Search

We use data from the applications North Carolina public school districts and charter schools submitted for Elementary and Secondary School Emergency Relief (ESSER) to investigate the sense that educational leaders made of the pandemic as it unfolded. LEAs understood the pandemic as a multifaceted problem. Nearly all applications addressed four problems: (1) public health, (2) academics and learning loss, (3) student and community well-being, and (4) instructional access. However, we document considerable variation in problem emphasis over time, across LEAs, and across organizational sector. The pandemic was not a single organizational problem, but many simultaneous problems posed in varying and shifting combinations. We argue this multi-faceted organizational view should be a starting point for assessments of LEAs' pandemic response.

Particle discretizations of partial differential equations are advantageous for high-dimensional kinetic models in phase space due to their better scalability than continuum approaches with respect to dimension. Complex processes collectively referred to as \textit{particle noise} hamper long-time simulations with particle methods. One approach to address this problem is particle mesh adaptivity or remapping, known as \textit{particle resampling}. This paper introduces a resampling method that projects particles to and from a (finite element) function space. The method is simple; using standard sparse linear algebra and finite element techniques, it can adapt to almost any set of new particle locations and preserves all moments up to the order of polynomial represented exactly by the continuum function space. This work is motivated by the Vlasov-Maxwell-Landau model of magnetized plasmas with up to six dimensions, $3X$ in physical space and $3V$ in velocity space, and is developed in the context of a $1X$ + $1V$ Vlasov-Poisson model of Landau damping with logically regular particle and continuum phase space grids. The evaluation codes are publicly available, along with the data and reproducibility artifacts, and developed in the PETSc numerical library.

The intense magnetic fields of neutron stars naturally lead to strong anisotropy and polarization of radiation emanating from their surfaces, both being sensitive to the hot spot position on the surface. Accordingly, pulse phase-resolved intensities and polarizations depend on the angle between the magnetic and spin axes and the observer's viewing direction. In this paper, results are presented from a Monte Carlo simulation of neutron star atmospheres that uses a complex electric field vector formalism to treat polarized radiative transfer due to magnetic Thomson scattering. General relativistic influences on the propagation of light from the stellar surface to a distant observer are taken into account. The paper outlines a range of theoretical predictions for pulse profiles at different X-ray energies, focusing on magnetars and also neutron stars of lower magnetization. By comparing these models with observed intensity and polarization pulse profiles for the magnetar 1RXS J1708-40, and the light curve for the pulsar PSR J0821-4300, constraints on the stellar geometry angles and the size of putative polar cap hot spots are obtained., Comment: 6 pages, 3 figures, accepted for publication in Astronomische Nachrichten in the special issue for the XMM-Newton 2024 Science Workshop: The X-Ray Mysteries of Neutron Stars and White Dwarfs

Computed Tomography (CT) reconstruction of objects with cylindrical symmetry can be performed with a single projection. When the measured rays are parallel, and the axis of symmetry is perpendicular to the optical axis, the data can be modeled with the so-called Abel Transform. The Abel Transform has been extensively studied and many methods exist for accurate reconstruction. However, most CT geometries are cone-beam rather than parallel-beam. Using Abel methods for reconstruction in these cases can lead to distortions and reconstruction artifacts. Here, we develop analytic and model-based iterative reconstruction (MBIR) methods to reconstruct symmetric objects with an arbitrary axis of symmetry from a cone-beam geometry. The MBIR methods demonstrate superior results relative to the analytic inversion methods by mitigating artifacts and reducing noise while retaining fine image features. We demonstrate the efficacy of our methods using simulated and experimentally-acquired x-ray and neutron projections.

We present the detection and analysis of GRB 231115A, a candidate extragalactic magnetar giant flare (MGF) observed by Fermi/GBM and localized by INTEGRAL to the starburst galaxy M82. This burst exhibits distinctive temporal and spectral characteristics that align with known MGFs, including a short duration and a high peak energy. Gamma-ray analyses reveal significant insights into this burst, supporting conclusions already established in the literature: our time-resolved spectral studies provide further evidence that GRB 231115A is indeed a MGF. Significance calculations also suggest a robust association with M82, further supported by a high Bayes factor that minimizes the probability of chance alignment with a neutron star merger. Despite extensive follow-up efforts, no contemporaneous gravitational wave or radio emissions were detected. The lack of radio emission sets stringent upper limits on possible radio luminosity. Constraints from our analysis show no fast radio bursts (FRBs) associated with two MGFs. X-ray observations conducted post-burst by Swift/XRT and XMM/Newton provided additional data, though no persistent counterparts were identified. Our study underscores the importance of coordinated multi-wavelength follow-up and highlights the potential of MGFs to enhance our understanding of short GRBs and magnetar activities in the cosmos. Current MGF identification and follow-up implementation are insufficient for detecting expected counterparts; however, improvements in these areas may allow for the recovery of follow-up signals with existing instruments. Future advancements in observational technologies and methodologies will be crucial in furthering these studies.

We analyze four epochs of HST imaging over 18 years for the Draco dwarf spheroidal galaxy. We measure precise proper motions (PMs) for hundreds of stars and combine these with existing line-of-sight (LOS) velocities. This provides the first radially-resolved 3D velocity dispersion profiles for any dwarf galaxy. These constrain the intrinsic velocity anisotropy and resolve the mass-anisotropy degeneracy. We solve the Jeans equations in oblate axisymmetric geometry to infer the mass profile. We find the velocity dispersion to be radially anisotropic along the symmetry axis and tangentially anisotropic in the equatorial plane, with a globally-averaged value $\overline{\beta_{\mathrm B}}=-0.20^{+ 0.28}_{- 0.53}$, (where $1 - \beta_{\mathrm B} \equiv \langle v_{\mathrm{ tan}}^2 \rangle / \langle v_{\mathrm{ rad}}^2 \rangle$ in 3D). The logarithmic dark matter (DM) density slope over the observed radial range, $\Gamma_{\mathrm{ dark}}$, is $-0.83^{+ 0.32}_{- 0.37}$, consistent with the inner cusp predicted in $\Lambda$CDM cosmology. As expected given Draco's low mass and ancient star formation history, it does not appear to have been dissolved by baryonic processes. We rule out cores larger than 487, 717, 942 pc at respective 1-, 2-, 3-$\sigma$ confidence, thus imposing important constraints on the self-interacting DM cross-section. Spherical models yield biased estimates for both the velocity anisotropy and the inferred slope. The circular velocity at our outermost data point (900 pc) is $24.19^{+ 6.31}_{- 2.97} \ \mathrm{km~s^{-1}}s$. We infer a dynamical distance of $75.37^{+ 4.73}_{- 4.00}$ kpc, and show that Draco has a modest LOS rotation, with $\left = 0.22 \pm 0.09$. Our results provide a new stringent test of the so-called `cusp-core' problem that can be readily extended to other dwarfs., Comment: 35 pages, 18 figures, 3 Tables. Accepted for publication in ApJ. Journal version has better readability. Data is available at Zenodo: https://zenodo.org/records/11111113

Although the use of technologies like multimedia and virtual reality (VR) in training offer the promise of improved learning, these richer and potentially more engaging materials do not consistently produce superior learning outcomes. Default approaches to such training may inadvertently mimic concepts like naive realism in display design, and desirable difficulties in the science of learning - fostering an impression of greater learning dissociated from actual gains in memory. This research examined the influence of format of instructions in learning to assemble items from components. Participants in two experiments were trained on the steps to assemble a series of bars, that resembled Meccano pieces, into eight different shapes. After training on pairs of shapes, participants rated the likelihood they would remember the shapes and then were administered a recognition test. Relative to viewing a static diagram, viewing videos of shapes being constructed in a VR environment (Experiment 1) or viewing within an immersive VR system (Experiment 2) elevated participants' assessments of their learning but without enhancing learning outcomes. Overall, these findings illustrate how future workers might mistakenly come to believe that technologically advanced support improves learning and prefer instructional designs that integrate similarly complex cues into training., Comment: published and presented in I/ITSEC 2022

Landmark universal function approximation results for neural networks with trained weights and biases provided impetus for the ubiquitous use of neural networks as learning models in Artificial Intelligence (AI) and neuroscience. Recent work has pushed the bounds of universal approximation by showing that arbitrary functions can similarly be learned by tuning smaller subsets of parameters, for example the output weights, within randomly initialized networks. Motivated by the fact that biases can be interpreted as biologically plausible mechanisms for adjusting unit outputs in neural networks, such as tonic inputs or activation thresholds, we investigate the expressivity of neural networks with random weights where only biases are optimized. We provide theoretical and numerical evidence demonstrating that feedforward neural networks with fixed random weights can be trained to perform multiple tasks by learning biases only. We further show that an equivalent result holds for recurrent neural networks predicting dynamical system trajectories. Our results are relevant to neuroscience, where they demonstrate the potential for behaviourally relevant changes in dynamics without modifying synaptic weights, as well as for AI, where they shed light on multi-task methods such as bias fine-tuning and unit masking., Comment: change to article metadata only: author name typo correction

Strip and pixels sensors, fabricated on high resistivity silicon substrate, normally of p-type, are used in detectors for High Energy Physics (HEP) typically in a hybrid detector assembly. Furthermore, and owing to their inherent advantages over hybrid sensors, Monolithic Active Pixel Sensors (MAPS) fabricated in CMOS technology have been increasingly implemented in HEP experiments. In all cases, their use in higher radiation areas (HL-LHC and beyond) will require options to improve their radiation hardness and time resolution. These aspects demand a deep understanding of their radiation damage and reliable models to predict their behaviours at high fluences. As a first step, we fabricated several Schottky and n-on-p diodes, to allow a comparison of results and provide a backup solution for test devices, on 6 or 4-inch p-type silicon wafers with 50 {\mu}m epitaxial thickness and of doping concentration as they are normally used in HEP detectors and CMOS MAPS devices. In this paper, details of the design and fabrication process, along with test results of the fabricated devices before irradiation, will be provided. Additional test results on irradiated devices will be provided in subsequent publications.

We present an analysis of high-resolution optical spectra recorded for 30 stars of the split extended main-sequence turnoff (eMSTO) of the young ($\sim$ 40 Myr) Small Magellanic Cloud (SMC) globular cluster NGC 330. Spectra were obtained with the M2FS and MIKE spectrographs located on the Magellan-Clay 6.5m telescope. These spectra revealed the presence of Be stars, occupying primarily the cool side of the split main sequence (MS). Rotational velocity ($v\sin{i}$) measurements for most of the targets are consistent with the presence of two populations of stars in the cluster: one made up of rapidly rotating Be stars ($ \approx 200$ $\rm km\,s^{-1}$), and {the other} consisting of warmer stars with slower rotation ($<\!v\sin{i}\!>\approx50$ $\rm km\,s^{-1}$). Core emission in the H$\delta$ photospheric lines was observed for most of the H$\alpha$ emitters. The shell parameter computed for the targets in our sample indicate that most of the observed stars should have inclinations below 75$^{\circ}$. These results confirm the detection of Be stars obtained through photometry, but also reveal the presence of narrow H$\alpha$ and H$\delta$ features for some targets that cannot be detected with low-resolution spectroscopy or photometry. Asymmetry variability of H$\alpha$ line profiles on the timescales of a few years is also observed, and could provide information on the geometry of the decretion disks. Observations revealed the presence of nebular H$\alpha$ emission, strong enough in faint targets to compromise the extraction of spectra and to impact narrow band photometry used to assess the presence of H$\alpha$ emission., Comment: 15 pages, 13 figures, accepted for publication in The Astrophysical Journal

We use analytical and $N$-body methods to study the capture of field stars by gravitating substructures moving across a galactic environment. The majority of stars captured by a substructure move on temporarily-bound orbits that are lost to galactic tides after a few orbital revolutions. In numerical experiments where a substructure model is immersed into a sea of field particles on a circular orbit, we find a population of particles that remain bound to the substructure potential for indefinitely-long times. This population is absent from substructure models initially placed outside the galaxy on an eccentric orbit. We show that gravitational capture is most efficient in dwarf spheroidal galaxies (dSphs) on account of their low velocity dispersions and high stellar phase-space densities. In these galaxies `dark' sub-subhaloes which do not experience in-situ star formation may capture field stars and become visible as stellar overdensities with unusual properties: (i) they would have a large size for their luminosity, (ii) contain stellar populations indistinguishable from the host galaxy, and (iii) exhibit dark matter (DM)-dominated mass-to-light ratios. We discuss the nature of several `anomalous' stellar systems reported as star clusters in the Fornax and Eridanus II dSphs which exhibit some of these characteristics. DM sub-subhaloes with a mass function $d N/d M_\bullet\sim M_\bullet^{-\alpha}$ are expected to generate stellar systems with a luminosity function, $d N/d M_\star\sim M_\star^{-\beta}$, where $\beta=(2\alpha+1)/3=1.6$ for $\alpha=1.9$. Detecting and characterizing these objects in dSphs would provide unprecedented constraints on the particle mass and cross section of a large range of DM particle candidates., Comment: 21 pages. Accepted

We present results from simultaneous modeling of 2D (projected along the line of sight) position, proper motion and line-of-sight velocity for \textit{Gaia}- and APOGEE-observed stars near the centre of the Sagittarius (Sgr) dwarf spheroidal galaxy. We use a mixture model that allows for independent sub-populations contributed by the Sgr galaxy, its nuclear star cluster M54, and the Milky Way foreground. We find an offset of $0.295\pm 0.029$ degrees between the inferred centroids of Sgr and M54, corresponding to a (projected) physical separation of $0.135\pm 0.013$ kpc. The detected offset might plausibly be driven by unmodelled asymmetry in Sgr's stellar configuration; however, standard criteria for model selection favour our symmetric model over an alternative that allows for bilateral asymmetry. We infer an offset between the proper motion centres of Sgr and M54 of $[\Delta\mu_{\alpha}\cos\delta,\Delta\mu_{\delta}]=[4.9, -19.7] \pm [6.8, 6.2]$ $\mu$as yr$^{-1}$ ($[0.61, -2.46] \pm [0.85, 0.77] $ km s$^{-1}$), with magnitude similar to the covariance expected due to spatially-correlated systematic error. We infer an offset of $4.1\pm 1.2$ km s$^{-1}$ in line-of-sight velocity. Using inferred values for the systemic positions and motions of Sgr and M54 as initial conditions, we calculate the recent orbital history of a simplified Sgr/M54 system, which we demonstrate to be sensitive to any line-of-sight distance offset between M54 and Sgr, and to the distribution of dark matter within Sgr.

We present a novel method for minimizing the effects of radiative depolarization in electron storage rings by use of vertical orbit bumps in the arcs. Electron polarization is directly characterized by the RMS of the so-called spin orbit coupling function in the bends. In the Electron Storage Ring (ESR) of the Electron-Ion Collider (EIC), as was the case in HERA, this function is excited by the spin rotators. Individual vertical corrector coils in the arcs can have varying impacts on this function globally. In this method, we use a singular value decomposition of the response matrix of the spin-orbit coupling function with each coil to define a minimal number of most effective groups of coils, motivating the name "Best Adjustment Groups for ELectron Spin" (BAGELS) method. The BAGELS method can be used to minimize the depolarizing effects in an ideal lattice, and to obtain fine-tuning knobs to restore the minimization in rings with realistic closed orbit distortions. Furthermore, the least effective groups can instead be chosen for other applications where no impact on polarization is desirable, e.g. global coupling compensation or vertical emittance creation. Application of the BAGELS method has significantly increased the polarization in simulations of the 18 GeV ESR, beyond achievable with conventional methods.

SGR J1935+2154 has truly been the most prolific magnetar over the last decade: It has been entering into burst active episodes once every 1-2 years since its discovery in 2014, it emitted the first Galactic fast radio burst associated with an X-ray burst in 2020, and has emitted hundreds of energetic short bursts. Here, we present the time-resolved spectral analysis of 51 bright bursts from SGR J1935+2154. Unlike conventional time-resolved X-ray spectroscopic studies in the literature, we follow a two-step approach to probe true spectral evolution. For each burst, we first extract spectral information from overlapping time segments, fit them with three continuum models, and employ a machine learning based clustering algorithm to identify time segments that provide the largest spectral variations during each burst. We then extract spectra from those non-overlapping (clustered) time segments and fit them again with the three models: the cutoff power-law model, the sum of two blackbody functions, and the model considering the emission of a modified black body undergoing resonant cyclotron scattering, which is applied systematically at this scale for the first time. Our novel technique allowed us to establish the genuine spectral evolution of magnetar bursts. We discuss the implications of our results and compare their collective behavior with the average burst properties of other magnetars., Comment: Accepted for publication in ApJ

This paper provides an introduction to quantum machine learning, exploring the potential benefits of using quantum computing principles and algorithms that may improve upon classical machine learning approaches. Quantum computing utilizes particles governed by quantum mechanics for computational purposes, leveraging properties like superposition and entanglement for information representation and manipulation. Quantum machine learning applies these principles to enhance classical machine learning models, potentially reducing network size and training time on quantum hardware. The paper covers basic quantum mechanics principles, including superposition, phase space, and entanglement, and introduces the concept of quantum gates that exploit these properties. It also reviews classical deep learning concepts, such as artificial neural networks, gradient descent, and backpropagation, before delving into trainable quantum circuits as neural networks. An example problem demonstrates the potential advantages of quantum neural networks, and the appendices provide detailed derivations. The paper aims to help researchers new to quantum mechanics and machine learning develop their expertise more efficiently., Comment: Published as a DTIC report under the title "Quantum Computing for Machine Learning - An Introduction". Distribution Statement A: Approved for Public Release. Distribution is Unlimited

Magnetars are neutron stars with extremely high magnetic fields that exhibit various X-ray phenomena such as sporadic sub-second bursts, long-term persistent flux enhancements, and variable rates of rotation period change. In 2020, a fast radio burst (FRB), akin to cosmological millisecond-duration radio bursts, was detected from the Galactic magnetar SGR 1935+2154, confirming the long-suspected association between some FRBs and magnetars. However, the mechanism for FRB generation in magnetars remains unclear. Here we report the X-ray discovery of an unprecedented double glitch in SGR 1935+2154 within a time interval of approximately nine hours, bracketing an FRB that occurred on October 14, 2022. Each glitch involved a significant increase in the magnetar's spin frequency, being among the largest abrupt changes in neutron star rotation ever observed. Between the glitches, the magnetar exhibited a rapid spin-down phase, accompanied by a profound increase and subsequent decline in its persistent X-ray emission and burst rate. We postulate that a strong, ephemeral, magnetospheric wind provides the torque that rapidly slows the star's rotation. The trigger for the first glitch couples the star's crust to its magnetosphere, enhances the various X-ray signals, and spawns the wind that alters magnetospheric conditions that might produce the FRB., Comment: 46 pages, 9figures, 4 tables, a submitted version of Nature 626, 500 (https://www.nature.com/articles/s41586-023-07012-5)

Dictation enables efficient text input on mobile devices. However, writing with speech can produce disfluent, wordy, and incoherent text and thus requires heavy post-processing. This paper presents Rambler, an LLM-powered graphical user interface that supports gist-level manipulation of dictated text with two main sets of functions: gist extraction and macro revision. Gist extraction generates keywords and summaries as anchors to support the review and interaction with spoken text. LLM-assisted macro revisions allow users to respeak, split, merge and transform dictated text without specifying precise editing locations. Together they pave the way for interactive dictation and revision that help close gaps between spontaneous spoken words and well-structured writing. In a comparative study with 12 participants performing verbal composition tasks, Rambler outperformed the baseline of a speech-to-text editor + ChatGPT, as it better facilitates iterative revisions with enhanced user control over the content while supporting surprisingly diverse user strategies., Comment: To appear at ACM CHI 2024

In this work, we introduce a new algorithm for N-to-M checkpointing in finite element simulations. This new algorithm allows efficient saving/loading of functions representing physical quantities associated with the mesh representing the physical domain. Specifically, the algorithm allows for using different numbers of parallel processes for saving and loading, allowing for restarting and post-processing on the process count appropriate to the given phase of the simulation and other conditions. For demonstration, we implemented this algorithm in PETSc, the Portable, Extensible Toolkit for Scientific Computation, and added a convenient high-level interface into Firedrake, a system for solving partial differential equations using finite element methods. We evaluated our new implementation by saving and loading data involving 8.2 billion finite element degrees of freedom using 8,192 parallel processes on ARCHER2, the UK National Supercomputing Service., Comment: author accepted manuscript

We present spectroscopic data for 16369 stellar targets within and/or toward 38 dwarf spheroidal galaxies and faint star clusters within the Milky Way halo environment. All spectra come from observations with the multi-object, fiber-fed echelle spectrographs M2FS at the Magellan/Clay telescope or Hectochelle at the MMT, reaching a typical limiting magnitude G < 21. Data products include processed spectra from all observations and catalogs listing estimates -- derived from template model fitting -- of line-of-sight velocity (median uncertainty 1.1 km/s) effective temperature (234 K), (base10 logarithm of) surface gravity (0.52 dex in cgs units), [Fe/H] (0.38 dex) and [Mg/Fe] (0.24 dex) abundance ratios. The sample contains multi-epoch measurements for 3720 sources, with up to 15 epochs per source, enabling studies of intrinsic spectroscopic variability. The sample contains 6078 likely red giant stars (based on surface gravity), and 4494 likely members (based on line-of-sight velocity and Gaia-measured proper motion) of the target systems. The number of member stars per individual target system ranges from a few, for the faintest systems, to ~ 850 for the most luminous. For most systems, our new samples extend over wider fields than have previously been observed; of the likely members in our samples, 823 lie beyond twice the projected halflight radius of their host system, and 42 lie beyond 5 Rhalf., Comment: Published September 2023 in The Astrophysical Journal Supplement Series, processed spectra and catalogs publicly available at the Zenodo database doi:10.5281/zenodo.7837922