Science Impacts of the SPHEREx All-Sky Optical to Near-Infrared Spectral Survey: Report of a Community Workshop Examining Extragalactic, Galactic, Stellar and Planetary Science

SPHEREx is a proposed SMEX mission selected for Phase A. SPHEREx will carry out the first all-sky spectral survey and provide for every 6.2" pixel a spectra between 0.75 and 4.18 $\mu$m [with R$\sim$41.4] and 4.18 and 5.00 $\mu$m [with R$\sim$135]. The SPHEREx team has proposed three specific science investigations to be carried out with this unique data set: cosmic inflation, interstellar and circumstellar ices, and the extra-galactic background light. It is readily apparent, however, that many other questions in astrophysics and planetary sciences could be addressed with the SPHEREx data. The SPHEREx team convened a community workshop in February 2016, with the intent of enlisting the aid of a larger group of scientists in defining these questions. This paper summarizes the rich and varied menu of investigations that was laid out. It includes studies of the composition of main belt and Trojan/Greek asteroids; mapping the zodiacal light with unprecedented spatial and spectral resolution; identifying and studying very low-metallicity stars; improving stellar parameters in order to better characterize transiting exoplanets; studying aliphatic and aromatic carbon-bearing molecules in the interstellar medium; mapping star formation rates in nearby galaxies; determining the redshift of clusters of galaxies; identifying high redshift quasars over the full sky; and providing a NIR spectrum for most eROSITA X-ray sources. All of these investigations, and others not listed here, can be carried out with the nominal all-sky spectra to be produced by SPHEREx. In addition, the workshop defined enhanced data products and user tools which would facilitate some of these scientific studies. Finally, the workshop noted the high degrees of synergy between SPHEREx and a number of other current or forthcoming programs, including JWST, WFIRST, Euclid, GAIA, K2/Kepler, TESS, eROSITA and LSST.Comment: Report of the First SPHEREx Community Workshop, http://spherex.caltech.edu/Workshop.html , 84 pages, 28 figure

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Auto-tuned thermal control on stratospheric balloon experiments

Balloon-borne experiments present unique thermal design challenges, which are a combination of those present for both space and ground experiments. Radiation and conduction are the predominant heat transfer mechanisms with convection effects being minimal and difficult to characterize at 35-40 km. This greatly constrains the thermal design options and makes predicting flight thermal behaviour very difficult. Due to the limited power available on long duration balloon flights, efficient heater control is an important factor in minimizing power consumption. SuperBIT, or the Super-Pressure Balloon-borne Imaging Telescope, aims to study weak gravitational lensing using a 0.5m modified Dall-Kirkham telescope capable of achieving 0.02" stability and capturing deep exposures from visible to near UV wavelengths. To achieve the theoretical stratospheric diffraction-limited resolution of 0.25", mirror deformation gradients must be kept to within 20 nm. The thermal environment must be stable on time scales of an hour and the thermal gradients on the telescope must be minimized. During its 2018 test-flight, SuperBIT will implement two types of thermal parameter solvers: one for post-flight characterization and one for in-flight control. The payload has 85 thermistors as well as pyranometers and far-infrared sensors which will be used post-flight to further understand heat transfer in the stratosphere. This document describes the in-flight thermal control method, which predicts the thermal circuit of components and then auto-tunes the heater PID gains. Preliminary ground testing shows the ability to control the components to within 0.01 K

Host galaxy identification for supernova surveys

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey

Core Cosmology Library: Precision Cosmological Predictions for LSST

The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a python interface and publicly available at https://github.com/LSSTDESC/CCL.Comment: 38 pages, 18 figures, matches ApJS accepted versio