Engineering topics

Perrefort, Daniel

Publications and source records attributed to Perrefort, Daniel.

4 records

DOE OSTI2022

GPS Measurements of Precipitable Water Vapor Can Improve Survey Calibration: A Demonstration from KPNO and the Mayall z -band Legacy Survey

Dual-band Global Positioning Satellite (GPS) measurements of precipitable water vapor (PWV) at the Kitt Peak National Observatory predict the overall per-image sensitivity of the Mayall z-band Legacy Survey (MzLS). The per-image variation in the brightness of individual stars is strongly correlated with the measured PWV and the color of the star. Synthetic stellar spectra through TAPAS transmission models successfully predict the observed PWV-induced photometric variation. We find that PWV absorption can be well approximated by a linear relationship with (airmass × PWV) 0.6 and present an update on the traditional treatment in the literature. The MzLS zero-point sensitivity in electrons s –1 varies with a normalized-mean absolute deviation of 61 mmag. PWV variation accounts 23 mmag of this zero-point variation. The MzLS per-image absolute sensitivity decreases by 40 mmag per effective mm of PWV. The overall gray offset portion of this variation is corrected by the calibration to a reference catalog. But the relative calibration error between blue (r – z < 0.5 mag) versus red (1.2 mag < r – z) stars increases by 0.3–2 mmag per effective mm of PWV. We argue that GPS systems provide more precise PWV measurements than using differential measurements of stars of different colors and recommend that observatories install dual-band GPS as a low-maintenance, low-cost, auxiliary calibration system. We extend our results of the need for well-calibrated PWV measurements by presenting the calculations of the PWV photometric impact on three science cases of interest: stellar photometry, supernova cosmology, and quasar identification and variability.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The Dependence of the Type Ia Supernova Host Bias on Observation or Fitting Technique

More luminous Type Ia supernovae prefer less massive hosts and regions of higher star formation. This correlation is inverted during width–color–luminosity light-curve standardization resulting in step-like biases of distance measurements with respect to host properties. Using the PMAS/PPak Integral-field Supernovahosts COmpilation (PISCO) supernova host sample and Sloan Digital Sky Survey, Galaxy Evolution Explorer, and Two Micron All Sky Survey photometry, we compare host stellar mass and specific star-formation rate (sSFR) from different observation methods, including local versus global, and fitting techniques to measure their impact on the host step biases. Mass-step measurements for all our mass samples are consistent within a 1σ significance from –0.03 ± 0.02 mag to –0.04 ± 0.02 mag. Including or excluding UV information had no effect on measured mass-step size or location. sSFR step sizes are more significant than mass-step measurements and varied from 0.05 ± 0.03 mag (Hα) and 0.06 ± 0.02 mag (UV) for a 51 host sample. The sSFR step location is influenced by the mass sample used to normalize star formation and by sSFR tracer choice. The step size is reduced to 0.04 ± 0.03 mag when using all available 73 hosts with Hα measurements. This 73 PISCO host subsample overall lacked a clear step signal, but here we are searching for whether different choices of mass or sSFR estimation can create a step signal. We find no evidence that different observation or fitting techniques choices can create a distance measurement step in either mass or sSFR.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

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.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

A Template-based Approach to the Photometric Classification of SN 1991bg-like Supernovae in the SDSS-II Supernova Survey

The use of SNe Ia to measure cosmological parameters has grown significantly over the past two decades. However, there exists a significant diversity in the SN Ia population that is not well understood. Overluminous SN 1991T-like and subluminous SN 1991bg-like objects are two characteristic examples of peculiar SNe. The identification and classification of such objects is an important step in studying what makes them unique from the remaining SN population. With the upcoming Vera C. Rubin Observatory promising on the order of a million new SNe over a 10 year survey, spectroscopic classifications will be possible for only a small subset of observed targets. As such, photometric classification has become an increasingly important concern in preparing for the next generation of astronomical surveys. Using observations from the Sloan Digital Sky Survey II (SDSS-II) SN Survey, we apply here an empirically based classification technique targeted at the identification of SN 1991bg-like SNe in photometric data sets. By performing dedicated fits to photometric data in the rest-frame redder and bluer bandpasses, we classify 16 previously unidentified 91bg-like SNe. Using SDSS-II host galaxy measurements, we find that these SNe are preferentially found in host galaxies with an older average stellar age than the hosts of normal SNe Ia. We also find that these SNe are found at a further physical distance from the center of their host galaxies. We find no statistically significant bias in host galaxy mass or specific star formation rate for these targets.

Astronomy & Astrophysics↗