arXiv subjects

R. Morgan

Publications and source records attributed to R. Morgan.

81 records · Page 5Linked to original sources

arXiv2020

A statistical standard siren measurement of the Hubble constant from the LIGO/Virgo gravitational wave compact object merger GW190814 and Dark Energy Survey galaxies

We present a measurement of the Hubble constant $H_0$ using the gravitational wave (GW) event GW190814, which resulted from the coalescence of a 23 $M_\odot$ black hole with a 2.6 $M_\odot$ compact object, as a standard siren. No compelling electromagnetic counterpart has been identified for this event, thus our analysis accounts for thousands of potential host galaxies within a statistical framework. The redshift information is obtained from the photometric redshift (photo-$z$) catalog from the Dark Energy Survey. The luminosity distance is provided by the LIGO/Virgo gravitational wave sky map. Since this GW event has the second-smallest localization volume after GW170817, GW190814 is likely to provide the best constraint on cosmology from a single standard siren without identifying an electromagnetic counterpart. Our analysis uses photo-$z$ probability distribution functions and corrects for photo-$z$ biases. We also reanalyze the binary-black hole GW170814 within this updated framework. We explore how our findings impact the $H_0$ constraints from GW170817, the only GW merger associated with a unique host galaxy. From a combination of GW190814, GW170814 and GW170817, our analysis yields $H_0 = 72.0^{+ 12}_{- 8.2 }~{\rm km~s^{-1}~Mpc^{-1}}$ (68\% Highest Density Interval, HDI) for a prior in $H_0$ uniform between $[20,140]~{\rm km~s^{-1}~Mpc^{-1}}$. The addition of GW190814 and GW170814 to GW170817 improves the 68\% HDI from GW170817 alone by $\sim 18\%$, showing how well-localized mergers without counterparts can provide a significant contribution to standard siren measurements, provided that a complete galaxy catalog is available at the location of the event.

astro-ph.CO↗

arXiv2020

Dark Energy Survey Year 3 Results: Clustering Redshifts -- Calibration of the Weak Lensing Source Redshift Distributions with redMaGiC and BOSS/eBOSS

We present the calibration of the Dark Energy Survey Year 3 (DES Y3) weak lensing source galaxy redshift distributions $n(z)$ from clustering measurements. In particular, we cross-correlate the weak lensing (WL) source galaxies sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) and a spectroscopic sample from BOSS/eBOSS to estimate the redshift distribution of the DES sources sample. Two distinct methods for using the clustering statistics are described. The first uses the clustering information independently to estimate the mean redshift of the source galaxies within a redshift window, as done in the DES Y1 analysis. The second method establishes a likelihood of the clustering data as a function of $n(z)$, which can be incorporated into schemes for generating samples of $n(z)$ subject to combined clustering and photometric constraints. Both methods incorporate marginalisation over various astrophysical systematics, including magnification and redshift-dependent galaxy-matter bias. We characterise the uncertainties of the methods in simulations; the first method recovers the mean $z$ of tomographic bins to RMS (precision) of $\sim 0.014$. Use of the second method is shown to vastly improve the accuracy of the shape of $n(z)$ derived from photometric data. The two methods are then applied to the DES Y3 data.

astro-ph.CO↗

arXiv2020

The Dark Energy Survey Supernova Program: Modelling selection efficiency and observed core collapse supernova contamination

The analysis of current and future cosmological surveys of type Ia supernovae (SNe Ia) at high-redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-year photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 5.8 to 9.3 per cent, with an average of 7.0 per cent and r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty.

astro-ph.CO↗

arXiv2020

Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects

In this paper we investigate how implementing machine learning could improve the efficiency of the search for Trans-Neptunian Objects (TNOs) within Dark Energy Survey (DES) data when used alongside orbit fitting. The discovery of multiple TNOs that appear to show a similarity in their orbital parameters has led to the suggestion that one or more undetected planets, an as yet undiscovered "Planet 9", may be present in the outer Solar System. DES is well placed to detect such a planet and has already been used to discover many other TNOs. Here, we perform tests on eight different supervised machine learning algorithms, using a dataset consisting of simulated TNOs buried within real DES noise data. We found that the best performing classifier was the Random Forest which, when optimised, performed well at detecting the rare objects. We achieve an area under the receiver operating characteristic (ROC) curve, (AUC) $= 0.996 \pm 0.001$. After optimizing the decision threshold of the Random Forest, we achieve a recall of 0.96 while maintaining a precision of 0.80. Finally, by using the optimized classifier to pre-select objects, we are able to run the orbit-fitting stage of our detection pipeline five times faster.

astro-ph.EP↗

arXiv2020

Reducing ground-based astrometric errors with Gaia and Gaussian processes

Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable at the locations of stars with accurate positions provided by the Gaia DR2 catalog; we develop the use of Gaussian process regression (GPR) to interpolate the distortion field to arbitrary locations in each exposure. We introduce an extension to standard GPR techniques that exploits the knowledge that the 2-dimensional distortion field is curl-free. Applied to several hundred 90-second exposures from the Dark Energy Survey as a testbed, we find that the GPR correction reduces the variance of the turbulent distortions $\approx12\times$, on average, with better performance in denser regions of the Gaia catalog. The RMS per-coordinate distortion in the $riz$ bands is typically $\approx7$ mas before any correction, and $\approx2$ mas after application of the GPR model. The GPR astrometric corrections are validated by the observation that their use reduces, from 10 to 5 mas RMS, the residuals to an orbit fit to $riz$-band observations over 5 years of the $r=18.5$ trans-Neptunian object Eris. We also propose a GPR method, not yet implemented, for simultaneously estimating the turbulence fields and the 5-dimensional stellar solutions in a stack of overlapping exposures, which should yield further turbulence reductions in future deep surveys.

astro-ph.IM↗

arXiv2020

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Correlations

Combining multiple observational probes is a powerful technique to provide robust and precise constraints on cosmological parameters. In this letter, we present the first joint analysis of cluster abundances and auto/cross correlations of three cosmic tracer fields measured from the first year data of the Dark Energy Survey: galaxy density, weak gravitational lensing shear, and cluster density split by optical richness. From a joint analysis of cluster abundances, three cluster cross-correlations, and auto correlations of galaxy density, we obtain $Ω_{\rm{m}}=0.305^{+0.055}_{-0.038}$ and $σ_8=0.783^{+0.064}_{-0.054}$. This result is consistent with constraints from the DES-Y1 galaxy clustering and weak lensing two-point correlation functions for the flat $νΛ$CDM model. We thus combine cluster abundances and all two-point correlations from three cosmic tracer fields and find improved constraints on cosmological parameters as well as on the cluster observable--mass scaling relation. This analysis is an important advance in both optical cluster cosmology and multi-probe analyses of upcoming wide imaging surveys.

astro-ph.CO↗

arXiv2020

A DESGW Search for the Electromagnetic Counterpart to the LIGO/Virgo Gravitational Wave Binary Neutron Star Merger Candidate S190510g

We present the results from a search for the electromagnetic counterpart of the LIGO/Virgo event S190510g using the Dark Energy Camera (DECam). S190510g is a binary neutron star (BNS) merger candidate of moderate significance detected at a distance of 227$\pm$92 Mpc and localized within an area of 31 (1166) square degrees at 50\% (90\%) confidence. While this event was later classified as likely non-astrophysical in nature within 30 hours of the event, our short latency search and discovery pipeline identified 11 counterpart candidates, all of which appear consistent with supernovae following offline analysis and spectroscopy by other instruments. Later reprocessing of the images enabled the recovery of 6 more candidates. Additionally, we implement our candidate selection procedure on simulated kilonovae and supernovae under DECam observing conditions (e.g., seeing, exposure time) with the intent of quantifying our search efficiency and making informed decisions on observing strategy for future similar events. This is the first BNS counterpart search to employ a comprehensive simulation-based efficiency study. We find that using the current follow-up strategy, there would need to be 19 events similar to S190510g for us to have a 99\% chance of detecting an optical counterpart, assuming a GW170817-like kilonova. We further conclude that optimization of observing plans, which should include preference for deeper images over multiple color information, could result in up to a factor of 1.5 reduction in the total number of followups needed for discovery.

astro-ph.HE↗

arXiv2020

Supernova Siblings: Assessing the Consistency of Properties of Type Ia Supernovae that Share the Same Parent Galaxies

While many studies have shown a correlation between properties of the light curves of Type Ia SN (SNe Ia) and properties of their host galaxies, it remains unclear what is driving these correlations. We introduce a new direct method to study these correlations by analyzing `parent' galaxies that host multiple SNe Ia 'siblings'. Here, we search the Dark Energy Survey SN sample, one of the largest samples of discovered SNe, and find 8 galaxies that hosted two likely Type Ia SNe. Comparing the light-curve properties of these SNe and recovered distances from the light curves, we find no better agreement between properties of SNe in the same galaxy as any random pair of galaxies, with the exception of the SN light-curve stretch. We show at $2.8σ$ significance that at least 1/2 of the intrinsic scatter of SNe Ia distance modulus residuals is not from common host properties. We also discuss the robustness with which we could make this evaluation with LSST, which will find $100\times$ more pairs of galaxies, and pave a new line of study on the consistency of Type Ia supernovae in the same parent galaxies. Finally, we argue that it is unlikely some of these SNe are actually single, lensed SN with multiple images.

astro-ph.GA↗

arXiv2014

Population trapping in bound states during IR-assisted ultra-fast photoionization of Ne$^+$

We have investigated photoionization of Ne$^+$ in the combined field of a short infra-red laser pulse and a delayed ultra-short pulse of the infra-red laser's 23$^r$$^d$ harmonic. We observe an ionization yield compatible with a picture in which one electron gets excited into Rydberg states by the harmonic laser field and is subsequently removed by the infra-red laser field. Modulations are seen in the ionization yield as a function of time delay. These modulations originate from the trapping of population in low members of the Rydberg series with different states being populated at different ranges of delay times. The calculations further demonstrate that single-threshold calculations cannot reproduce the Ne$^+$ photoionization yields obtained in multi-threshold calculations.

physics.atom-ph↗