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Register a new userEvaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST)
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Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing twelve photo-z algorithms applied to mock data produced for The Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. We report systematic biases and overall over/under-breadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate (CDE) loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performancemetrics.
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Recent work has shown that the correlation between SDSS colors and optical albedo can be used to estimate asteroid sizes from optical data alone. We revisit a correlation between SDSS colors and optical albedo for asteroids, with the albedo derived using WISE-based size estimates. Moeyens, Myhrvold & Ivezi{c} (2020) showed that this correlation can be used to estimate asteroid sizes with optical data alone, with a precision of about 17% relative to WISE-based size estimates. We present here several more sophisticated data-driven models for the variation of optical albedo with colors and estimate the contribution of SDSS photometric errors to the albedo and size estimate uncertainties. We use the results of our analysis to predict that LSST data will enable asteroid size precision of about 15% relative to WISE-based size estimates. Compared to the accuracy of WISE-based size estimates of 15-20%, the implied accuracy of optical size estimates, in the range 21-25%, is thus only a factor of 1.3 to 1.4 worse. This size estimation accuracy is significantly better than commonly assumed for optical data and is due to accurate and homogeneous multi-band photometry delivered by modern digital sky surveys.
Supernova (SN) classification and redshift estimation using photometric data only have become very important for the Large Synoptic Survey Telescope (LSST), given the large number of SNe that LSST will observe and the impossibility of spectroscopically following up all the SNe. We investigate the performance of a SN classifier that uses SN colors to classify LSST SNe with the Random Forest classification algorithm. Our classifier results in an AUC of 0.98 which represents excellent classification. We are able to obtain a photometric SN sample containing 99$%$ SNe Ia by choosing a probability threshold. We estimate the photometric redshifts (photo-z) of SNe in our sample by fitting the SN light curves using the SALT2 model with nested sampling. We obtain a mean bias ($left<z_mathrm{phot}-z_mathrm{spec}right>$) of 0.012 with $sigmaleft( frac{z_mathrm{phot}-z_mathrm{spec}}{1+z_mathrm{spec}}right) = 0.0294$ without using a host-galaxy photo-z prior, and a mean bias ($left<z_mathrm{phot}-z_mathrm{spec}right>$) of 0.0017 with $sigmaleft( frac{z_mathrm{phot}-z_mathrm{spec}}{1+z_mathrm{spec}}right) = 0.0116$ using a host-galaxy photo-z prior. Assuming a flat $Lambda CDM$ model with $Omega_m=0.3$, we obtain $Omega_m$ of $0.305pm0.008$ (statistical errors only), using the simulated LSST sample of photometric SNe Ia (with intrinsic scatter $sigma_mathrm{int}=0.11$) derived using our methodology without using host-galaxy photo-z prior. Our method will help boost the power of SNe from the LSST as cosmological probes.
We explore synergies between the space-based Wide-Field Infrared Survey Telescope (WFIRST) and the ground-based Rubin Observatory Legacy Survey of Space and Time (LSST). In particular, we consider a scenario where the currently envisioned survey strategy for WFIRSTs High Latitude Survey (HLS), i.e., 2000 square degrees in four narrow photometric bands is altered in favor of a strategy that combines rapid coverage of the LSST area (to full LSST depth) in one band. We find that a 5-month WFIRST survey in the W-band can cover the full LSST survey area providing high-resolution imaging for >95% of the LSST Year 10 gold galaxy sample. We explore a second, more ambitious scenario where WFIRST spends 1.5 years covering the LSST area. For this second scenario we quantify the constraining power on dark energy equation of state parameters from a joint weak lensing and galaxy clustering analysis, and compare it to an LSST-only survey and to the Reference WFIRST HLS survey. Our survey simulations are based on the WFIRST exposure time calculator and redshift distributions from the CANDELS catalog. Our statistical uncertainties account for higher-order correlations of the density field, and we include a wide range of systematic effects, such as uncertainties in shape and redshift measurements, and modeling uncertainties of astrophysical systematics, such as galaxy bias, intrinsic galaxy alignment, and baryonic physics. Assuming the 5-month WFIRST wide scenario, we find a significant increase in constraining power for the joint LSST+WFIRST wide survey compared to LSST Y10 (FoM(Wwide)= 2.4 FoM(LSST)) and compared to LSST+WFIRST HLS (FoM(Wwide)= 5.5 FoM(HLS)).
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Vera C. Rubin Observatory LSST Solar System Science Collaboration
, R.n Lynne Jones
, Michelle T. Bannister
2020
Vera C. Rubin Observatory will be a key facility for small body science in planetary astronomy over the next decade. It will carry out the Legacy Survey of Space and Time (LSST), observing the sky repeatedly in u, g, r, i, z, and y over the course of ten years using a 6.5 m effective diameter telescope with a 9.6 square degree field of view, reaching approximately r = 24.5 mag (5-{sigma} depth) per visit. The resulting dataset will provide extraordinary opportunities for both discovery and characterization of large numbers (10--100 times more than currently known) of small solar system bodies, furthering studies of planetary formation and evolution. This white paper summarizes some of the expected science from the ten years of LSST, and emphasizes that the planetary astronomy community should remain invested in the path of Rubin Observatory once the LSST is complete.
The 8.4m Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will start a ten-year survey of the southern hemisphere sky in 2023. LSST will revolutionise low surface brightness astronomy. It will transform our understanding of galaxy evolution, through the study of low surface brightness features around galaxies (faint shells, tidal tails, halos and stellar streams), discovery of low surface brightness galaxies and the first set of statistical measurements of the intracluster light over a significant range of cluster masses and redshifts.
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