1906.01638
KiDS-SQuaD II: Machine learning selection of bright extragalactic objects to search for new gravitationally lensed quasars
Khramtsov, et al
The KiDS Strongly lensed QUAsar Detection project (KiDS-SQuaD) aims at finding as many previously undiscovered gravitational lensed quasars as possible in the Kilo Degree Survey. This is the second paper of this series where we present a new, automatic object classification method based on machine learning technique. The main goal of this paper is to build a catalogue of bright extragalactic objects (galaxies and quasars), from the KiDS Data Release 4, with a minimum stellar contamination, preserving the completeness as much as possible, to then apply morphological methods to select reliable gravitationally lensed (GL) quasar candidates. After testing some of the most used machine learning algorithms, decision trees based classifiers, we decided to use CatBoost, that was specifically trained with the aim of creating a sample of extragalactic sources as clean as possible from stars. We discuss the input data, define the training sample for the classifier, give quantitative estimates of its performances, and finally describe the validation results with Gaia DR2, AllWISE, and GAMA catalogues. We have built and make available to the scientific community the KiDS Bright EXtraGalactic Objects catalogue (KiDS-BEXGO), specifically created to find gravitational lenses. This is made of $\approx6$ millions of sources classified as quasars ($\approx 200\,000$) and galaxies ($\approx 5.7$M), up to $r<22^m$. From this catalog we selected 'Multiplets': close pairs of quasars or galaxies surrounded by at least one quasar, presenting the 12 most reliable gravitationally lensed quasar candidates, to demonstrate the potential of the catalogue, which will be further explored in a forthcoming paper. We compared our search to the previous one, presented in the first paper from this series, showing that employing a machine learning method decreases the stars-contaminators within the GL candidates.
KiDS-SQuaD II: Machine learning selection of bright extragalactic objects to search for new gravitationally lensed quasars
Khramtsov, et al
The KiDS Strongly lensed QUAsar Detection project (KiDS-SQuaD) aims at finding as many previously undiscovered gravitational lensed quasars as possible in the Kilo Degree Survey. This is the second paper of this series where we present a new, automatic object classification method based on machine learning technique. The main goal of this paper is to build a catalogue of bright extragalactic objects (galaxies and quasars), from the KiDS Data Release 4, with a minimum stellar contamination, preserving the completeness as much as possible, to then apply morphological methods to select reliable gravitationally lensed (GL) quasar candidates. After testing some of the most used machine learning algorithms, decision trees based classifiers, we decided to use CatBoost, that was specifically trained with the aim of creating a sample of extragalactic sources as clean as possible from stars. We discuss the input data, define the training sample for the classifier, give quantitative estimates of its performances, and finally describe the validation results with Gaia DR2, AllWISE, and GAMA catalogues. We have built and make available to the scientific community the KiDS Bright EXtraGalactic Objects catalogue (KiDS-BEXGO), specifically created to find gravitational lenses. This is made of $\approx6$ millions of sources classified as quasars ($\approx 200\,000$) and galaxies ($\approx 5.7$M), up to $r<22^m$. From this catalog we selected 'Multiplets': close pairs of quasars or galaxies surrounded by at least one quasar, presenting the 12 most reliable gravitationally lensed quasar candidates, to demonstrate the potential of the catalogue, which will be further explored in a forthcoming paper. We compared our search to the previous one, presented in the first paper from this series, showing that employing a machine learning method decreases the stars-contaminators within the GL candidates.
1906.01846
Brighter-fatter effect in near-infrared detectors -- I. Theory of flat auto-correlations
Hirata, Choi
Weak gravitational lensing studies aim to measure small distortions in the shapes of distant galaxies, and thus place very tight demands on the understanding of detector-induced systematic effects in astronomical images. The Wide-Field Infrared Survey Telescope (WFIRST) will carry out weak lensing measurements in the near infrared using the new Teledyne H4RG-10 detector arrays, which makes the range of possible detector systematics very different from traditional weak lensing measurements using optical CCDs. One of the non-linear detector effects observed in CCDs is the brighter-fatter effect (BFE), in which charge already accumulated in a pixel alters the electric field geometry and causes new charge to be deflected away from brighter pixels. Here we describe the formalism for measuring the BFE using flat field correlation functions in infrared detector arrays. The auto-correlation of CCD flat fields is often used to measure the BFE, but because the infrared detector arrays are read out with the charge "in place," the flat field correlations are dominated by capacitive cross-talk between neighboring pixels (the inter-pixel capacitance, or IPC). We show that because the infrared detector arrays can be read out non-destructively, one can compute numerous cross-correlation functions between different time slices of the same flat exposures, and that correlations due to IPC and BFE leave distinct imprints. We generate a suite of simulated flat fields and show that the underlying IPC and BFE parameters can be extracted, even when both are present in the simulation. There are some biases in the BFE coefficients up to 12%, which are likely caused by higher order terms that are dropped from this analysis. The method is applied to laboratory data in the companion Paper II.
Brighter-fatter effect in near-infrared detectors -- I. Theory of flat auto-correlations
Hirata, Choi
Weak gravitational lensing studies aim to measure small distortions in the shapes of distant galaxies, and thus place very tight demands on the understanding of detector-induced systematic effects in astronomical images. The Wide-Field Infrared Survey Telescope (WFIRST) will carry out weak lensing measurements in the near infrared using the new Teledyne H4RG-10 detector arrays, which makes the range of possible detector systematics very different from traditional weak lensing measurements using optical CCDs. One of the non-linear detector effects observed in CCDs is the brighter-fatter effect (BFE), in which charge already accumulated in a pixel alters the electric field geometry and causes new charge to be deflected away from brighter pixels. Here we describe the formalism for measuring the BFE using flat field correlation functions in infrared detector arrays. The auto-correlation of CCD flat fields is often used to measure the BFE, but because the infrared detector arrays are read out with the charge "in place," the flat field correlations are dominated by capacitive cross-talk between neighboring pixels (the inter-pixel capacitance, or IPC). We show that because the infrared detector arrays can be read out non-destructively, one can compute numerous cross-correlation functions between different time slices of the same flat exposures, and that correlations due to IPC and BFE leave distinct imprints. We generate a suite of simulated flat fields and show that the underlying IPC and BFE parameters can be extracted, even when both are present in the simulation. There are some biases in the BFE coefficients up to 12%, which are likely caused by higher order terms that are dropped from this analysis. The method is applied to laboratory data in the companion Paper II.
1906.01847
Brighter-Fatter effect in near-infrared detectors -- II. Auto-correlation analysis of H4RG-10 flats
Choi, Hirata
The Wide Field Infrared Survey Telescope (WFIRST) will investigate the origins of cosmic acceleration using weak gravitational lensing at near infrared wavelengths. Lensing analyses place strict constraints on the precision of size and ellipticity measurements of the point spread function. WFIRST will use hybrid complementary metal oxide semiconductor (CMOS) detector arrays, which must be fully characterized to inform data reduction and calibration procedures such that unbiased cosmological results can be achieved. Hirata & Choi 2019 introduces formalism to connect the cross-correlation signal of different flat field time samples to non-linear detector behaviors such as the brighter fatter effect (BFE) and non-linear inter-pixel capacitance (NL-IPC), and this paper applies that framework to a WFIRST development detector, SCA 18237. We find a residual correlation signal after accounting for classical non-linearity. This residual correlation contains a combination of the BFE and NL-IPC; however, further tests suggest that the BFE is the dominant mechanism. If interpreted as a pure BFE, it suggests that the effective area of a pixel is increased by $(2.87\pm0.03)\times 10^{-7}$ (stat.) for every electron in the 4 nearest neighbors, with a rapid $\sim r^{-5.6\pm0.2}$ fall-off of the effect for more distant neighbors. We show that the IPC inferred from hot pixels contains the same large-scale spatial variations as the IPC inferred from auto-correlations, albeit with an overall offset of $\sim 0.06\%$. The NL-IPC inferred from hot pixels is too small to explain the cross-correlation measurement, further supporting the BFE hypothesis. This work presents the first evidence for the BFE in an H4RG-10 detector, demonstrates some of the useful insights that can be gleaned from flat field statistics, and represents a significant step towards calibration of WFIRST data.
1906.01967
Local monitoring of atmospheric transparency from the NASA MERRA-2 global assimilation system
Guyonnet, et al
Ground-based astronomy has to correct astronomical observations from the impact of the atmospheric transparency and its variability. The current objective of several observatories is to achieve a sub-percent level monitoring of atmospheric transmission. A promising approach has been to combine internal calibration of the observations with various external meteorological probes, upon availability and depending on quality. In this paper we investigate the use of the NASA Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) which is a global climate monitoring project that renders freely available for any given site, at any time, all the parameters constraining atmospheric transmission. This paper demonstrates the extraction of the relevant atmospheric parameters for optical astronomy at two sites: Mauna Kea in Hawaii and Cerro Tololo International Observatory in Chile. The temporal variability for the past eight years (annual, overnight and hourly), as well as the spatial gradients of ozone, precipitable water vapor, and aerosol optical depth is presented and their respective impacts on the atmospheric transparency is analyzed.
1906.02214
A pathfinder for imaging extrasolar Earths from the ground
Currie
The Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) project is an instrument on the Subaru telescope that is pushing the frontiers of what is possible with ground-based high-contrast imaging of extrasolar planets. The system features key breakthroughs in wavefront sensing and coronagraphy to yield extremely high Strehl ratio corrections and deep planet-to-star contrasts, even for optically faint stars. SCExAO is coupled to a near-infrared integral field spectrograph -- CHARIS -- yielding robust planet spectral characterization. In its first full year of operations, SCExAO has already clarified the properties of candidate companions around $\kappa$ And, LkCa 15, and HD 163296, showing the former to be a likely low-gravity, planet-mass object and the latter two to be misidentified disk signals. SCExAO's planet imaging capabilities in the near future will be further upgraded; the system is emerging as a prototype of the kind of dedicated planet-imaging system that could directly detect an Earth-like planet around a nearby low-mass star with Extremely Large Telescopes like the Thirty Meter Telescope.
1906.02217
A null test to probe the scale-dependence of the growth of structure as a test of General Relativity
Franco, et al
The main science driver for the coming generation of cosmological surveys is understanding dark energy which relies on testing General Relativity on the largest scales. Once we move beyond the simplest explanation for dark energy of a cosmological constant, the space of possible theories becomes both vast and extremely hard to compute realistic observables. A key discriminator of a cosmological constant, however, is that the growth of structure is scale-invariant on large scales. By carefully weighting observables derived from distributions of numbers of galaxies and a dipole pattern in their apparent sizes, we construct a null test which vanishes for any model of gravity or dark energy where the growth of structure is scale-independent. It relies only on very few assumptions about cosmology, and does not require any modelling of the growth of structure at late times. We show that with a survey like the Dark Energy Spectroscopic Instrument a scale-dependence of the order of 10-20 percent can be detected with 3 standard deviations with the null test, which will drop by a factor of 2 for a survey with a larger number of galaxies and volume, like the Square Kilometre Array will be capable of. We also show that the null test is very insensitive to typical uncertainties in other cosmological parameters including massive neutrinos and scale-dependent bias, making this a key null test for the cosmological constant.
1906.02747
The relationship between black hole mass and galaxy properties: examining the black hole feedback model in IllustrisTNG
Terrazas, et al
Supermassive black hole feedback is thought to be responsible for the lack of star formation, or quiescence, in a significant fraction of galaxies. We explore how observable correlations between the specific star formation rate (sSFR), stellar mass (M$_{\rm{star}}$), and black hole mass (M$_{\rm{BH}}$) are sensitive to the physics of black hole feedback in a galaxy formation model. We use the IllustrisTNG simulation suite, specifically the TNG100 simulation and ten model variations that alter the parameters of the black hole model. Focusing on central galaxies at $z = 0$ with M$_{\rm{star}} > 10^{10}$ M$_{\odot}$, we find that the sSFR of galaxies in IllustrisTNG decreases once the energy from black hole kinetic winds at low accretion rates becomes larger than the gravitational binding energy of gas within the galaxy stellar radius. This occurs at a particular M$_{\rm{BH}}$ threshold above which galaxies are found to sharply transition from being mostly star-forming to mostly quiescent. As a result of this behavior, the fraction of quiescent galaxies as a function of M$_{\rm{star}}$ is sensitive to both the normalization of the M$_{\rm{BH}}$-M$_{\rm{star}}$ relation and the M$_{\rm{BH}}$ threshold for quiescence in IllustrisTNG. Finally, we compare these model results to observations of 91 central galaxies with dynamical M$_{\rm{BH}}$ measurements with the caveat that this sample is not representative of the whole galaxy population. While IllustrisTNG reproduces the observed trend that quiescent galaxies host more massive black holes, the observations exhibit a broader scatter in M$_{\rm{BH}}$ at a given M$_{\rm{star}}$ and show a smoother decline in sSFR with M$_{\rm{BH}}$.
The relationship between black hole mass and galaxy properties: examining the black hole feedback model in IllustrisTNG
Terrazas, et al
Supermassive black hole feedback is thought to be responsible for the lack of star formation, or quiescence, in a significant fraction of galaxies. We explore how observable correlations between the specific star formation rate (sSFR), stellar mass (M$_{\rm{star}}$), and black hole mass (M$_{\rm{BH}}$) are sensitive to the physics of black hole feedback in a galaxy formation model. We use the IllustrisTNG simulation suite, specifically the TNG100 simulation and ten model variations that alter the parameters of the black hole model. Focusing on central galaxies at $z = 0$ with M$_{\rm{star}} > 10^{10}$ M$_{\odot}$, we find that the sSFR of galaxies in IllustrisTNG decreases once the energy from black hole kinetic winds at low accretion rates becomes larger than the gravitational binding energy of gas within the galaxy stellar radius. This occurs at a particular M$_{\rm{BH}}$ threshold above which galaxies are found to sharply transition from being mostly star-forming to mostly quiescent. As a result of this behavior, the fraction of quiescent galaxies as a function of M$_{\rm{star}}$ is sensitive to both the normalization of the M$_{\rm{BH}}$-M$_{\rm{star}}$ relation and the M$_{\rm{BH}}$ threshold for quiescence in IllustrisTNG. Finally, we compare these model results to observations of 91 central galaxies with dynamical M$_{\rm{BH}}$ measurements with the caveat that this sample is not representative of the whole galaxy population. While IllustrisTNG reproduces the observed trend that quiescent galaxies host more massive black holes, the observations exhibit a broader scatter in M$_{\rm{BH}}$ at a given M$_{\rm{star}}$ and show a smoother decline in sSFR with M$_{\rm{BH}}$.
1906.02787
The B-star exoplanet abundance study: a co-moving 16-25 Mjup companion to the young binary system HIP 79098
Janson, et al
Wide low-mass substellar companions are known to be very rare among low-mass stars, but appear to become increasingly common with increasing stellar mass. However, B-type stars, which are the most massive stars within ~150 pc of the Sun, have not yet been examined to the same extent as AFGKM-type stars in that regard. In order to address this issue, we launched the ongoing B-star Exoplanet Abundance Study (BEAST) to examine the frequency and properties of planets, brown dwarfs, and disks around B-type stars in the Scorpius-Centaurus (Sco-Cen) association; we also analyzed archival data of B-type stars in Sco-Cen. During this process, we identified a candidate substellar companion to the B9-type spectroscopic binary HIP 79098 AB, which we refer to as HIP 79098 (AB)b. The candidate had been previously reported in the literature, but was classified as a background contaminant on the basis of its peculiar colors. Here we demonstrate that the colors of HIP 79098 (AB)b are consistent with several recently discovered young and low-mass brown dwarfs, including other companions to stars in Sco-Cen. Furthermore, we show unambiguous common proper motion over a 15-year baseline, robustly identifying HIP 79098 (AB)b as a bona fide substellar circumbinary companion at a 345+/-6 AU projected separation to the B9-type stellar pair. With a model-dependent mass of 16-25 Mjup yielding a mass ratio of <1%, HIP 79098 (AB)b joins a growing number of substellar companions with planet-like mass ratios around massive stars. Our observations underline the importance of common proper motion analysis in the identification of physical companionship, and imply that additional companions could potentially remain hidden in the archives of purely photometric surveys.
1906.03035
The impact of the fiducial cosmology assumption on BAO cosmological parameter inference
Carter, et al
Standard analysis pipelines for measurements of Baryon Acoustic Oscillations (BAO) in galaxy surveys make use of a fiducial cosmological model to guide the data compression required to transform from observed redshifts and angles to the measured angular and radial BAO peak positions. In order to remove any dependence on the fiducial cosmology from the results, all models compared to the data should mimic the compression and its dependence on the fiducial model. In practice, approximations are made when testing models: (1) There is assumed to be no residual dependence on the fiducial cosmology after reconstruction, (2) differences in the distance--redshift relationship are assumed to match a linear scaling, and (3) differences in clustering between true and fiducial models are assumed to be removed by the free parameters used to null the non-BAO signal. We test these approximations using the current standard measurement procedure with a set of halo catalogs from the {\sc Aemulus} suite of $N$-body simulations, which span a range of $w\mathrm{CDM}$ cosmological models. We focus on reconstruction of the primordial BAO and locating the BAO. For the range of $w\mathrm{CDM}$ cosmologies covered by the {\sc Aemulus} suite, we find no evidence for systematic errors in the measured BAO shift parameters $\alpha_{\parallel}$ and $\alpha_{\bot}$ to $< 0.1\%$. However, the measured errors $\sigma_{\alpha_{\parallel}}$ and $\sigma_{\alpha_{\bot}}$ show a notable absolute increase by up to $+0.001$ and $+0.002$ respectively in the case that the fiducial cosmology does not match the truth. These effects on the inferred BAO scale will be important given the precision of measurements expected from future surveys including DESI, Euclid, and WFIRST.
1906.03156
Cosmological constraints with deep learning from KiDS-450 weak lensing maps
Fluri, et al
Convolutional Neural Networks (CNN) have recently been demonstrated on synthetic data to improve upon the precision of cosmological inference. In particular they have the potential to yield more precise cosmological constraints from weak lensing mass maps than the two-point functions. We present the cosmological results with a CNN from the KiDS-450 tomographic weak lensing dataset, constraining the total matter density $\Omega_m$, the fluctuation amplitude $\sigma_8$, and the intrinsic alignment amplitude $A_{\rm{IA}}$. We use a grid of N-body simulations to generate a training set of tomographic weak lensing maps. We test the robustness of the expected constraints to various effects, such as baryonic feedback, simulation accuracy, different value of $H_0$, or the lightcone projection technique. We train a set of ResNet-based CNNs with varying depths to analyze sets of tomographic KiDS mass maps divided into 20 flat regions, with applied Gaussian smoothing of $\sigma=2.34$ arcmin. The uncertainties on shear calibration and $n(z)$ error are marginalized in the likelihood pipeline. Following a blinding scheme, we derive constraints of $S_8 = \sigma_8 (\Omega_m/0.3)^{0.5} = 0.777^{+0.038}_{-0.036}$ with our CNN analysis, with $A_{\rm{IA}}=1.398^{+0.779}_{-0.724}$. We compare this result to the power spectrum analysis on the same maps and likelihood pipeline and find an improvement of about $30\%$ for the CNN. We discuss how our results offer excellent prospects for the use of deep learning in future cosmological data analysis.
1906.03673
The ssos Pipeline: identification of Solar System Objects in Astronomical images
Mahlke, et al
Observatories and satellites around the globe produce tremendous amounts of imaging data to study many different astrophysical phenomena. The serendipitous observations of Solar System objects are a fortunate by-product which have often been neglected due to the lack of a simple yet efficient identification algorithm. Meanwhile, the determination of the orbit, chemical composition, and physical properties such as rotation period and 3D-shape of Solar System objects requires a large number of astrometry and multi-band photometry observations. Such observations are hidden in current and future astrophysical archives, and a method to harvest these goldmines is needed. This article presents an easy-to-implement, light-weight software package which detects bodies of the Solar System in astronomical images and measures their astrometry and photometry. The ssos pipeline is versatile, allowing for application to all kinds of observatory imaging products. The sole principle requirement is that the images observe overlapping areas of the sky within a reasonable time range. Both known and unknown Solar System objects are recovered, from fast-moving near-Earth asteroids to slow objects in the Kuiper belt. The high-level pipeline design and two test applications are described here, highlighting the versatility of the algorithm with both narrow-field pointed and wide-field survey observations. In the first study, 2,828 detections of 204 SSOs are recovered from publicly available images of the GTC OSIRIS Broad Band DR1. The false-positive ratio of SSO detections ranges from 0%-23% depending on the pipeline setup. The second test study utilizes the images of the first data release of J-PLUS, a 12-band optical survey. 4,606 SSO candidates are recovered, with a false-positive ratio of (2.0 +- 0.2)%.
No comments:
Post a Comment