Abstracts of Interest
Selected by:
Tristan Betterman
Abstract: 2204.00002
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Title:Moosinesq Convection in the Cores of Moosive Stars
Download PDFAbstract: Stars with masses $\gtrsim 4 \times 10^{27}M_{\rm{moose}} \approx 1.1 M_\odot$ have core convection zones during their time on the main sequence. In these moosive stars, convection introduces many uncertainties in stellar modeling. In this Letter, we build upon the Boussinesq approximation to present the first-ever simulations of Moosinesq convection, which captures the complex geometric structure of the convection zones of these stars. These flows are bounded in a manner informed by the majestic terrestrial Alces alces (moose) and could have important consequences for the evolution of these stars. We find that Moosinesq convection results in very interesting flow morphologies and rapid heat transfer, and posit this as a mechanism of biomechanical thermoregulation.
Abstract: 2204.00285
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Title:KilonovaNet: Surrogate Models of Kilonova Spectra with Conditional Variational Autoencoders
Download PDFAbstract: Detailed radiative transfer simulations of kilonova spectra play an essential role in multimessenger astrophysics. Using the simulation results in parameter inference studies requires building a surrogate model from the simulation outputs to use in algorithms requiring sampling. In this work, we present KilonovaNet, an implementation of conditional variational autoencoders (cVAEs) for the construction of surrogate models of kilonova spectra. This method can be trained on spectra directly, removing overhead time of pre-processing spectra, and greatly speeds up parameter inference time. We build surrogate models of three state-of-the-art kilonova simulation data sets and present in-depth surrogate error evaluation methods, which can in general be applied to any surrogate construction method. By creating synthetic photometric observations from the spectral surrogate, we perform parameter inference for the observed light curve data of GW170817 and compare the results with previous analyses. Given the speed with which KilonovaNet performs during parameter inference, it will serve as a useful tool in future gravitational wave observing runs to quickly analyze potential kilonova candidates
Abstract: 2204.00267
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Full Text: [ PostScript, PDF]
Title:Spatial extension of dark subhalos as seen by Fermi-LAT and implications for WIMP constraints
Download PDFAbstract: Spatial extension has been hailed as a "smoking gun" in the gamma-ray search of dark galactic subhalos, which would appear as unidentified sources for gamma-ray telescopes. In this work, we study the sensitivity of the Fermi-LAT to extended subhalos using simulated data based on a realistic sky model. We simulate spatial templates for a set of representative subhalos, whose parameters were derived from our previous work with N-body cosmological simulation data. We find that detecting an extended subhalo and finding an unequivocal signal of angular extension requires, respectively, a flux 2 to 10 times larger than in the case of a point-like source. By studying a large grid of models, where parameters such as the WIMP mass, annihilation channel or subhalo model are varied significantly, we obtain the response of the LAT as a function of the product of annihilation cross section times the J-factor. Indeed, we show that spatial extension can be used as an additional filter to reject subhalos candidates among the pool of unidentified LAT sources, as well as a "smoking gun" for positive identification. For instance, typical angular extensions of a few tenths of degree are expected for the considered scenarios. Finally, we also study the impact of the obtained LAT sensitivity to such extended subhalos on the achievable dark matter constraints, which are a few times less constraining than comparable point-source limits.
Abstract: 2204.00346
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Full Text: [ PostScript, PDF]
Title:A Comparative Study of Machine Learning Methods for X-ray Binary Classification
Download PDFAbstract: X-ray Binaries (XRBs) consist of a compact object that accretes material from an orbiting secondary star. The most secure method we have for determining if the compact object is a black hole is to determine its mass: this is limited to bright objects, and requires substantial time-intensive spectroscopic monitoring. With new X-ray sources being discovered with different X-ray observatories, developing efficient, robust means to classify compact objects becomes increasingly important. We compare three machine learning classification methods (Bayesian Gaussian Processes (BGP), K-Nearest Neighbors (KNN), Support Vector Machines (SVM)) for determining the compact objects as neutron stars or black holes (BHs) in XRB systems. Each machine learning method uses spatial patterns which exist between systems of the same type in 3D Color-Color-Intensity diagrams. We used lightcurves extracted using six years of data with MAXI/GSC for 44 representative sources. We find that all three methods are highly accurate in distinguishing pulsing from non-pulsing neutron stars (NPNS) with 95\% of NPNS and 100\% of pulsars accurately predicted. All three methods have high accuracy distinguishing BHs from pulsars (92\%) but continue to confuse BHs with a subclass of NPNS, called the Bursters, with KNN doing the best at only 50\% accuracy for predicting BHs. The precision of all three methods is high, providing equivalent results over 5-10 independent runs. In a future work, we suggest a fourth dimension be incorporated to mitigate the confusion of BHs with Bursters. This work paves the way towards more robust methods to efficiently distinguish BHs, NPNS, and pulsars.
Abstract: 2204.00500
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Title:ASAS-SN follow-up of IceCube high-energy neutrino alerts
Download PDFAbstract: We report on the search for optical counterparts to IceCube neutrino alerts released between April 2016 and August 2021 with the All-Sky Automated Survey for SuperNovae (ASAS-SN). Despite the discovery of a diffuse astrophysical high-energy neutrino flux in 2013, the source of those neutrinos remains largely unknown. Since 2016, IceCube has published likely-astrophysical neutrinos as public realtime alerts. Through a combination of normal survey and triggered target-of-opportunity observations, ASAS-SN obtained images within 1 hour of the neutrino detection for 20% (11) of all observable IceCube alerts and within one day for another 57% (32). For all observable alerts, we obtained images within at least two weeks from the neutrino alert. ASAS-SN provides the only optical follow-up for about 17% of IceCube's neutrino alerts. We recover the two previously claimed counterparts to neutrino alerts, the flaring-blazar TXS 0506+056 and the tidal disruption event AT2019dsg. We investigate the light curves of previously-detected transients in the alert footprints, but do not identify any further candidate neutrino sources. We also analysed the optical light curves of Fermi 4FGL sources coincident with high-energy neutrino alerts, but do not identify any contemporaneous flaring activity. Finally, we derive constraints on the luminosity functions of neutrino sources for a range of assumed evolution models.
Abstract: 2204.00579
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Full Text: [ PostScript, PDF]
Title:On the X-ray, optical and radio afterglows of the BdHN I GRB 180720B generated by the synchrotron emission
Download PDFAbstract: Gamma-ray bursts (GRBs) are systems of unprecedented complexity across all the electromagnetic spectrum, including the radio, optical, X-rays, gamma-rays in the megaelectronvolt (MeV) and gigaelectronvolt (GeV) regime, as well as ultrahigh-energy cosmic rays (UHECRs), each manifested in seven specific physical processes with widely different characteristic evolution timescales ranging from $10^{-14}$ s to $10^{7}$ s or longer. We here study the long GRB 180720B originating from a binary system composed of a massive CO$_{\rm core}$ of about $10 M_\odot$ and a companion neutron star (NS). The gravitational collapse of the CO$_{\rm core}$ gives rise to a spinning newborn NS ($\nu$NS), with an initial period of $P_0=1$ ms that powers the synchrotron radiation in the radio, optical, and X-ray wavelengths. We here investigate solely the GRB 180720B afterglows and present a detailed treatment of its origin based on the synchrotron radiation released by the interaction of the $\nu$NS and the SN ejecta. We show that in parallel to the X-ray afterglow, the spinning $\nu$NS also powers the optical and radio afterglows and allows to infer the $\nu$NS and ejecta parameters that fit the observational data.
Abstract: 2204.02398
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Title:fBLS -- a fast-folding BLS algorithm
Download PDFAbstract: We present fBLS -- a novel fast-folding technique to search for transiting planets, based on the fast-folding algorithm (FFA), which is extensively used in pulsar astronomy. For a given lightcurve with $N$ data points, fBLS simultaneously produces all the binned phase-folded lightcurves for an array of $N_p$ trial periods. For each folded lightcurve produced by fBLS, the algorithm generates the standard BLS periodogram and statistics. The number of performed arithmetic operations is $\mathcal{O}\big(N_p\cdot\log N_p \big)$, while regular BLS requires $\mathcal{O}\big(N_p\cdot N\big)$ operations. fBLS can be used to detect small rocky transiting planets, with periods shorter than one day, a period range for which the computation is extensive. We demonstrate the capabilities of the new algorithm by performing a preliminary fBLS search for planets with ultra-short periods in the Kepler main-sequence lightcurves. In addition, we developed a simplistic signal validation scheme for vetting the planet candidates. This two-stage preliminary search identified all known ultra-short planet candidates and found three new ones.
Abstract: 2204.01550
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Full Text: [ PostScript, PDF]
Title:Physical Properties of the Supernova Remnant Population in the Small Magellanic Cloud
Download PDFAbstract: The X-ray emission from a supernova remnant is a powerful diagnostic of the state of its shocked plasma. The temperature and the emission measure are related to the energy of the explosion, the age of the remnant, and the density of the surrounding medium. Here we present the results of a study of the remnant population of the Small Magellanic Cloud. Progress in X-ray observations of remnants has resulted in a sample of 20 remnants in the Small Magellanic Clound with measured temperatures and emission measures. We apply spherically symmetric supernova remnant evolution models to this set of remnants, to estimate ages, explosion energies, and circumstellar medium densities. The distribution of ages yields a remnant birthrate of $\sim$1/1200 yr. The energies and densities are well fit with log-normal distributions, with means of 1.6$\times10^{51}$ erg and 0.14 cm$^{-3}$, and 1$\sigma$ dispersions of a factor of 1.87 in energy and 3.06 in density, respectively.
Abstract: 2204.01515
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Title:Modeling the GRB jet properties with 3D general relativistic simulations of magnetically arrested accretion flows
Download PDFAbstract: We investigate the dependence of the GRB jet structure and its evolution on the properties of the accreting torus in the central engine. Our models numerically evolve the accretion disk around a Kerr black hole using 3D general relativistic magnetohydrodynamic simulations. We use two different analytical hydrodynamical models of the accretion disk, based on the Fishbone-Moncrief and Chakrabarti solutions, as our initial states for the structure of the collapsar disk and the remnant after a binary neutron star merger, respectively. We impose poloidal magnetic fields of two different geometries upon the initial stable solutions. We study the formation and evolution of the magnetically arrested disk state and its effect on the properties of the emitted jet. The jets produced in our models are structured and have a relatively hollow core and reach higher Lorentz factors at an angle $\gtrsim 9{^\circ}$ from the axis. The jet in our short GRB model has an opening angle of up to $\sim 25^{\circ}$ while our long GRB engine produces a narrower jet, of up to $\sim 11^{\circ}$. We also study the time variability of the jets and provide an estimate of the minimum variability timescale in our models. The application of our models to the GRB jets in the binary neutron star post-merger system and to the ultra-relativistic jets launched from collapsing stars are briefly discussed.
Abstract: 2204.01183
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Title:Cluster Structures with Machine Learning Support in Neutron Star M-R relations
Download PDFAbstract: Neutron stars (NS) are compact objects with strong gravitational fields, and a matter composition subject to extreme physical conditions. The properties of strongly interacting matter at ultra-high densities and temperatures impose a big challenge to our understanding and modelling tools. Some difficulties are critical, since one cannot reproduce such conditions in our laboratories or assess them purely from astronomical observations. The information we have about neutron star interiors are often extracted indirectly, e.g., from the star mass-radius relation. The mass and radius are global quantities and still have a significant uncertainty, which leads to great variability in studying the micro-physics of the neutron star interior. This leaves open many questions in nuclear astrophysics and the suitable equation of state (EoS) of NS. Recently, new observations appear to constrain the mass-radius and consequently has helped to close some open questions. In this work, utilizing modern machine learning techniques, we analyze the NS mass-radius (M-R) relationship for a set of EoS containing a variety of physical models. Our objective is to determine patterns through the M-R data analysis and develop tools to understand the EoS of neutron stars in forthcoming works.
Abstract: 2204.00636
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Title:The Andromeda Gamma-Ray Excess: Background Systematics of the Millisecond Pulsars and Dark Matter Interpretations
Download PDFAbstract: Since the discovery of an excess in gamma rays in the direction of M31, its cause has been unclear. Published interpretations focus on a dark matter or stellar related origin. Studies of a similar excess in the Milky Way center motivate a correlation of the spatial morphology of the signal with the distribution of stellar mass in M31. However, a robust determination of the best theory for the observed excess emission is very challenging due to large uncertainties in the astrophysical gamma-ray foreground model. Here we perform a spectro-morphological analysis of the M31 gamma-ray excess using state-of-the-art templates for the distribution of stellar mass in M31 and novel astrophysical foreground models for its sky region. We construct maps for the old stellar populations of M31 based on observational data from the PAndAS survey and carefully remove the foreground stars. We also produce improved astrophysical foreground models by using novel image inpainting techniques based on machine learning methods. We find that our stellar maps, taken as a proxy for the location of a putative population of millisecond pulsars in the bulge of M31, reach a statistical significance of $5.4\sigma$, making them as strongly favoured as the simple phenomenological models usually considered in the literature, e.g., a disk-like template with uniform brightness. Our detection of the stellar templates is robust to generous variations of the astrophysical foreground model. Once the stellar templates are included in the astrophysical model, we show that the dark matter annihilation interpretation of the signal is unwarranted. Using the results of a binary population synthesis model we demonstrate that a population of about one million unresolved MSPs could naturally explain the observed gamma-ray luminosity per stellar mass, energy spectrum, and stellar bulge-to-disk flux ratio.
Abstract: 2204.01746
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Title:Perspectives for multi-messenger astronomy with the next generation of gravitational-wave detectors and high-energy satellites
Download PDFAbstract: The Einstein Telescope (ET) is going to bring a revolution for the future of multi-messenger astrophysics. In order to detect the counterparts of binary neutron star (BNS) mergers at high redshift, the high-energy observations will play a crucial role. Here, we explore the perspectives of ET, as single observatory and in a network of gravitational-wave (GW) detectors, operating in synergy with future $\gamma$-ray and X-ray satellites. We predict the high-energy emission of BNS mergers and its detectability in a theoretical framework which is able to reproduce the properties of the current sample of observed short GRBs (SGRB). We estimate the joint GW and high-energy detection rate for both the prompt and afterglow emissions, testing several combinations of instruments and observational strategies. We find that the vast majority of SGRBs detected in $\gamma$-rays will have a detectable GW counterpart; the joint detection efficiency approaches $100\%$ considering a network of third generation GW observatories. The probability of identifying the electromagnetic counterpart of BNS mergers is significantly enhanced if the sky localisation provided by GW instruments is observed by wide field X-ray monitors. We emphasize that the role of the future X-ray observatories will be very crucial for the detection of the fainter emission outside the jet core, which will allow us to probe the yet unexplored population of low-luminosity SGRBs in the nearby Universe, as well as to unveil the nature of the jet structure and the connections with the progenitor properties.
Abstract: 2204.02361
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Title:Origin of supermassive black holes in massive metal-poor protoclusters
Download PDFAbstract: While large numbers of supermassive black holes have been detected at z>6, their origin is still essentially unclear. Numerical simulations have shown that the conditions for the classical direct collapse scenario are very restrictive and fragmentation is very difficult to be avoided. We thus consider here a more general case of a dense massive protostar cluster at low metallicity (<~ 10^{-3} Z_solar) embedded in gas. We estimate the mass of the central massive object, formed via collisions and gas accretion, considering the extreme cases of a logarithmically flat and a Salpeter-type initial mass function. Objects with masses of at least 10^4 solar could be formed for inefficient radiative feedback, whereas ~10^3 solar mass objects could be formed when the accretion time is limited via feedback. These masses will vary depending on the environment and could be considerably larger, particularly due to the continuous infall of gas into the cloud. As a result, one may form intermediate mass black holes of ~ 10^4 solar masses or more. Upcoming observations with the James Webb Space Telescope (JWST) and other observatories may help to detect such massive black holes and their environment, thereby shedding additional light on such a formation channel.
Abstract: 2204.02080
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Title:Photometric redshift-aided classification using ensemble learning
Download PDFAbstract: We present SHEEP, a new machine learning approach to the classic problem of astronomical source classification, which combines the outputs from the XGBoost, LightGBM, and CatBoost learning algorithms to create stronger classifiers. A novel step in our pipeline is that prior to performing the classification, SHEEP first estimates photometric redshifts, which are then placed into the dataset as an additional feature for classification model training; this results in significant improvement in the subsequent classification performance. SHEEP contains two distinct classification methodologies: (i) Multi-class; (ii) one vs all with correction by a meta-learner. We demonstrate the performance of SHEEP for the classification of stars, galaxies and quasars using a dataset composed of SDSS and WISE photometry of 3.5 million astronomical sources. The resulting F1-scores are as follows: (i) 0.992 for galaxies; (ii) 0.967 for quasars; (iii) and 0.985 for stars. In terms of the F1-scores for the three classes, SHEEP is found to outperform the recent RandomForest-based classification approach of Clarke et al. (2020) using an essentially identical dataset. Our methodology also facilitates model and dataset explainability via feature importances; it also allows the selection of sources whose uncertain classifications may make them interesting sources for follow-up observations.
Abstract: 2204.03363
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Title:Characterization of the GRB Fundamental Plane using Fermi-GBM data
Download PDFAbstract: A recent work has found a tight global relation between the GRB fluence, peak flux ( based on the optimum time scale determined from the Bayesian Blocks-based analysis) and duration using data from the Fermi Gamma-Ray burst monitor, which they have dubbed as "Fundamental Plane". We quantitatively characterize the tightness of this Fundamental Plane relation using by calculating the scatter in dex. We also check for a fundamental plane using the peak flux over time scales of 64 ms, 256 ms and 1024 ms. For our analysis, we incorporate the uncertainties in the above observables and carried out both a PCA as well as regression-based analysis. We find that the scatter in the fundamental plane is 0.16-0.17 dex. This is not as as tight as some of the other well known scaling relations in Astrophysics.
Abstract: 2204.03517
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Full Text: [ PostScript, PDF]
Title:Finding magnetic north: an extraordinary magnetic field detection in Polaris and first results of a magnetic survey of classical Cepheids
Download PDFAbstract: Classical Cepheids are essential objects in the study of stellar evolution and cosmology; however, we know little about their magnetic properties. We report the detection of Stokes $V$ features interpreted as Zeeman signatures in four classical Cepheids using high-resolution spectropolarimetric observations obtained with ESPaDOnS at CFHT. Eight observations of $\eta$ Aql were acquired in 2017 covering its 7.2 d pulsation period, and single observations of Polaris, $\zeta$ Gem, $\delta$ Cep and RT Aur were obtained in 2020 as part of our ongoing systematic survey. We use mean circular polarization Stokes $V$ profiles generated using the Least-Squares Deconvolution procedure to diagnose Zeeman signatures and measure mean longitudinal field strengths $\langle B_{z}\rangle$. We detect magnetic signatures across all pulsation phases of $\eta$ Aql ($-0.89\pm0.47$ G$\,<\langle B_{z}\rangle<1.27\pm 0.40$ G), as well as in the single observations of Polaris ($0.59\pm0.16$ G), $\zeta$ Gem ($0.41\pm0.16$ G) and $\delta$ Cep ($0.43\pm0.19$ G). The Stokes $V$ profile of Polaris is detected at extremely high S/N and implies a complex magnetic field topology. It stands in stark contrast to all other detected Stokes $V$ profiles, which show unusual approximately unipolar positive circular polarization lobes analogous to those observed in some Am stars.
Abstract: 2204.00017
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Full Text: [ PostScript, PDF]
Title:Evaluating the feasibility of interpretable machine learning for globular cluster detection
Download PDFAbstract: Extragalactic globular clusters (GCs) are important tracers of galaxy formation and evolution. Obtaining GC catalogues from photometric data involves several steps which will likely become too time-consuming to perform on the large data volumes that are expected from upcoming wide-field imaging projects such as Euclid. In this work, we explore the feasibility of various machine learning (ML) methods to aid the search for GCs. We use archival Hubble Space Telescope data in the F475W and F850LP bands of 141 early-type galaxies in the Fornax and Virgo galaxy clusters. Using existing GC catalogues to label the data, we obtain an extensive data set of 84929 sources containing 18556 GCs and we train several ML methods both on image and tabular data containing physically relevant features extracted from the images. We find that our evaluated ML models are capable of producing catalogues of similar quality as the existing ones. The best performing methods, ensemble-based models like random forests and convolutional neural networks, recover ~ 90-94 % of GCs while producing an acceptable amount of false detections (~ 6-8 %) - with some falsely detected sources being identifiable as GCs that have not been labelled as such in the used catalogues. In the magnitude range 22 < m4_g < 24.5 mag, 98 - 99 % of GCs are recovered. We even find such high performance levels when training on Virgo and evaluating on Fornax data (and vice versa), illustrating that the models are transferable to environments with different conditions such as different distances than in the used training data. Additionally, we demonstrate how interpretable methods can be used to better understand model predictions, recovering that magnitudes, colours, and sizes are important for identifying GCs. These are encouraging results, indicating that similar methods can be applied for creating GC catalogues for a large number of galaxies.
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