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R. H. Schindler

Publications and source records attributed to R. H. Schindler.

3 recordsLinked to original sources

photoD with Rubin's Data Preview 1: first stellar photometric distances and deficit of faint blue stars. Stellar distances with Rubin's DP1

Aims: We investigate the utility of Rubin's Data Preview 1 for estimating stellar number density profile in the Milky Way halo. Methods: Stellar broad-band near-UV to near-IR $ugrizy$ photometry released in Rubin's Data Preview 1 is used to estimate distance and metallicity for blue main sequence stars brighter than $r=24$ in three $\sim$1.1. sq.~deg. fields at southern Galactic latitudes. Results: Compared to TRILEGAL simulations of the Galaxy's stellar content by (Dal Tio, 2022), we find a significant deficit of blue main sequence turn-off stars with $22 < r < 24$. We interpret this discrepancy as a signature of a much steeper halo number density profile at galactocentric distances $10-50$ kpc than the cannonical $\sim1/r^3$ profile assumed in TRILEGAL simulations. Conclusions: This interpretation is consistent with earlier suggestions based on observations of more luminous, but much less numerous, evolved stellar populations, and a few pencil beam surveys of blue main sequence stars in the northern sky. These results bode well for the future Galactic halo exploration with Rubin's Legacy Survey of Space and Time.

astro-ph.GA↗

Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)

We present the first systematic analysis of photometric redshifts (photo-z) estimated from the Rubin Observatory Data Preview 1 (DP1) data taken with the Legacy Survey of Space and Time (LSST) Commissioning Camera. Employing the Redshift Assessment Infrastructure Layers (RAIL) framework, we apply eight photo-z algorithms to the DP1 photometry, using deep ugrizy coverage in the Extended Chandra Deep Field South (ECDFS) field and griz data in the Rubin_SV_38_7 field. In the ECDFS field, we construct a reference catalog from spectroscopic redshift (spec-z), grism redshift (grism-z), and multiband photo-z for training and validating photo-z. Performance metrics of the photo-z are evaluated using spec-zs from ECDFS and Dark Energy Spectroscopic Instrument Data Release 1 samples. Across the algorithms, we achieve per-galaxy photo-z scatter of $σ_{\rm NMAD} \sim 0.03$ and outlier fractions around 10% in the 6-band data, with performance degrading at faint magnitudes and z>1.2. The overall bias and scatter of our machine-learning based photo-zs satisfy the LSST Y1 requirement. We also use our photo-z to infer the ensemble redshift distribution n(z). We study the photo-z improvement by including near-infrared photometry from the Euclid mission, and find that Euclid photometry improves photo-z at z>1.2. Our results validate the RAIL pipeline for Rubin photo-z production and demonstrate promising initial performance.

astro-ph.IM↗

The Dark Energy Camera

The Dark Energy Camera is a new imager with a 2.2-degree diameter field of view mounted at the prime focus of the Victor M. Blanco 4-meter telescope on Cerro Tololo near La Serena, Chile. The camera was designed and constructed by the Dark Energy Survey Collaboration, and meets or exceeds the stringent requirements designed for the wide-field and supernova surveys for which the collaboration uses it. The camera consists of a five element optical corrector, seven filters, a shutter with a 60 cm aperture, and a CCD focal plane of 250 micron thick fully-depleted CCDs cooled inside a vacuum Dewar. The 570 Mpixel focal plane comprises 62 2kx4k CCDs for imaging and 12 2kx2k CCDs for guiding and focus. The CCDs have 15 microns x15 microns pixels with a plate scale of 0.263 arc sec per pixel. A hexapod system provides state-of-the-art focus and alignment capability. The camera is read out in 20 seconds with 6-9 electrons readout noise. This paper provides a technical description of the camera's engineering, construction, installation, and current status.

astro-ph.IM↗