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The state-of-the-art in biometric recognition algorithms and operational systems has advanced quickly in recent years providing high accuracy and robustness in more challenging collection environments and consumer applications. However, the technology still suffers greatly when applied to non-conventional settings such as those seen when performing identification at extreme distances or from elevated cameras on buildings or mounted to UAVs. This paper summarizes an extension to the largest dataset currently focused on addressing these operational challenges, and describes its composition as well as methodologies of collection, curation, and annotation., Comment: 9 pages, 11 figures, 2 tables

We present Mantis Shrimp, a multi-survey deep learning model for photometric redshift estimation that fuses ultra-violet (GALEX), optical (PanSTARRS), and infrared (UnWISE) imagery. Machine learning is now an established approach for photometric redshift estimation, with generally acknowledged higher performance in areas with a high density of spectroscopically identified galaxies over template-based methods. Multiple works have shown that image-based convolutional neural networks can outperform tabular-based color/magnitude models. In comparison to tabular models, image models have additional design complexities: it is largely unknown how to fuse inputs from different instruments which have different resolutions or noise properties. The Mantis Shrimp model estimates the conditional density estimate of redshift using cutout images. The density estimates are well calibrated and the point estimates perform well in the distribution of available spectroscopically confirmed galaxies with (bias = 1e-2), scatter (NMAD = 2.44e-2) and catastrophic outlier rate ($\eta$=17.53$\%$). We find that early fusion approaches (e.g., resampling and stacking images from different instruments) match the performance of late fusion approaches (e.g., concatenating latent space representations), so that the design choice ultimately is left to the user. Finally, we study how the models learn to use information across bands, finding evidence that our models successfully incorporates information from all surveys. The applicability of our model to the analysis of large populations of galaxies is limited by the speed of downloading cutouts from external servers; however, our model could be useful in smaller studies such as generating priors over redshift for stellar population synthesis.

We employ dynamical mean-field theory (DMFT) combined with density functional theory (DFT) and the non-equilibrium Green's function technique to investigate the steady-state transport properties of an Fe/MgO/Fe magnetic tunnel junction (MTJ), focusing on the impact of dynamical electron correlations on the Fe $3d$ orbitals. By applying the rigid shift approximation, we extend the calculations from zero- to finite-bias in a simple and computationally efficient manner, obtaining the bias-dependent electronic structure and current-versus-voltage characteristic curve in both the parallel and antiparallel configurations. In particular, we find that dynamical electron correlation manifests as a reduction in the spin splitting of the Fe $3d_{z^2}$ state compared to DFT predictions and introduces a finite relaxation time. The impact of these effects on the transport properties, however, varies significantly between magnetic configurations. In the parallel configuration, the characteristic curves obtained with DFT and DMFT are similar, as the transport is mostly due to the coherent transmission of spin-up electrons through the MgO barrier. Conversely, in the antiparallel configuration, correlation effects become more significant, with DMFT predicting a sharp current increase due to bias-driven inelastic electron-electron scattering. As a consequence, DMFT gives a lower bias threshold for the suppression of the tunneling magnetoresistance ratio compared to DFT, matching experimental data more closely.

The Suborbital Imaging Spectrograph for Transition region Irradiance from Nearby Exoplanet host stars (SISTINE) is a rocket-borne ultraviolet (UV) imaging spectrograph designed to probe the radiation environment of nearby stars. SISTINE operates over a bandpass of 98 -- 127 and 130 -- 158 nm, capturing a broad suite of emission lines tracing the full 10$^4$ -- 10$^5$ K formation temperature range critical for reconstructing the full UV radiation field incident on planets orbiting solar-type stars. SISTINE serves as a platform for key technology developments for future ultraviolet observatories. SISTINE operates at moderate resolving power ($R\sim$1500) while providing spectral imaging over an angular extent of $\sim$6', with $\sim$2" resolution at the slit center. The instrument is composed of an f/14 Cassegrain telescope that feeds a 2.1x magnifying spectrograph, utilizing a blazed holographically ruled diffraction grating and a powered fold mirror. Spectra are captured on a large format microchannel plate (MCP) detector consisting of two 113 x 42 mm segments each read out by a cross delay-line anode. Several novel technologies are employed in SISTINE to advance their technical maturity in support of future NASA UV/optical astronomy missions. These include enhanced aluminum lithium fluoride coatings (eLiF), atomic layer deposition (ALD) protective optical coatings, and ALD processed large format MCPs. SISTINE was launched a total of three times with two of the three launches successfully observing targets Procyon A and $\alpha$ Centauri A and B.

The moist shallow water equations offer a promising route for advancing understanding of the coupling of physical parametrisations and dynamics in numerical atmospheric models, an issue known as 'physics-dynamics coupling'. Without moist physics, the traditional shallow water equations are a simplified form of the atmospheric equations of motion and so are computationally cheap, but retain many relevant dynamical features of the atmosphere. Introducing physics into the shallow water model in the form of moisture provides a tool to experiment with numerical techniques for physics-dynamics coupling in a simple dynamical model. In this paper, we compare some of the different moist shallow water models by writing them in a general formulation. The general formulation encompasses three existing forms of the moist shallow water equations and also a fourth, previously unexplored formulation. The equations are coupled to a three-state moist physics scheme that interacts with the resolved flow through source terms and produces two-way physics-dynamics feedback. We present a new compatible finite element discretisation of the equations and apply it to the different formulations of the moist shallow water equations in three test cases. The results show that the models capture generation of cloud and rain and physics-dynamics interactions, and demonstrate some differences between moist shallow water formulations and the implications of these different modelling choices.

The considerable body of data available for evaluating biometric recognition systems in Research and Development (R\&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T\&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios. To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.

This paper examines covariate effects on fused whole body biometrics performance in the IARPA BRIAR dataset, specifically focusing on UAV platforms, elevated positions, and distances up to 1000 meters. The dataset includes outdoor videos compared with indoor images and controlled gait recordings. Normalized raw fusion scores relate directly to predicted false accept rates (FAR), offering an intuitive means for interpreting model results. A linear model is developed to predict biometric algorithm scores, analyzing their performance to identify the most influential covariates on accuracy at altitude and range. Weather factors like temperature, wind speed, solar loading, and turbulence are also investigated in this analysis. The study found that resolution and camera distance best predicted accuracy and findings can guide future research and development efforts in long-range/elevated/UAV biometrics and support the creation of more reliable and robust systems for national security and other critical domains.

We present new near-ultraviolet (NUV, $\lambda$ = 2479 $-$ 3306 $\r{A}$) transmission spectroscopy of KELT-9b, the hottest known exoplanet, obtained with the Colorado Ultraviolet Transit Experiment ($CUTE$) CubeSat. Two transits were observed on September 28th and September 29th 2022, referred to as Visits 1 and 2 respectively. Using a combined transit and systematics model for each visit, the best-fit broadband NUV light curves are R$_{\text{p}}$/R$_{\star}$ $=$ 0.136$_{0.0146}^{0.0125}$ for Visit 1 and R$_{\text{p}}$/R$_{\star}$ $=$ 0.111$_{0.0190}^{0.0162}$ for Visit 2, appearing an average of 1.54$\times$ larger in the NUV than at optical wavelengths. While the systematics between the two visits vary considerably, the two broadband NUV light curves are consistent with each other. A transmission spectrum with 25 $\r{A}$ bins suggests a general trend of excess absorption in the NUV, consistent with expectations for ultra-hot Jupiters. Although we see an extended atmosphere in the NUV, the reduced data lack the sensitivity to probe individual spectral lines.

The Solar eruptioN Integral Field Spectrograph (SNIFS) is a solar-gazing spectrograph scheduled to fly in the summer of 2025 on a NASA sounding rocket. Its goal is to view the solar chromosphere and transition region at a high cadence (1s) both spatially (0.5") and spectrally (33 m{\AA}) viewing wavelengths around Lyman Alpha (1216 {\AA}), Si iii (1206 {\AA}) and O v (1218 {\AA}) to observe spicules, nanoflares, and possibly a solar flare. This time cadence will provide yet-unobserved detail about fast-changing features of the Sun. The instrument is comprised of a Gregorian-style reflecting telescope combined with a spectrograph via a specialized mirrorlet array that focuses the light from each spatial location in the image so that it may be spectrally dispersed without overlap from neighboring locations. This paper discusses the driving science, detailed instrument and subsystem design, and pre-integration testing of the SNIFS instrument., Comment: 22 pages (not including references), 7 figures, submitting to Solar Physics

The recent emergence of van der Waals (vdW) ferromagnets has opened new opportunities for designing spintronic devices. We theoretically investigate the coherent spin-dependent transport properties of the vdW ferromagnet Fe$_4$GeTe$_2$, by using density functional theory combined with the non-equilibrium Green's functions method. We find that the conductance in the direction perpendicular to the layers is half-metallic, namely it is entirely spin-polarized, as a result of the material's electronic structure. This characteristic persists from bulk to single layer, even under significant bias voltages, and it is little affected by spin-orbit coupling and electron correlation. Motivated by this observation, we then investigate the tunnel magnetoresistance (TMR) effect in an magnetic tunnel junction, which comprises two Fe$_4$GeTe$_2$ layers separated by the vdW gap acting as insulating barrier. We predict a TMR ratio of almost 500\%, which can be further boosted by increasing the number of Fe$_4$GeTe$_2$ layers in the junction., Comment: 16 pages, 15 figures and 4 tables

The availability of large, public, multi-modal astronomical datasets presents an opportunity to execute novel research that straddles the line between science of AI and science of astronomy. Photometric redshift estimation is a well-established subfield of astronomy. Prior works show that computer vision models typically outperform catalog-based models, but these models face additional complexities when incorporating images from more than one instrument or sensor. In this report, we detail our progress creating Mantis Shrimp, a multi-survey computer vision model for photometric redshift estimation that fuses ultra-violet (GALEX), optical (PanSTARRS), and infrared (UnWISE) imagery. We use deep learning interpretability diagnostics to measure how the model leverages information from the different inputs. We reason about the behavior of the CNNs from the interpretability metrics, specifically framing the result in terms of physically-grounded knowledge of galaxy properties., Comment: 4 pages, 1 figure, 1 table. Submitted to AI4Differential Equations in Science Workshop at ICLR24. Public repository unavailable while under institutional review

The Far- and Lyman-Ultraviolet Imaging Demonstrator (FLUID) is a rocket-borne arcsecond-level ultraviolet (UV) imaging instrument covering four bands between 92 -- 193 nm. FLUID will observe nearby galaxies to find and characterize the most massive stars that are the primary drivers of the chemical and dynamical evolution of galaxies, and the co-evolution of the surrounding galactic environment. The FLUID short wave channel is designed to suppress efficiency at Lyman-$\alpha$ (121.6 nm), while enhancing the reflectivity of shorter wavelengths. Utilizing this technology, FLUID will take the first ever images of local galaxies isolated in the Lyman ultraviolet (90 -- 120 nm). As a pathfinder instrument, FLUID will employ and increase the TRL of band-selecting UV coatings, and solar-blind UV detector technologies including microchannel plate and solid state detectors; technologies prioritized in the 2022 NASA Astrophysical Biennial Technology Report. These technologies enable high throughput and high sensitivity observations in the four co-aligned UV imaging bands that make up the FLUID instrument. We present the design of FLUID, status on the technology development, and results from initial assembly and calibration of the FLUID instrument., Comment: Accepted to JATIS, March 18, 2024

As part of their training all medical students and residents have to pass basic surgical tasks such as knot tying, needle-passing, and suturing. Their assessment is typically performed in the operating room by surgical faculty where mistakes and failure by the student increases the operation time and cost. This evaluation is quantitative and has a low margin of error. Simulation has emerged as a cost effective option but it lacks assessment or requires additional expensive hardware for evaluation. Apps that provide training videos on surgical knot trying are available to students but none have evaluation. We propose a cascaded neural network architecture that evaluates a student's performance just from a video of themselves simulating a surgical knot tying task. Our model converts video frame images into feature vectors with a pre-trained deep convolutional network and then models the sequence of frames with a temporal network. We obtained videos of medical students and residents from the Robert Wood Johnson Hospital performing knot tying on a standardized simulation kit. We manually annotated each video and proceeded to do a five-fold cross-validation study on them. Our model achieves a median precision, recall, and F1-score of 0.71, 0.66, and 0.65 respectively in determining the level of knot related tasks of tying and pushing the knot. Our mean precision score averaged across different probability thresholds is 0.8. Both our F1-score and mean precision score are 8% and 30% higher than that of a recently published study for the same problem. We expect the accuracy of our model to further increase as we add more training videos to the model thus making it a practical solution that students can use to evaluate themselves., Comment: To appear in proceedings of 11th IEEE International Conference on Healthcare Informatics (ICHI) 2023

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

We study Clark measures on the unit polydisc, giving an overview of recent research and investigating the Clark measures of some new examples of multivariate inner functions. In particular, we study the relationship between Clark measures and multiplication; first by introducing compositions of inner functions and multiplicative embeddings, and then by studying products of one-variable inner functions., Comment: 21 pages, 5 figures

Ultraviolet observations of Ultra-hot Jupiters (UHJs), exoplanets with temperatures over 2000\,K, provide us with an opportunity to investigate if and how atmospheric escape shapes their upper atmosphere. Near-ultraviolet transit spectroscopy offers a unique tool to study this process owing to the presence of strong metal lines and a bright photospheric continuum as the light source against which the absorbing gas is observed. WASP-189b is one of the hottest planets discovered to date, with a day-side temperature of about 3400\,K orbiting a bright A-type star. We present the first near-ultraviolet observations of WASP-189b, acquired with the Colorado Ultraviolet Transit Experiment ($CUTE$). $CUTE$ is a 6U NASA-funded ultraviolet spectroscopy mission, dedicated to monitoring short-period transiting planets. WASP-189b was one of the $CUTE$ early science targets and was observed during three consecutive transits in March 2022. We present an analysis of the $CUTE$ observations and results demonstrating near-ultraviolet (2500--3300~\AA) broadband transit depth ($1.08^{+0.08}_{-0.08}\%$) of about twice the visual transit depth indicating that the planet has an extended, hot upper atmosphere with a temperature of about 15000\,K and a moderate mass loss rate of about \SI{4e8}{\kg\per\second}. We observe absorption by Mg{\sc ii} lines ($R_p/R_s$ of $0.212^{+0.038}_{-0.061}$) beyond the Roche lobe at $>$4$\sigma$ significance in the transmission spectrum at a resolution of 10~\AA, while at lower resolution (100~\AA), we observe a quasi-continuous absorption signal consistent with a "forest" of low-ionization metal absorption dominated by Fe{\sc ii}. The results suggest an upper atmospheric temperature ($\sim15000$\,K), higher than that predicted by current state-of-the-art hydrodynamic models., Comment: Accepted for publication in The Astrophysical Journal Letters

Far ultraviolet (FUV) emission lines from dwarf stars are important driving sources of photochemistry in planetary atmospheres. Properly interpreting spectral features of planetary atmospheres critically depends on the emission of its host star. While the spectral energy distributions (SEDs) of K- and M-type stars have been extensively characterized by previous observational programs, the full X-ray to infrared SED of F-type stars has not been assembled to support atmospheric modeling. On the second flight of the Suborbital Imaging Spectrograph for Transition-region Irradiance from Nearby Exoplanet host stars (SISTINE-2) rocket-borne spectrograph, we successfully captured the FUV spectrum of Procyon A (F5 IV-V) and made the first simultaneous observation of several emission features across the FUV bandpass (1010 - 1270 and 1300 - 1565 \r{A}) of any cool star. We combine flight data with stellar models and archival observations to develop the first SED of a mid-F star. We model the response of a modern Earth-like exoplanet's upper atmosphere to the heightened X-ray and extreme ultraviolet radiation within the habitable zone of Procyon A. These models indicate that this planet would not experience significant atmospheric escape. We simulate observations of the Ly$\alpha$ transit signal of this exoplanet with the Hubble Space Telescope (HST) and the Habitable Worlds Observatory (HWO). While marginally detectable with HST, we find that H I Ly$\alpha$ transits of potentially habitable exoplanets orbiting high radial velocity F-type stars could be observed with HWO for targets up to 150 pc away., Comment: 22 Pages, 13 Figures, 3 Tables, to be published in ApJ

Atmospheric escape is a fundamental process that affects the structure, composition, and evolution of many planets. The signatures of escape are detectable on close-in, gaseous exoplanets orbiting bright stars, owing to the high levels of extreme-ultraviolet irradiation from their parent stars. The Colorado Ultraviolet Transit Experiment (CUTE) is a CubeSat mission designed to take advantage of the near-ultraviolet stellar brightness distribution to conduct a survey of the extended atmospheres of nearby close-in planets. The CUTE payload is a magnifying NUV (2479~--~3306 Ang) spectrograph fed by a rectangular Cassegrain telescope (206mm x 84mm); the spectrogram is recorded on a back-illuminated, UV-enhanced CCD. The science payload is integrated into a 6U Blue Canyon Technology XB1 bus. CUTE was launched into a polar, low-Earth orbit on 27 September 2021 and has been conducting this transit spectroscopy survey following an on-orbit commissioning period. This paper presents the mission motivation, development path, and demonstrates the potential for small satellites to conduct this type of science by presenting initial on-orbit science observations. The primary science mission is being conducted in 2022~--~2023, with a publicly available data archive coming on line in 2023., Comment: 12 pages, 5 figures, AJ - accepted

We present the on-orbit performance of the Colorado Ultraviolet Transit Experiment ($CUTE$). $CUTE$ is a 6U CubeSat that launched on September 27th, 2021 and is obtaining near-ultraviolet (NUV, 2480 A -- 3306 A) transit spectroscopy of short-period exoplanets. The instrument comprises a 20 cm $\times$ 8 cm rectangular Cassegrain telescope, an NUV spectrograph with a holographically ruled aberration-correcting diffraction grating, and a passively cooled, back-illuminated NUV-optimized CCD detector. The telescope feeds the spectrograph through an 18$'$ $\times$ 60$''$ slit. The spacecraft bus is a Blue Canyon Technologies XB1, which has demonstrated $\leq$ 6$''$ jitter in 56% of $CUTE$ science exposures. Following spacecraft commissioning, an on-orbit calibration program was executed to characterize the $CUTE$ instrument's on-orbit performance. The results of this calibration indicate that the effective area of $CUTE$ is $\approx$ 19.0 -- 27.5 cm$^{2}$ and that the average intrinsic resolution element is 2.9 A across the bandpass. This paper describes the measurement of the science instrument performance parameters as well as the thermal and pointing characteristics of the observatory.

The Colorado Ultraviolet Transit Experiment (CUTE) is a 6U NASA CubeSat carrying on-board a low-resolution, near-ultraviolet (2479-3306 A) spectrograph. It has a Cassegrain telescope with a rectangular primary to maximize the collecting area, given the shape of the satellite bus, and an aberration correcting grating to improve the image quality, and thus spectral resolution. CUTE, launched on the 27th of September 2021 to a Low Earth Orbit, is designed to monitor transiting extra-solar planets orbiting bright, nearby stars to improve our understanding of planet atmospheric escape and star-planet interaction processes. We present here the CUTE autONomous daTa ReductiOn pipeLine (CONTROL), developed for reducing CUTE data. The pipeline has been structured with a modular approach, which also considers scalability and adaptability to other missions carrying on-board a long-slit spectrograph. The CUTE data simulator has been used to generate synthetic observations used for developing and testing the pipeline functionalities. The pipeline has been tested and updated employing ight data obtained during commissioning and initial science operations of the mission., Comment: Accepted for publication in the Publications of the Astronomical Society of the Pacific

Face recognition technology has advanced significantly in recent years due largely to the availability of large and increasingly complex training datasets for use in deep learning models. These datasets, however, typically comprise images scraped from news sites or social media platforms and, therefore, have limited utility in more advanced security, forensics, and military applications. These applications require lower resolution, longer ranges, and elevated viewpoints. To meet these critical needs, we collected and curated the first and second subsets of a large multi-modal biometric dataset designed for use in the research and development (R&D) of biometric recognition technologies under extremely challenging conditions. Thus far, the dataset includes more than 350,000 still images and over 1,300 hours of video footage of approximately 1,000 subjects. To collect this data, we used Nikon DSLR cameras, a variety of commercial surveillance cameras, specialized long-rage R&D cameras, and Group 1 and Group 2 UAV platforms. The goal is to support the development of algorithms capable of accurately recognizing people at ranges up to 1,000 m and from high angles of elevation. These advances will include improvements to the state of the art in face recognition and will support new research in the area of whole-body recognition using methods based on gait and anthropometry. This paper describes methods used to collect and curate the dataset, and the dataset's characteristics at the current stage.

Recent global growth in the interest of smart cities has led to trillions of dollars of investment toward research and development. These connected cities have the potential to create a symbiosis of technology and society and revolutionize the cost of living, safety, ecological sustainability, and quality of life of societies on a world-wide scale. Some key components of the smart city construct are connected smart grids, self-driving cars, federated learning systems, smart utilities, large-scale public transit, and proactive surveillance systems. While exciting in prospect, these technologies and their subsequent integration cannot be attempted without addressing the potential societal impacts of such a high degree of automation and data sharing. Additionally, the feasibility of coordinating so many disparate tasks will require a fast, extensible, unifying framework. To that end, we propose FaRO2, a completely reimagined successor to FaRO1, built from the ground up. FaRO2 affords all of the same functionality as its predecessor, serving as a unified biometric API harness that allows for seamless evaluation, deployment, and simple pipeline creation for heterogeneous biometric software. FaRO2 additionally provides a fully declarative capability for defining and coordinating custom machine learning and sensor pipelines, allowing the distribution of processes across otherwise incompatible hardware and networks. FaRO2 ultimately provides a way to quickly configure, hot-swap, and expand large coordinated or federated systems online without interruptions for maintenance. Because much of the data collected in a smart city contains Personally Identifying Information (PII), FaRO2 also provides built-in tools and layers to ensure secure and encrypted streaming, storage, and access of PII data across distributed systems.

Longitudinal studies are subject to nonresponse when individuals fail to provide data for entire waves or particular questions of the survey. We compare approaches to nonresponse bias analysis (NRBA) in longitudinal studies and illustrate them on the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). Wave nonresponse with attrition often yields a monotone missingness pattern, and the missingness mechanism can be missing at random (MAR) or missing not at random (MNAR). We discuss weighting, multiple imputation (MI), incomplete data modeling, and Bayesian approaches to NRBA for monotone patterns. Weighting adjustments are effective when the constructed weights are correlated to the survey outcome of interest. MI allows for variables with missing values to be included in the imputation model, yielding potentially less biased and more efficient estimates. Multilevel models with maximum likelihood estimation and marginal models estimated using generalized estimating equations can also handle incomplete longitudinal data. Bayesian methods introduce prior information and potentially stabilize model estimation. We add offsets in the MAR results to provide sensitivity analyses to assess MNAR deviations. We conduct NRBA for descriptive summaries and analytic model estimates and find that in the ECLS-K:2011 application, NRBA yields minor changes to the substantive conclusions. The strength of evidence about our NRBA depends on the strength of the relationship between the characteristics in the nonresponse adjustment and the key survey outcomes, so the key to a successful NRBA is to include strong predictors.

The Baldwin, Philips, & Terlevich diagram of [O III]/H$\beta$ vs. [N II]/H$\alpha$ (hereafter N2-BPT) has long been used as a tool for classifying galaxies based on the dominant source of ionizing radiation. Recent observations have demonstrated that galaxies at $z\sim2$ reside offset from local galaxies in the N2-BPT space. In this paper, we conduct a series of controlled numerical experiments to understand the potential physical processes driving this offset. We model nebular line emission in a large sample of galaxies, taken from the SIMBA cosmological hydrodynamic galaxy formation simulation, using the CLOUDY photoionization code to compute the nebular line luminosities from H II regions. We find that the observed shift toward higher [O III]/H$\beta$ and [N II]/H$\alpha$ values at high redshift arises from sample selection: when we consider only the most massive galaxies $M_* \sim 10^{10-11} M_\odot$, the offset naturally appears, due to their high metallicities. We predict that deeper observations that probe lower-mass galaxies will reveal galaxies that lie on a locus comparable to $z\sim 0$ observations. Even when accounting for sample selection effects, we find that there is a subtle mismatch between simulations and observations. To resolve this discrepancy, we investigate the impact of varying ionization parameters, H II region densities, gas-phase abundance patterns, and increasing radiation field hardness on N2-BPT diagrams. We find that either decreasing the ionization parameter or increasing the N/O ratio of galaxies at fixed O/H can move galaxies along a self-similar arc in N2-BPT space that is occupied by high-redshift galaxies., Comment: 25 pages, 15 figures. Accepted for publication in ApJ

Nonresponse bias is a widely prevalent problem for data on education. We develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in cross-sectional studies and apply these steps to the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11. A key step is the construction of indices of nonresponse bias based on proxy pattern-mixture models for survey variables of interest. A novel feature is to characterize the strength of evidence about nonresponse bias contained in these indices, based on the strength of the relationship between the characteristics in the nonresponse adjustment and the key survey variables. Our NRBA improves existing methods by incorporating both missing at random and missing not at random mechanisms, and all analyses can be done straightforwardly with standard statistical software.

The space ultraviolet (UV) is a critical astronomical observing window, where a multitude of atomic, ionic, and molecular signatures provide crucial insight into planetary, interstellar, stellar, intergalactic, and extragalactic objects. The next generation of large space telescopes require highly sensitive, moderate-to-high resolution UV spectrograph. However, sensitive observations in the UV are difficult, as UV optical performance and imaging efficiencies have lagged behind counterparts in the visible and infrared regimes. This has historically resulted in simple, low-bounce instruments to increase sensitivity. In this study, we present the design, fabrication, and calibration of a simple, high resolution, high throughput far-UV spectrograph - the Colorado High-resolution Echelle Stellar Spectrograph (CHESS). CHESS is a sounding rocket payload to demonstrate the instrument design for the next-generation UV space telescopes. We present tests and results on the performance of several state-of-the-art diffraction grating and detector technologies for far-UV astronomical applications that were flown aboard the first two iterations of CHESS. The CHESS spectrograph was used to study the atomic-to-molecular transitions within translucent cloud regions in the interstellar medium (ISM) through absorption spectroscopy. The first two flights looked at the sightlines towards alpha Virgo and epsilon Persei, and flight results are presented., Comment: pre-print; accepted for publication in Experimental Astronomy; 44 pages, 14 figures

Our ability to study the properties of the interstellar medium (ISM) in the earliest galaxies will rely on emission line diagnostics at rest-frame ultraviolet (UV) wavelengths. In this work, we identify metallicity-sensitive diagnostics using UV emission lines. We compare UV-derived metallicities with standard, well-established optical metallicities using a sample of galaxies with rest-frame UV and optical spectroscopy. We find that the He2-O3C3 diagnostic (He II 1640 / C III 1906,1909 vs. O III 1666 / C III 1906,1909) is a reliable metallicity tracer, particularly at low metallicity (12+log(O/H) < 8), where stellar contributions are minimal. We find that the Si3-O3C3 diagnostic (Si III 1883 / C III 1906,1909 vs. O III 1666 / C III 1906,1909) is a reliable metallicity tracer, though with large scatter (0.2-0.3 dex), which we suggest is driven by variations in gas-phase abundances. We find that the C4-O3C3 diagnostic (C IV 1548,1550 / O III 1666 vs. O III 1666 / C III 1906,1909) correlates poorly with optically-derived metallicities. We discuss possible explanations for these discrepant metallicity determinations, including the hardness of the ionizing spectrum, contribution from stellar wind emission, and non-solar-scaled gas-phase abundances. Finally, we provide two new UV oxygen abundance diagnostics, calculated from polynomial fits to the model grid surface in the He2-O3C3 and Si3-O3C3 diagrams., Comment: ApJ accepted

The computation of excited electronic states with commonly employed (approximate) methods is challenging, typically yielding states of lower quality than the corresponding ground state for a higher computational cost. In this work, we present a mean field method that extends the previously proposed eXcited Constrained DFT (XCDFT) from single Slater determinants to ensemble 1-RDMs for computing low-lying excited states. The method still retains an associated computational complexity comparable to a semilocal DFT calculation while at the same time is capable of approaching states with multireference character. We benchmark the quality of this method on well-established test sets, finding good descriptions of the electronic structure of multireference states and maintaining an overall accuracy for the predicted excitation energies comparable to semilocal TDDFT.

We present MUSE Integral Field Unit (IFU) observations of five individual HII regions in two giant (>100 pc in radius) star-forming complexes in the low-metallicity ($Z$~0.33 $Z_{\odot}$) nearby (D ~ 2 Mpc) dwarf spiral galaxy NGC 300. We combine the IFU data with high spatial resolution HST photometry to demonstrate the extraction of stellar spectra and the classification of individual stars from ground-based data at the distance of 2 Mpc. For the two star-forming complexes, in which no O-type stars had previously been identified, we find a total of 13 newly identified O-type stars in the mass range 15-50 M$_{\odot}$, as well as 4 Wolf-Rayet stars. We use the derived massive stellar content to analyze the impact of stellar feedback on the HII regions. As already found for HII regions in the Magellanic Clouds, the dynamics of the analyzed NGC 300 HII regions are dominated by a combination of the pressure of the ionized gas and stellar winds. By comparing the derived ionized gas mass loading factors to the total gas mass loading factor across the NGC 300 disk, we find that the latter is an order of magnitude higher, either indicating very early evolutionary stages for these HII regions, or being a direct result of the multi-phase nature of feedback-driven bubbles. Moreover, we analyze the relation between the star formation rate and the pressure of the ionized gas as derived from small (<100 pc) scales, as both quantities are systematically overestimated when derived on galactic scales. With the wealth of ongoing and upcoming IFU instruments and programs, this study serves as a pathfinder for the systematic investigation of resolved stellar feedback in nearby galaxies, and it delivers the necessary analysis tools to enable massive stellar content and feedback studies sampling an unprecedented range of HII region properties across entire galaxies in the nearby Universe., Comment: Accepted for publication in ApJ

We study and compare different examples of stellar evolutionary synthesis input parameters used to produce photoionisation model grids using the MAPPINGS V modelling code. The aim of this study is to (a) explore the systematic effects of various stellar evolutionary synthesis model parameters on the interpretation of emission lines in optical strong-line diagnostic diagrams, (b) characterise the combination of parameters able to reproduce the spread of local galaxies located in the star-forming region in the Sloan Digital Sky Survey, and (c) investigate the emission from extremely metal-poor galaxies using photoionisation models. We explore and compare the stellar input ionising spectrum (stellar population synthesis code [Starburst99, SLUG, BPASS], stellar evolutionary tracks, stellar atmospheres, star-formation history, sampling of the initial mass function) as well as parameters intrinsic to the H II region (metallicity, ionisation parameter, pressure, H II region boundedness). We also perform a comparison of the photoionisation codes MAPPINGS and CLOUDY. On the variations in the ionising spectrum model parameters, we find that the differences in strong emission-line ratios between varying models for a given input model parameter are small, on average ~0.1 dex. An average difference of ~0.1 dex in emission-line ratio is also found between models produced with MAPPINGS and CLOUDY. Large differences between the emission-line ratios are found when comparing intrinsic H II region parameters. We find that low-metallicity galaxies are better explained by a density-bounded H II region and higher pressures better encompass the spread of galaxies at high redshift., Comment: 33 pages, 26 figures, accepted for publication in ApJ

Measuring the temperature and abundance patterns of clouds in the interstellar medium (ISM) provides an observational basis for models of the physical conditions within the clouds, which play an important role in studies of star and planet formation. The Colorado High-resolution Echelle Stellar Spectrograph (CHESS) is a far ultraviolet rocket-borne instrument designed to study the atomic-to-molecular transitions within diffuse molecular and translucent cloud regions. The final two flights of the instrument observed $\beta^{1}$ Scorpii ($\beta$ Sco) and $\gamma$ Arae. We present flight results of interstellar molecular hydrogen (H$_{\rm 2}$) excitation on the sightlines, including measurements of the column densities and temperatures. These results are compared to previous values that were measured using the damping wings of low J$^{\prime \prime}$ H$_{\rm 2}$ absorption features (Savage et al. 1977). For $\beta$ Sco, we find that the derived column density of the J$^{\prime \prime}$ = 1 rotational level differs by a factor of 2-3 when compared to the previous observations. We discuss the discrepancies between the two measurements and show that the source of the difference is due to the opacity of higher rotational levels contributing to the J$^{\prime \prime}$ = 1 absorption wing, increasing the inferred column density in the previous work. We extend this analysis to 9 $Copernicus$ and 13 $FUSE$ spectra to explore the interdependence of the column densities of different rotational levels and how the H$_{\rm 2}$ kinetic temperature is influenced by these relationships. We find a revised average gas kinetic temperature of the diffuse molecular ISM of T$_{01}$ = 68 $\pm$ 13 K, 12% lower than the value found previously., Comment: 20 pages, 10 Figures, Accepted in ApJ

Early type galaxies (ETGs) frequently show emission from warm ionized gas. These Low Ionization Emission Regions (LIERs) were originally attributed to a central, low-luminosity active galactic nuclei. However, the recent discovery of spatially-extended LIER emission suggests ionization by both a central source and an extended component that follows a stellar-like radial distribution. For passively-evolving galaxies with old stellar populations, hot post-Asymptotic Giant Branch (AGB) stars are the only viable extended source of ionizing photons. In this work, we present the first prediction of LIER-like emission from post-AGB stars that is based on fully self-consistent stellar evolution and photoionization models. We show that models where post-AGB stars are the dominant source of ionizing photons reproduce the nebular emission signatures observed in ETGs, including LIER-like emission line ratios in standard optical diagnostic diagrams and H$\alpha$ equivalent widths of order 0.1-3 angstroms. We test the sensitivity of LIER-like emission to the details of post-AGB models, including the mass loss efficiency and convective mixing efficiency, and show that line strengths are relatively insensitive to post-AGB timescale variations. Finally, we examine the UV-optical colors of the models and the stellar populations responsible for the UV-excess observed in some ETGs. We find that allowing as little as 3% of the HB population to be uniformly distributed to very hot temperatures (30,000 K) produces realistic UV colors for old, quiescent ETGs., Comment: ApJ accepted. 20 pages, 8 figures

Diagnosing the physical and chemical conditions within star-forming galaxies (SFGs) is of paramount importance to understanding key components of galaxy formation and evolution: star-formation, gas enrichment, outflows, and accretion. Well established optical emission-line diagnostics used to discern such properties (i.e., metal content, density, strength/shape of ionizing radiation) will be observationally inaccessible for the earliest galaxies, emphasizing the need for robust, reliable interstellar medium (ISM) diagnostics at ultraviolet (UV) wavelengths. Calibrating these UV diagnostics requires a comprehensive comparison of the UV and optical emission lines in nearby SFGs. Optical integral field unit (IFU) surveys have revealed the inhomogeneous nature of the ISM in SFGs, which leads to non-systematic biases in the interpretation of unresolved sources. Spatial variations are especially important to consider at UV wavelengths, where the strongest emission features originate from only the highest excitation regions of the nebula and are challenging to distinguish from competing high-ionization sources (e.g., shocks, AGN, etc.). Since surveys collecting large-scale optical integral field unit (IFU) spectroscopy are already underway, this white paper calls for an IFU or multi-object far-UV (FUV) spectroscopic instrument with high sensitivity, high spatial resolution, and large field of view (FoV). Given the impact of large-scale optical IFU surveys over the past decade, this white paper emphasizes the scientific need for a comparable foundation of spatially-resolved far-UV spectroscopy survey of nearby galaxies that will lay the foundation of diagnostics critical to the interpretation of the distant universe., Comment: Astro2020 White Paper

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (July 2014-July 2017). This is the third data release for SDSS-IV, and the fifteenth from SDSS (Data Release Fifteen; DR15). New data come from MaNGA - we release 4824 datacubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g. stellar and gas kinematics, emission line, and other maps) from the MaNGA Data Analysis Pipeline (DAP), and a new data visualisation and access tool we call "Marvin". The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials and examples of data use. While SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020-2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data., Comment: Paper to accompany DR15. 25 pages, 6 figures. Accepted for publication in ApJSS. The two papers on the MaNGA Data Analysis Pipeline (DAP, Westfall et al. and Belfiore et al., see Section 4.1.2), and the paper on Marvin (Cherinka et al., see Section 4.2) have been submitted for collaboration review and will be posted to arXiv in due course. v2 fixes some broken URLs in the PDF

In this note, we construct a distal expansion for the structure $(\mathbb{R}; +,<,H)$, where $H\subseteq \mathbb{R}$ is a dense $\mathbb{Q}$-vector space basis of $\mathbb{R}$ (a so-called Hamel basis). Our construction is also an expansion of the dense pair $(\mathbb{R}; +,<,\mathbb{Q})$ and has full quantifier elimination in a natural language.

We analyze far-ultraviolet spectra and ancillary data of the super star cluster SSC-N and its surrounding H II region in the nearby dwarf galaxy II Zw 40. From the ultraviolet spectrum, we derive a low internal reddening of E(B-V) = 0.07 +/- 0.03, a mass of (9.1 +/- 1.0) x 10^5 Lsol, a bolometric luminosity of (1.1 +/- 0.1) x 10^9 Lsol, a number of ionizing photons of (6 +/- 2) x 10^52 s^-1, and an age of (2.8 +/- 0.1) Myr. These parameters agree with the values derived from optical and radio data, indicating no significant obscured star formation, absorption of photons by dust, or photon leakage. SSC-N and its nebulosity are an order of magnitude more massive and luminous than 30 Doradus and its ionizing cluster. Photoionization modeling suggests a high ionization parameter and a C/O ratio where C is between primary and secondary. We calculate diagnostic emission-line ratios and compare SSC-N to local star-forming galaxies. The SSC-N nebula does not coincide with the locus defined by local galaxies. Rather, it coincides with the location of "Green Pea" galaxies, objects which are often considered nearby analogs of the galaxies reionizing the universe. Most stellar features are well-reproduced by synthetic spectra. However, the SSC-N cluster has strong, broad, stellar He II 1640 emission that cannot be reproduced, suggesting a deficit of He-enhanced stars with massive winds in the models. We discuss possible sources for the broad He II emission, including very massive stars and/or enhanced mixing processes., Comment: The Astrophysical Journal, accepted

Performance optimization for large-scale applications has recently become more important as computation continues to move towards data centers. Data-center applications are generally very large and complex, which makes code layout an important optimization to improve their performance. This has motivated recent investigation of practical techniques to improve code layout at both compile time and link time. Although post-link optimizers had some success in the past, no recent work has explored their benefits in the context of modern data-center applications. In this paper, we present BOLT, a post-link optimizer built on top of the LLVM framework. Utilizing sample-based profiling, BOLT boosts the performance of real-world applications even for highly optimized binaries built with both feedback-driven optimizations (FDO) and link-time optimizations (LTO). We demonstrate that post-link performance improvements are complementary to conventional compiler optimizations, even when the latter are done at a whole-program level and in the presence of profile information. We evaluated BOLT on both Facebook data-center workloads and open-source compilers. For data-center applications, BOLT achieves up to 8.0% performance speedups on top of profile-guided function reordering and LTO. For the GCC and Clang compilers, our evaluation shows that BOLT speeds up their binaries by up to 20.4% on top of FDO and LTO, and up to 52.1% if the binaries are built without FDO and LTO.

In the face of shifting means of production from manual human labor to labor automation, one solution that stands out is the advancement of a Universal Basic Income, UBI to every citizen from the government with no strings attached. The proposal, however, has encountered sharp criticism from different quarters questioning the morality behind sourcing of funds, largely through taxation, to uphold an institution designed to provide social support. Others also perceive the idea as a form of socialism, or a capitalist road to communism. The current discussion, however, seeks to demonstrate that the provision of such stipend can occur through the utilization of revenues realized from production driven by Artificial Intelligence (AI), and to a small extent, philanthropic contributions from the top 1 percent of the population., Comment: 5 pages

There is a long history of using optical emission and absorption lines to constrain the metallicity and ionization parameters of gas in galaxies. However, comparable diagnostics are less well-developed for the UV. Here, we assess the diagnostic potential of both absorption and emission features in the UV and evaluate the diagnostics against observations of local and high redshift galaxies. We use the CloudyFSPS nebular emission model of Byler et al. 2017, extended to include emission predictions in the UV, to evaluate the metallicity sensitivity of established UV stellar absorption indices, and to identify those that include a significant contribution from nebular emission. We present model UV emission line fluxes as a function of metallicity and ionization parameter, assuming both instantaneous bursts and constant SFRs. We identify combinations of strong emission lines that constrain metallicity and ionization parameter, including [CIII] 1907, CIII] 1909, OIII] 1661,1666, SiIII]1883,1892, CIV 1548,1551, NII] 1750,1752, and MgII 2796, and develop UV versions of the canonical "BPT" diagram. We quantify the relative contribution from stellar wind emission and nebular line emission to diagnostic line ratios that include the CIV 1548,1551 lines, and also develop an observationally motivated relationship for N and C enrichment that improves the performance of photoionization models. We summarize the best diagnostic choices and the associated redshift range for low-, mid-, and high-resolution rest-UV spectroscopy in preparation for the launch of the James Webb Space Telescope.

The aim of this work is an analysis of distal and non-distal behavior in dense pairs of o-minimal structures. A characterization of distal types is given through orthogonality to a generic type in $M^{\operatorname{eq}}$, non-distality is geometrically analyzed through Keisler measures, and a distal expansion for the case of pairs of ordered vector spaces is computed.

The Colorado Ultraviolet Transit Experiment (CUTE) is a near-UV (2550 - 3300 Angstrom) 6U cubesat mission designed to monitor transiting hot Jupiters to quantify their atmospheric mass loss and magnetic fields. CUTE will probe both atomic (Mg and Fe) and molecular (OH) lines for evidence of enhanced transit absorption, and to search for evidence of early ingress due to bow shocks ahead of the planet's orbital motion. As a dedicated mission, CUTE will observe more than 100 spectroscopic transits of hot Jupiters over a nominal seven month mission. This represents the equivalent of more than 700 orbits of the only other instrument capable of these measurements, the Hubble Space Telescope. CUTE efficiently utilizes the available cubesat volume by means of an innovative optical design to achieve a projected effective area of 28 sq. cm, low instrumental background, and a spectral resolving power of 3000 over the primary science bandpass. These performance characteristics enable CUTE to discern transit depths between 0.1 - 1% in individual spectral absorption lines. We present the CUTE optical and mechanical design, a summary of the science motivation and expected results, and an overview of the projected fabrication, calibration and launch timeline., Comment: Accepted for publication in the Journal of Astronomical Telescopes, Instruments and Systems

Let $T$ be a consistent o-minimal theory extending the theory of densely ordered groups and let $T'$ be a consistent theory. Then there is a complete theory $T^*$ extending $T$ such that $T$ is an open core of $T^*$, but every model of $T^*$ interprets a model of $T'$. If $T'$ is NIP, $T^*$ can be chosen to be NIP as well. From this we deduce the existence of an NIP expansion of the real field that has no distal expansion.

We investigate the integrated properties of massive (>10 Msun), rotating, single-star stellar populations for a variety of initial rotation rates (v/vcrit=0.0, 0.2, 0.4, 0.5, and 0.6). We couple the new MESA Isochrone and Stellar Tracks (MIST) models to the Flexible Stellar Population Synthesis (FSPS) package, extending the stellar population synthesis models to include the contributions from very massive stars (>100 Msun), which can be significant in the first ~4 Myr after a starburst. These models predict ionizing luminosities that are consistent with recent observations of young nuclear star clusters. We also construct composite stellar populations assuming a distribution of initial rotation rates. Even in low-metallicity environments where rotation has a significant effect on the evolution of massive stars, we find that stellar population models require a significant contribution from fast-rotating (v/vcrit>0.4) stars in order to sustain the production of ionizing photons beyond a few Myr following a starburst. These results have potentially important implications for cosmic reionization by massive stars and the interpretation of nebular emission lines in high-redshift star-forming galaxies., Comment: 16 pages, 17 figures. Resubmitted to ApJ following a referee report