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At least 1,387 records · Page 77

The Atacama Cosmology Telescope: Mitigating the Impact of Extragalactic Foregrounds for the DR6 Cosmic Microwave Background Lensing Analysis

We investigate the impact and mitigation of extragalactic foregrounds for the cosmic microwave background (CMB) lensing power spectrum analysis of Atacama Cosmology Telescope (ACT) data release 6 (DR6) data. Two independent microwave sky simulations are used to test a range of mitigation strategies. We demonstrate that finding and then subtracting point sources, finding and then subtracting models of clusters, and using a profile bias-hardened lensing estimator together reduce the fractional biases to well below statistical uncertainties, with the inferred lensing amplitude, A lens , biased by less than 0.2σ. We also show that another method where a model for the cosmic infrared background (CIB) contribution is deprojected and high-frequency data from Planck is included has similar performance. Other frequency-cleaned options do not perform as well, either incurring a large noise cost or resulting in biased recovery of the lensing spectrum. In addition to these simulation-based tests, we also present null tests on the ACT DR6 data for sensitivity of our lensing spectrum estimation to differences in foreground levels between the two ACT frequencies used, while nulling the CMB lensing signal. These tests pass whether the nulling is performed at the map or bandpower level. The CIB-deprojected measurement performed on the DR6 data is consistent with our baseline measurement, implying that contamination from the CIB is unlikely to significantly bias the DR6 lensing spectrum. This collection of tests gives confidence that the ACT DR6 lensing measurements and cosmological constraints presented in companion papers to this work are robust to extragalactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗

The NuSTAR extragalactic surveys: the number counts of active galactic nuclei and the resolved fraction of the cosmic X-ray background

We present the 3–8 keV and 8–24 keV number counts of active galactic nuclei (AGNs) identified in the Nuclear Spectroscopic Telescope Array (NuSTAR) extragalactic surveys. NuSTAR has now resolved 33%–39% of the X-ray background in the 8–24 keV band, directly identifying AGNs with obscuring columns up to ∼10{sup 25} cm{sup −2}. In the softer 3–8 keV band the number counts are in general agreement with those measured by XMM-Newton and Chandra over the flux range 5×10{sup −15} ≲ S(3–8 keV)/erg s{sup −1} cm{sup −2} ≲ 10{sup −12} probed by NuSTAR. In the hard 8–24 keV band NuSTAR probes fluxes over the range 2×10{sup −14} ≲ S(8–24 keV)/erg s{sup −1} cm{sup −2} ≲ 10{sup −12}, a factor ∼100 fainter than previous measurements. The 8–24 keV number counts match predictions from AGN population synthesis models, directly confirming the existence of a population of obscured and/or hard X-ray sources inferred from the shape of the integrated cosmic X-ray background. The measured NuSTAR counts lie significantly above simple extrapolation with a Euclidian slope to low flux of the Swift/BAT 15–55 keV number counts measured at higher fluxes (S(15–55 keV) ≳ 10{sup −11} erg s{sup −1} cm{sup −2}), reflecting the evolution of the AGN population between the Swift/BAT local (z<0.1) sample and NuSTAR’s z∼1 sample. CXB synthesis models, which account for AGN evolution, lie above the Swift/BAT measurements, suggesting that they do not fully capture the evolution of obscured AGNs at low redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

Classification and computation of extreme events in turbulent combustion

In the design of practical combustion systems, ensuring safety and reliability is an important requirement. For instance, reliably avoiding lean blowout, flame flashback or inlet unstart is critical for ensuring safe operation. Currently, the science of predicting such events is based on prior experience, limited modeling or diagnostic tools and purely statistical approaches. Even though computational and experimental tools for studying combustion devices have vastly advanced in the last three decades, the analysis of such failure events has not been pursued widely. While the use of data for model development and calibration is being widely accepted, the extension to failure events introduces numerous challenges. In particular, the focus here is on so-called data-poor problems, where the cost of generating data is extremely high and is not easily amenable to existing computational and experimental approaches. Data-poor problems are particularly relevant when related to extreme events (also called anomalous events) that can lead to catastrophic failure of the system. It is argued that transient events that describe such failure can have different causal mechanisms. To develop the scientific inference process, a classification of such problems is used to determine specific modeling paths as well as computational tools needed. Research opportunities in the emerging field of extreme event prediction are highlighted in order to identify critical and immediate needs.

97 MATHEMATICS AND COMPUTING↗

Models for HEU objects in the NDSE IV and III series

A Neutron-Diagnosed Subcritical Experiment (NDSE) proof-of-principle setup exists at area-11 in Nevada. An exquisite set of gamma-ray flux die-away data has been obtained at this facility for a number of highly-enriched uranium (HEU) objects, including objects referred to as IV, IV', IV'' (the object IV series), IIIa, and IIIb (the object III series). These objects are constructed via a set of hemi-spherical concentric HEU shells (known as the Rocky Flats shells), surrounded by a sphere of aluminum (Al), encased in an outer sphere of high-density polyethylene (HDP). The “as built” detailed MCNP-calculated k eff values obtained by Goorley, for the object IV and III series, are listed in Table II. These model calculations contain detailed information about the inner and outer radii and masses of each hemi-shell used to make each of the objects. Objects IV', and IV'' were obtained by replacing inner HEU shells with Al. The low k eff of object IIIa was obtained by substituting a single HEU shell, with an inner radius of ~5 cm, with an Al shell. For object IIIb the substitution was a little further out but only in one hemi-shell. Except for the inner most shell (ball), all HEU shells have a thickness close to 0.333 cm. Previously the k eff of objects IV', IV'', IIIa, and IIIb, were determined from measured gamma ray die-away data via an analysis using a simple modification of the density of the HEU in our simple three layered model (HEU, Al, and HDP) of object IV including the outer safety can. This was done to see the quality of the inference and investigate any limitations associated with not using detailed information about the known perturbations used to make these objects. In this work, we built models (priors) of objects IV', IV'', IIIa, and IIIb that make use of our knowledge about the nature of the perturbations. With these models, instead of adjusting the density of the HEU in our object IV model to match the data from objects IV', IV'', IIIa, and IIIb, as done previously, we will be able to (in future studies) adjust r AL , and r i to infer the k eff of the corresponding objects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The overarching framework of core-collapse supernova explosions as revealed by 3D fornax simulations

We have conducted 19 state-of-the-art 3D core-collapse supernova simulations spanning a broad range of progenitor masses. This is the largest collection of sophisticated 3D supernova simulations ever performed. We have found that while the majority of these models explode, not all do, and that even models in the middle of the available progenitor mass range may be less explodable. This does not mean that those models for which we did not witness explosion would not explode in Nature, but that they are less prone to explosion than others. One consequence is that the ‘compactness’ measure is not a metric for explodability. We find that lower-mass massive star progenitors likely experience lower-energy explosions, while the higher-mass massive stars likely experience higher-energy explosions. Moreover, most 3D explosions have a dominant dipole morphology, have a pinched, wasp-waist structure, and experience simultaneous accretion and explosion. We reproduce the general range of residual neutron-star masses inferred for the galactic neutron-star population. The most massive progenitor models, however, in particular vis à vis explosion energy, need to be continued for longer physical times to asymptote to their final states. We find that while the majority of the inner ejecta have Ye = 0.5, there is a substantial proton-rich tail. This result has important implications for the nucleosynthetic yields as a function of progenitor. Finally, we find that the non-exploding models eventually evolve into compact inner configurations that experience a quasi-periodic spiral SASI mode. We otherwise see little evidence of the SASI in the exploding models.

79 ASTRONOMY AND ASTROPHYSICS↗

(U) An Analytic Examination of Piezoelectric Ejecta Mass Measurements

Ongoing efforts to validate a Richtmyer-Meshkov instability (RMI) based ejecta source model [1, 2, 3] in LANL ASC codes use ejecta areal masses derived from piezoelectric sensor data [4, 5, 6]. However, the standard technique for inferring masses from sensor voltages implicitly assumes instantaneous ejecta creation [7], which is not a feature of the RMI source model. To investigate the impact of this discrepancy, we define separate “areal mass functions” (AMFs) at the source and sensor in terms of typically unknown distribution functions for the ejecta particles, and derive an analytic relationship between them. Then, for the case of single-shock ejection into vacuum, we use the AMFs to compare the analytic (or “true”) accumulated mass at the sensor with the value that would be inferred from piezoelectric voltage measurements. We confirm the inferred mass is correct when creation is instantaneous, and furthermore prove that when creation is not instantaneous, the inferred values will always overestimate the true mass. Finally, we derive an upper bound for the error imposed on a perfect system by the assumption of instantaneous ejecta creation. When applied to shots in the published literature, this bound is frequently less than several percent. Errors exceeding 15% may require velocities or timescales at odds with experimental observations.

47 OTHER INSTRUMENTATION↗

Impact of Varying Dark Energy on Future Large-Scale Structure Studies

The cosmos withholds multiple mysteries such as dark forms of matter and energy that are yet beyond human comprehension. In the standard cosmological model, $\Lambda$CDM, the cosmological constant $\Lambda$ is thought to be responsible for the late accelerated expansion of the Universe. However, recent results from the Dark Energy Spectroscopic Instrument (DESI) suggest the possibility of evolving dark energy, which warrants further exploration. Future surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST) will map the large-scale structure (LSS) with unprecedented precision, giving us valuable statistical information about the cosmos. The goal of this research is to investigate the potential impact of an evolving dark energy scenario on cosmological parameters constrained by LSS probes, as will be mapped by the LSST. For this, we examine the power spectra of lens galaxies, source galaxies, and cross-power spectra between lens galaxies and source galaxies. The combination of these statistics is commonly referred to as '3 $\times$ 2 points'. For this investigation, we created a set of simulations resembling LSST data and used them to perform cosmological parameter inference in two scenarios: one in which the simulated data is based on the fiducial model and another on evolving dark energy. We then examined the degeneracy between the cosmological parameters and checked for potential shifts in the parametric space when the data contains dynamical dark energy but the modeling assumes $\Lambda$CDM. Our findings indicate that mismodeling the dark energy equation of state can significantly impact parameter inference, particularly affecting the total matter density, $\Omega_m$, and the growth of structures, as represented by the $S_8$ parameter. These results highlight the importance of further exploring extensions of the $\Lambda$CDM model in future LSS studies.

Yaman Acharya, A.↗

Accurate field-level weak lensing inference for precision cosmology

We present miko, a catalog-to-cosmology pipeline for general flat-sky field-level inference, which provides access to cosmological information beyond the two-point statistics. In the context of weak lensing, we identify several new field-level analysis systematics (such as aliasing, Fourier mode-coupling, and density-induced shape noise), quantify their impact on cosmological constraints, and correct the biases to a percent level. Next, we find that model misspecification can lead to both absolute bias and incorrect uncertainty quantification for the inferred cosmological parameters in realistic simulations. The Gaussian map prior infers unbiased cosmological parameters, regardless of the true data distribution, but it yields overconfident uncertainties. The log-normal map prior quantifies the uncertainties accurately, although it requires careful calibration of the shift parameters for unbiased cosmological parameters. Here, we demonstrate systematics control down to the 2% level for both models, making them suitable for ongoing weak lensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simultaneous inference of equation of state parameters and unknown data errors with uncertainty quantification via hierarchical Bayesian posterior maximization

Equations of state (EOSs) are a key component in running hydrodynamic simulations as they relate the thermodynamic states for the material. The Davis reactants EOS is commonly used for modeling high explosives (HEs), and the EOS model parameters are calibrated using material specific data. The calibrations are often performed with uncertainty quantification via Bayesian inference to account for uncertainty in the data and generate ensembles of likely parameters. However, there are relatively few HE data sets to use for calibration and many are historical and lack error information. In this work, we simultaneously calibrate the Davis reactants EOS model parameters and unknown data error terms for the high explosive PBX 9501. To quantify the uncertainty in the models and the data, we use a Bayesian framework for the calibration and compute the hierarchical Bayesian posterior distribution with both a posteriori maximization approach and Markov Chain Monte Carlo. In general, we find that, given our assumptions, the two approaches result in similar calibrated parameters, posterior covariance matrices, and insights about the parameters but that the posterior maximization requires far less computational resources.

97 MATHEMATICS AND COMPUTING↗

Structural Control on Downdip Locking Extent of the Himalayan Megathrust

Here, geologic reconstructions of the Main Himalayan Thrust in Nepal show a laterally extensive midcrustal ramp, hypothesized to form the downdip boundary of interseismic locking. Using a recent compilation of interseismic GPS velocities and a simplified model of fault coupling, we estimate the width of coupling across Nepal using a series of two-dimensional transects. We find that the downdip width of fault coupling increases smoothly from 70 to 90 km in eastern Nepal to 100–110 km in central Nepal, then narrows again in western Nepal. The inferred coupling transition is closely aligned with geologic reconstructions of the base of the midcrustal ramp in central and eastern Nepal, but in western Nepal, the data suggest that the location is intermediate between two proposed ramp locations. The result for western Nepal implies either an anomalous coupling transition that occurs along a shallowly dipping portion of the fault or that both ramps may be partially coupled and that a proposed crustal-scale duplexing process may be active during the interseismic period. We also find that the models require a convergence rate of 15.5 ± 2 mm/year throughout Nepal, reducing the geodetic moment accumulation rate by up to 30% compared with earlier models, partially resolving an inferred discrepancy between geodetic and paleoseismic estimates of moment release across the Himalaya.

58 GEOSCIENCES↗

Comprehensive Neural Posterior Estimation for Galaxy-Galaxy Strong Lensing

We present a deep learning model based on neural posterior estimation (NPE) for comprehensive extraction of astrophysical parameters from galaxy-scale strong gravitational lenses. The unprecedentedly large amount of galaxy-scale strong lenses expected in future cosmological surveys (${\cal O}(10^5)$) promises to enable valuable statistical constraints in various studies ranging from galaxy formation to the nature of dark matter, but it also poses a significant challenge for traditional modelling pipelines. To this end, our automated model includes several new, state-of-the-art features and approaches leveraging the framework of simulation-based inference (SBI). We infer a total of 20 parameters describing the mass and light profiles of both lens and source galaxies, using simulated raw multi-band data modelled under noise and observing conditions expected by the Legacy Survey of Space and Time (LSST), with its summary statistics generated by a residual network. We examine the efficacy of multi-band data in extracting nearly 20 model parameters simultaneous from strong lensing images including lens light. Finally, We perform a comprehensive set of diagnostics for SBI models, evaluating the model's prediction accuracy, stability, and uncertainty quantification.

Zhao, Roy J. [Chicago U., KICP]↗

The effects of the small-scale DM power on the cosmological neutral hydrogen (HI) distribution at high redshifts

The particle nature of dark matter remains a mystery. In this paper, we consider two dark matter models—Late Forming Dark Matter (LFDM) and Ultra-Light Axion (ULA) models—where the matter power spectra show novel effects on small scales. The high redshift universe offers a powerful probe of their parameters. In particular, we study two cosmological observables: the neutral hydrogen (HI) redshifted 21-cm signal from the epoch of reionization, and the evolution of the collapsed fraction of HI in the redshift range 2 < z < 5. We model the theoretical predictions of the models using CDM-like N-body simulations with modified initial conditions, and generate reionization fields using an excursion set model. The N-body approximation is valid on the length and halo mass scales studied. We show that LFDM and ULA models predict an increase in the HI power spectrum from the epoch of reionization by a factor between 2–10 for a range of scales 0.1 < k < 4 Mpc{sup −1}. Assuming a fiducial model where a neutral hydrogen fraction x-bar {sub HI} = 0.5 must be achieved by z = 8, the reionization process allows us to put approximate bounds on the redshift of dark matter formation z{sub f} > 4 × 10{sup 5} (for LFDM) and the axion mass m{sub a} > 2.6 × 10{sup −23} eV (for ULA). The comparison of the collapsed mass fraction inferred from damped Lyman-α observations to the theoretical predictions of our models lead to the weaker bounds: z{sub f} > 2 × 10{sup 5} and m{sub a} > 10{sup −23} eV. These bounds are consistent with other constraints in the literature using different observables; we briefly discuss how these bounds compare with possible constraints from the observation of luminosity function of galaxies at high redshifts. In the case of ULAs, these constraints are also consistent with a solution to the cusp-core problem of CDM.

79 ASTRONOMY AND ASTROPHYSICS↗

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗

The Influence of Shallow Subsurface Properties on Particle Motion in Acoustic-Seismic Coupling

Atmospheric acoustic waves transmit energy into the solid Earth through air-to-ground coupling. These waves are recorded by seismic sensors and provide insight into both atmospheric phenomena and subsurface properties. Interpreting these signals is often challenging because they are modulated by subsurface structure and the incidence angle of the acoustic wave. This study examines acoustic--seismic coupling generated by the 2012 Camp Minden Explosion, which was recorded by hundreds of seismoacoustic stations. We apply a novel technique to quantify the seismic particle motion, model coupled waves with a propagator matrix approach, and apply a Bayesian inversion to infer properties of the shallow subsurface. Our analysis reveals that prograde motion is widespread and focused in low shear-wave velocity regions, such as the Mississippi Embayment, and retrograde motion is more common in higher shear-velocity areas. Inversion results at some stations produce plausible subsurface models with strong waveform fits, while inversions at other sites are less successful. These results indicate prograde particle motion in air-to-ground coupled waves is more prevalent than previously recognized and may serve as a diagnostic for shallow velocity structure. Our comprehensive modeling and inversion framework provides a potential method to extract layered near-surface properties from acoustic-seismic coupling observations.

58 GEOSCIENCES↗

C/2014 UN 271 (Bernardinelli-Bernstein): The Nearly Spherical Cow of Comets

Abstract Comet C/2014 UN 271 (Bernardinelli-Bernstein), incoming from the Oort cloud, is remarkable in having the brightest (and presumably largest) nucleus of any well-measured comet and having been discovered at the heliocentric distance r h ≈ 29 au, farther than any Oort cloud comet. In this work, we describe the discovery process and observations and the properties that can be inferred from images recorded until the first reports of activity in 2021 June. The orbit has i = 95°, with a perihelion of 10.97 au to be reached in 2031 and a previous aphelion at 40,400 ± 260 au. Backward integration of the orbit under a standard Galactic tidal model and known stellar encounters suggests a perihelion of q ≈ 18 au on its previous perihelion passage 3.5 Myr ago; hence, the current data could be the first ever obtained of a comet that has not been inside Uranus’s orbit in 4 Gyr. The photometric data show an unresolved nucleus with absolute magnitude H r = 8.0, colors that are typical of comet nuclei or Damocloids, and no secular trend as it traversed the range 34–23 au. For the r -band geometric albedo p r , this implies a diameter of 150 ( p r / 0.04 ) − 0.5 km. There is strong evidence of brightness fluctuations at the ±0.2 mag level, but no rotation period can be discerned. A coma, nominally consistent with a “stationary” 1/ ρ surface brightness distribution, grew in scattering cross section at an exponential rate from A f ρ ≈ 1 to ≈150 m as the comet approached from 28 to 20 au. The activity rate is consistent with a very simple model of sublimation of a surface species in radiative equilibrium with the Sun. The inferred enthalpy of sublimation matches those of CO 2 and NH 3 . More volatile species, such as N 2 , CH 4 , and CO, must be far less abundant on the sublimating surfaces.

79 ASTRONOMY AND ASTROPHYSICS↗

The Evolution of the Tully–Fisher Relation between z ∼ 2.3 and z ∼ 0.9 with KMOS{sup 3D}

We investigate the stellar mass and baryonic mass Tully–Fisher relations (TFRs) of massive star-forming disk galaxies at redshift z∼2.3 and z∼0.9 as part of the KMOS{sup 3D} integral field spectroscopy survey. Our spatially resolved data allow reliable modeling of individual galaxies, including the effect of pressure support on the inferred gravitational potential. At fixed circular velocity, we find higher baryonic masses and similar stellar masses at z∼2.3 as compared to z∼0.9. Together with the decreasing gas-to-stellar mass ratios with decreasing redshift, this implies that the contribution of dark matter to the dynamical mass on the galaxy scale increases toward lower redshift. A comparison to local relations reveals a negative evolution of the stellar and baryonic TFR zero points from z = 0 to z∼0.9, no evolution of the stellar TFR zero point from z∼0.9 to z∼2.3, and a positive evolution of the baryonic TFR zero point from z∼0.9 to z∼2.3. We discuss a toy model of disk galaxy evolution to explain the observed nonmonotonic TFR evolution, taking into account the empirically motivated redshift dependencies of galactic gas fractions and the relative amount of baryons to dark matter on galaxy and halo scales.

79 ASTRONOMY AND ASTROPHYSICS↗

Goal-oriented a-posteriori estimation of model error as an aid to parameter estimation

In this work, a Bayesian model calibration framework is presented that utilizes goal-oriented a-posterior error estimates in quantities of interest (QoIs) for classes of high-fidelity models characterized by PDEs. It is shown that for a large class of computational models, it is possible to develop a computationally inexpensive procedure for calibrating parameters of high-fidelity models of physical events when the parameters of low-fidelity (surrogate) models are known with acceptable accuracy. The main ingredients in the proposed model calibration scheme are goal-oriented a-posteriori estimates of error in QoIs computed using a so-called lower fidelity model compared to those of an uncalibrated higher fidelity model. The estimates of error in QoIs are used to define likelihood functions in Bayesian inversion analysis. A standard Bayesian approach is employed to compute the posterior distribution of model parameters of high-fidelity models. As applications, parameters in a quasi-linear second-order elliptic boundary-value problem (BVP) are calibrated using a second-order linear elliptic BVP. In a second application, parameters of a tumor growth model involving nonlinear time-dependent PDEs are calibrated using a lower fidelity linear tumor growth model with known parameter values.

A-posterior estimates↗