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Gravitational lensing magnification of Type Ia supernovae (SNe Ia) allows information to be obtained about the distribution of matter on small scales. In this paper, we derive limits on the fraction $\alpha$ of the total matter density in compact objects (which comprise stars, stellar remnants, small stellar groupings and primordial black holes) of mass $M > 0.03 M_{\odot}$ over cosmological distances. Using 1,532 SNe Ia from the Dark Energy Survey Year 5 sample (DES-SN5YR) combined with a Bayesian prior for the absolute magnitude $M$, we obtain $\alpha < 0.12$ at the 95\% confidence level after marginalisation over cosmological parameters, lensing due to large-scale structure, and intrinsic non-Gaussianity. Similar results are obtained using priors from the cosmic microwave background, baryon acoustic oscillations and galaxy weak lensing, indicating our results do not depend on the background cosmology. We argue our constraints are likely to be conservative (in the sense of the values we quote being higher than the truth), but discuss scenarios in which they could be weakened by systematics of the order of $\Delta \alpha \sim 0.04$, Comment: Submitted to MNRAS

We present constraints on the $f(R)$ gravity model using a sample of 1,005 galaxy clusters in the redshift range $0.25 - 1.78$ that have been selected through the thermal Sunyaev-Zel'dovich effect (tSZE) from South Pole Telescope (SPT) data and subjected to optical and near-infrared confirmation with the Multi-component Matched Filter (MCMF) algorithm. We employ weak gravitational lensing mass calibration from the Dark Energy Survey (DES) Year 3 data for 688 clusters at $z < 0.95$ and from the Hubble Space Telescope (HST) for 39 clusters with $0.6 < z < 1.7$. Our cluster sample is a powerful probe of $f(R)$ gravity, because this model predicts a scale-dependent enhancement in the growth of structure, which impacts the halo mass function (HMF) at cluster mass scales. To account for these modified gravity effects on the HMF, our analysis employs a semi-analytical approach calibrated with numerical simulations. Combining calibrated cluster counts with primary cosmic microwave background (CMB) temperature and polarization anisotropy measurements from the Planck2018 release, we derive robust constraints on the $f(R)$ parameter $f_{R0}$. Our results, $\log_{10} |f_{R0}| < -5.32$ at the 95 % credible level, are the tightest current constraints on $f(R)$ gravity from cosmological scales. This upper limit rules out $f(R)$-like deviations from general relativity that result in more than a $\sim$20 % enhancement of the cluster population on mass scales $M_\mathrm{200c}>3\times10^{14}M_\odot$., Comment: 21 pages, 6 figures, submitted to Phys. Rev. D

Using a sample of 2800 galaxy clusters identified in the Dark Energy Survey across the redshift range $0.20 < z < 0.60$, we characterize the hierarchical assembly of Bright Central Galaxies (BCGs) and the surrounding intracluster light (ICL). To quantify hierarchical formation we use the stellar mass - halo mass (SMHM) relation for the BCG+ICL system and incorporate the magnitude gap (M14), the difference in brightness between the BCG (measured within 30kpc) and 4th brightest cluster member galaxy within 0.5 $R_{200,c}$. The inclusion of M14, which traces BCG hierarchical growth, increases the slope and decreases the intrinsic scatter in the SMHM relation, highlighting that it is a latent variable within the BCG+ICL SMHM relation. Moreover, the correlation with M14 decreases at large radii from the BCG's centre. However, the stellar light within the BCG+ICL transition region (30kpc - 80kpc) most strongly correlates with the dark matter halo mass and has a statistically significant correlation with M14. As the light in the transition region and M14 are independent measurements, the transition region may grow as a result of the BCG's hierarchical two-phase formation. Additionally, as M14 and ICL result from hierarchical growth, we use a stacked sample and find that clusters with large M14 values are characterized by larger ICL and BCG+ICL fractions, which illustrates that the merger processes that build the BCG stellar mass also grow the ICL. Furthermore, this may suggest that M14 combined with the ICL fraction can be used as a method to identify dynamically relaxed clusters., Comment: 16 pages, 5 Figures, submitted to MNRAS on 8/30/2024

Using 1533 type Ia supernovae (SNe Ia) from the five-year sample of the Dark Energy Survey (DES), we investigate the effects of projected galactocentric separation between the SNe and their host galaxies on their light curves and standardization. We show, for the first time, that the difference in SN Ia post-standardization brightnesses between high and low-mass hosts reduces from $0.078\pm0.011$ mag in the full sample to $0.036 \pm 0.018$ mag for SNe Ia located in the outer regions of their host galaxies, while increasing to $0.100 \pm 0.014$ mag for SNe in the inner regions. In these inner regions, the step can be reduced (but not removed) using a model where the $R_V$ of dust along the line-of-sight to the SN changes as a function of galaxy properties. To explain the remaining difference, we use the distributions of the SN Ia stretch parameter to test whether the inferred age of SN progenitors are more varied in the inner regions of galaxies. We find that the proportion of high-stretch SNe Ia in red (older) environments is more prominent in outer regions and that the outer regions stretch distributions are overall more homogeneous compared to inner regions, but conclude that this effect cannot explain the reduction in significance of any Hubble residual step in outer regions. We conclude that the standardized distances of SNe Ia located in the outer regions of galaxies are less affected by their global host galaxy properties than those in the inner regions., Comment: 17 pages, 13 figures

The present state of cosmology is facing a crisis where there is a fundamental disagreement in measurements of the Hubble constant ($H_{0}$), with significant tension between the early and late universe methods. Type Ia supernovae (SNe Ia) are important to measuring $H_{0}$ through the astronomical distance ladder. However, there remains potential to better standardise SN Ia light curves by using known dependencies on host galaxy properties after the standard light curve width and colour corrections have been applied to the peak SN Ia luminosities. To explore this, we use the 5-year photometrically identified SNe Ia sample obtained by the Dark Energy Survey, along with host galaxy spectra obtained by the Australian Dark Energy Survey. Using host galaxy spectroscopy, we find a significant trend with the equivalent width (EW) of the [OII] $\lambda\lambda$ 3727, 29 doublet, a proxy for specific star formation rate, and Hubble residuals. We find that the correlation with [OII] EW is a powerful alternative to the commonly used mass step after initial light curve corrections. We applied our [OII] EW correction to a sample of 20 SN Ia hosted by calibrator galaxies observed using WiFeS, and examined the impact on both the SN Ia absolute magnitude and $H_{0}$. We then explored different [OII] EW corrections and found $H_{0}$ values ranging between $72.80$ to $73.28~\mathrm{km} \mathrm{s}^{-1} \mathrm{Mpc}^{-1}$. Notably, even after using an additional [OII] EW correction, the impact of host galaxy properties in standardising SNe Ia appears limited in reducing the current tension ($\sim$5$\sigma$) with the Cosmic Microwave Background result for $H_{0}$., Comment: 16 pages, 13 figures. Submitting to MNRAS

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})<11.51$. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at $\log(M_\mathrm{host}/M_\odot) < 11.84$. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs., Comment: 16 pages, 15 figures

Cosmological analyses with Type Ia Supernovae (SNe Ia) have traditionally been reliant on spectroscopy for both classifying the type of supernova and obtaining reliable redshifts to measure the distance-redshift relation. While obtaining a host-galaxy spectroscopic redshift for most SNe is feasible for small-area transient surveys, it will be too resource intensive for upcoming large-area surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time, which will observe on the order of millions of SNe. Here we use data from the Dark Energy Survey (DES) to address this problem with photometric redshifts (photo-z) inferred directly from the SN light-curve in combination with Gaussian and full p(z) priors from host-galaxy photo-z estimates. Using the DES 5-year photometrically-classified SN sample, we consider several photo-z algorithms as host-galaxy photo-z priors, including the Self-Organizing Map redshifts (SOMPZ), Bayesian Photometric Redshifts (BPZ), and Directional-Neighbourhood Fitting (DNF) redshift estimates employed in the DES 3x2 point analyses. With detailed catalog-level simulations of the DES 5-year sample, we find that the simulated w can be recovered within $\pm$0.02 when using SN+SOMPZ or DNF prior photo-z, smaller than the average statistical uncertainty for these samples of 0.03. With data, we obtain biases in w consistent with simulations within ~1$\sigma$ for three of the five photo-z variants. We further evaluate how photo-z systematics interplay with photometric classification and find classification introduces a subdominant systematic component. This work lays the foundation for next-generation fully photometric SNe Ia cosmological analyses., Comment: 19 pages, 9 figures. Submitting to MNRAS, comments welcome

We present a study of the weak lensing matter profiles of 698 South Pole Telescope (SPT) thermal Sunyaev-Zel'dovich effect (tSZE) selected galaxy clusters in the redshift range $0.25

We report on Chandra X-ray observations of SN 2016jae and SN 2018cqj, both low luminosity Type Ia supernova that showed the presence of a H line in their early optical spectrum. No X-ray emission is detected at the location of either SN. Upper limits to the luminosity of up to 2 $\times 10^{40}\,$ erg s$^{-1}$ are calculated for each SN, depending on the assumed spectral model, temperature and column density. This luminosity is comparable to that of another low-luminosity Type Ia SN, SN 2018fhw, that was observed with Chandra. It is generally lower than upper limits calculated for Type Ia-CSM SNe observed in X-rays, and also below that of SN 2012ca, the only Type Ia-CSM SN to have been detected in X-rays. Comparisons are made to other Type Ia SN with a H line observed in X-rays. The observations suggest that while the density into which the SN is expanding may have been high at the time the H$\alpha$ line was detected, it had decreased considerably by the time of X-ray observations., Comment: 9 pages, 4 figures and 3 Tables. Accepted to MNRAS. arXiv admin note: text overlap with arXiv:2211.09274

We present $griz$ photometric light curves for the full 5 years of the Dark Energy Survey Supernova program (DES-SN), obtained with both forced Point Spread Function (PSF) photometry on Difference Images (DIFFIMG) performed during survey operations, and Scene Modelling Photometry (SMP) on search images processed after the survey. This release contains $31,636$ DIFFIMG and $19,706$ high-quality SMP light curves, the latter of which contains $1635$ photometrically-classified supernovae that pass cosmology quality cuts. This sample spans the largest redshift ($z$) range ever covered by a single SN survey ($0.1

Type Ia Supernovae (SNe Ia) are a critical tool in measuring the accelerating expansion of the universe. Recent efforts to improve these standard candles have focused on incorporating the effects of dust on distance measurements with SNe Ia. In this paper, we use the state-of-the-art Dark Energy Survey 5 year sample to evaluate two different families of dust models: empirical extinction models derived from SNe Ia data, and physical attenuation models from the spectra of galaxies. Among the SNe Ia-derived models, we find that a logistic function of the total-to-selective extinction RV best recreates the correlations between supernova distance measurements and host galaxy properties, though an additional 0.02 magnitudes of grey scatter are needed to fully explain the scatter in SNIa brightness in all cases. These empirically-derived extinction distributions are highly incompatible with the physical attenuation models from galactic spectral measurements. From these results, we conclude that SNe Ia must either preferentially select extreme ends of galactic dust distributions, or that the characterisation of dust along the SNe Ia line-of-sight is incompatible with that of galactic dust distributions.

Commensurability phenomena abound in nature and are typically associated with mismatched lengths, as can occur in quasiperiodic systems. However, not all commensuration effects are spatial in nature. In finite-sized Dirac systems, an intriguing example arises in tilted or warped Dirac cones wherein the degeneracy in the speed of right- and left-moving electrons within a given Dirac cone or valley is lifted. Bound states can be purely fast-moving or purely slow-moving, giving rise to incommensurate energy level spacings and a vernier spectrum. In this work, we present evidence for this vernier spectrum in Coulomb blockade measurements of ultraclean suspended carbon nanotube quantum dots. The addition-energy spectrum of the quantum dots reveals an energy-level structure that oscillates between aligned and misaligned energy levels. Our data suggest that the fast- and slow-moving bound states hybridize at certain gate voltages. Thus, gate-voltage tuning can select states with varying degrees of hybridization, suggesting numerous applications based on accessing this isospin-like degree of freedom., Comment: 14 pages including 3 figures

The detection of gravitational waves from a binary neutron star merger by Advanced LIGO and Advanced Virgo (GW170817), along with the discovery of the electromagnetic counterparts of this gravitational wave event, ushered in a new era of multimessenger astronomy, providing the first direct evidence that BNS mergers are progenitors of short gamma-ray bursts (GRBs). Such events may also produce very-high-energy (VHE, > 100GeV) photons which have yet to be detected in coincidence with a gravitational wave signal. The Cherenkov Telescope Array (CTA) is a next-generation VHE observatory which aims to be indispensable in this search, with an unparalleled sensitivity and ability to slew anywhere on the sky within a few tens of seconds. New observing modes and follow-up strategies are being developed for CTA to rapidly cover localization areas of gravitational wave events that are typically larger than the CTA field of view. This work will evaluate and provide estimations on the expected number of of gravitational wave events that will be observable with CTA, considering both on- and off-axis emission. In addition, we will present and discuss the prospects of potential follow-up strategies with CTA., Comment: Presented at the 38th International Cosmic Ray Conference (ICRC 2023), 2023 (arXiv:2309.08219)

I report on Chandra X-ray observations of SN 2018cqj, a low luminosity Type Ia supernova that showed an H$\alpha$ line in its optical spectrum. No X-ray emission was detected at the location of the SN, with an upper limit to the X-ray luminosity of 2 $\times 10^{39}$ erg s$^{-1}$., Comment: 3 pages, 1 table. Published in RNAAS

The structure and evolution of wind-blown bubbles (WBBs) around massive stars has primarily been investigated using an energy-conserving model of wind-blown bubbles. While this model is useful in explaining the general properties of the evolution, several problems remain, including inconsistencies between observed wind luminosities and those derived using this formulation. Major difficulties include the low X-ray temperature and X-ray luminosity, compared to the model. In this paper, we re-examine the evolution, dynamics, and kinematics of WBBs around massive stars, using published ionization gasdynamic simulations of wind-blown bubbles. We show that WBBs can cool efficiently due to the presence of various instabilities and turbulence within the bubble. The expansion of WBBs is more consistent with a momentum-conserving solution, rather than an energy-conserving solution. This compares well with the dynamics and kinematics of observed wind bubbles. Despite the cooling of the bubble, the shocked wind temperature is not reduced to the observed values. We argue that the X-ray emission arise mainly from clumps and filaments within the hot shocked wind region, with temperatures just above 10$^6$ K. The remainder of the plasma can contribute to a lesser extent., Comment: 22 pages, 7 figures. Published in Galaxies. Only low-resolution figures are included due to size requirements; original high-resolution figures, especially Figure 1, can be obtained from the published paper in the journal

Concept-based explanations for convolutional neural networks (CNNs) aim to explain model behavior and outputs using a pre-defined set of semantic concepts (e.g., the model recognizes scene class ``bedroom'' based on the presence of concepts ``bed'' and ``pillow''). However, they often do not faithfully (i.e., accurately) characterize the model's behavior and can be too complex for people to understand. Further, little is known about how faithful and understandable different explanation methods are, and how to control these two properties. In this work, we propose UFO, a unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations. UFO formalizes understandability and faithfulness as mathematical objectives and unifies most existing concept-based explanations methods for CNNs. Using UFO, we systematically investigate how explanations change as we turn the knobs of faithfulness and understandability. Our experiments demonstrate a faithfulness-vs-understandability tradeoff: increasing understandability reduces faithfulness. We also provide insights into the ``disagreement problem'' in explainable machine learning, by analyzing when and how concept-based explanations disagree with each other.

Current dataset collection methods typically scrape large amounts of data from the web. While this technique is extremely scalable, data collected in this way tends to reinforce stereotypical biases, can contain personally identifiable information, and typically originates from Europe and North America. In this work, we rethink the dataset collection paradigm and introduce GeoDE, a geographically diverse dataset with 61,940 images from 40 classes and 6 world regions, and no personally identifiable information, collected through crowd-sourcing. We analyse GeoDE to understand differences in images collected in this manner compared to web-scraping. Despite the smaller size of this dataset, we demonstrate its use as both an evaluation and training dataset, highlight shortcomings in current models, as well as show improved performances when even small amounts of GeoDE (1000 - 2000 images per region) are added to a training dataset. We release the full dataset and code at https://geodiverse-data-collection.cs.princeton.edu/

We report on Chandra X-ray observations of ASASSN-18tb/SN 2018fhw, a low luminosity Type Ia supernova that showed a H line in its optical spectrum. No X-ray emission was detected at the location of the SN. Upper limits to the luminosity of up to 3 $\times 10^{39}$ erg s$^{-1}$ are calculated, depending on the assumed spectral model, temperature and column density. These are compared to two Type Ia-CSM SNe, SN 2005gj and SN 2002ic, that have been observed with Chandra in the past. The upper limits are lower than the X-ray luminosity found for the Type Ia-CSM SN 2012ca, the only Type Ia SN to have been detected in X-rays. Consideration of various scenarios for the H$\alpha$ line suggests that the density of the surrounding medium at the time of H$\alpha$ line detection could have been as high as 10$^8$ cm$^{-3}$, but must have decreased below 5 $\times\, 10^6$ cm$^{-3}$ at the time of X-ray observation. Continual X-ray observations of SNe which show a H line in their spectrum are necessary in order to establish Type Ia SNe as an X-ray emitting class., Comment: 9 pages, 1 figure, 3 tables. Accepted to MNRAS

We present broadband radio flux-density measurements supernova (SN) 1996cr, made with MeerKAT, ATCA and ALMA, and images made from very long baseline interferometry (VLBI) observations with the Australian Long Baseline Array. The spectral energy distribution of SN 1996cr in 2020, at age, $t \sim$8700 d, is a power-law, with flux density, $S \propto \nu^{-0.588 \pm 0.011}$ between 1 and 34 GHz, but may steepen at $>35$ GHz. The spectrum has flattened since $t = 5370$ d (2010). Also since $t = 5370$ d, the flux density has declined rapidly, with $S_{\rm 9 \, GHz} \propto t^{-2.9}$. The VLBI image at $t = 8859$ d shows an approximately circular structure, with a central minimum reminiscent of an optically-thin spherical shell of emission. For a distance of 3.7 Mpc, the average outer radius of the radio emission at $t = 8859$ d was $(5.1 \pm 0.3) \times 10^{17}$ cm, and SN 1996cr has been expanding with a velocity of $4650 \pm 1060$ km s$^{-1}$ between $t=4307$ and 8859 d. It must have undergone considerable deceleration before $t = 4307$ d. Deviations from a circular shell structure in the image suggest a range of velocities up to $\sim$7000 km s$^{-1}$, and hint at the presence of a ring- or equatorial-belt-like structure rather than a complete spherical shell., Comment: 10 Pages, 5 figures; Accepted for publication in MNRAS; this version (3) differs from version 2 by further minor revision

Concept-based interpretability methods aim to explain deep neural network model predictions using a predefined set of semantic concepts. These methods evaluate a trained model on a new, "probe" dataset and correlate model predictions with the visual concepts labeled in that dataset. Despite their popularity, they suffer from limitations that are not well-understood and articulated by the literature. In this work, we analyze three commonly overlooked factors in concept-based explanations. First, the choice of the probe dataset has a profound impact on the generated explanations. Our analysis reveals that different probe datasets may lead to very different explanations, and suggests that the explanations are not generalizable outside the probe dataset. Second, we find that concepts in the probe dataset are often less salient and harder to learn than the classes they claim to explain, calling into question the correctness of the explanations. We argue that only visually salient concepts should be used in concept-based explanations. Finally, while existing methods use hundreds or even thousands of concepts, our human studies reveal a much stricter upper bound of 32 concepts or less, beyond which the explanations are much less practically useful. We make suggestions for future development and analysis of concept-based interpretability methods. Code for our analysis and user interface can be found at \url{https://github.com/princetonvisualai/OverlookedFactors}, Comment: Published at CVPR 2023

Gender biases are known to exist within large-scale visual datasets and can be reflected or even amplified in downstream models. Many prior works have proposed methods for mitigating gender biases, often by attempting to remove gender expression information from images. To understand the feasibility and practicality of these approaches, we investigate what $\textit{gender artifacts}$ exist within large-scale visual datasets. We define a $\textit{gender artifact}$ as a visual cue that is correlated with gender, focusing specifically on those cues that are learnable by a modern image classifier and have an interpretable human corollary. Through our analyses, we find that gender artifacts are ubiquitous in the COCO and OpenImages datasets, occurring everywhere from low-level information (e.g., the mean value of the color channels) to the higher-level composition of the image (e.g., pose and location of people). Given the prevalence of gender artifacts, we claim that attempts to remove gender artifacts from such datasets are largely infeasible. Instead, the responsibility lies with researchers and practitioners to be aware that the distribution of images within datasets is highly gendered and hence develop methods which are robust to these distributional shifts across groups., Comment: ICCV 2023

Deep learning models have achieved remarkable success in different areas of machine learning over the past decade; however, the size and complexity of these models make them difficult to understand. In an effort to make them more interpretable, several recent works focus on explaining parts of a deep neural network through human-interpretable, semantic attributes. However, it may be impossible to completely explain complex models using only semantic attributes. In this work, we propose to augment these attributes with a small set of uninterpretable features. Specifically, we develop a novel explanation framework ELUDE (Explanation via Labelled and Unlabelled DEcomposition) that decomposes a model's prediction into two parts: one that is explainable through a linear combination of the semantic attributes, and another that is dependent on the set of uninterpretable features. By identifying the latter, we are able to analyze the "unexplained" portion of the model, obtaining insights into the information used by the model. We show that the set of unlabelled features can generalize to multiple models trained with the same feature space and compare our work to two popular attribute-oriented methods, Interpretable Basis Decomposition and Concept Bottleneck, and discuss the additional insights ELUDE provides.

The antiferromagnetic topological insulator MnBi2Te4 (MBT) exhibits an ideal platform to study exotic topological phenomena and magnetic properties. The transport signatures of magnetic phase transitions in the MBT family materials have been well-studied. However, their mechanical properties and magneto-mechanical coupling have not been well-explored. We use nanoelectromechanical systems to study the intrinsic magnetism in MBT thin flakes via their magnetostrictive coupling. We investigate mechanical resonance signatures of magnetic phase transitions from antiferromagnetic (AFM) to canted antiferromagnetic (cAFM) to ferromagnetic (FM) phases versus magnetic field at different temperatures. The spin-flop transitions in MBT are revealed by frequency shifts of mechanical resonance. With temperatures going above TN, the transitions disappear in the resonance frequency map, consistent with transport measurements. We use a magnetostrictive model to correlate the frequency shifts with the spin-canting states. Our work demonstrates a technique to study magnetic phase transitions, magnetization and magnetoelastic properties of the magnetic topological insulator.

We demonstrate advantages of samples made by mechanical stacking of exfoliated van der Waals materials for controlling the topological surface state of a 3-dimensional topological insulator (TI) via interaction with an adjacent magnet layer. We assemble bilayers with pristine interfaces using exfoliated flakes of the TI BiSbTeSe2 and the magnet Cr2Ge2Te6, thereby avoiding problems caused by interdiffusion that can affect interfaces made by top-down deposition methods. The samples exhibit an anomalous Hall effect (AHE) with abrupt hysteretic switching. For the first time in samples composed of a TI and a separate ferromagnetic layer, we demonstrate that the amplitude of the AHE can be tuned via gate voltage with a strong peak near the Dirac point. This is the signature expected for the AHE due to Berry curvature associated with an exchange gap induced by interaction between the topological surface state and an out-of-plane-oriented magnet., Comment: submitted version

We probe the environmental properties of X-ray supernova remnants (SNRs) at various points along their evolutionary journey, especially the S-T phase, and their conformance with theoretically derived models of SNR evolution. The remnant size is used as a proxy for the age of the remnant. Our data set includes 34 Milky Way, 59 Large Magellanic Cloud (LMC), and 5 Small Magellanic Cloud (SMC) SNRs. We select remnants that have been definitively typed as either core-collapse (CC) or Type Ia supernovae, with well-defined size estimates, and a thermal X-ray flux measured over the entire remnant. A catalog of SNR size and X-ray luminosity is presented and plotted, with ambient density and age estimates from the literature. Model remnants with a given density, in the Sedov-Taylor (S-T) phase, are overplotted on the diameter-vs-luminosity plot, allowing the evolutionary state and physical properties of SNRs to be compared to each other, and to theoretical models. We find that small, young remnants are predominantly Type Ia remnants or high luminosity CCs, suggesting that many CC SNRs are not detected until after they have emerged from the progenitor's wind-blown bubble. An examination of the distribution of SNR diameters in the Milky Way and LMC reveals that LMC SNRs must be evolving in an ambient medium which is 30% as dense as that in the Milky Way. This is consistent with ambient density estimates for the Galaxy and LMC., Comment: 22 pages, 6 figures. Accepted to MNRAS. Online version of Fig 2 with all SNR names is available at https://voices.uchicago.edu/vikramvd/snrspaper/

Research in machine learning fairness has historically considered a single binary demographic attribute; however, the reality is of course far more complicated. In this work, we grapple with questions that arise along three stages of the machine learning pipeline when incorporating intersectionality as multiple demographic attributes: (1) which demographic attributes to include as dataset labels, (2) how to handle the progressively smaller size of subgroups during model training, and (3) how to move beyond existing evaluation metrics when benchmarking model fairness for more subgroups. For each question, we provide thorough empirical evaluation on tabular datasets derived from the US Census, and present constructive recommendations for the machine learning community. First, we advocate for supplementing domain knowledge with empirical validation when choosing which demographic attribute labels to train on, while always evaluating on the full set of demographic attributes. Second, we warn against using data imbalance techniques without considering their normative implications and suggest an alternative using the structure in the data. Third, we introduce new evaluation metrics which are more appropriate for the intersectional setting. Overall, we provide substantive suggestions on three necessary (albeit not sufficient!) considerations when incorporating intersectionality into machine learning., Comment: ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2022

SN 2014C was originally classified as a Type Ib supernova, but at phase {\phi} = 127 d post-explosion strong H{\alpha} emission was observed. SN 2014C has since been observed in radio, infrared, optical and X-ray bands. Here we present new optical spectroscopic and photometric data spanning {\phi} = 947 - 2494 d post-explosion. We address the evolution of the broadened H{\alpha} emission line, as well as broad [O III] emission and other lines. We also conduct a parallel analysis of all publicly available multi-wavelength data. From our spectra, we find a nearly constant H{\alpha} FWHM velocity width of {\sim}2000 km/s that is significantly lower than that of other broadened atomic transitions ({\sim}3000 - 7000 km/s) present in our spectra ([O I] {\lambda}6300; [O III] {\lambda}{\lambda}4959,5007; He I {\lambda}7065; [Ca II] {\lambda}{\lambda}7291,7324). The late radio data demand a fast forward shock ({\sim}10,000 km/s at {\phi} = 1700 d) in rarified matter that contrasts with the modest velocity of the H{\alpha}. We propose that the infrared flux originates from a toroidal-like structure of hydrogen surrounding the progenitor system, while later emission at other wavelengths (radio, X-ray) likely originates predominantly from the reverse shock in the ejecta and the forward shock in the quasi-spherical progenitor He wind. We propose that the H{\alpha} emission arises in the boundary layer between the ejecta and torus. We also consider the possible roles of a pulsar and a binary companion., Comment: 33 pages, 12 figures

Using a code that employs a self-consistent method for computing the effects of photo-ionization on circumstellar gas dynamics, we model the formation of wind-driven nebulae around massive stars. We take into account changes in stellar properties and mass-loss over the star's evolution. Our simulations show how various properties, such as the density and ionization fraction, change throughout the evolution of the star. The multi-dimensional simulations reveal the presence of strong ionization front instabilities in the main-sequence phase, similar to those seen in galactic ionization fronts. Hydrodynamic instabilities at the interfaces lead to the formation of filaments and clumps that are continually being stripped off and mixed with the low density interior. Even though the winds start out as completely radial, the spherical symmetry is quickly destroyed, and the shocked wind region is manifestly asymmetrical. The simulations demonstrate that it is important to include the effects of the photoionizing photons from the star, and simulations that do not include this may fail to reproduce the observed density profile and ionization structure of wind-blown bubbles around massive stars., Comment: 3 figures, 1 table. 13 pages. Author version of published paper, with reduced size figures 2 and 3. For full resolution figures see the published paper at https://www.mdpi.com/2075-4434/10/1/37. Accepted to Galaxies. This article belongs to the special issue of the conference Asymmetrical Post Main-Sequence Nebulae 8