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We combine the isothermal Jeans model and the model of adiabatic halo contraction into a simple semi-analytic procedure for computing the density profile of self-interacting dark-matter (SIDM) haloes with the gravitational influence from the inhabitant galaxies. We show that the model agrees well with cosmological SIDM simulations over the entire core-forming stage and up to the onset of gravothermal core-collapse. Using this model, we show that the halo response to baryons is more diverse in SIDM than in CDM and depends sensitively on galaxy size, a desirable link in the context of the structural diversity of bright dwarf galaxies. The fast speed of the method facilitates analyses that would be challenging for numerical simulations -- notably, 1) we quantify the SIDM halo response as functions of the baryonic properties, on a fine mesh grid spanned by the baryon-to-total-mass ratio, $M_{\rm b}/M_{\rm vir}$, and galaxy compactness, $r_{1/2}/R_{\rm vir}$; 2) we show with high statistical precision that for typical Milky-Way-like systems, the SIDM profiles are similar to their CDM counterparts; and 3) we delineate the regime of gravothermal core-collapse in the $M_{\rm b}/M_{\rm vir}$-$r_{1/2}/R_{\rm vir}$ space, for a given cross section and a given halo concentration. Finally, we compare the isothermal Jeans model with the more sophisticated gravothermal fluid model, and show that the former yields faster core formation and agrees better with cosmological simulations. We attribute the difference to whether the target CDM halo is used as a boundary condition or as the initial condition for the gravothermal evolution, and thus comment on possible future improvements of the fluid model. We have made our programs for the model publicly available at https://github.com/JiangFangzhou/SIDM., Comment: 15 pages, 9 figures, submitted to MNRAS

Modelling the growth histories of specific galaxies often involves generating the entire population of objects that arise in a given cosmology and selecting systems with appropriate properties. This approach is highly inefficient when targeting rare systems such as the extremely luminous high-redshift galaxy candidates detected by JWST. Here, we present a novel framework for generating merger trees with branches that are guaranteed to achieve a desired halo mass at a chosen redshift. This method augments extended Press Schechter theory solutions with constrained random processes known as Brownian bridges and is implemented in the open-source semi-analytic model $\texttt{Galacticus}$. We generate ensembles of constrained merger trees to predict the growth histories of seven high-redshift JWST galaxy candidates, finding that these systems most likely merge $\approx 2~\mathrm{Gyr}$ after the observation epoch and occupy haloes of mass $\gtrsim 10^{14}~M_{\mathrm{\odot}}$ today. These calculations are thousands of times more efficient than existing methods, are analytically controlled, and provide physical insights into the evolution of haloes with rapid early growth. Our constrained merger tree implementation is publicly available at http://github.com/galacticusorg/galacticus., Comment: 20 pages, 12 figures. Updated to published version

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 stellar population synthesis. 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, and 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 modeling the colors of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speedup 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., Comment: 13 pages, 2 appendices. Version accepted for publication in MNRAS

We describe a simple extension to existing models for the tidal heating of dark matter subhalos which takes into account second order terms in the impulse approximation for tidal heating. We show that this revised model can accurately match the tidal tracks along which subhalos evolve as measured in high-resolution N-body simulations. We further demonstrate that, when a constant density core is introduced into a subhalo, this model is able to quantitatively reproduce the evolution and artificial disruption of N-body subhalos arising from finite resolution effects. Combining these results we confirm prior work indicating that artificial disruption in N-body simulations can result in a factor two underestimate of the subhalo mass function in the inner regions of host halos, and a 10--20% reduction over the entire virial volume., 9 pages, accepted for publication in MNRAS

Abstract The future U.S. electric grid is being transformed with deep decarbonization of generation (i.e., removing or reducing reliance on fossil fuels and replacing them with renewable and clean energy resources), which in practice is not achievable without a dramatic increase in the reliance on long-duration energy storage (LDES) technologies. Regulators at both the state and federal level are well advised to take steps to address current policy gaps, build frameworks that will enable a greater role for LDES to contribute to grid reliability and be fairly compensated for its grid services.. Decarbonization by definition is dependent on an increasing reliance on variable renewable energy, primarily wind and solar resources, that needs to be stored for longer durations to maintain electric grid reliability and provide operational flexibility to grid operators. However, despite the growing realization of the need for long-duration energy storage (LDES) technologies, a persistent gap of policy levers at the federal and state level creates a vacuum in terms of defining how and where LDES technologies can be utilized to support the electric grid, along with an inadequate regulatory framework wherein these resources will need to be valued and compensated for the services they can provide. This paper—which is primarily intended for US decision makers, but should be of value for all energy professionals and the general public—addresses policy gaps, needs, and opportunities for LDES that require urgent attention from US-based policymakers at the federal and state level. This paper also provides background information on how the US E&U industry is structured and regulated, along with perspectives on LDES technologies and applications, all of which have direct relevance to the paper’s primary focus on the need for LDES policymaking. Discussion Despite a generally accepted future need for long-duration energy storage (LDES) technologies that is directly tied to the rapid of renewable resources on the U.S. electric grid, there is a lack of policymaking, market designs, and compensation mechanisms for LDES technologies. Decarbonization (i.e., the goal of removing or reducing reliance on fossil fuels) cannot be achieved at the aggressive levels envisioned without utilizing LDES. Policymakers must take steps now to build frameworks that recognize the unique ways in which LDES will increasingly contribute to grid reliability and resilience, and receive appropriate compensation for the services it provides. Graphical abstract

Accurate models of the structural evolution of dark matter subhaloes, as they orbit within larger systems, are fundamental to understanding the detailed distribution of dark matter at the present day. Numerical simulations of subhalo evolution support the idea that the mass loss associated with tidal stripping is most naturally understood in energy space, with the particles that are the least bound being removed first. Starting from this premise, we recently proposed a zero-parameter "energy-truncation model" for subhalo evolution. We tested this model with simulations of tidal stripping of satellites with initial NFW profiles, and showed that the energy-truncation model accurately predicts both the mass loss and density profiles. In this work, we apply the model to a variety of Hernquist, Einasto and King profiles. We show that it matches the simulation results quite closely in all cases, indicating that it may serve as a universal model to describe tidally stripped collisionless systems. A key prediction of the energy-truncation model is that the central density of dark matter subhaloes is conserved as they lose mass; this has important implications for dark matter annihilation calculations, and for other observational tests of dark matter., 19 pages, 14 figures. Accepted for publication in MNRAS

The primordial matter power spectrum quantifies fluctuations in the distribution of dark matter immediately following inflation. Over cosmic time, over-dense regions of the primordial density field grow and collapse into dark matter halos, whose abundance and density profiles retain memory of the initial conditions. By analyzing the image magnifications in eleven strongly-lensed and quadruply-imaged quasars, we infer the abundance and concentrations of low-mass halos, and cast the measurement in terms of the amplitude of the primordial matter power spectrum. We anchor the power spectrum on large scales, isolating the effect of small-scale deviations from the $\Lambda$CDM prediction. Assuming an analytic model for the power spectrum and accounting for several sources of potential systematic uncertainty, including three different models for the halo mass function, we obtain correlated inferences of $\log_{10}\left(P / P_{\Lambda \rm{CDM}}\right)$, the power spectrum amplitude relative to the predictions of the concordance cosmological model, of $0.0_{-0.4}^{+0.5}$, $0.1_{-0.6}^{+0.7}$, and $0.2_{-0.9}^{+1.0}$ at k = 10, 25 and 50 $\rm{Mpc^{-1}}$ at $68 \%$ confidence, consistent with cold dark matter and single-field slow-roll inflation., Comment: accepted to MNRAS; includes expanded discussion of results, tests with simulated data, and additional references

Many compelling dark matter (DM) scenarios feature Coulomb-like interactions between DM particles and baryons, in which the cross section for elastic scattering scales with relative particle velocity as $v^{-4}$. Previous studies have invoked such interactions to produce heat exchange between cold DM and baryons and alter the temperature evolution of hydrogen. In this study, we present a comprehensive study of the effects of Coulomb-like scattering on structure formation, in addition to the known effects on the thermal history of hydrogen. We find that interactions which significantly alter the temperature of hydrogen at Cosmic Dawn also dramatically suppress the formation of galaxies that source the Lyman-$\alpha$ background, further affecting the global 21-cm signal. In particular, an interaction cross section at the current observational upper limit leads to a decrease in the abundance of star-forming halos by a factor of $\sim 2$ at $z\sim 20$, relative to cold, collisionless DM. We also find that DM that is 100% millicharged cannot reproduce the depth and the timing of the reported EDGES anomaly in any part of the parameter space. These results critically inform modeling of the global 21-cm signal and structure formation in cosmologies with DM-baryon scattering, with repercussions for future and upcoming cosmological data analysis., Comment: 21 pages, 10 figures, submitted to PRD

We present Symphony, a compilation of $262$ cosmological, cold-dark-matter-only zoom-in simulations spanning four decades of host halo mass, from $10^{11}$$-$$10^{15}~M_{\mathrm{\odot}}$. This compilation includes three existing simulation suites at the cluster and Milky Way$-$mass scales, and two new suites: $39$ Large Magellanic Cloud-mass ($10^{11}~M_{\mathrm{\odot}}$) and $49$ strong-lens-analog ($10^{13}~M_{\mathrm{\odot}}$) group-mass hosts. Across the entire host halo mass range, the highest-resolution regions in these simulations are resolved with a dark matter particle mass of $\approx 3\times 10^{-7}$ times the host virial mass and a Plummer-equivalent gravitational softening length of $\approx 9\times 10^{-4}$ times the host virial radius, on average. We measure correlations between subhalo abundance and host concentration, formation time, and maximum subhalo mass, all of which peak at the Milky Way host halo mass scale. Subhalo abundances are $\approx 50\%$ higher in clusters than in lower-mass hosts at fixed sub-to-host halo mass ratios. Subhalo radial distributions are approximately self-similar as a function of host mass and are less concentrated than hosts' underlying dark matter distributions. We compare our results to the semianalytic model $\mathrm{\texttt{Galacticus}}$, which predicts subhalo mass functions with a higher normalization at the low-mass end and radial distributions that are slightly more concentrated than Symphony. We use $\mathrm{\texttt{UniverseMachine}}$ to model halo and subhalo star formation histories in Symphony, and we demonstrate that these predictions resolve the formation histories of the halos that host nearly all currently observable satellite galaxies in the universe. To promote open use of Symphony, data products are publicly available at http://web.stanford.edu/group/gfc/symphony., 39 pages, 20 figures, 2 tables. Updated to published version

The avian inner perivitelline layer (IPVL), containing the zona pellucida (ZP) family of proteins, surrounds the ovulated ovum. Sperm binding at the germinal disc (GD) region of the IPVL initiates fertilization in avian species, and the amount of sperm binding at the GD reflects female fertility. RT-PCR and quantitative Western blot analyses were used to determine differences in ZP protein mRNA expression and protein concentration between GD and nongerminal disc (NGD) regions among four genetic strains of broiler breeders. Both the mRNA expression and protein concentration of chicken ZPB2 was greater in the GD region, compared to the NGD region, and ZPB2 protein was more abundant in the small prehierarchical follicles. Chicken ZPC mRNA, but not ZPC protein, was greater in the NGD region compared to the GD region, and hepatically expressed ZPB1 protein was more concentrated in the NGD region. Testosterone increased the expression of both ZPC mRNA and protein in cultured granulosa cells from prehierarchical follicles. The current research is the first to investigate the relative amount of ZP proteins between the GD region and NGD region in chicken IPVL. The results provide further evidence that ZPB2 may be critical for avian sperm binding at the GD region of the IPVL.

Several bioactive components of the human diet have major effects on composition and function of the gut microbiome, but no systematic framework exists for understanding variation in microbiome-active components amid the vast amount of genotypic and phenotypic variation within a given species of food crop. Here we present a powerful new approach for complex trait analysis of Microbiome-Active Traits (MATs) in food crops. Capitalizing on a novel automated in vitro microbiome screening (AiMS) methodology to quantify human gut microbiome phenotypes after fermentation of grain from genetically diverse lines, we show how microbiome phenotypes can be used as quantitative traits for genetic analysis. Quantitative Trait Locus (QTL) analysis of AiMS-based phenotypes across grain samples from 294 sorghum (Sorghum bicolor) recombinant inbred lines identified significant QTLs at 10 different genomic regions that collectively control MATs affecting 16 different microbial taxa. Segregation analysis and validation in Near-Isogenic Lines (NILs) confirmed that overlapping QTL peaks for microbiome phenotypes, seed color, and tannin concentration are driven by variation in the Tan2 (chromosome 2) and Tan1 (chromosome 4) regulators of the tannin biosynthetic pathway. Candidate genes at other QTLs suggest that variation in a diverse array of plant molecules can drive MATs.

Strongly lensed systems are powerful probes of the distribution of dark matter on small scales. In this paper, we show that line-of-sight haloes between the source and the observers give rise to a distinct anisotropic signature in the two-point function of the effective lensing deflection field. We show in particular that the non-linear coupling between line-of-sight haloes and the main-lens plane imprints a characteristic quadrupole moment on this two-point function whose amplitude reflects the abundance of such haloes within the strongly lensed field. We discuss how, by taking ratios of different multipole moments, such observables could be made robust under the mass-sheet transform. We also demonstrate that future extremely large telescopes have the ability to detect the quadrupole moment due to this unique anisotropic signature under ideal conditions. Our approach opens the door to statistically distinguish the effect of line-of-sight haloes from that of the main-lens substructure on lensed images, hence allowing one to probe dark matter physics in a new way., Comment: 12 pages, 8 figures + appendices. Matches the published version in MNRAS

Dwarf galaxies are ubiquitous throughout the universe and are extremely sensitive to various forms of internal and external feedback. Over the last two decades, the census of dwarf galaxies in the Local Group and beyond has increased markedly. While hydrodynamic simulations (e.g. FIRE II, MINT Justice League) have reproduced the observed dwarf properties down to the ultra-faints, such simulations require extensive computational resources to run. In this work, we constrain the standard physical implementations in the semi-analytic model Galacticus to reproduce the observed properties of the Milky Way satellites down to the ultra-faint dwarfs found in SDSS. We run Galacticus on merger trees from our high-resolution N-body simulation of a Milky Way analog. We determine the best-fit parameters by matching the cumulative luminosity function and luminosity-metallicity relation from both observations and hydrodynamic simulations. With the correct parameters, the standard physics in Galacticus can reproduce the observed luminosity function and luminosity-metallicity relation of the Milky Way dwarfs. In addition, we find a multi-dimensional match with half-light radii, velocity dispersions and mass-to-light ratios at z = 0 down to M_V = 10^4 L_solar). In addition to successfully reproducing the properties of the z = 0 Milky Way satellite population, our modeled dwarfs have star formation histories which are consistent with those of the Local Group dwarfs., 18 pages, 15 figures, submitted to ApJ

The impact of the SARS-CoV-2 virus on delivery of hospital care during the ongoing COVID-19 pandemic has required effective nursing leadership of large teams of Advanced Practice Registered Nurses (APRNs). At a large academic medical center in the mid-Atlantic United States, nurse leaders combined knowledge of the psychological phases of disaster and principles of the Serving Leadership framework to mobilize and lead APRN teams to deliver high-quality care to all patients and provide a safe working environment for healthcare teams. In this article, we discuss exemplars that demonstrate the flexibility and strengths of APRNs in all roles who addressed rapidly evolving needs such as resource allocation and education. The conclusion highlights the value and relevance of APRN skillsets to clinical practice and the opportunity to further capitalize on these strengths during the continuing journey through this COVID-19 pandemic and beyond.

Self-interacting dark matter (SIDM) cosmologies admit an enormous diversity of dark matter (DM) halo density profiles, from low-density cores to high-density core-collapsed cusps. The possibility of the growth of high central density in low-mass halos, accelerated if halos are subhalos of larger systems, has intriguing consequences for small-halo searches with substructure lensing. However, following the evolution of $\lesssim 10^8 M_\odot$ subhalos in lens-mass systems ($\sim 10^{13}M_\odot$) is computationally expensive with traditional N-body simulations. In this work, we develop a new hybrid semi-analytical + N-body method to study the evolution of SIDM subhalos with high fidelity, from core formation to core-collapse, in staged simulations. Our method works best for small subhalos ($\lesssim 1/1000$ host mass), for which the error caused by dynamical friction is minimal. We are able to capture the evaporation of subhalo particles by interactions with host halo particles, an effect that has not yet been fully explored in the context of subhalo core-collapse. We find three main processes drive subhalo evolution: subhalo internal heat outflow, host-subhalo evaporation, and tidal effects. The subhalo central density grows only when the heat outflow outweighs the energy gain from evaporation and tidal heating. Thus, evaporation delays or even disrupts subhalo core-collapse. We map out the parameter space for subhalos to core-collapse, finding that it is nearly impossible to drive core-collapse in subhalos in SIDM models with constant cross sections. Any discovery of ultra-compact dark substructures with future substructure lensing observations favors additional degrees of freedom, such as velocity-dependence, in the cross section., 25 pages, 15 figures, 2 animations. Matched published version

Certified Registered Nurse Anesthetists (CRNAs) are uniquely skilled anesthesia providers with substantial experience managing critically ill patients. During the coronavirus disease 2019 (COVID) pandemic, CRNAs at a large academic medical center in the Mid-Atlantic United States experienced a shift in their daily responsibilities. As the hospital transitioned to the management of patients who tested positive for the virus that causes COVID, the severe acute respiratory syndrome-coronavirus type 2 (SARS-CoV-2), CRNAs were redeployed into the roles of respiratory therapists and intensive care unit registered nurses. Although facing the stress of the global pandemic, this facility's CRNAs proved to be flexible, capable, and necessary members of the care team for patients with COVID-19.