Identifying new X-ray binary candidates in M31 using random forest classification

Identifying X-ray binary (XRB) candidates in nearby galaxies requires distinguishing them from possible contaminants including foreground stars and background active galactic nuclei. This work investigates the use of supervised machine learning algorithms to identify highprobability XRB candidates. Using a catalogue of 943 Chandra X-ray sources in the Andromeda galaxy, we trained and tested several classification algorithms using the X-ray properties of 163 sources with previously known types. Amongst the algorithms tested, we find that random forest classifiers give the best performance and work better in a binary classification (XRB/non-XRB) context compared to the use of multiple classes. Evaluating our method by comparingwith classifications from visible-light and hardX-ray observations as part of the Panchromatic Hubble Andromeda Treasury, we find compatibility at the 90 per cent level, although we caution that the number of source in common is rather small. The estimated probability that an object is an XRB agrees well between the random forest binary and multiclass approaches and we find that the classifications with the highest confidence are in the XRB class. Themost discriminating X-ray bands for classification are the 1.7-2.8, 0.5-1.0, 2.0-4.0, and 2.0-7.0 keV photon flux ratios. Of the 780 unclassified sources in the Andromeda catalogue, we identify 16 new high-probability XRB candidates and tabulate their properties for follow-up

Astro 2020 Science White Paper: Time Domain Studies of Neutron Star and Black Hole Populations: X-ray Identification of Compact Object Types

What are the most important conditions and processes governing the growth of stellar-origin compact objects? The identification of compact object type as either black hole (BH) or neutron star (NS) is fundamental to understanding their formation and evolution. To date, time-domain determination of compact object type remains a relatively untapped tool. Measurement of orbital periods, pulsations, and bursts will lead to a revolution in the study of the demographics of NS and BH populations, linking source phenomena to accretion and galaxy parameters (e.g., star formation, metallicity). To perform these measurements over sufficient parameter space, a combination of a wide-field (>5000 deg^2) transient X-ray monitor over a dynamic energy range (~1-100 keV) and an X-ray telescope for deep surveys with <5 arcsec PSF half-energy width (HEW) angular resolution are required. Synergy with multiwavelength data for characterizing the underlying stellar population will transform our understanding of the time domain properties of transient sources, helping to explain details of supernova explosions and gravitational wave event rates.Comment: 9 pages, 2 figures. Submitted to the Astro2020 Decadal Surve

The Next Generation X-ray Galaxy Survey with eROSITA

eROSITA, launched on 13 July 2019, will be completing the first all-sky survey in the soft and medium X-ray band in nearly three decades. This 4-year survey, finishing in late 2023, will present a rich legacy for the entire astrophysics community and complement upcoming multi-wavelength surveys (with, e.g. the Large Synoptic Survey Telescope and the Dark Energy Survey). Besides the major scientific aim to study active galactic nuclei (AGN) and galaxy clusters, eROSITA will contribute significantly to X-ray studies of normal (i.e., not AGN) galaxies. Starting from multi-wavelength catalogues, we measure star formation rates and stellar masses for 60 212 galaxies constrained to distances of 50-200 Mpc. We chose this distance range to focus on the relatively unexplored volume outside the local Universe, where galaxies will be largely spatially unresolved and probe a range of X-ray luminosities that overlap with the low luminosity and/or highly obscured AGN population. We use the most recent X-ray scaling relations as well as the on-orbit eROSITA instrument performance to predict the X-ray emission from XRBs and diffuse hot gas and to perform both an analytic prediction and an end-to-end simulation using the mission simulation software, SIXTE. We consider potential contributions from hidden AGN and comment on the impact of normal galaxies on the measurement of the faint end of the AGN luminosity function. We predict that the eROSITA 4-year survey, will detect $\gtrsim$ 15 000 galaxies (3 $\sigma$ significance) at 50-200 Mpc, which is ~100X more normal galaxies than detected in any X-ray survey to date.Comment: 18 pages, 15 figures. Accepted for publication in MNRA

Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules

Morphologically rich languages accentuate two properties of distributional vector space models: 1) the difficulty of inducing accurate representations for low-frequency word forms; and 2) insensitivity to distinct lexical relations that have similar distributional signatures. These effects are detrimental for language understanding systems, which may infer that inexpensive is a rephrasing for expensive or may not associate acquire with acquires. In this work, we propose a novel morph-fitting procedure which moves past the use of curated semantic lexicons for improving distributional vector spaces. Instead, our method injects morphological constraints generated using simple language-specific rules, pulling inflectional forms of the same word close together and pushing derivational antonyms far apart. In intrinsic evaluation over four languages, we show that our approach: 1) improves low-frequency word estimates; and 2) boosts the semantic quality of the entire word vector collection. Finally, we show that morph-fitted vectors yield large gains in the downstream task of dialogue state tracking, highlighting the importance of morphology for tackling long-tail phenomena in language understanding tasks

Black Holes and Neutron Stars in Nearby Galaxies: Insights from NuSTAR

Nearby galaxy surveys have long classified X-ray binaries (XRBs) by the mass category of their donor stars (high-mass and low-mass). The NuSTAR observatory, which provides imaging data at E $>10$ keV, has enabled the classification of extragalactic XRBs by their compact object type: neutron star (NS) or black hole (BH). We analyzed NuSTAR/Chandra/XMM-Newton observations from a NuSTAR-selected sample of 12 galaxies within 5 Mpc having stellar masses ($M_{\star}$) $10^{7-11}$ $M_{\odot}$ and star formation rates (SFR) $\approx0.01-15$ $M_{\odot}$ yr$^{-1}$. We detect 128 NuSTAR sources to a sensitivity of $\approx10^{38}$ erg s$^{-1}$. Using NuSTAR color-intensity and color-color diagrams we classify 43 of these sources as candidate NS and 47 as candidate BH. We further subdivide BH by accretion states (soft, intermediate, and hard) and NS by weak (Z/Atoll) and strong (accreting pulsar) magnetic field. Using 8 normal (Milky Way-type) galaxies in the sample, we confirm the relation between SFR and galaxy X-ray point source luminosity in the 4-25 and 12-25 keV energy bands. We also constrain galaxy X-ray point source luminosity using the relation $L_{\rm{X}}=\alpha M_{\star}+\beta\text{SFR}$, finding agreement with previous work. The XLF of all sources in the 4-25 and 12-25 keV energy bands matches with the $\alpha=1.6$ slope for high-mass XRBs. We find that NS XLFs suggest a decline beginning at the Eddington limit for a 1.4 $M_{\odot}$ NS, whereas the BH fraction shows an approximate monotonic increase in the 4-25 and 12-25keV energy bands. We calculate the overall ratio of BH to NS to be $\approx1$ for 4-25 keV and $\approx2$ for 12-25 keV.Comment: 38 pages, 12 figures, 8 tables. ApJ, in pres

Plasma-derived proteomic biomarkers in human leukocyte antigen-haploidentical or human leukocyte antigen-matched bone marrow transplantation using post-transplantation cyclophosphamide

Recent studies have suggested that plasma-derived proteins may be potential biomarkers relevant for graft-versus-host disease and/or non-relapse mortality occurring after allogeneic blood or marrow transplantation. However, none of these putative biomarkers have been assessed in patients treated either with human leukocyte antigen-haploidentical blood or marrow transplantation or with post-transplantation cyclophosphamide, which has been repeatedly associated with low rates of severe acute graft-versus-host disease, chronic graft-versus-host disease, and non-relapse mortality. We explored whether seven of these plasma-derived proteins, as measured by enzyme-linked immunosorbent assays, were predictive of clinical outcomes in post-transplantation cyclophosphamide-treated patients using plasma samples collected at serial predetermined timepoints from patients treated on prospective clinical studies of human leukocyte antigen-haploidentical (n=58; clinicaltrials.gov Identifier: 00796562) or human leukocyte antigen-matched-related or -unrelated (n=100; clinicaltrials.gov Identifiers: 00134017 and 00809276) T-cell-replete bone marrow transplantation. Day 30 levels of interleukin-2 receptor α, tumor necrosis factor receptor 1, serum STimulation-2 (IL1RL1 gene product), and regenerating islet-derived 3-α all had high areas under the curve of 0.74–0.97 for predicting non-relapse mortality occurrence by 3 months post-transplant in both the human leukocyte antigen-matched and human leukocyte antigen-haploidentical cohorts. In both cohorts, all four of these proteins were also predictive of subsequent non-relapse mortality occurring by 6, 9, or 12 months post-transplant and were significantly associated with non-relapse mortality in univariable analyses. Furthermore, day 30 elevations of interleukin-2 receptor α were associated with grade II–IV and III–IV acute graft-versus-host disease occurring after day 30 in both cohorts. These data confirm that plasma-derived proteins previously assessed in other transplantation platforms appear to retain prognostic and predictive utility in patients treated with post-transplantation cyclophosphamide

Mutations in two global regulators lower individual mortality in Escherichia coli

There has been considerable investigation into the survival of bacterial cells under stress conditions, but little is known about the causes of mortality in the absence of exogenous stress. That there is a basal frequency of cell death in such populations may reflect that it is either impossible to avoid all lethal events, or alternatively, that it is too costly. Here, through a genetic screen in the model organism Escherichia coli, we identify two mutants with lower frequencies of mortality: rssB and fliA. Intriguingly, these two genes both affect the levels of different sigma factors within the cell. The rssB mutant displays enhanced resistance to multiple external stresses, possibly indicating that the cell gains its increased vitality through elevated resistance to spontaneous, endogenous stresses. The loss of fliA does not result in elevated stress resistance; rather, its survival is apparently due to a decreased physical stress linked to the insertion of the flagellum through the membrane and energy saved through the loss of the motor proteins. The identification of these two mutants implies that reducing mortality is not impossible; rather, due to its cost, it is subject to trade-offs with other traits that contribute to the competitive success of the organism