Search

We present a measurement of the relativistic corrections to the thermal Sunyaev-Zel'dovich (SZ) effect spectrum, the rSZ effect, toward the massive galaxy cluster RX J1347.5-1145 by combining sub-mm images from Herschel-SPIRE with mm-wave Bolocam maps. Our analysis simultaneously models the SZ effect signal, the population of cosmic infrared background (CIB) galaxies, and galactic cirrus dust emission in a manner that fully accounts for their spatial and frequency-dependent correlations. Gravitational lensing of background galaxies by RX J1347.5-1145 is included in our methodology based on a mass model derived from HST observations. Utilizing a set of realistic mock observations, we employ a forward modelling approach that accounts for the non-Gaussian covariances between observed astrophysical components to determine the posterior distribution of SZ effect brightness values consistent with the observed data. We determine a maximum a posteriori (MAP) value of the average Comptonization parameter of the intra-cluster medium (ICM) within R$_{2500}$ to be $\langle y \rangle_{2500} = 1.56 \times 10^{-4}$, with corresponding 68~per cent credible interval $[1.42,1.63] \times 10^{-4}$, and a MAP ICM electron temperature of $\langle \textrm{T}_{\textrm{sz}} \rangle_{2500} = 22.4$~keV with 68~per cent credible interval spanning $[10.4,33.0]$~keV. This is in good agreement with the pressure-weighted temperature obtained from {\it Chandra} X-ray observations, $\langle \textrm{T}_{\textrm{x,pw}}\rangle_{2500} = 17.4 \pm 2.3$~keV. We aim to apply this methodology to comparable existing data for a sample of 39 galaxy clusters, with an estimated uncertainty on the ensemble mean $\langle \textrm{T}_{\textrm{sz}} \rangle_{2500}$ at the $\simeq 1$~keV level, sufficiently precise to probe ICM physics and to inform X-ray temperature calibration., Comment: 20 pages, 9 figures

Considerable observational efforts are being dedicated to measuring the sky-averaged (global) 21-cm signal of neutral hydrogen from Cosmic Dawn and the Epoch of Reionization. Deriving observational constraints on the astrophysics of this era requires modeling tools that can quickly and accurately generate theoretical signals across the wide astrophysical parameter space. For this purpose artificial neural networks were used to create the only two existing global signal emulators, 21cmGEM and globalemu. In this paper we introduce 21cmVAE, a neural network-based global signal emulator, trained on the same dataset of ~30,000 global signals as the other two emulators, but with a more direct prediction algorithm that prioritizes accuracy and simplicity. Using neural networks, we compute derivatives of the signals with respect to the astrophysical parameters and establish the most important astrophysical processes that drive the global 21-cm signal at different epochs. 21cmVAE has a relative rms error of only 0.34 - equivalently 0.54 mK - on average, which is a significant improvement compared to the existing emulators, and a run time of 0.04 seconds per parameter set. The emulator, the code, and the processed datasets are publicly available at https://github.com/christianhbye/21cmVAE and through https://zenodo.org/record/5904939., 11 pages, 7 figures, 2 tables (including appendices). In press (ApJ). Code available at https://github.com/christianhbye/21cmVAE

The complex interplay of magnetohydrodynamics, gravity, and supersonic turbulence in the interstellar medium (ISM) introduces non-Gaussian structure that can complicate comparison between theory and observation. We show that the Wavelet Scattering Transform (WST), in combination with linear discriminant analysis (LDA), is sensitive to non-Gaussian structure in 2D ISM dust maps. WST-LDA classifies magnetohydrodynamic (MHD) turbulence simulations with up to a 97\% true positive rate in our testbed of 8 simulations with varying sonic and Alfv\'{e}nic Mach numbers. We present a side-by-side comparison with two other methods for non-Gaussian characterization, the Reduced Wavelet Scattering Transform (RWST) and the 3-Point Correlation Function (3PCF). We also demonstrate the 3D-WST-LDA and apply it to classification of density fields in position-position-velocity (PPV) space, where density correlations can be studied using velocity coherence as a proxy. WST-LDA is robust to common observational artifacts, such as striping and missing data, while also sensitive enough to extract the net magnetic field direction for sub-Alfv\'{e}nic turbulent density fields. We include a brief analysis of the effect of point spread functions and image pixelization on 2D-WST-LDA applied to density fields, which informs the future goal of applying WST-LDA to 2D or 3D all-sky dust maps to extract hydrodynamic parameters of interest., Comment: 21 pages, 13 figures, submitted to ApJ

Deep learning (DL) models have achieved paradigm-changing performance in many fields with high dimensional data, such as images, audio, and text. However, the black-box nature of deep neural networks is not only a barrier to adoption in applications such as medical diagnosis, where interpretability is essential, but it also impedes diagnosis of under performing models. The task of diagnosing or explaining DL models requires the computation of additional artifacts, such as activation values and gradients. These artifacts are large in volume, and their computation, storage, and querying raise significant data management challenges.In this paper, we develop a novel data sampling technique that produces approximate but accurate results for these model debugging queries. Our sampling technique utilizes the lower dimension representation learned by the DL model and focuses on model decision boundaries for the data in this lower dimensional space.

Turbulence is a key process in many fields of astrophysics. Advances in numerical simulations of fluids over the last several decades have revolutionized our understanding of turbulence and related processes such as star formation and cosmic ray propagation. However, data from numerical simulations of astrophysical turbulence are often not made public. We introduce a new simulation-oriented database for the astronomical community: The Catalogue for Astrophysical Turbulence Simulations (CATS), located at www.mhdturbulence.com. CATS includes magnetohydrodynamic (MHD) turbulent box simulation data products generated by the public codes athena++, arepo, enzo, and flash. CATS also includes several synthetic observational data sets, such as turbulent HI data cubes. We also include measured power spectra and 3-point correlation functions from some of these data. We discuss the importance of open source statistical and visualization tools for the analysis of turbulence simulations such as those found in CATS., Comment: Accepted to ApJ

Probabilistic cataloging (PCAT) outperforms traditional cataloging methods on single-band optical data in crowded fields (Portillo et al. 2017). We extend our work to multiple bands, achieving greater sensitivity ($\sim$ 0.4 mag) and greater speed (500x) compared to previous single-band results. We demonstrate the effectiveness of multiband PCAT on mock data, both in terms of recovering accurate posteriors in the catalog space, and in directly deblending sources. When applied to Sloan Digital Sky Survey (SDSS) observations of M2, taking Hubble Space Telescope data as truth, our joint fit on $r$ and $i$ band data goes $\sim0.4$ mag deeper than single-band probabilistic cataloging and has a false discovery rate less than 20\% for F606W$\leq 20$. Compared to DAOPHOT, the two-band SDSS catalog fit goes nearly 1.5 magnitudes deeper using the same data, and maintains a lower false discovery rate down to F606W$\sim 20.5$. Given recent improvements in computational speed, multiband PCAT shows promise in application to large-scale surveys and is a plausible framework for joint analysis of multi-instrument observational data., Comment: 25 pages, 15 figures. Incorporated comments from referee process

We present a new technique to determine distances to major star-forming regions across the Perseus Molecular Cloud, using a combination of stellar photometry, astrometric data, and $\rm ^{12} CO$ spectral-line maps. Incorporating the Gaia DR2 parallax measurements when available, we start by inferring the distance and reddening to stars from their Pan-STARRS1 and 2MASS photometry, based on a technique presented in Green et al. 2014; Green et al. 2015 and implemented in their 3D "Bayestar" dust map of three-quarters of the sky. We then refine the Green et al. technique by using the velocity slices of a CO spectral cube as dust templates and modeling the cumulative distribution of dust along the line of sight towards these stars as a linear combination of the emission in the slices. Using a nested sampling algorithm, we fit these per-star distance-reddening measurements to find the distances to the CO velocity slices towards each star-forming region. This results in distance estimates explicitly tied to the velocity structure of the molecular gas. We determine distances to the B5, IC348, B1, NGC1333, L1448, and L1451 star-forming regions and find that individual clouds are located between $\approx 275-300$ pc, with typical combined uncertainties of $\approx 5\%$. We find that the velocity gradient across Perseus corresponds to a distance gradient of about 25 pc, with the eastern portion of the cloud farther away than the western portion. We determine an average distance to the complex of $294\pm 17$ pc, about 60 pc higher than the distance derived to the western portion of the cloud using parallax measurements of water masers associated with young stellar objects. The method we present is not limited to the Perseus Complex, but may be applied anywhere on the sky with adequate CO data in the pursuit of more accurate 3D maps of molecular clouds in the solar neighborhood and beyond., Comment: Accepted for publication in The Astrophysical Journal

We obtain novel closed form solutions to the Friedmann equation for cosmological models containing a component whose equation of state is that of radiation $(w=1/3)$ at early times and that of cold pressureless matter $(w=0)$ at late times. The equation of state smoothly transitions from the early to late-time behavior and exactly describes the evolution of a species with a Dirac Delta function distribution in momentum magnitudes $|\vec{p}_0|$ (i.e. all particles have the same $|\vec{p}_0|$). Such a component, here termed "hot matter", is an approximate model for both neutrinos and warm dark matter. We consider it alone and in combination with cold matter and with radiation, also obtaining closed-form solutions for the growth of super-horizon perturbations in each case. The idealized model recovers $t(a)$ to better than $1.5\%$ accuracy for all $a$ relative to a Fermi-Dirac distribution (as describes neutrinos). We conclude by adding the second moment of the distribution to our exact solution and then generalizing to include all moments of an arbitrary momentum distribution in a closed form solution., Comment: 13 pages, 7 figures, MNRAS submitted

Multiple Coulomb scattering (MCS) is the largest contributor to blurring in proton imaging. In this work, we developed a maximum likelihood least squares estimator that improves proton radiography's spatial resolution. The water equivalent thickness (WET) through projections defined from the source to the detector pixels were estimated such that they maximizes the likelihood of the energy loss of every proton crossing the volume. The length spent in each projection was calculated through the optimized cubic spline path estimate. The proton radiographies were produced using Geant4 simulations. Three phantoms were studied here: a slanted cube in a tank of water to measure 2D spatial resolution, a voxelized head phantom for clinical performance evaluation as well as a parametric Catphan phantom (CTP528) for 3D spatial resolution. Two proton beam configurations were used: a parallel and a conical beam. Proton beams of 200 and 330 MeV were simulated to acquire the radiography. Spatial resolution is increased from 2.44 lp cm-1 to 4.53 lp cm-1 in the 200 MeV beam and from 3.49 lp cm-1 to 5.76 lp cm-1 in the 330 MeV beam. Beam configurations do not affect the reconstructed spatial resolution as investigated between a radiography acquired with the parallel (3.49 lp cm-1 to 5.76 lp cm-1) or conical beam (from 3.49 lp cm-1 to 5.56 lp cm-1). The improved images were then used as input in a photon tomography algorithm. The proton CT reconstruction of the Catphan phantom shows high spatial resolution (from 2.79 to 5.55 lp cm-1 for the parallel beam and from 3.03 to 5.15 lp cm-1 for the conical beam) and the reconstruction of the head phantom, although qualitative, shows high contrast in the gradient region. The proposed formulation of the optimization demonstrates serious potential to increase the spatial resolution (up by 65[Formula: see text]) in proton radiography and greatly accelerate proton computed tomography reconstruction.

We present the first application of the angle-dependent 3-Point Correlation Function (3PCF) to the density fields magnetohydrodynamic (MHD) turbulence simulations intended to model interstellar (ISM) turbulence. Previous work has demonstrated that the angle-averaged bispectrum, the 3PCF's Fourier-space analog, is sensitive to the sonic and Alfv\'enic Mach numbers of turbulence. Here we show that introducing angular information via multipole moments with respect to the triangle opening angle offers considerable additional discriminatory power on these parameters. We exploit a fast, order $N_{\rm g} \log N_{\rm g}$ ($N_{\rm g}$ the number of grid cells used for a Fourier Transform) 3PCF algorithm to study a suite of MHD turbulence simulations with 10 different combinations of sonic and Alfv\'enic Mach numbers over a range from sub to super-sonic and sub to super-Alfv\'{e}nic. The 3PCF algorithm's speed for the first time enables full quantification of the time-variation of our signal: we study 9 timeslices for each condition, demonstrating that the 3PCF is sufficiently time-stable to be used as an ISM diagnostic. In future, applying this framework to 3-D dust maps will enable better treatment of dust as a cosmological foreground as well as reveal conditions in the ISM that shape star formation., Comment: 19 pages, 16 figures; version accepted by ApJ

In this work, a generic rigorous Bayesian formalism is introduced to predict the most likely path of any ion crossing a medium between two detection points. The path is predicted based on a combination of the particle scattering in the material and measurements of its initial and final position, direction and energy. The path estimate's precision is compared to the Monte Carlo simulated path. Every ion from hydrogen to carbon is simulated in two scenarios to estimate the accuracy achievable: one where the range is fixed and one where the initial velocity is fixed. In the scenario where the range is kept constant, the maximal root-mean-square error between the estimated path and the Monte Carlo path drops significantly between the proton path estimate (0.50 mm) and the helium path estimate (0.18 mm), but less so up to the carbon path estimate (0.09 mm). In the scenario where the initial velocity is kept constant, helium have systematically the minimal root-mean-square error throughout the path. As a result, helium is found to be the optimal particle for ion imaging., Comment: 20 pages, 6 figures, 1 table

Detection of point sources in images is a fundamental operation in astrophysics, and is crucial for constraining population models of the underlying point sources or characterizing the background emission. Standard techniques fall short in the crowded-field limit, losing sensitivity to faint sources and failing to track their covariance with close neighbors. We construct a Bayesian framework to perform inference of faint or overlapping point sources. The method involves probabilistic cataloging, where samples are taken from the posterior probability distribution of catalogs consistent with an observed photon count map. In order to validate our method we sample random catalogs of the gamma-ray sky in the direction of the North Galactic Pole (NGP) by binning the data in energy and Point Spread Function (PSF) classes. Using three energy bins spanning $0.3 - 1$, $1 - 3$ and $3 - 10$ GeV, we identify $270\substack{+30 \\ -10}$ point sources inside a $40^\circ \times 40^\circ$ region around the NGP above our point-source inclusion limit of $3 \times 10^{-11}$/cm$^2$/s/sr/GeV at the $1-3$ GeV energy bin. Modeling the flux distribution as a power law, we infer the slope to be $-1.92\substack{+0.07 \\ -0.05}$ and estimate the contribution of point sources to the total emission as $18\substack{+2 \\ -2}$\%. These uncertainties in the flux distribution are fully marginalized over the number as well as the spatial and spectral properties of the unresolved point sources. This marginalization allows a robust test of whether the apparently isotropic emission in an image is due to unresolved point sources or of truly diffuse origin.

Cataloging is challenging in crowded fields because sources are extremely covariant with their neighbors and blending makes even the number of sources ambiguous. We present the first optical probabilistic catalog, cataloging a crowded (~0.1 sources per pixel brighter than 22nd magnitude in F606W) Sloan Digital Sky Survey r band image from M2. Probabilistic cataloging returns an ensemble of catalogs inferred from the image and thus can capture source-source covariance and deblending ambiguities. By comparing to a traditional catalog of the same image and a Hubble Space Telescope catalog of the same region, we show that our catalog ensemble better recovers sources from the image. It goes more than a magnitude deeper than the traditional catalog while having a lower false discovery rate brighter than 20th magnitude. We also present an algorithm for reducing this catalog ensemble to a condensed catalog that is similar to a traditional catalog, except it explicitly marginalizes over source-source covariances and nuisance parameters. We show that this condensed catalog has a similar completeness and false discovery rate to the catalog ensemble. Future telescopes will be more sensitive, and thus more of their images will be crowded. Probabilistic cataloging performs better than existing software in crowded fields and so should be considered when creating photometric pipelines in the Large Synoptic Space Telescope era., Comment: 29 pages, 27 figures; changed prior on number of sources, added discussion on use of posterior sample catalogs in Section 4.2, added discussion of convergence in Section 5.4, expanded Introduction and Discussion, added cross-checks on assumed flux function index and PSF width in Appendices D and E; version to be published in the Astrophysical Journal

Past studies have identified a spatially extended excess of ~1-3 GeV gamma rays from the region surrounding the Galactic Center, consistent with the emission expected from annihilating dark matter. We revisit and scrutinize this signal with the intention of further constraining its characteristics and origin. By applying cuts to the Fermi event parameter CTBCORE, we suppress the tails of the point spread function and generate high resolution gamma-ray maps, enabling us to more easily separate the various gamma-ray components. Within these maps, we find the GeV excess to be robust and highly statistically significant, with a spectrum, angular distribution, and overall normalization that is in good agreement with that predicted by simple annihilating dark matter models. For example, the signal is very well fit by a 36-51 GeV dark matter particle annihilating to bb with an annihilation cross section of σv=(1-3)×10-26cm3/s (normalized to a local dark matter density of 0.4 GeV/cm 3 ). Furthermore, we confirm that the angular distribution of the excess is approximately spherically symmetric and centered around the dynamical center of the Milky Way (within ~0.05 ° of Sgr A * ), showing no sign of elongation along the Galactic Plane. The signal is observed to extend to at least ≃10° from the Galactic Center, which together with its other morphological traits disfavors the possibility that this emission originates from previously known or modeled pulsar populations. Keywords: Dark matter; Indirect detection; Gamma-rays, United States. Department of Energy (Contract DE-FG02-05ER41360)

Micromechanical resonators are very useful for detection of magnetic torque. We have developed nanoscale torsional resonators fabricated within silicon nitride membranes, as a platform for magnetometry of nanoscale magnetic elements. We describe the rotational magnetic hysteresis of a 10 nm thick film deposited on a resonator, and a study of magnetic hysteresis in a single, 1 m diameter permalloy disk. The torsional resonator is patterned using a dual beam scanning electron/focused ion system. For the 1 m diameter disk, it is found to be possible to tune the conditions such that an apparent magnetic supercooling of vortex nucleation is observed, as would be suggested by the modified Landau theory of the C- to vortex-state switch as a first-order phase transition. Complementary transmission electron and Lorentz microscopy of the same structures have also been performed. © 2011 American Institute of Physics.

The Large Area Telescope on the Fermi Gamma-ray Space Telescope has a point spread function with large tails, consisting of events affected by tracker ineffiencies, inactive volumes, and hard scattering; these tails can make source confusion a limiting factor. The parameter CTBCORE, available in the publicly available Extended Fermi LAT data, estimates the quality of each event's direction reconstruction; by implementing a cut in this parameter, the tails of the point spread function can be suppressed at the cost of losing effective area. We implement cuts on CTBCORE and present updated instrument response functions derived from the Fermi LAT data itself, along with all-sky maps generated with these cuts. Having shown the effectiveness of these cuts, especially at low energies, we encourage their use in analyses where angular resolution is more important than Poisson noise., Comment: 6 pages, 6 figures; extended PSF analysis down to 100 MeV, typos corrected; to be published in The Astrophysical Journal