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The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.

We describe the physical relativity of light and matter quantum subsystems, their correlations, and energy exchanges. We examine the most commonly adopted definitions of atoms and photons, noting the significant difference in their localisation properties when expressed in terms of primitive manifestly gauge-invariant and local fields. As a result, different behaviours for entanglement generation and energy exchange occur for different definitions. We explore such differences in detail using toy models of a single photonic mode interacting with one and two dipoles., Comment: This paper is an invited contribution to the Lindblad memorial volume in Open Systems and Information Dynamics. 33 pages, 6 figures

Cooperative perception has been widely used in autonomous driving to alleviate the inherent limitation of single automated vehicle perception. To enable cooperation, vehicle-to-vehicle (V2V) communication plays an indispensable role. This work analyzes the performance of cooperative perception accounting for communications channel impairments. Different fusion methods and channel impairments are evaluated. A new late fusion scheme is proposed to leverage the robustness of intermediate features. In order to compress the data size incurred by cooperation, a convolution neural network-based autoencoder is adopted. Numerical results demonstrate that intermediate fusion is more robust to channel impairments than early fusion and late fusion, when the SNR is greater than 0 dB. Also, the proposed fusion scheme outperforms the conventional late fusion using detection outputs, and autoencoder provides a good compromise between detection accuracy and bandwidth usage.

Tracking the fundamental frequency (f0) of a monophonic instrumental performance is effectively a solved problem with several solutions achieving 99% accuracy. However, the related task of automatic music transcription requires a further processing step to segment an f0 contour into discrete notes. This sub-task of note segmentation is necessary to enable a range of applications including musicological analysis and symbolic music generation. Building on CREPE, a state-of-the-art monophonic pitch tracking solution based on a simple neural network, we propose a simple and effective method for post-processing CREPE's output to achieve monophonic note segmentation. The proposed method demonstrates state-of-the-art results on two challenging datasets of monophonic instrumental music. Our approach also gives a 97% reduction in the total number of parameters used when compared with other deep learning based methods.

This paper develops and analyzes a new algorithm for QR decomposition with column pivoting (QRCP) of rectangular matrices with large row counts. The algorithm combines methods from randomized numerical linear algebra in a particularly careful way in order to accelerate both pivot decisions for the input matrix and the process of decomposing the pivoted matrix into the QR form. The source of the latter acceleration is a use of randomized preconditioning and CholeskyQR. Comprehensive analysis is provided in both exact and finite-precision arithmetic to characterize the algorithm's rank-revealing properties and its numerical stability granted probabilistic assumptions of the sketching operator. An implementation of the proposed algorithm is described and made available inside the open-source RandLAPACK library, which itself relies on RandBLAS - also available in open-source format. Experiments with this implementation on an Intel Xeon Gold 6248R CPU demonstrate order-of-magnitude speedups relative to LAPACK's standard function for QRCP, and comparable performance to a specialized algorithm for unpivoted QR of tall matrices, which lacks the strong rank-revealing properties of the proposed method., Comment: v1: 26 pages in the body, 10 pages in the appendices, 10 figures. v2: performance experiments now use a larger sketch size for CQRRPT

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods to aid the novice and experienced researcher. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics.

Large language models (LLMs) are trained on web-scale corpora that inevitably include contradictory factual information from sources of varying reliability. In this paper, we propose measuring an LLM property called trusted source alignment (TSA): the model's propensity to align with content produced by trusted publishers in the face of uncertainty or controversy. We present FactCheckQA, a TSA evaluation dataset based on a corpus of fact checking articles. We describe a simple protocol for evaluating TSA and offer a detailed analysis of design considerations including response extraction, claim contextualization, and bias in prompt formulation. Applying the protocol to PaLM-2, we find that as we scale up the model size, the model performance on FactCheckQA improves from near-random to up to 80% balanced accuracy in aligning with trusted sources.

We report on an observational campaign on the bright black hole X-ray binary Swift J1727.8$-$1613 centered around five observations by the Imaging X-ray Polarimetry Explorer (IXPE). These observations track for the first time the evolution of the X-ray polarization of a black hole X-ray binary across a hard to soft state transition. The 2--8 keV polarization degree decreased from $\sim$4\% to $\sim$3\% across the five observations, but the polarization angle remained oriented in the North-South direction throughout. Based on observations with the Australia Telescope Compact Array (ATCA), we find that the intrinsic 7.25 GHz radio polarization aligns with the X-ray polarization. Assuming the radio polarization aligns with the jet direction (which can be tested in the future with higher spatial resolution images of the jet), our results imply that the X-ray corona is extended in the disk plane, rather than along the jet axis, for the entire hard intermediate state. This in turn implies that the long ($\gtrsim$10 ms) soft lags that we measure with the Neutron star Interior Composition ExploreR (NICER) are dominated by processes other than pure light-crossing delays. Moreover, we find that the evolution of the soft lag amplitude with spectral state does not follow the trend seen for other sources, implying that Swift J1727.8$-$1613 is a member of a hitherto under-sampled sub-population., Comment: Accepted for publication in ApJ. 21 pages, 8 figures

Accretion is a universal astrophysical process that plays a key role in cosmic history, from the epoch of reionization to galaxy and stellar formation and evolution. Accreting stellar-mass black holes in X-ray binaries are one of the best laboratories to study the accretion process and probe strong gravity -- and most importantly, to measure the angular momentum, or spin, of black holes, and its role as a powering mechanism for relativistic astrophysical phenomena. Comprehensive characterization of the disk-corona system of accreting black holes, and their co-evolution, is fundamental to measurements of black hole spin. Here, we use simulated data to demonstrate how key unanswered questions in the study of accreting stellar-mass black holes will be addressed by the {\it High Energy X-ray Probe} (\hexp). \hexp\ is a probe-class mission concept that will combine high spatial resolution X-ray imaging and broad spectral coverage ($0.2\mbox{--}80$keV) with a sensitivity superior to current facilities (including \xmm\ and \nustar) to enable revolutionary new insights into a variety of important astrophysical problems. We illustrate the capability of \hexp\ to: 1) measure the evolving structures of black hole binary accretion flows down to low ($\lesssim0.1\%$) Eddington-scaled luminosities via detailed X-ray reflection spectroscopy; 2) provide unprecedented spectral observations of the coronal plasma, probing its elusive geometry and energetics; 3) perform detailed broadband studies of stellar mass black holes in nearby galaxies, thus expanding the repertoire of sources we can use to study accretion physics and determine the fundamental nature of black holes; and 4) act as a complementary observatory to a range of future ground and space-based astronomical observatories, thus providing key spectral measurements of the multi-component emission from the inner accretion flows of BH-XRBs., Comment: 31 pages, 7 figures

Coronal Mass Ejections (CMEs) are immense eruptions of plasma and magnetic fields that are propelled outward from the Sun, sometimes with velocities greater than 2000 km/s. They are responsible for some of the most severe space weather at Earth, including geomagnetic storms and solar energetic particle (SEP) events. We have developed CORHEL-CME, an interactive tool that allows non-expert users to routinely model multiple CMEs in a realistic coronal and heliospheric environment. The tool features a web-based user interface that allows the user to select a time period of interest, and employs RBSL flux ropes to create stable and unstable pre-eruptive configurations within a background global magnetic field. The properties of these configurations can first be explored in a zero-beta magnetohydrodynamic (MHD) model, followed by complete CME simulations in thermodynamic MHD, with propagation out to 1 AU. We describe design features of the interface and computations, including the innovations required to efficiently compute results on practical timescales with moderate computational resources. CORHEL-CME is now implemented at NASA's Community Coordinated Modeling Center (CCMC) using NASA Amazon Web Services (AWS). It will be available to the public by the time this paper is published., Comment: 10 pages, 6 figures, submitted to Journal of Physics Conference Series

We study quasi-freestanding bilayer graphene on silicon carbide intercalated by calcium. The intercalation, and subsequent changes to the system, were investigated by low-energy electron diffraction, angle-resolved photoemission spectroscopy (ARPES) and density-functional theory (DFT). Calcium is found to intercalate only at the graphene-SiC interface, completely displacing the hydrogen terminating SiC. As a consequence, the system becomes highly n-doped. Comparison to DFT calculations shows that the band dispersion, as determined by ARPES, deviates from the band structure expected for Bernal-stacked bilayer graphene. Instead, the electronic structure closely matches AA-stacked bilayer graphene on Ca-terminated SiC, indicating a spontaneous transition from AB- to AA-stacked bilayer graphene following calcium intercalation of the underlying graphene-SiC interface., Comment: 14 pages, 3 figures

We present FiloBass: a novel corpus of music scores and annotations which focuses on the important but often overlooked role of the double bass in jazz accompaniment. Inspired by recent work that sheds light on the role of the soloist, we offer a collection of 48 manually verified transcriptions of professional jazz bassists, comprising over 50,000 note events, which are based on the backing tracks used in the FiloSax dataset. For each recording we provide audio stems, scores, performance-aligned MIDI and associated metadata for beats, downbeats, chord symbols and markers for musical form. We then use FiloBass to enrich our understanding of jazz bass lines, by conducting a corpus-based musical analysis with a contrastive study of existing instructional methods. Together with the original FiloSax dataset, our work represents a significant step toward a fully annotated performance dataset for a jazz quartet setting. By illuminating the critical role of the bass in jazz, this work contributes to a more nuanced and comprehensive understanding of the genre., Comment: ISMIR 2023

Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. DOE Exascale Computing Project have been tackling new frontiers in modeling, simulation, and analysis by exploiting unprecedented exascale computing capabilities-building an advanced software ecosystem that supports next-generation applications and addresses disruptive changes in computer architectures. However, concerns are growing about the productivity of the developers of scientific software, its sustainability, and the trustworthiness of the results that it produces. Members of the IDEAS project serve as catalysts to address these challenges through fostering software communities, incubating and curating methodologies and resources, and disseminating knowledge to advance developer productivity and software sustainability. This paper discusses how these synergistic activities are advancing scientific discovery-mitigating technical risks by building a firmer foundation for reproducible, sustainable science at all scales of computing, from laptops to clusters to exascale and beyond., Comment: 12 pages, 1 figure

We report on a highly selective experimental setup for particle-$\gamma$ coincidence experiments at the Super-Enge Split-Pole Spectrograph (SE-SPS) of the John D. Fox Superconducting Linear Accelerator Laboratory at Florida State University (FSU) using fast CeBr$_3$ scintillators for $\gamma$-ray detection. Specifically, we report on the results of characterization tests for the first five CeBr$_3$ scintillation detectors of the CeBr$_3$ Array (CeBrA) with respect to energy resolution and timing characteristics. We also present results from the first particle-$\gamma$ coincidence experiments successfully performed with the CeBrA demonstrator and the FSU SE-SPS. We show that with the new setup, $\gamma$-decay branching ratios and particle-$\gamma$ angular correlations can be measured very selectively using narrow excitation energy gates, which are possible thanks to the excellent particle energy resolution of the SE-SPS. In addition, we highlight that nuclear level lifetimes in the nanoseconds regime can be determined by measuring the time difference between particle detection with the SE-SPS focal-plane scintillator and $\gamma$-ray detection with the fast CeBrA detectors. Selective excitation energy gates with the SE-SPS exclude any feeding contributions to these lifetimes.

We obtain bounds on the average size of Bohr sets with coefficients parametrised by polynomials over finite fields and obtain a series of general results and also some sharper results for specific sets which are important for applications to computer science. In particular, we use our estimates to show that a heuristic assumption used in the many variable version of Coppersmith's method holds with high probability. We demonstrate the use of our results on the approximate greatest common divisor problem and obtain a fully rigorous version of the heuristic algorithm of H. Cohn and N. Heninger (2013).

Through observational tests of strong lensing galaxy clusters, we can test simulation derived structure predictions that follow from $\Lambda$ Cold Dark Matter ($\Lambda$CDM) cosmology. The shape and centroid deviations between the total matter distribution, stellar matter distributions, and hot intracluster gas distribution serve as an observational test of these theoretical structure predictions. We measure the position angles, ellipticities, and locations/centroids of the brightest cluster galaxy (BCG), intracluster light (ICL), the hot intracluster medium (ICM), and the core lensing mass for a sample of strong lensing galaxy clusters from the SDSS Giant Arcs Survey (SGAS). We utilize HST WFC3/IR imaging data to measure the shapes/centroids of the ICL and BCG distributions and use Chandra ACIS-I X-ray data to measure the shapes/centroids of ICM. Additionally, we measure the concentration parameter c and asymmetry parameter A to incorporate cluster dynamical state into our analysis. Using this multicomponent approach, we attempt to constrain the astrophysics of our strong lensing cluster sample and evaluate the different components in terms of their ability to trace out the DM halo of clusters in various dynamical states., Comment: 6 pages, 4 figures, to appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

This work focuses on accelerating the multiplication of a dense random matrix with a (fixed) sparse matrix, which is frequently used in sketching algorithms. We develop a novel scheme that takes advantage of blocking and recomputation (on-the-fly random number generation) to accelerate this operation. The techniques we propose decrease memory movement, thereby increasing the algorithm's parallel scalability in shared memory architectures. On the Intel Frontera architecture, our algorithm can achieve 2x speedups over libraries such as Eigen and Intel MKL on some examples. In addition, with 32 threads, we can obtain a parallel efficiency of up to approximately 45%. We also present a theoretical analysis for the memory movement lower bound of our algorithm, showing that under mild assumptions, it's possible to beat the data movement lower bound of general matrix-matrix multiply (GEMM) by a factor of $\sqrt M$, where $M$ is the cache size. Finally, we incorporate our sketching algorithm into a randomized least squares solver. For extremely over-determined sparse input matrices, we show that our results are competitive with SuiteSparse; in some cases, we obtain a speedup of 10x over SuiteSparse.

The current and next observation seasons will detect hundreds of gravitational waves (GWs) from compact binary systems coalescence at cosmological distances. When combined with independent electromagnetic measurements, the source redshift will be known, and we will be able to obtain precise measurements of the Hubble constant $H_0$ via the distance-redshift relation. However, most observed mergers are not expected to have electromagnetic counterparts, which prevents a direct redshift measurement. In this scenario, one of the possibilities is to use the dark sirens method that statistically marginalizes over all the potential host galaxies within the GW location volume to provide a probabilistic redshift to the source. Here we presented $H_{0}$ measurements using two new dark sirens compared to previous analyses using DECam data, GW190924$\_$021846 and GW200202$\_$154313. The photometric redshifts of the possible host galaxies of these two events are acquired from the DECam Local Volume Exploration Survey (DELVE) carried out on the Blanco telescope at Cerro Tololo in Chile. The combination of the $H_0$ posterior from GW190924$\_$021846 and GW200202$\_$154313 together with the bright siren GW170817 leads to $H_{0} = 68.84^{+15.51}_{-7.74}\, \rm{km/s/Mpc}$. Including these two dark sirens improves the 68% confidence interval (CI) by 7% over GW170817 alone. This demonstrates that the inclusion of well-localized dark sirens in such analysis improves the precision with which cosmological measurements can be made. Using a sample containing 10 well-localized dark sirens observed during the third LIGO/Virgo observation run, we determine a measurement of $H_{0} = 76.00^{+17.64}_{-13.45}\, \rm{km /s/Mpc}$., Comment: v2: minor corrections and references added

During the outbursts of black hole X-ray binaries (BHXRBs), their accretion flows transition through several states. The source luminosity rises in the hard state, dominated by non-thermal emission, before transitioning to the blackbody-dominated soft state. As the luminosity decreases, the source transitions back into the hard state and fades to quiescence. This picture does not always hold, as $\approx$ 40$\%$ of the outbursts never leave the hard state. Identifying the physics that govern state transitions remains one of the outstanding open questions in black hole astrophysics. In this paper we present an analysis of archival RXTE data of multiple outbursts of GX 339-4. We compare the properties of the X-ray variability and time-averaged energy spectrum and demonstrate that the variability (quantified by the power spectral hue) systematically evolves $\approx$ 10-40 days ahead of the canonical state transition (quantified by a change in spectral hardness); no such evolution is found in hard state only outbursts. This indicates that the X-ray variability can be used to predict if and when the hard-to-soft state transition will occur. Finally, we find a similar behavior in ten outbursts of four additional BHXRBs with more sparse observational coverage. Based on these findings, we suggest that state transitions in BHXRBs might be driven by a change in the turbulence in the outer regions of the disk, leading to a dramatic change in variability. This change is only seen in the spectrum days to weeks later, as the fluctuations propagate inwards towards the corona., Comment: Accepted for publication in ApJ

We performed a measurement of the $^{52}$Cr$(d,p)^{53}$Cr reaction at 16 MeV using the Florida State University Super-Enge Split-Pole Spectrograph (SE-SPS) and observed 26 states. While all of the states observed here had been seen in previous $(d,p)$ experiments, we changed five $L$ assignments from those reported previously and determined $L$ values for nine states that had not had such assignments made previously. The $g_{9/2}$ neutron strength observed in $^{53}$Cr in the present work and in the $N=29$ isotones $^{49}$Ca, $^{51}$Ti, and $^{55}$Fe via $(d,p)$ reactions is much smaller than the sum rule for this strength. Most of the observed $L=4$ strength in these nuclei is located in states near 4 MeV excitation energy. The remaining $g_{9/2}$ strength may be located in the continuum or may be fragmented among many bound states. A covariant density functional theory calculation provides support for the hypothesis that the $g_{9/2}$ neutron orbit is unbound in $^{53}$Cr. The ($\alpha,^3$He) reaction may provide a more sensitive probe for the missing $g_{9/2}$ neutron strength. In addition, particle-$\gamma$ coincidence experiments may help resolve some remaining questions in this nucleus., Comment: 15 pages, 5 figures. arXiv admin note: text overlap with arXiv:2212.04384

We present a comprehensive mathematical model and experimental measurements for the evolution of a trapped particle ensemble driven by collisions with a room-temperature background vapor. The model accommodates any trap geometry, confining potential, initial trapped distribution, and other experimental details; it only depends on the the probability distribution function $P_t(E)$ for the collision-induced energy transfer to the trapped ensemble. We describe how to find $P_t(E)$ using quantum scattering calculations and how it can be approximated using quantum diffractive universality. We then compare our model to experimental measurements of a $^{87}$Rb ensemble energy evolution exposed to a room temperature background gas of Ar by means of a single parameter fit for the total collision rate $\Gamma$. We extracted a collision rate of $\Gamma = 0.646(1)\ \text{s}^{-1}$. This is compared to a value of $0.664(4)\ \text{s}^{-1}$ found by the commonly used method of zero-trap depth extrapolation, a $2.8\%$ correction that is a result of our model fully taking ensemble loss and heating into account. Finally, we report a five-fold increase in the precision of our collision rate extraction from the experimental data., Comment: 14 pages, 6 figures