Testing LSST dither strategies for Survey Uniformity and Large-Scale Structure Systematics

The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022{2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the eects of telescope-pointing osets (called dithers) on the r-band coadded 5 depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g.,random, hexagonal lattice, spiral) with amplitude as large as the radius of the LSST eld-of-view, implemented on dierent timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more eective than per season. Also, we find that some dither geometries (e.g., hexagonal lattice) are particularly sensitive to the timescale on whichthe dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to articial uctuations in galaxy counts, which are a systematic for large-scale structure studies. We calculate the bias in galaxy counts caused by the observing strategy, accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the observing strategy. We nd that after 10 years of the LSST survey, the best dither strategies lead to uncertainties in this bias smaller than the minimum statistical floor for a galaxy catalog as deep asr<27.5. A few of these strategies bring the uncertainties close to the statistical floor for r<25.7 after only one year of survey.Fil: Awan, Humna. Rutgers University; Estados UnidosFil: Gawiser, Eric. Rutgers University; Estados UnidosFil: Kurczynski, Peter. Rutgers University; Estados UnidosFil: Lynne Jones, R.. University of Washington; Estados UnidosFil: Zhan, Hu. Chinese Academy of Sciences; República de ChinaFil: Padilla, Nelson David. Pontificia Universidad Católica de Chile; ChileFil: Muñoz Arancibia, Alejandra M.. Pontificia Universidad Católica de Chile; ChileFil: Orsi, Alvaro. Centro de Estudios de Fisica del Cosmos de Aragon; EspañaFil: Cora, Sofia Alejandra. Universidad Nacional de la Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; ArgentinaFil: Yoachim, Peter. University of Washington; Estados Unido

A Simultaneous Stacking and Deblending Algorithm for Astronomical Images

Stacking analysis is a means of detecting faint sources using a priori position information to estimate an aggregate signal from individually undetected objects. Confusion severely limits the effectiveness of stacking in deep surveys with limited angular resolution, particularly at far infrared to submillimeter wavelengths, and causes a bias in stacking results. Deblending corrects measured fluxes for confusion from adjacent sources; however, we find that standard deblending methods only reduce the bias by roughly a factor of two while tripling the variance. We present an improved algorithm for simultaneous stacking and deblending that greatly reduces bias in the flux estimate with nearly minimum variance. When confusion from neighboring sources is the dominant error, our method improves upon RMS error by at least a factor of three and as much as an order of magnitude compared to other algorithms. This improvement will be useful for Herschel and other telescopes working in a source confused, low signal to noise regime.Comment: accepted to The Astronomical Journal. 18 pages, 6 figure

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.Comment: 9 pages, 6 figures, published in SPIE proceedings; corrected typo in equation

Breaking the Curve with CANDELS: A Bayesian Approach to Reveal the Non-Universality of the Dust-Attenuation Law at High Redshift

Dust attenuation affects nearly all observational aspects of galaxy evolution, yet very little is known about the form of the dust-attenuation law in the distant Universe. Here, we model the spectral energy distributions (SEDs) of galaxies at z = 1.5--3 from CANDELS with rest-frame UV to near-IR imaging under different assumptions about the dust law, and compare the amount of inferred attenuated light with the observed infrared (IR) luminosities. Some individual galaxies show strong Bayesian evidence in preference of one dust law over another, and this preference agrees with their observed location on the plane of infrared excess (IRX, $L_{\text{TIR}}/L_{\text{UV}}$) and UV slope ($\beta$). We generalize the shape of the dust law with an empirical model, $A_{\lambda,\delta}=E(B-V)\ k_\lambda\ (\lambda/\lambda_V)^\delta$ where $k_\lambda$ is the dust law of Calzetti et al. (2000), and show that there exists a correlation between the color excess ${E(B-V)}$ and tilt $\delta$ with ${\delta=(0.62\pm0.05)\log(E(B-V))}$+ ${(0.26~\pm~0.02)}$. Galaxies with high color excess have a shallower, starburst-like law, and those with low color excess have a steeper, SMC-like law. Surprisingly, the galaxies in our sample show no correlation between the shape of the dust law and stellar mass, star-formation rate, or $\beta$. The change in the dust law with color excess is consistent with a model where attenuation is caused by by scattering, a mixed star-dust geometry, and/or trends with stellar population age, metallicity, and dust grain size. This rest-frame UV-to-near-IR method shows potential to constrain the dust law at even higher ($z>3$) redshifts.Comment: 20 pages, 18 figures, resubmitted to Ap

Testing LSST dither strategies for survey uniformity and large-scale structure systematics

The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022-2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the effects of telescope-pointing offsets (called dithers) on the r-band coadded 5σ depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g., random, hexagonal lattice, spiral) with amplitudes as large as the radius of the LSST field of view, implemented on different timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more effective than per season assignments. Also, we find that some dither geometries (e.g., hexagonal lattice) are particularly sensitive to the timescale on which the dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to artificial fluctuations in galaxy counts, which are a systematic for LSS studies. We calculate the bias in galaxy counts caused by the observing strategy accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the observing strategy. We find that after 10 years of the LSST survey, the best dither strategies lead to uncertainties in this bias that are smaller than the minimum statistical floor for a galaxy catalog as deep as r < 27.5. A few of these strategies bring the uncertainties close to the statistical floor for r < 25.7 after the first year of survey.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat