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The United States (US) rail network is a large and crucial element of its infrastructure and economy, with approximately 140,000 miles of track. Extreme temperature events can cause rail damage and increase the risk of derailments, putting lives at risk and causing huge economic damage. High rail temperatures during heatwaves can lead to heat-induced buckling, while freezing temperatures can create cracking. Previous research has investigated the effects of temperature on rail failure and the probability of their failure using various approaches such as finite element analysis, lab experiments, machine learning, and others. However, there is a need for research that investigates the higher-level impact of extreme weather events on the large rail network and its operations. Accordingly, this paper addresses that knowledge gap and proposes a framework to investigate the vulnerability of the rail network using a weather-informed graph-based probability-impact risk assessment. A graph of the US rail network is created and embedded with weather data simulating historic extreme weather events; and a probability-impact risk assessment is conducted based on the probability (i.e. what is the probability of a rail segment to fail), impact (i.e. what is the impact if a rail segment fails), and the combined risk severity. The model can quantify the risk severity on all railroads connecting any two nodes, such as any two major cities, on the US rail network. Results of a case study revealed five high-risk regions. This paper proposes a developed framework to support decision making as related to improving the resilience of existing roads and planning new alternative routes to minimize the impact of extreme weather events and improve rail safety. 

Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial for understanding how large-scale environment influences galaxy evolution. We combine wide-field Lyαimaging from the One-hundred-deg²DECam Imaging in Narrowbands survey with extensive Dark Energy Spectroscopic Instrument and ancillary spectroscopy across the extended COSMOS and XMM Large Scale Structure (LSS) fields (≈14 deg²) to search for massive protoclusters. We confirm six systems atz ≈ 2.4 and ≈ 3.1, including three newly identified structures and three which overlap with previously known structures and/or systems detected using other tracers. We reconstruct their three-dimensional structures, estimate descendant halo masses, and for one structure atz ≈ 3.12, demonstrate that overlapping narrowband filters (NB497 and N501) provide accurate redshift tomography for emission-line galaxies. One protocluster atz ≈ 2.45 overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H ioverdensities traced by Lyαforest absorption. Another atz ≈ 3.12 hosts a massive quiescent galaxy (M_* ≈ 1.2 × 10¹¹M_⊙), suggesting that overdense environments may play a role in accelerating galaxy assembly and quenching. Comparing Lyαemission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when combining 2D and 3D density information, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger atz ≈ 3.1 than atz ≈ 2.4, suggesting possible redshift evolution. 

Abstract We present a new measurement of the Hubble constant,H₀, following the gravitational-wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance ∼40 Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy owing to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group’s properties and NGC 4993’s membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a fivefold increase in galaxies compared to previous observations, with many contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is a part with a halo mass of order ∼10¹³M_⊙. Using peculiar velocity measurements from our fundamental plane galaxy observations, we find $H_0=70.9_{-8.5}^{+6.4}$  km s⁻¹ Mpc⁻¹. In addition, using a peculiar velocity measurement for NGC 4993 from surface brightness fluctuations in Cosmicflows-4, we find $H_0=73.4_{-3.9}^{+3.3}$  km s⁻¹ Mpc⁻¹. We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on theH₀measurement. Our results demonstrate the value of multiplexed spectroscopic observations for probing the local environments of gravitational-wave events used in standard siren measurements. 

The ubiquity and relative ease of discovery make 2 

We present a study of the weak lensing inferred matter profiles ΔΣ(R) of 698 South Pole Telescope (SPT) thermal Sunyaev-Zel’dovich effect (tSZE) selected and MCMF optically confirmed galaxy clusters in the redshift range 0.25 <  z <  0.94 that have associated weak gravitational lensing shear profiles from the Dark Energy Survey (DES). Rescaling these profiles to account for the mass dependent size and the redshift dependent density produces average rescaled matter profiles ΔΣ(R/R_200c)/(ρ_critR_200c) with a lower dispersion than the unscaled ΔΣ(R) versions, indicating a significant degree of self-similarity. Galaxy clusters from hydrodynamical simulations also exhibit matter profiles that suggest a high degree of self-similarity, with RMS variation among the average rescaled matter profiles with redshift and mass falling by a factor of approximately six and 23, respectively, compared to the unscaled average matter profiles. We employed this regularity in a new Bayesian method for weak lensing mass calibration that employs the so-called cluster mass posteriorP(M₂₀₀|ζ̂, λ̂,z), which describes the individual cluster masses given their tSZE (ζ̂) and optical (λ̂,z) observables. This method enables simultaneous constraints on richnessλ-mass and tSZE detection significanceζ-mass relations using average rescaled cluster matter profiles. We validated the method using realistic mock datasets and present observable-mass relation constraints for the SPT×DES sample, where we constrained the amplitude, mass trend, redshift trend, and intrinsic scatter. Our observable-mass relation results are in agreement with the mass calibration derived from the recent cosmological analysis of the SPT×DES data based on a cluster-by-cluster lensing calibration. Our new mass calibration technique offers a higher efficiency when compared to the single cluster calibration technique. We present new validation tests of the observable-mass relation that indicate the underlying power-law form and scatter are adequate to describe the real cluster sample but that also suggest a redshift variation in the intrinsic scatter of theλ-mass relation may offer a better description. In addition, the average rescaled matter profiles offer high signal-to-noise ratio (S/N) constraints on the shape of real cluster matter profiles, which are in good agreement with available hydrodynamical ΛCDM simulations. This high S/N profile contains information about baryon feedback, the collisional nature of dark matter, and potential deviations from general relativity. 

Abstract We measure the projected two-point correlation functions of emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument One-Percent Survey and model their dependence on stellar mass and [OII] luminosity. We select ∼180,000 ELGs with redshifts of 0.8 < z < 1.6, and define 27 samples according to cuts in redshift and both galaxy properties. Following a framework that describes the conditional [OII] luminosity–stellar mass distribution as a function of halo mass, we simultaneously model the clustering measurements of all samples at fixed redshift. Based on the modeling result, most ELGs in our samples are classified as central galaxies, residing in halos of a narrow mass range with a typical median of ∼10^12.2−12.4h⁻¹M_⊙. We observe a weak dependence of clustering amplitude on stellar mass, which is reflected in the model constraints and is likely a consequence of the 0.5 dex measurement uncertainty in the stellar mass estimates. The model shows a trend between galaxy bias and [OII] luminosity at high redshift (1.2 < z < 1.6) that is otherwise absent at lower redshifts.