canonical linear programming to assess temperature-dependent Gibbs free energies, reaction products, and elemental chemical activity during the oxidation of MAX phases. The thermodynamic stability, and chemical activity of constituent elements of Ti 2 AlC with respect to oxygen were fully assessed to understand the high-temperature oxidation behavior. The predictions are in good agreement with oxidation experiments performed on Ti 2 AlC. We were also able to explain the metastability of Ti 2 SiC, which could not be synthesized experimentally due to higher stability of competing phases. For generality of the proposed approach, we discuss the oxidation mechanism of Cr 2 AlC. The insights of oxidation behavior will enable more efficient design and accelerated discovery of MAX phases with maintained performance in oxidizing environments at high temperatures. 

Double- and single-differential cross sections for inclusive charged-current ${\nu }_{\mu }$-nucleus scattering are reported for the kinematic domain 0 to $2\mathrm{GeV}/c$in three-momentum transfer and 0 to 2 GeV in available energy, at a mean ${\nu }_{\mu }$energy of 1.86 GeV. The measurements are based on an estimated 995,760 ${\nu }_{\mu }$charged-current (CC) interactions in the scintillator medium of the NOvA Near Detector. The subdomain populated by 2-particle-2-hole (2p2h) reactions is identified by the cross section excess relative to predictions for ${\nu }_{\mu }$-nucleus scattering that are constrained by a data control sample. Models for 2-particle-2-hole processes are rated by ${\chi }^2$comparisons of the predicted-versus-measured ${\nu }_{\mu }$CC inclusive cross section over the full phase space and in the restricted subdomain. Shortfalls are observed in neutrino generator predictions obtained using the theory-based València and SuSAv2 2p2h models. Published by the American Physical Society2025