arXiv subjects

W. Michael Wood-Vasey

Publications and source records attributed to W. Michael Wood-Vasey.

At least 19 recordsLinked to original sources

arXiv2025

phrosty: A difference imaging pipeline for Roman

NASA's Nancy Grace Roman Space Telescope (Roman) will provide an opportunity to study dark energy with unprecedented precision using several techniques, including measurements of Type Ia Supernovae (SNe Ia). Here, we present `phrosty` (PHotometry for ROman with SFFT for tYpe Ia supernovae): a difference imaging pipeline for measuring the brightness of transient point sources in the sky, primarily SNe Ia, using Roman data. `phrosty` is written in Python. We implement a GPU-accelerated version of the Saccadic Fast Fourier Transform (SFFT) method for difference imaging.

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arXiv2025

DESC DC2 Data Release Note

In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg$^2$ simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository.

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arXiv2024

Simulating image coaddition with the Nancy Grace Roman Space Telescope: II. Analysis of the simulated images and implications for weak lensing

One challenge for applying current weak lensing analysis tools to the Nancy Grace Roman Space Telescope is that individual images will be undersampled. Our companion paper presented an initial application of Imcom - an algorithm that builds an optimal mapping from input to output pixels to reconstruct a fully sampled combined image - on the Roman image simulations. In this paper, we measure the output noise power spectra, identify the sources of the major features in the power spectra, and show that simple analytic models that ignore sampling effects underestimate the power spectra of the coadded noise images. We compute the moments of both idealized injected stars and fully simulated stars in the coadded images, and their 1- and 2-point statistics. We show that the idealized injected stars have root-mean-square ellipticity errors (1 - 6) x 10-4 per component depending on the band; the correlation functions are >= 2 orders of magnitude below requirements, indicating that the image combination step itself is using a small fraction of the overall Roman 2nd moment error budget, although the 4th moments are larger and warrant further investigation. The stars in the simulated sky images, which include blending and chromaticity effects, have correlation functions near the requirement level (and below the requirement level in a wide-band image constructed by stacking all 4 filters). We evaluate the noise-induced biases in the ellipticities of injected stars, and explain the resulting trends with an analytical model. We conclude by enumerating the next steps in developing an image coaddition pipeline for Roman.

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arXiv2024

Simulating image coaddition with the Nancy Grace Roman Space Telescope: I. Simulation methodology and general results

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as Imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired "target" point spread function (PSF). We present here an initial application of Imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that Imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the "leakage"), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moiré patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper ("Paper II") explores the implications for weak lensing analyses.

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arXiv2022

Faro: A framework for measuring the scientific performance of petascale Rubin Observatory data products

The Vera C. Rubin Observatory will advance many areas of astronomy over the next decade with its unique wide-fast-deep multi-color imaging survey, the Legacy Survey of Space and Time (LSST). The LSST will produce approximately 20TB of raw data per night, which will be automatically processed by the LSST Science Pipelines to generate science-ready data products -- processed images, catalogs and alerts. To ensure that these data products enable transformative science with LSST, stringent requirements have been placed on their quality and scientific fidelity, for example on image quality and depth, astrometric and photometric performance, and object recovery completeness. In this paper we introduce faro, a framework for automatically and efficiently computing scientific performance metrics on the LSST data products for units of data of varying granularity, ranging from single-detector to full-survey summary statistics. By measuring and monitoring metrics, we are able to evaluate trends in algorithmic performance and conduct regression testing during development, compare the performance of one algorithm against another, and verify that the LSST data products will meet performance requirements by comparing to specifications. We present initial results using faro to characterize the performance of the data products produced on simulated and precursor data sets, and discuss plans to use faro to verify the performance of the LSST commissioning data products.

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arXiv2021

Are Type Ia Supernovae in Restframe $H$ Brighter in More Massive Galaxies?

We analyze 143 Type Ia supernovae (SNeIa) observed in $H$ band (1.6-1.8 $μ$m) and find SNeIa are intrinsically brighter in $H$-band with increasing host galaxy stellar mass. We find SNeIa in galaxies more massive than $10^{10.43} M_{\odot}$ are $0.13 \pm 0.04$ mag brighter in $H$ than SNeIa in less massive galaxies. The same set of SNeIa observed at optical wavelengths, after width-color-luminosity corrections, exhibit a $0.10 \pm 0.03$ mag offset in the Hubble residuals. We observe an outlier population ($|ΔH_{\rm max}| > 0.5$ mag) in the $H$ band and show that removing the outlier population moves the mass threshold to $10^{10.65} M_{\odot}$ and reduces the step in $H$ band to $0.08 \pm 0.04$ mag, but the equivalent optical mass step is increased to $0.13 \pm 0.04$ mag. We conclude the outliers do not drive the brightness--host-mass correlation. Less massive galaxies preferentially host more higher-stretch SNeIa, which are intrinsically brighter and bluer. It is only after correction for width-luminosity and color-luminosity relationships that SNeIa have brighter optical Hubble residuals in more massive galaxies. Thus finding SNeIa are intrinsically brighter in $H$ in more massive galaxies is an opposite correlation to the intrinsic (pre-width-luminosity correction) optical brightness. If dust and the treatment of intrinsic color variation were the main driver of the host galaxy mass correlation, we would not expect a correlation of brighter $H$-band SNeIa in more massive galaxies.

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arXiv2021

The LSST DESC DC2 Simulated Sky Survey

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology.

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arXiv2020

The LSST DESC Data Challenge 1: Generation and Analysis of Synthetic Images for Next Generation Surveys

Data Challenge 1 (DC1) is the first synthetic dataset produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST dataset. DC1 is comprised of $r$-band observations of 40 deg$^{2}$ to 10-year LSST depth. We present each stage of the simulation and analysis process: a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; b) reduction using a development version of the LSST Science Pipelines; and c) matching to the input cosmological catalog for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: i) survey properties have an impact of 50\% of the statistical uncertainty for the scales and models used in DC1 ii) a selection to eliminate artifacts in the catalogs is necessary to avoid biases in the measured clustering; iii) the presence of bright objects has a significant impact (2- to 6-$σ$) in the estimated power spectra at small scales ($\ell > 1200$), highlighting the impact of blending in studies at small angular scales in LSST;

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arXiv2019

Next Generation LSST Science

The Large Synoptic Survey Telescope (LSST) can advance scientific frontiers beyond its groundbreaking 10-year survey. Here we explore opportunities for extended operations with proposal-based observing strategies, new filters, or transformed instrumentation. We recommend the development of a mid-decade community- and science-driven process to define next-generation LSST capabilities.

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arXiv2016

Incorporating Astrophysical Systematics into a Generalized Likelihood for Cosmology with Type Ia Supernovae

Traditional cosmological inference using Type Ia supernovae (SNeIa) have used stretch- and color-corrected fits of SN Ia light curves and assumed a resulting fiducial mean and symmetric intrinsic dispersion for the resulting relative luminosity. As systematics become the main contributors to the error budget, it has become imperative to expand supernova cosmology analyses to include a more general likelihood to model systematics to remove biases with losses in precision. To illustrate an example likelihood analysis, we use a simple model of two populations with a relative luminosity shift, independent intrinsic dispersions, and linear redshift evolution of the relative fraction of each population. Treating observationally viable two-population mock data using a one-population model results in an inferred dark energy equation of state parameter $w$ that is biased by roughly 2 times its statistical error for a sample of N $ \gtrsim$ 2500 SNeIa. Modeling the two-population data with a two-population model removes this bias at a cost of an approximately $\sim20\%$ increase in the statistical constraint on $w$. These significant biases can be realized even if the support for two underlying SNeIa populations, in the form of model selection criteria, is inconclusive. With the current observationally-estimated difference in the two proposed populations, a sample of N $ \gtrsim$ 10,000 SNeIa is necessary to yield conclusive evidence of two populations.

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arXiv2016

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample

We present cosmological results from the final galaxy clustering data set of the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III. Our combined galaxy sample comprises 1.2 million massive galaxies over an effective area of 9329 deg^2 and volume of 18.7 Gpc^3, divided into three partially overlapping redshift slices centred at effective redshifts 0.38, 0.51, and 0.61. We measure the angular diameter distance DM and Hubble parameter H from the baryon acoustic oscillation (BAO) method after applying reconstruction to reduce non-linear effects on the BAO feature. Using the anisotropic clustering of the pre-reconstruction density field, we measure the product DM*H from the Alcock-Paczynski (AP) effect and the growth of structure, quantified by fσ8(z), from redshift-space distortions (RSD). We combine measurements presented in seven companion papers into a set of consensus values and likelihoods, obtaining constraints that are tighter and more robust than those from any one method. Combined with Planck 2015 cosmic microwave background measurements, our distance scale measurements simultaneously imply curvature Ω_K =0.0003+/-0.0026 and a dark energy equation of state parameter w = -1.01+/-0.06, in strong affirmation of the spatially flat cold dark matter model with a cosmological constant (ΛCDM). Our RSD measurements of fσ_8, at 6 per cent precision, are similarly consistent with this model. When combined with supernova Ia data, we find H0 = 67.3+/-1.0 km/s/Mpc even for our most general dark energy model, in tension with some direct measurements. Adding extra relativistic species as a degree of freedom loosens the constraint only slightly, to H0 = 67.8+/-1.2 km/s/Mpc. Assuming flat ΛCDM we find Ω_m = 0.310+/-0.005 and H0 = 67.6+/-0.5 km/s/Mpc, and we find a 95% upper limit of 0.16 eV/c^2 on the neutrino mass sum.

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arXiv2016

Light Curves of 213 Type Ia Supernovae from the ESSENCE Survey

The ESSENCE survey discovered 213 Type Ia supernovae at redshifts 0.1 < z < 0.81 between 2002 and 2008. We present their R and I-band photometry, measured from images obtained using the MOSAIC II camera at the CTIO 4 m Blanco telescope, along with rapid-response spectroscopy for each object. We use our spectroscopic follow-up observations to determine an accurate, quantitative classification and a precise redshift. Through an extensive calibration program we have improved the precision of the CTIO Blanco natural photometric system. We use several empirical metrics to measure our internal photometric consistency and our absolute calibration of the survey. We assess the effect of various potential sources of systematic bias on our measured fluxes, and we estimate that the dominant term in the systematic error budget from the photometric calibration on our absolute fluxes is ~1%.

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arXiv2015

Improving the LSST dithering pattern and cadence for dark energy studies

The Large Synoptic Survey Telescope (LSST) will explore the entire southern sky over 10 years starting in 2022 with unprecedented depth and time sampling in six filters, $ugrizy$. Artificial power on the scale of the 3.5 deg LSST field-of-view will contaminate measurements of baryonic acoustic oscillations (BAO), which fall at the same angular scale at redshift $z \sim 1$. Using the HEALPix framework, we demonstrate the impact of an "un-dithered" survey, in which $17\%$ of each LSST field-of-view is overlapped by neighboring observations, generating a honeycomb pattern of strongly varying survey depth and significant artificial power on BAO angular scales. We find that adopting large dithers (i.e., telescope pointing offsets) of amplitude close to the LSST field-of-view radius reduces artificial structure in the galaxy distribution by a factor of $\sim$10. We propose an observing strategy utilizing large dithers within the main survey and minimal dithers for the LSST Deep Drilling Fields. We show that applying various magnitude cutoffs can further increase survey uniformity. We find that a magnitude cut of $r < 27.3$ removes significant spurious power from the angular power spectrum with a minimal reduction in the total number of observed galaxies over the ten-year LSST run. We also determine the effectiveness of the observing strategy for Type Ia SNe and predict that the main survey will contribute $\sim$100,000 Type Ia SNe. We propose a concentrated survey where LSST observes one-third of its main survey area each year, increasing the number of main survey Type Ia SNe by a factor of $\sim$1.5, while still enabling the successful pursuit of other science drivers.

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arXiv2013

SweetSpot: Near-Infrared Observations of Thirteen Type Ia Supernovae from a New NOAO Survey Probing the Nearby Smooth Hubble Flow

We present 13 Type Ia supernovae (SNe Ia) observed in the restframe near-infrared (NIR) from 0.02 < z < 0.09 with the WIYN High-resolution Infrared Camera (WHIRC) on the WIYN 3.5-m telescope. With only 1-3 points per light curve and a prior on the time of maximum from the spectrum used to type the object we measure an H-band dispersion of spectroscopically normal SNe Ia of 0.164 mag. These observations continue to demonstrate the improved standard brightness of SNe Ia in H-band even with limited data. Our sample includes two SNe Ia at z ~ 0.09, which represent the most distant restframe NIR H-band observations published to date. This modest sample of 13 NIR SNe Ia represent the pilot sample for "SweetSpot" - a three-year NOAO Survey program that will observe 144 SNe Ia in the smooth Hubble flow. By the end of the survey we will have measured the relative distance to a redshift of z ~ 0.05 to 1%. Nearby Type Ia supernova (SN Ia) observations such as these will test the standard nature of SNe Ia in the restframe NIR, allow insight into the nature of dust, and provide a critical anchor for future cosmological SN Ia surveys at higher redshift.

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arXiv2013

The Sloan Digital Sky Survey quasar catalog: tenth data release

We present the Data Release 10 Quasar (DR10Q) catalog from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. The catalog includes all BOSS objects that were targeted as quasar candidates during the first 2.5 years of the survey and that are confirmed as quasars via visual inspection of the spectra. The catalog also includes known quasars (mostly from SDSS-I and II) that were reobserved by BOSS. The catalog contains 166,583 quasars (74,454 are new discoveries since SDSS-DR9) detected over 6,373 deg$^{2}$ with robust identification and redshift measured by a combination of principal component eigenspectra. The number of quasars with $z>2.15$ (117,668) is $\sim$5 times greater than the number of $z>2.15$ quasars known prior to BOSS. Redshifts and FWHMs are provided for the strongest emission lines (CIV, CIII, MgII). The catalog identifies 16,461 broad absorption line quasars and gives their characteristics. For each object, the catalog presents five-band (u, g, r, i, z) CCD-based photometry with typical accuracy of 0.03 mag and information on the optical morphology and selection method. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra cover the wavelength region 3,600-10,500Å at a spectral resolution in the range 1,300$<$R$<$2,500; the spectra can be retrieved from the SDSS Catalog Archive Server. We also provide a supplemental list of an additional 2,376 quasars that have been identified among the galaxy targets of the SDSS-III/BOSS.

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arXiv2013

Spectroscopy in the Era of LSST

This report summarizes the results of the 'Spectroscopy in the Era of LSST' workshop held April 11-12, 2013 in Tucson, Arizona. At the workshop, there were breakout sessions covering four broad science topics. These were: time domain science, Galactic structure and stellar populations, galaxies and AGN, and dark energy and cosmology. We present the science cases discussed in these breakout sessions and provide a synthesis of highly desired capabilities that meet needs across all four broad topics. We also present a table that will be useful to characterize the needs of specific science cases in a format that provides a general framework for discussion of future spectroscopic capabilities.

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arXiv2013

Very Low Mass Stellar and Substellar Companions to Solar-Like Stars From MARVELS V: A Low Eccentricity Brown Dwarf from the Driest Part of the Desert, MARVELS-6b

We describe the discovery of a likely brown dwarf (BD) companion with a minimum mass of 31.7 +/- 2.0 M_Jup to GSC 03546-01452 from the MARVELS radial velocity survey, which we designate as MARVELS-6b. For reasonable priors, our analysis gives a probability of 72% that MARVELS-6b has a mass below the hydrogen-burning limit of 0.072 M_Sun, and thus it is a high-confidence BD companion. It has a moderately long orbital period of 47.8929 +0.0063/-0.0062 days with a low eccentricty of 0.1442 +0.0078/-0.0073, and a semi-amplitude of 1644 +12/-13 m/s. Moderate resolution spectroscopy of the host star has determined the following parameters: T_eff = 5598 +/- 63, log g = 4.44 +/- 0.17, and [Fe/H] = +0.40 +/- 0.09. Based upon these measurements, GSC 03546-01452 has a probable mass and radius of M_star = 1.11 +/- 0.11 M_Sun and R_star = 1.06 +/- 0.23 R_Sun with an age consistent with less than ~6 Gyr at a distance of 219 +/- 21 pc from the Sun. Although MARVELS-6b is not observed to transit, we cannot definitively rule out a transiting configuration based on our observations. There is a visual companion detected with Lucky Imaging at 7.7 arcsec from the host star, but our analysis shows that it is not bound to this system. The minimum mass of MARVELS-6b exists at the minimum of the mass functions for both stars and planets, making this a rare object even compared to other BDs.

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arXiv2013

Likelihood-Free Cosmological Inference with Type Ia Supernovae: Approximate Bayesian Computation for a Complete Treatment of Uncertainty

Cosmological inference becomes increasingly difficult when complex data-generating processes cannot be modeled by simple probability distributions. With the ever-increasing size of data sets in cosmology, there is increasing burden placed on adequate modeling; systematic errors in the model will dominate where previously these were swamped by statistical errors. For example, Gaussian distributions are an insufficient representation for errors in quantities like photometric redshifts. Likewise, it can be difficult to quantify analytically the distribution of errors that are introduced in complex fitting codes. Without a simple form for these distributions, it becomes difficult to accurately construct a likelihood function for the data as a function of parameters of interest. Approximate Bayesian computation (ABC) provides a means of probing the posterior distribution when direct calculation of a sufficiently accurate likelihood is intractable. ABC allows one to bypass direct calculation of the likelihood but instead relies upon the ability to simulate the forward process that generated the data. These simulations can naturally incorporate priors placed on nuisance parameters, and hence these can be marginalized in a natural way. We present and discuss ABC methods in the context of supernova cosmology using data from the SDSS-II Supernova Survey. Assuming a flat cosmology and constant dark energy equation of state we demonstrate that ABC can recover an accurate posterior distribution. Finally we show that ABC can still produce an accurate posterior distribution when we contaminate the sample with Type IIP supernovae.

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