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Spherex: an All-Sky Spectral Survey

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Spherex: an All-Sky Spectral Survey SPHEREx: An All-Sky Spectral Survey Designed to Explore ▪ The Origin of the Universe ▪ The Origin and History of Galaxies ▪ The Origin of Water in Planetary Systems The First All-Sky Near-IR Spectral Survey A Rich Legacy Archive for the Astronomy Community with 100s of Millions of Stars and Galaxies Low-Risk Implementation ▪ Single Observing Mode ▪ No Moving Parts ▪ Large Technical & Scientific Margins SPHEREx Science Themes How did the Universe begin? New constraints on non-Gaussianity What are the conditions for life How did galaxies begin? outside the solar system? Deep intensity mapping fields Survey of interstellar ices SPHEREx Creates an All-Sky Legacy Archive A spectrum for every 6″ pixel on the sky Medium- High- Accuracy Accuracy Detected Spectra Spectra Clusters > 1 billion > 100 million > 10 million 100,000 All-Sky surveys demonstrate high scientiFic returns with a lasting data legacy used across astronomy Galaxies Main COBE Sequence Brown Spectra Dust-forming Dwarfs Cataclysms IRAS > 100 million 10,000 > 400 > 1,000 GALEX WMAP Stars Planck WISE Asteroid & Comet Galactic Quasars Quasars z >7 Spectra Line Maps More than 1.8 million total citations > 1.5 million 2 – 300? 100,000 PAH, HI, H2 Other SPHEREx science: Doré et al. 2014 SPHEREx workshops: Doré et al. 2016 & 2018 SPHEREx Overview High-Throughput LVF Spectrometer Linear Variable Filter Focal Plane Assembly Spectra obtained by stepping source over the -18 -2 Speed ≡ 1/(time to map full sky to dF = 10 Wm ) FOV in multiple images: no moving parts Power ≡ ∫ Speed (dl/l) How Do We Probe Inflation Physics? Observables ● Inflationary gravitational waves – CMB “B-mode” polarization ● Spectral index of fluctuations – CMB and large-scale structure ● Non-Gaussianity – Sensitive to Inflaton field, single- or multi-field 2 f = flinear + fNL f linear CMB: fNL < 10.8 (2s) Local fNL; Planck 2015 results Large-Scale Structure will give best non-Gaussianity measurements Non-Gaussianity appears on largest spatial scales – need large volume survey SPHEREx Large Volume Galaxy Survey Catalog Split into Redshift Accuracy Bins SPHEREx Surveys Maximum Cosmic Volume sz/(1+z) SPHEREx Large-Volume Redshift Catalog • Largest effective volume of any survey, near cosmic limit • Excels at z < 1, complements dark energy missions (Euclid, WFIRST) targeting z ~ 2 • SPHEREx + Euclid measures gravitational lensing and calibrates Euclid photo-zs Survey Designed for Two Tests of Non-Gaussianity • Large scale power from power speCtrum: large # of low-accuracy redshifts • Modulation of fine-scale power from bispeCtrum: fewer high-accuracy redshifts COMPLEMENTARITY BETWEEN NON- GAUSSIANITY AND B-MODES Single-field models from CMB-S4 Science paper Primordial non-Gaussianity discriminates between models Single-field inflation → FNL << 1 Multi-field inFlation → FNL ≳ 1 Cyclic models → FNL ~ 1 (Steinhardt, Ijjas) de Putter, Gleyzes, Doré 16 Multi-field models • Multi-field with primordial perturbations generated by inflaton • Primordial perturbations generated by second field (i.e. spectator-dominated models) SPHEREX AND INFLATION • SPHEREx improves non- Gaussianity accuracy by a factor of ~10 Improves ΔfNL ~ 5 accuracy today to ΔfNL < 0.5 • SPHEREx optimized for non- Gaussianity measurement Broad redshift range Survey designed to cover large spatial scales Two independent tests of non-Gaussianity: - Power spectrum (PoS) - Bispectrum (BiS) CMB LENSING CROSS-CORRELATION • The SPHEREx galaxy clustering measurement covers the full sky and G )/D G is cosmic variance limited on large (D s ~ g scales b )/ g b ( s • SPHEREx determines galaxy bias bg from the galaxy power spectrum analysis • Given bg, Galaxy x CMB lensing: Measures the growth of structure DG over a wide redshift range -- Probes gravity on large scales -- Constrains the amplitude Alens Calculation by E. Schaan Doré, Werner++16 KSZ CROSS-CORRELATION • SPHEREx + CMB-S4 greatly increase our ability to measure the baryon component of the kinematic Sunyaev-Zel’dovich effect • Using the velocity reconstruction method, and using only the two highest redshift accuracy (~24.5M galaxies) S/N~55 assuming half the sky (CMB map noise of 14 μK-arcmin) • Using direct cross-correlation between T2 and δgal (Doré++03, Hill++16, Ferraro++16) allows a statistical measurement with less stringent requirements on redshift errors: S/N > 100 can be achieved by combining SPHEREx with future CMB experiments Calculation by S. Ferraro & E. Schaan Doré, Werner++16 CLUSTER IDENTIFICATION AND REDSHIFTS mission will discover 100,000 massive systems • CMB-S4 + eROSITA will find 100,000+ massive clusters contain no redsHift information auxiliary data are required • SPHEREx cluster redsHift errors* over tHe full sky will Equal or exCeed current optiCal surveys for redshifts z < 0.6 Give σ(z)/(1 + z) < 0.03 for z < 0.9 Provide virial masses for large SPHEREx errors statistiCal Cluster sample • SPHEREx will also find ~30,000 clusters independently Doré, Werner++16 *Cluster redshift errors simulated by Lindsey Bleem SPHEREx Science Team Jamie Bock Caltech/JPL Principal Investigator Rachel Akeson IPAC Stellar catalog Matt Ashby CfA Interstellar ices Lindsey Bleem Argonne Galaxy cluster catalog Peter Capak IPAC Galaxy redshifts Tzu-Ching Chang JPL Intensity mapping Asantha Cooray UC Irvine Extragalactic backgrounds Brendan Crill JPL Pipeline architect Roland de Putter Caltech Cosmology Olivier Doré JPL Project Scientist Tim Eifler JPL/U. Arizona LSST/DESI synergies Thanks Salman Habib Argonne Cosmology simulations Katrin Heitmann Argonne Cosmology simulations Chris Hirata Ohio State Cosmology Woong-Seob Jeong KASI KASI PI for Davy Kirkpatrick IPAC Brown dwarfs Phil Korngut Caltech Instrument Scientist Elisabeth Krause JPL/U. Arizona Cosmology Carey Lisse JHU Solar system catalog Listening! Daniel Masters Caltech Spectral redshift fitting Phil Mauskopf Arizona State Survey planning Gary Melnick CfA Interstellar ices Hien Nguyen JPL Instrumentation Karin Öberg CfA Ice properties Roger Smith Caltech Detector arrays Yong-Seon Song KASI Cosmology Harry Teplitz IPAC/Caltech Data Archive Volker Tolls CfA Ices pipeline Steve Unwin JPL Interstellar ices Mike Werner JPL Legacy science Rogier Windhorst Arizona State JWST synergies Yujin Yang KASI Survey science Mike Zemcov RIT Data pipeline Measuring Primordial Non-Gaussianity to σ(fNL) < 1 A test to distinguish between single- and multi-field Inflation Single-Field Inflation: ΦS ΦS Squeezed limit consistency condition by Φ Maldacena (2003): (infl) L fNL ~ (ns −1) <<1 Non-Gaussianity Produces Two Signatures Multi-Field Inflation: Enhanced power on large spatial scales FL Modulated small-scale power FS on large scales FL due to non-linear mode coupling - measured with power spectrum and bispectrum (infl) fNL ≥1 Redshifts with SPHEREx We extract the spectra of known sources using the full-sky catalogs from PanSTARRS/DES. Controls blending and confusion We compare this spectra to a template library (robust for low redshift sources): WISE For each galaxy: redshift & type Multiple types test galaxy bias effects PanSTARRS The 1.6 μm bump is a well known universal photometric indicator (Simpson & Eisenhardt 99) We simulated this process using the COSMOS data set using the same process as Euclid/WFIRST (Stickley et al.). The power of low-resolution spectroscopy has been demonstrated with PRIMUS (Cool++14), COSMOS (Ilbert++09), NMBS (van Dokkum++09). Testing Redshift Reliability Inject Real Galaxies into SPHEREx Pipeline Input Deep Galaxy Catalog Preparation Example Template and Redshift Fits 30 band observations of the Each galaxy and star is SPHEREx simulation input Published COSMOS catalog: COSMOS-based deep COSMOS field from HST, photometric catalog with assigned a best fit SED Subaru, Spitzer, GALEX, template using measured galaxy catalog (position, SED, measured spectroscopic or redshift, luminosity, flux in all Subaru, CFHT, Chandra, photometric redshift and redshift and data-based SED Keck template library SPHEREx, Pan-STARRS, DES and stellar types WISE bands) Image Simulation Generate 8x spatially-oversampled Convolve with three different images at SPHEREx’s 96 spectral Gaussians to account for Add instrumental noise plus overall and source-by-source calibration Simulated channels summing the emission of diffraction, telescope wave-front Images all galaxies in every pixel error at 0.75 µm, and pointing jitter errors (Table M.5.3-4) over 150 seconds Source Extraction Use sources detected in Measure fluxes in each Simulated Pan-STARRs or DES to define Exclude sources where Remove confusion SPHEREx band using Galaxy SPHEREx galaxy sample and blending is important mean offset estimate forward modeling with Catalog the associated astrometry Tractor Fluxes Spectroscopic Redshift Estimation Use SED template library from Brown et al. (or Galaxy catalog with associated SED template, SPHEREx others) to fit each galaxy’s SPHEREx and dust extinction, luminosity, redshift, associated Spectroscopic Pan-STARRS fluxes errors and goodness of fit Catalog Parameter Forecasts Assign each bin a Compute errors on Marginalize over SPHEREx Inflation Discard galaxies PoS and BiS in galaxy bias using Compute errors for Investigation with poor published each wavelength bias and other redshift accuracy parameters Cosmological goodness of fit bins CFHT/COSMOS and redshift bins Forecasts data prescriptions Resulting Redshift Errors Mapping the Sky with LVFs 1 orbit Spectral image 2 orbits N orbits A complete spectrum is made from a series of images SPHEREx maps the sky
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