arXiv subjects

Richard Kessler

Publications and source records attributed to Richard Kessler.

At least 19 recordsLinked to original sources

arXiv2026

Chromatic Effects Across the Roman Focal Plane: Implications for Supernova Photometry and Measurements of Cosmological Parameters

Calibration uncertainties are the leading systematics in cosmological analyses using Type Ia supernovae (SNe Ia). For the \textit{Nancy Grace Roman Space Telescope (Roman)}, we quantify the impact of chromatic effects on SNe Ia photometry and derived cosmological parameters, using simulated light curves from the High-Latitude Time Domain Survey. We investigate two sources of wavelength-dependent bias: focal plane array (FPA)-dependent wavelength shifts arising from spatial variations across \textit{Roman's} 18 detectors, and coherent wavelength shifts corresponding to the measured $0.06\%$ uncertainty in absolute filter wavelength calibration. Using simulated SNe Ia light curves, we find that the FPA-dependent shifts -- which range from +6 to -80 $\rm \AA$ introduce a redshift-dependent distance modulus bias that, if left uncorrected, propagates to $\Delta w_0 \sim -0.06$ and $\Delta w_a = -0.236$, which are larger than the forecast statistical uncertainties of $\sigma_{\rm stat, w_0} = 0.025$ and $\sigma_{\rm stat, w_a} = 0.114$, rendering the survey systematics-limited. We probe the impact of chromatic effects by employing detector-specific filter curves that recover unbiased cosmological constraints; to remain below the statistical noise floor, FPA wavelength shifts must be characterized to within 20\%. In contrast, a coherent 0.06\% offset in filter wavelength calibration -- ranging from -3 to -11 $\rm \AA$ -- produces negligible redshift-dependent bias, with a minimal spread in $w_a$ ($\Delta w_a = -0.0004, \sigma_{w_{a,\rm sys}} = 0.114)$, demonstrating that the achieved pre-launch calibration precision is sufficient for this systematic to remain subdominant. Our results establish that chromatic effects are a required component of SN Ia cosmology with \textit{Roman}.

astro-ph.CO↗

arXiv2026

Calibration-Induced Systematics in SALT3 Training and Their Impact on Dark Energy Constraints from Stage IV Supernova Surveys

In the coming years, the Vera Rubin Observatory's Legacy Survey of Space and Time (Rubin-LSST) and the Nancy Grace Roman Space Telescope's (Roman) High Latitude Time Domain Survey (HLTDS) are expected to discover more than a million Type Ia supernovae (SNe Ia), several orders of magnitude more than current samples and with a tighter control on systematic uncertainties. One of the largest systematic uncertainties in cosmological analyses with SNe Ia is the accuracy of the spectro-photometric model for SNe Ia time series data, which depends on the photometric calibration of the surveys. To quantify the impact of this uncertainty, we analyze simulated Rubin-LSST and HLTDS data, perturb the photometric zero-points and filter mean wavelengths, and propagate these systematics to spectral model recovery, estimated distances, and dark energy figure of merit (FoM) based on the $w_0 w_a$CDM model. Zero-point shifts of 5 mmag and filter mean wavelength shifts of 5 angstrom lead to a $\sim 50\%$ decrease in the FoM relative to a statistical-only case when calibration uncertainties are propagated only through light-curve fitting. The same calibration shifts applied only during model training produce a smaller $\sim 13\%$ degradation. Contrary to previous analyses, calibration uncertainties in light-curve fitting dominate over those from model training. Their effect during light-curve fitting varies smoothly with redshift and is nearly degenerate with cosmology, preventing mitigation through self-calibration. Finally, we show that the FoM dependence on the size of the calibration uncertainties (in the range of expected sizes) is roughly linear.

astro-ph.CO↗

arXiv2026

SLSim: a strong lensing population simulation package

Gravitational lensing offers unique insights into cosmology by bending light around massive objects. Strong gravitational lensing, in particular, produces magnified and often multiple images of distant sources, crucial for precise cosmological measurements and understanding the distribution of dark matter in the universe. Current studies are limited by the number of strong gravitational lenses. From upcoming cosmological surveys, we anticipate observing a several orders of magnitude increase in the number of lenses, for both static and transient phenomena. However, detecting and analyzing these events from vast surveys like Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) presents significant challenges. To prepare for these challenges, we introduce SLSim, a versatile simulation tool tailored for the Vera C. Rubin Observatory. SLSim integrates advanced astrophysical models with computational efficiency to generate synthetic strong lens populations under realistic observational conditions. SLSim simulates static and variable lensing scenarios, essential for cosmological studies, training and testing lens search and data analysis pipelines. This paper details SLSim,'s design and implementation, emphasizing its modularity and capabilities across various astrophysical regimes. Validation against observational data and existing simulations confirms SLSim's accuracy in reproducing observed lensing phenomena. SLSim is publicly available at https://github.com/LSST-strong-lensing/slsim, and we anticipate continued development and expansion of its capabilities. Users are encouraged to check the repository for updates and to contribute to ongoing community efforts in strong lensing simulations.

astro-ph.CO↗

arXiv2026

FlowSN: Neural Simulation-Based Inference under Realistic Selection Effects applied to Supernova Cosmology

We present FlowSN, a statistical framework using simulation-based inference (SBI) with normalising flows to account for selection effects in observational astronomy. Failure to account for selection effects can lead to biased inference on global parameters. An example is Malmquist bias, where detection limits result in a sample skewed towards brighter objects. In Type Ia supernova (SN Ia) cosmology, these selection effects can systematically shift the inferred posterior distributions of cosmological parameters, necessitating the development of robust statistical frameworks to account for the biases. SBI enables us to implicitly learn probability distributions that are analytically intractable to calculate. In this work, we introduce a novel approach that employs a normalising flow to learn the non-analytic selected SN likelihood for a given survey from forward simulations, independent of the assumed cosmological model. The resulting likelihood approximation is incorporated into a hierarchical Bayesian framework and posterior sampling is performed using Hamiltonian Monte Carlo to obtain constraints on cosmological parameters conditioned on the observed data. The modular learnt likelihood approximation can be reused without retraining to evaluate different cosmological models, providing a key advantage over other SBI approaches. We demonstrate the performance of this methodology by training and testing the SBI technique using realistic LSST-like SNANA simulations for the first time. Our FlowSN approach yields accurate posterior estimates on cosmological parameters, including the dark energy equation of state $w_0$, that are an order of magnitude less biased than those obtained with conventional techniques and also exhibit improved frequentist calibration.

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arXiv2026

Probing Physics Beyond the Standard Model through Combined Analyses of Next-Generation Type Ia Supernova, CMB, and BAO Surveys

Observations of Type Ia supernovae (\sne), which probe the late Universe, together with baryon acoustic oscillations (BAO) and the cosmic microwave background (CMB), which probe the intermediate and early epochs, provide complementary constraints on the expansion history of the Universe. In this work, we forecast constraints on dark energy and other extensions to the standard cosmological model by combining the SNIa sample expected from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), data from current and forthcoming CMB surveys, and BAO measurements from the Dark Energy Spectroscopic Instrument (DESI). For the CMB, we use temperature, polarization, and lensing power spectra ($TT/EE/TE/\phi\phi$) from South Pole Telescope, the planned Advanced Simons Observatory, and a CMB-S4-like experiment. We derive constraints on $\Lambda {\rm CDM}$ and its extensions involving the dark energy equation of state parameters $(w_{0}, w_{a})$ and the sum of neutrino masses $\sum m_{\nu}$, using a Markov Chain Monte Carlo (MCMC) sampling framework. We find that the LSST Year-3 SNIa sample can improve upon the DES Year-5 dark energy constraints by a factor of $\times2-\times2.5$, with the gains driven primarily by the significantly higher SNIa density in the LSST sample. Similarly, DESI-DR3 shows up to a $\times1.8$ improvement on dark energy parameters over DR2, driven largely by the substantial increase in low-redshift sample. Combining CMB with LSST-Y3-SNIa and DESI-DR3-BAO yields $\sigma(w_{0}) = 0.028$ and $\sigma(w_{a}) = 0.11$ for $w_{0} w_{a} {\rm CDM}$ cosmology with the results being largely independent of the CMB dataset. The constraints weaken by 10%-30% when freeing $\sum m_{\nu}$ and spatial curvature. Moreover, the joint analysis of the three datasets can enable a $2-3\sigma$ detection of $\sum m_{\nu}$.

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arXiv2025

Feeling Blue: Constructing a Robust SALT3 UV Template and Constraining its Redshift Dependency

Upcoming cosmological surveys will obtain numerous rest-frame ultraviolet (UV) observations of Type Ia supernovae (SNe Ia), yet there is concern about how standardizable SNe Ia are in the UV. In this work, we train a robust optical--UV SED model for SNe Ia (SALT3-UV) with the open-source model-training software $\texttt{SALTshaker}$. We incorporate a spectroscopic UV data sample from HST, including 67 UV spectra from 18 nearby SNe Ia. Unlike previous training spectra, the HST spectra have sufficiently precise calibration that they do not require additional warping to match coincident photometric data. Additionally, while including this new SN Ia sample necessitates incorporating auxiliary photometric data from ZTF and ATLAS that have insufficient calibration for cosmological analyses, the improvements in the calibration of these data is anticipated in the near future. Compared to the previous SALT3-K21 model, the SALT3-UV model shows a significant improvement in the UV down to $2000\mathring{\text{A}}$, with over a threefold improvement in model uncertainty and a more physically accurate continuum and line features. We further evaluate potential redshift evolution in the UV template by separating the UV training sample into low- and high-$z$ subsamples. Our results reveal a non-negligible $\gtrsim 0.05$ mag difference between low- and high-$z$ SALT3-UV models in the $g-$band at $z\gtrsim0.5$ and the $u-$band at $z\gtrsim0.2$. We demonstrate that, if confirmed, such evolution could lead to a few-percent bias in the measurement of $w$ if high-$z$ rest-frame UV data are included in future cosmological surveys such as LSST and $\textit{Roman}$.

astro-ph.CO↗

arXiv2025

A Fully Photometric Approach to Type Ia Supernova Cosmology in the LSST Era: Host Galaxy Redshifts and Supernova Classification

The upcoming Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to discover nearly a million Type Ia supernovae (SNeIa), offering an unprecedented opportunity to constrain dark energy. The vast majority of these events will lack spectroscopic classification and redshifts, necessitating a fully photometric approach to maximize cosmology constraining power. We present detailed simulations based on the Extended LSST Astronomical Time Series Classification Challenge (ELAsTiCC), and a cosmological analysis using photometrically classified SNeIa with host galaxy photometric redshifts. This dataset features realistic multi-band light curves, non-SNIa contamination, host mis-associations, and transient-host correlations across the high-redshift Deep Drilling Fields (DDF) (~ 50 deg^2). We also include a spectroscopically confirmed low-redshift sample based on the Wide Fast Deep (WFD) fields. We employ a joint SN+host photometric redshift fit, a neural network based photometric classifier (SCONE), and BEAMS with Bias Corrections (BBC) methodology to construct a bias-corrected Hubble diagram. We produce statistical + systematic covariance matrices, and perform cosmology fitting with a prior using Cosmic Microwave Background constraints. We fit and present results for the wCDM dark energy model, and the more general Chevallier-Polarski-Linder (CPL) w0wa model. With a simulated sample of ~6000 events, we achieve a Figure of Merit (FoM) value of about 150, which is significantly larger than the DESVYR FoM of 54. Averaging analysis results over 25 independent samples, we find small but significant biases indicating a need for further analysis testing and development.

astro-ph.CO↗

arXiv2025

Cosmology Constraints from Type Ia Supernova Simulations of the Nancy Grace Roman Space Telescope Strategy Recommended by the High Latitude Time Domain Survey Definition Committee

Within the next few years, the upcoming Nancy Grace Roman Space Telescope will be gathering data for the High Latitude Time Domain Survey (HLTDS) that will be used to significantly improve the Type Ia supernova measurement of the dark energy equation of state parameters w0 and wa. Here we generate a catalog-level simulation of the in-guide strategy recommended by the HLTDS definition committee, and determine dark energy parameter constraints using a detailed analysis that includes light curve fitting, photometric redshifts and classification, BEAMS formalism, systematic uncertainties, and cosmology fitting. After analysis and selection requirements, the sample includes 10,000 Roman SNe Ia that we combine with 4,400 events from LSST. The resulting dark energy figure of merit is well above the NASA mission requirement of 326, with the caveat that SN Ia model training systematics have not been included.

astro-ph.CO↗

arXiv2024

Astrometric Redshifts of Supernovae

Differential Chromatic Refraction (DCR) is caused by the wavelength dependence of our atmosphere's refractive index, which shifts the apparent positions of stars and galaxies and distorts their shapes depending on their spectral energy distributions (SEDs). While this effect is typically mitigated and corrected for in imaging observations, we investigate how DCR can instead be used to our advantage to infer the redshifts of supernovae from multi-band, time-series imaging data. We simulate Type Ia supernovae (SNe Ia) in the proposed Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Deep Drilling Field (DDF), and evaluate astrometric redshifts. We find that the redshift accuracy improves dramatically with the statistical quality of the astrometric measurements as well as with the accuracy of the astrometric solution. For a conservative choice of a 5-mas systematic uncertainty floor, we find that our redshift estimation is accurate at $z < 0.6$. We then combine our astrometric redshifts with both host galaxy photometric redshifts and supernovae photometric (light-curve) redshifts and show that this considerably improves the overall redshift estimates. These astrometric redshifts will be valuable especially since Rubin will discover a vast number of supernovae for which we will not be able to obtain spectroscopic redshifts.

astro-ph.CO↗

arXiv2023

Amalgame: Cosmological Constraints from the First Combined Photometric Supernova Sample

Future constraints of cosmological parameters from Type Ia supernovae (SNe Ia) will depend on the use of photometric samples, those samples without spectroscopic measurements of the SNe Ia. There is a growing number of analyses that show that photometric samples can be utilised for precision cosmological studies with minimal systematic uncertainties. To investigate this claim, we perform the first analysis that combines two separate photometric samples, SDSS and Pan-STARRS, without including a low-redshift anchor. We evaluate the consistency of the cosmological parameters from these two samples and find they are consistent with each other to under $1\sigma$. From the combined sample, named Amalgame, we measure $\Omega_M = 0.328 \pm 0.024$ with SN alone in a flat $\Lambda$CDM model, and $\Omega_M = 0.330 \pm 0.018$ and $w = -1.016^{+0.055}_{-0.058}$ when combining with a Planck data prior and a flat $w$CDM model. These results are consistent with constraints from the Pantheon+ analysis of only spectroscopically confirmed SNe Ia, and show that there are no significant impediments to analyses of purely photometric samples of SNe Ia.

astro-ph.CO↗

arXiv2023

Binning is Sinning: Redemption for Hubble Diagram using Photometrically Classified Type Ia Supernovae

Bayesian Estimation Applied to Multiple Species (BEAMS) is implemented in the BEAMS with Bias Corrections (BBC) framework to produce a redshift-binned Hubble diagram (HD) for Type Ia supernovae (SNe Ia). BBC corrects for selection effects and non-SNIa contamination, and systematic uncertainties are described by a covariance matrix with dimension matching the number of BBC redshift bins. For spectroscopically confirmed SN Ia samples, a recent "Binning is Sinning" article (BHS21, arxiv:2012.05900) showed that an unbinned HD and covariance matrix reduces the systematic uncertainty by a factor of ~1.5 compared to the binned approach. Here we extend their analysis to obtain an unbinned HD for a photometrically identified sample processed with BBC. To test this new method, we simulate and analyze 50 samples corresponding to the Dark Energy Survey (DES) witha low-redshift anchor; the simulation includes SNe Ia, and contaminants from core-collapse SNe and peculiar SNe Ia. The analysis includes systematic uncertainties for calibration, and measures the dark energy equation of state parameter (w). Compared to a redshift-binned HD, the unbinned HD with nearly 2000 events results in a smaller systematic uncertainty, in qualitative agreement with BHS21, and averaging results among the 50 samples we find no evidence for a w-bias. To reduce computation time for fitting an unbinned HD with large samples, we propose an HD-rebinning method that defines the HD in bins of redshift, color, and stretch; the rebinned HD results in similar uncertainty as the unbinned case, and shows no evidence for a w-bias.

astro-ph.CO↗

arXiv2022

Impact of Rubin Observatory cadence choices on supernovae photometric classification

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will discover an unprecedented number of supernovae (SNe), making spectroscopic classification for all the events infeasible. LSST will thus rely on photometric classification, whose accuracy depends on the not-yet-finalized LSST observing strategy. In this work, we analyze the impact of cadence choices on classification performance using simulated multi-band light curves. First, we simulate SNe with an LSST baseline cadence, a non-rolling cadence, and a presto-color cadence which observes each sky location three times per night instead of twice. Each simulated dataset includes a spectroscopically-confirmed training set, which we augment to be representative of the test set as part of the classification pipeline. Then, we use the photometric transient classification library snmachine to build classifiers. We find that the active region of the rolling cadence used in the baseline observing strategy yields a 25% improvement in classification performance relative to the background region. This improvement in performance in the actively-rolling region is also associated with an increase of up to a factor of 2.7 in the number of cosmologically-useful Type Ia supernovae relative to the background region. However, adding a third visit per night as implemented in presto-color degrades classification performance due to more irregularly sampled light curves. Overall, our results establish desiderata on the observing cadence related to classification of full SNe light curves, which in turn impacts photometric SNe cosmology with LSST.

astro-ph.IM↗

arXiv2022

Using Host Galaxy Photometric Redshifts to Improve Cosmological Constraints with Type Ia Supernova in the LSST Era

We perform a rigorous cosmology analysis on simulated type Ia supernovae (SN~Ia) and evaluate the improvement from including photometric host-galaxy redshifts compared to using only the "zspec" subset with spectroscopic redshifts from the host or SN. We use the Deep Drilling Fields (~50 deg^2) from the Photometric LSST Astronomical Time-Series Classification Challenge (PLaSTiCC), in combination with a low-z sample based on Data Challenge2 (DC2). The analysis includes light curve fitting to standardize the SN brightness, a high-statistics simulation to obtain a bias-corrected Hubble diagram, a statistical+systematics covariance matrix including calibration and photo-z uncertainties, and cosmology fitting with a prior from the cosmic microwave background. Compared to using the zspec subset, including events with SN+host photo-z results in i) more precise distances for z>0.5, ii) a Hubble diagram that extends 0.3 further in redshift, and iii) a 50 % increase in the Dark Energy Task Force figure of merit (FoM) based on the w0-wa CDM model. Analyzing 25 simulated data samples, the average bias on w0 and wa is consistent with zero. The host photo-z systematic of 0.01 reduces FoM by only 2 % because i) most z<0.5 events are in the zspec subset, ii) the combined SN+host photo-z has X 2 smaller bias, and iii) the anti-correlation between fitted redshift and color self corrects distance errors. To prepare for analysing real data, the next SNIa-cosmology analysis with photo-z's should include non SN-Ia contamination and host galaxy mis-associations.

astro-ph.CO↗

arXiv2022

The Simulated Catalogue of Optical Transients and Correlated Hosts (SCOTCH)

As we observe a rapidly growing number of astrophysical transients, we learn more about the diverse host galaxy environments in which they occur. Host galaxy information can be used to purify samples of cosmological Type Ia supernovae, uncover the progenitor systems of individual classes, and facilitate low-latency follow-up of rare and peculiar explosions. In this work, we develop a novel data-driven methodology to simulate the time-domain sky that includes detailed modeling of the probability density function for multiple transient classes conditioned on host galaxy magnitudes, colours, star formation rates, and masses. We have designed these simulations to optimize photometric classification and analysis in upcoming large synoptic surveys. We integrate host galaxy information into the SNANA simulation framework to construct the Simulated Catalogue of Optical Transients and Correlated Hosts (SCOTCH), a publicly-available catalogue of 5 million idealized transient light curves in LSST passbands and their host galaxy properties over the redshift range $0<z<3$. This catalogue includes supernovae, tidal disruption events, kilonovae, and active galactic nuclei. Each light curve consists of true top-of-the-galaxy magnitudes sampled with high ($\lesssim$2 day) cadence. In conjunction with SCOTCH, we also release an associated set of tutorials and the transient-specific libraries to enable simulations of arbitrary space- and ground-based surveys. Our methodology is being used to test critical science infrastructure in advance of surveys by the Vera C. Rubin Observatory and the Nancy G. Roman Space Telescope.

astro-ph.IM↗

arXiv2022

High-Precision Redshifts for Type Ia Supernovae with the Nancy Grace Roman Space Telescope P127 Prism

We present results from simulating slitless spectroscopic observations with the Nancy Grace Roman Space Telescope's (Roman) Wide-Field Instrument (WFI) P127 prism spanning 0.75 $\mu m$ to 1.8 $\mu m$. We quantify the efficiency of recovered Type Ia supernovae (SNe Ia) redshifts, as a function of P127 prism exposure time, to guide planning for future observing programs with the Roman prism. Generating the two-dimensional dispersed images and extracting one-dimensional spectra is done with the slitless spectroscopy package pyLINEAR along with custom-written software. From the analysis of 1698 simulated SN Ia P127 prism spectra, we show the efficiency of recovering SN redshifts to $z\lesssim3.0$, highlighting the exceptional sensitivity of the Roman P127 prism. Redshift recovery is assessed by setting a requirement of $\sigma_z = (\left|z - z_\mathrm{true} \right|)/(1+z) \leq 0.01$. We find that 3 hr exposures are sufficient for meeting this requirement, for $\gtrsim 50\%$ of the sample of mock SNe Ia at $z\approx2$ and within $\pm5$ days of rest-frame maximum light in the optical. We also show that a 1 hr integration of Roman can achieve the same precision in completeness to a depth of $24.4 \pm 0.06$ AB mag (or $z\lesssim 1$). Implications for cosmological studies with Roman P127 prism spectra of SNe Ia are also discussed.

astro-ph.GA↗

arXiv2021

The Pantheon+ Analysis: Forward-Modeling the Dust and Intrinsic Colour Distributions of Type Ia Supernovae, and Quantifying their Impact on Cosmological Inferences

Recent studies have shown that the observed colour distributions of Type Ia SNe (SNIa) are well-described by a combination of distributions from dust and intrinsic colour. Here we present a new forward-modeling fitting method (Dust2Dust) to measure the parent dust and colour distributions, including their dependence on host-galaxy mass. At each fit step, the SNIa selection efficiency is determined from a large simulated sample that is re-weighted to reflect the proposed distributions. We use five separate metrics to constrain the Dust2Dust parameters: distribution of fitted light-curve colour $c$, cosmological residual trends with $c$, cosmological residual scatter with $c$, fitted colour-luminosity relationship $\beta_{\rm SALT2}$, and intrinsic scatter $\sigma_{\rm int}$. Using the Pantheon+ data sample, we present results for a Dust2Dust fit that includes 4 parameters describing intrinsic colour variations and 8 parameters describing dust. Furthermore, we propagate the Dust2Dust parameter uncertainties and covariance to the dark energy equation-of-state $w$ and Hubble constant H$_0$: we find $\sigma_w = 0.005$ and $\sigma_{\textrm{H}_0} = 0.145~$km/s/Mpc. The Dust2Dust code is publically available.

astro-ph.CO↗

arXiv2021

The Pantheon+ Analysis: Improving the Redshifts and Peculiar Velocities of Type Ia Supernovae Used in Cosmological Analyses

We examine the redshifts of a comprehensive set of published Type Ia supernovae, and provide a combined, improved catalogue with updated redshifts. We improve on the original catalogues by using the most up-to-date heliocentric redshift data available; ensuring all redshifts have uncertainty estimates; using the exact formulae to convert heliocentric redshifts into the Cosmic Microwave Background (CMB) frame; and utilising an improved peculiar velocity model that calculates local motions in redshift-space and more realistically accounts for the external bulk flow at high-redshifts. In total we reviewed 2821 supernova redshifts; 534 are comprised of repeat-observations of the same supernovae and 1764 pass the cosmology sample quality cuts. We found 5 cases of missing or incorrect heliocentric corrections, 44 incorrect or missing supernova coordinates, 230 missing heliocentric or CMB frame redshifts, and 1200 missing redshift uncertainties. Of the 2287 unique Type Ia supernovae in our sample (1594 of which satisfy cosmology-sample cuts) we updated 990 heliocentric redshifts. The absolute corrections range between $10^{-8} \leq \Delta z \leq 0.038$, and RMS$(\Delta z) \sim 3\times 10^{-3}$. The sign of the correction was essentially random, so the mean and median corrections are small: $4\times 10^{-4}$ and $4\times 10^{-6}$ respectively. We examine the impact of these improvements for $H_0$ and the dark energy equation of state $w$ and find that the cosmological results change by $\Delta H_0 = -0.11$ km s$^{-1}$ Mpc$^{-1}$ and $\Delta w = -0.001$, both significantly smaller than previously reported uncertainties for $H_0$ of 1.4 km s$^{-1}$ Mpc$^{-1}$ and $w$ of 0.04 respectively.

astro-ph.CO↗

arXiv2021

SOAR/Goodman Spectroscopic Assessment of Candidate Counterparts of the LIGO-Virgo Event GW190814

On 2019 August 14 at 21:10:39 UTC, the LIGO/Virgo Collaboration (LVC) detected a possible neutron star-black hole merger (NSBH), the first ever identified. An extensive search for an optical counterpart of this event, designated GW190814, was undertaken using the Dark Energy Camera (DECam) on the 4m Victor M. Blanco Telescope at the Cerro Tololo Inter-American Observatory. Target of Opportunity interrupts were issued on 8 separate nights to observe 11 candidates using the 4.1m Southern Astrophysical Research (SOAR) telescope's Goodman High Throughput Spectrograph in order to assess whether any of these transients was likely to be an optical counterpart of the possible NSBH merger. Here, we describe the process of observing with SOAR, the analysis of our spectra, our spectroscopic typing methodology, and our resultant conclusion that none of the candidates corresponded to the gravitational wave merger event but were all instead other transients. Finally, we describe the lessons learned from this effort. Application of these lessons will be critical for a successful community spectroscopic follow-up program for LVC observing run 4 (O4) and beyond.

astro-ph.HE↗