ALPACA A Superlative Deep, Wide, Ground-based Optical Imaging Survey JEDI An Orbital Near-IR Multiobject Spectrograph/ Multiband Imager Advanced Liquid-mirror Probe for Asteroids, Cosmology and Astrophysics (alpaca) is currently a collaboration between Columbia University Stony Brook University University of British Columbia American Museum of Natural History Pontificia Universidad Catolica de Chile and Cerro Tololo Inter-american Observatory ALPACA is a telescope and survey project consisting of • 8-meter diameter, mercury primary mirror o • Baker-Paul 3-mirror design with ~3 field • Zenith-pointing, drift-scan telescope+CCD • ~ 1 Gigapixel mosaic, 5 simultaneous bands o • ~ 1000 square degree field, at Dec = -30.16 • Nightly sampling all bands, reaching r ~ 25 • “Real-time” and archival image processing • Reaching r ~ 28 in 3y survey (~ HDF depth) Remarkable aspects of ALPACA include: • Diverse, superlative science return • Contains Galactic Center, South Galactic Pole area • Optimizing SNe Ia probe of dark energy dynamics • Extremely large AW (“etendue” or “grasp”) • Superlatively deep imaging, multiple bands • Good time sampling (time resolution Dt = 30s, 1d) • Simple, efficient operation; repetitive reductions • Simple design (few moving parts) • Largely established, off-the-shelf technology • Liquid-mirror technology now in advanced stages • Very cost-effective Liquid-Mirror Telescopes Large Zenith Telescope (6-meter) Time-delay integration (drift scan) • Image moves continuously across CCD due to Earth’s rotation • Charge being generated by photons is shifted electronically along the CCD columns at the same rate • Data are read continuously all night long • Integration time is the time taken for an image to cross the CCD NASA 3m LMT Liquid mirror surface waves • Spiral waves due to turbulence in rotating boundary layer • Effect of waves is to diffract light out of image core into a diffuse (I ~ r-3) halo • Waves height is proportional to mercury thickness • Concentric waves due to vibrations • RMS wave amplitude ~ 46 nm for 3m telescope • Solutions for large mirrors: – Mylar isolation film – Baffles to induce air co-rotation? LZT performance • 102 s exposure time • ~ 1 .4 seeing // • RAB ~ 23.1 (3) achieved so far • RAB ~ 23.5 expected Comments on Major Components • ALPACA has no “mount” – the telescope is zenith-looking and is supported without a moving mount. • Rotating 8-m mercury mirror can be constructed for under $1M, usually a ~$20M item. • The telescope building is largely a simple tube or silo and need not move with the telescope. It requires a roll-off roof and louvers to control airflow for seeing control. • Each detector surveys same strip of sky & photometric band every night, implying simple reduction stream Proto-ALPACA imaging focal plane • 0.86 deg diameter field (34 -> 240 deg2 strip) • 6 CCDs, 6.7 arcmin square, 2048x2048 E2V • 1 CCD for u,b,i,z; 2 CCDs for r • NASA NEOs: add two rows (18 CCDs total) for near- Earth asteroids (plus weak lensing, bulge microlensing, LSS, variable stars, etc.) Full ALPACA imaging focal plane 3 deg diameter field (830 deg2 strip) 240 CCDs, 8 arcmin square, 2048x2048 Fairchild deep strip, 8 columns with 6 rows of u, 4 b, and 2 each r, i, z wide strip, 8 more columns with 4 u, and 2 each b, r, i, z NEO “ears”: at least 4 more columns of 2 each of r, i ALPACA Survey Products (P. 1) • Well-sampled, 5-band SN light curves (to r ~ 25 each night, r ~ 28 each year) to discover and identify ~50000 SNe Ia and ~12000 SN Iab/II per year. SNe Ia mostly over 0.2 < z < 0.8 range, which is ideal for detailing the evolution and dynamics of dark energy • Weak Lensing: 700 square degrees with multiband data good for photometric z’s • Galaxy photometric redshift sample to r ~ 28; roughly 1 billion galaxies • For galaxy clusters, should achieve same richness as SDSS cluster catalog (to z = 0.3) but to z = 1. Sample of ~30000 clusters • Includes strong QSO lensing e.g., J12514-2914. Monitor 10-20 examples. • Map of Sculptor supercluster (z = 0.11). Novae, bright variables. • Should find several orphan GRB afterglows per year. ALPACA Survey Products (cont.) • Monitor 100,000s of AGNe to r ~ 26 for multiband variability. • Large scale structure over 4 Gpc3 (comoving) to z = 1 and 9 Gpc3 to z = 1.5. • Includes M83 (7 Mpc away, starburst); two Seyferts: NGC 2997 (17 Mpc), NGC 1097 (17 Mpc). Follow cepheids, miras, novae, eclipsing variables. • Passes through Galactic Nucleus; will find >5000 Bulge microlensing events per year; superlative extrasolar planet search resource. • Many 1000s of variable stars: Galactic structure. • Huge variety of stellar surveys. • Discover ~50 Kuiper Belt objects per night. • Trace near-Earth asteroids of 1 km diameter to Jupiter’s orbit, reconstruct orbits well within 1 AU and detect 50 m objects at 1 AU. (Proto-)ALPACA for Bulge Microlensing • OGLE III has 1.3m telescope with a 0.34 deg2 FOV, covers 90 deg2 total, spending ~60s/night per pointing, finds about 500 microlensing events per year. • Proto-ALPACA will spend ~160s per star, but has collecting area 35 times greater -> will go 10x deeper -> 30x(density of stars). Will cover 5 deg2 -> 1000 events per year (2500/year w/ NEO). • ALPACA will spend >500s/night per pointing -> 3 mag deeper -> 50x(stellar density); ~30 deg2 field -> >5000 events per year. Microlensing follow-up groups (PLANET, FUN, MOA) want to pick the ~100 best of these lightcurves in terms of early planet-like deviations in microlensing fit. Luminosity Distance versus Dark Energy Density The distance modulus (m – M) is cosmology dependent; distance at given z depends on expansion (de)acceleration and spatial curvature. SN Ia standard candle relation puts constraint on ~(Wde- 1.4Wm), whereas CMB anisotropy first acoustic peak constrains Wtot, which together currently constrain Wde, Wm the level of a few percent. Similar constraints are found by comparing cosmic microwave background constraints with Wm from cluster masses. Gives reasonable cosmic ages. SN Ia Peak Luminosity/Duration/Color Relations • L-relations : Dm15 (Phillips 1993)*, MLCS (Reiss et al. 1996, 98), stretch (Perlmutter et al. 1997, 99), CMAGIC (Wang et al. 2003), DC12 (Wang et al. 2005) relate duration (and color, shape) over light curve to brightness at maximum e.g., Dm15(B) = drop in brightness 15d post-maximum (0.5-1.5 mag). • Duration appears to be predicted primarily by mass of 56Ni. Are there other parameters? of SNe Ia is from Riess et al. 1995, ApJ, 438, L17. * MB =-19.52(+0.27) + 0.88(+0.17) [D m15(B) - 1.1] (Altavista 2003, PhD thesis) Parameters affecting SN Ia Luminosities Event width (Dm15) can predict SN Ia luminosity to ~15% r.m.s., including color measures (CMAGIC, DC12) reduce this to 7-10% r.m.s. Are the residual errors due to measurement error? Intrinsic processes? Extrinsic? Fundamentally stochastic? Possible factors include (some treated in publications, with disagreement on nature, size – even the sign – of effects): • 56Nimass • Single or double-degenerate progenitor • Metallicity • Progenitor compositional structure e.g., C/O varying with radius • Rotational velocity (rotational support influencing density structure) • Magnetic fields • Density structure depending on mass of progenitor before accretion • Convection structure in deflagration front • Viewing angle • Ejection asymmetries • Circumstellar interactions • Varying extinction laws • Weak lensing magnification variation SN Observations with Proto-ALPACA • Nightly photometry in 5 bands: u(310-410nm), b(415-550nm), r(565-745nm), i(750-1050nm), z(950-1050nm). ubri are spaced in log(), minimizing K-correction Simulated Proto-ALPACA SN Ia lightcurves including realistic errors; i band for high redshift. effects of weather & instrument (checked against Gemini ETC). Better exposure/sampling than LSST, DES, SNAP, Essence, … • Combined nightly sensitivity AB(r) ~ 25, provides S/N > 10 SN Ia detections in 3-5 bands for > 5 epochs each, to z = 0.8. • Expect ~4000 SNe Ia & ~2500 SNe Iab, II at this S/N level. • Our PUC collaborators (Minniti, Clocchiatti) have generous access to 8m-class scopes (devote ~10 nights/year, or ~200 SN, host galaxy redshifts) Yield of Supernovae from ALPACA • In 1 night: reach u = 24.3, b = 25.1, r = 24.1 (sum to r = 25). This implies 100 y-1 deg-2 of SNe Ia, 20 y-1 deg-2 of SNe II, hence (30000+6000) y-1 total. (Note: t = 2d SN Ia is 3.8 mag fainter than at maximum) • In one 14-night dark run: reach u = 25.7, b = 26.5, r = 25.5 (sum to r = 26.5) => (50000+ 60000) y-1 total. (Assuming 1 arcsec seeing and 100% good weather. Limits Number per year per deg 2 of SNe Ia (dashed), are for 10 detections.) II (dotted) & orphan GRB afterglows (solid – 2 models, Woods & Loeb 1998, ApJ, 508, 760) Depth of Multiband SN Ia Detection ALPACA can detect SNe Ia in a single night to z ~ 1, and find colors in three bands to z ~ 0.8. As we shall see, the u band is also crucial for SN type identification for z < 0.4, which ALPACA also handles superbly. 10 thresholds for typical SNe Ia in all 4 band after 1 night (dashed) & 14 nights (dash-dotted) ALPACA SN Ia Redshift Distribution • Consider only light curves detected at >10 at more than 5 epochs over the event (sufficient for calculating Dm15 and several higher moments of the flux distribution). • We recover a huge quantity of SNe Ia with this and better sampling, except at lower redshift. This is aided, however, by the solid angle covered for z < 0.4 is doubled to the full width of the array (discussed later), hence the numbers per 0.01 in Dz is actually twice that shown to the right. We have ~10000 SNe Ia (after 3 y) in 8- 10 bins. We will discuss in a few minutes what this will accomplish. “decent” means >5 points of >10 in at least 3 bands Photometric ID of SN Type • On the basis of color alone (7d post max) one can separate SNe Ia from all other types Reddening, AV = 4 • Slight degeneracy of z = 0.3 Ia with z = 0.1 Ibc is removed by different evolution of SNe types through color-color plot over event. Star = SNe Ia Circle = I bc Triangle = II P Square = II b Diamond = II N Number labels = int (10 z) SN Color Evolution • Red = SNe Ia • Green = I bc • Blue = II P Number labels = days after max. Color evolution over SN peak easily breaks degeneracy between z=1 SNe Ia and z=0.3 SNe I bc (and further isolates SNe Ia). SN Ia Host Galaxies SNe Ia tend to be closely associated with prominent host galaxy. (SNe Iab+II sometimes associated with disconnected star formation knots.) Sullivan et al. 2003 Tonry et al. 2003 Accuracy and Reliability of Photometric Redshifts • Accuracy of photometric redshifts – Systematic uncertainty ∆z / (1 + z) < 6.5% – Photometric uncertainty • Reliability of photometric redshifts – No “outliers” out of ≈ 150 redshifts – “Contamination” < 1% (Lanzetta et al. 1998) Plan for Proto-ALPACA SN Ia Studies • SNe Ia can be distinguished photometrically to z > 0.8. Redshift of SN can be determined photometrically with Dz ~ 0.2. Longterm image accumulation from Proto-ALPACA can determine host galaxy photometric redshift with accuracy Dz ~ 0.1. Positional coincidence of host galaxy and SN as well as redshift consistency will establish SN redshift to accuracy Dz ~ 0.1. • We will have large sample (~2000/y) of SNe Ia of well-sampled, multiband light curves from Proto-ALPACA. We plan to subject these to principal component analysis to find subcategories of SNe Ia. The goal then is to understand the physical nature of these differences and their effects on standard candle relation, both of which demand spectra. • Minniti and Clocchiatti have access to Gemini-S, VLT and Magellan time, each with multiobject spectrographs (GMOS: 5.5 arcmin, ~300 slits max.; FORS: 6.8 arcmin, ~20 max.; IMACS: 15 arcmin, ~250 max, respectively). They can devote ~10 nights/y -> ~75 fields total, corresponding to ~2-6% of Proto-ALPACA field (hence about 80-250 SN Ia host galaxies). • Also, we will need time on smaller scope to establish set of secondary photometric standards in ALPACA strip. (Minniti and Clocchiatti will help acquire this SMARTS time at CTIO.) Are Spectroscopic Redshifts Practical? • Spectrograph module operating with imager might obtain >20 spectra at a time (every ~50s) per module, x10 modules => number of spectra ~8,000,000/y vs. 30,000/y of “decent” SNe Ia • ~50% of host galaxies require < 10 integrations (for 5 detection, 1nm wavelength resolution) • 90% of host galaxies from High-z SN Team (HZT) have I < 25. Typically I ~ 23. (Williams et al. 2003, AJ, 126, 2608) • Spectrograph module must have drift scanning slit (perforated tape – “player 1 integration 10 integrations piano”) and low distortion (need ~0.1% vs. | | ~0.2% in reality for CTIO RCSP, f/7.8 -> f/1.0 ). This instrument can be prototyped Williams et al. 2003: magnitudes of HZT SN Ia hosts (0.43 < z < 1.06) using Proto-ALPACA. Full ALPACA: Improving SN Ia Standard Candles The primary challenge is the control of systematics. A method to improve this might be splitting the sample of ~105 well- sampled light curves into z bins (~0.1) small enough that z error due to cosmological uncertainty is insignificant, Dm< 0.1%, then perform a principle component analysis on ~10 subsamples of ~104, and compare different subsamples’ results to measure evolution. Quality of the data might allow us to explore 10-20 parameters. Finding the covariance of luminosity in a single bin with this parameter set should reduce the scatter significantly, producing a detailed luminosity model, or at least discarding outriggers. [Behavior of dark energy can be parameterized by its Equation of State: pressure versus mass density w = p/ r. w=0: “normal matter,” w= -1/3: cosmic strings, -1/3 < w < -1: quintessence, w= -1: cosmological see Lewis & Bridle 2002, Phys Rev D, 66, 103511 constant] Worked Example for 2000 SNe Ia 2000 SNe with r.m.s Dm = 0.2 mag, sampled in z via deep, ground-based imaging. Get maximal discrimination in dark energy density f at redshifts 0.3 < z < 0.8. This is true of most dark energy models, in this case quintessence (scalar field potential with slow-roll) versus k-essence (similar but with coupling to kinetic energy term) as might help explain why Wde ~ Wm Wang & Garnavich 2001, ApJ, 552 445 Luminosity Distance vs. Dark Energy Dynamics Statistical errors only: even assuming that we are unable to reduce scatter in inferred SN Ia luminosity below ~10% r.m.s., the number of SNe will allow us to achieve statistical errors in ~10 redshift bins of Dm ~ 0.002. This is the same size proportional error one sees across a Dz = 0.1 bin if one assumes value of Wm incorrect by 3%, roughly the uncertainty now. An error Dm = 0.002 is small compared to deviations between Standard candle apparent brightness at moderate redshifts for different models of dark energy: predictions of different physical (baseline) Wde=0.7 cosmological constant – value of models for dark energy; 10r value 0.6 or 0.8 varies by about 0.13 in Dmag at z=1, (thick) of a few percent is sufficient to pseudo Nambu-Goldstone boson, (thin) supergravity, differentiate most extant models. (long dashed) pure exponential, (thick dotted) inverse tracker, (short dashed) periodic potential (Weller & Albrecht 2001, PhysRevLet, 86, 1939) Cosmological Measures of Dark Energy Universal equation of state w=p/r describes expansion’s dynamics and therefore H(z). What we actually observe are measures of H(z) and redshift integrals* over H(z), the angle distance and luminosity distance: Supernovae as standard candles: luminosity distances dL(zi) Baryon acoustic oscillations as standard ruler: cosmic expansion rate H(zi) angular diameter distance dA(zi) Weak lensing cosmography: ratios of dA(zi) / dA(zj) *Comoving distance is related to expansion rate H(z): and the observed distances (in flat Universe) dL = R0 r (1+z), dA = R0 r / (1+z) Several independent methods will provide a powerful cross-check, and allow ALPACA to place precise constraints on dark energy (+growth of structure via cluster counts+strong lens delay timings+large-scale structure Alcock-Paczynski+cluster integrated Sachs-Wolfe…) Combining ALPACA Dark Energy Constraints The simplest dark energy investigation method sensitivities to estimate are SN Ia standard candles, weak lensing shear and baryon acoustic oscillations. To express dark energy dynamics, we use w = w0 + wa a = w0 + wa /(1+z), where wa describes the redshift change in w. A few points: • If SN Ia method systematics ~ 10%, baryon oscillations are more useful. If ~ 2%, SN are more useful, comparable to weak lensing constraints. • Current limits combining CMB anisotropies, LSS and SN Ia constrain w at the 10% level. ALPACA could Dataset error on: Wm w0 wa improve this 5x. Limit on wa would be SNe (2% syst.+WMAP) 0.03 0.15 1.0 vital in distinguishing dark energy SNe+BAO 0.02 0.11 0.65 WL 0.02 0.20 0.57 models. SNe+BAO+WL 0.01 0.04 0.16 SNe+BAO+WL+Planck 0.003 0.02 0.04 Planck only 0.013 0.19 0.94 Growth of Structure: Clusters Clusters are the largest collapsed structure, so respond to cosmological influence on scales near the linear regime. This is significantly affected by dark energy domination. At Columbia, Wang, Haiman, Khoury & May (2004) investigate cluster counts dN/dz and power spectrum P(k) to constrain cosmological parameters, including w’ - here parameterized as wa, which is roughly equivalent: w = w0 + wa (1 - a). We have run these models for ALPACA. Expected ALPACA accuracy used in conjunction with CMB anisotropies improves significantly on the best planned CMB-only constraints (Planck): 1- error Planck only dN/dz dN/dz+P(k) dN/dz+P(k)+CMB D(Wde) 0.07 0.03 0.017 0.004 D(Wmh2) 0.002 0.075 0.012 0.0004 D(8 ) 0.1 0.013 0.01 0.003 D(w0) 0.6 0.4 0.2 0.05 D(wa) 0.8 1.8 0.9 0.2 D(Wbh2) 0.0006 --- 0.004 0.0002 D(ns) 0.005 --- 0.05 0.002 CTIO Site Cerro Tololo is in the southern Atacama desert of Chile, Latitude -30o.16. The nights are 80-85% clear, and seeing is typically at or below 1 arcsec. Site is at the “prow” of the mountain summit, looking into the prevailing wind, hence best for seeing. There are no obstructions for many km, hence one can View from summit site looking NE into prevailing wind expect little ground-layer turbulence. Potential ALPACA Schedule • early 2007: first light on telescope (with smaller CCD imager) • early 2008: Gigapixel mosaic online • early 2011: finish nominal imaging survey • early 2012: start spectrographic survey? Joint Efficient Dark-energy Investigation (JEDI): a candidate implementation of the NASA-DOE Joint Dark Energy Mission (JDEM) JEDI Science Team: Yun Wang (PI), University of Oklahoma Arlin Crotts (co-PI), Columbia University Peter Garnavich (co-PI), University of Notre Dame William Priedhorsky (co-PI), LANL co-Is: Eddie Baron, University of Oklahoma David Branch, University of Oklahoma Edward Cheng, Conceptual Analytics Ian Dell’Antonio, Brown University Salman Habib, LANL Katrin Heitmann, LANL Alexander Kutyrev, NASA GSFC John Mackenty, Space Telescope Institute Harvey Moseley, NASA GSFC Gordon Squires, Caltech Max Tegmark, MIT Craig Wheeler, UT Austin Ned Wright, UCLA JEDI: exploiting 0.8-4 micron “sweet spot” - lowest sky background region in ~0.3-100micron wavelengths - rest wavelengths in red/near-IR for redshifts 0 < z < 4 Background sky spectrum: Leinert 1998, A&AS, 127, 1 What JEDI Hopes to Measure: (1) The cosmic expansion rate H(z) as a free function in 0.2 redshift bins to better than 2% accuracy (using three independent methods: supernovae, baryon oscillations, weak lensing). (2) For dark energy equation of state w(z)=w0+w’z (with a cutoff at z=2 such that w(z>2)= w0+2w’), measure w0 to better than 2%, and w’ to better than 5% accuracies. JEDI Data: (1) Supernovae: ≥ 7,000 type Ia supernovae with well-sampled light curves (every 5d) and good quality spectra. (2) Primary baryon oscillation data: 10-100 million galaxy spectra (H emission line galaxies) over 10,000 square degrees, with 0.5 ≤ z ≤ 2. The imaging over the same area serves as a weak lensing survey to H ~ 23. (3) Primary weak lensing data: accurate measurements of galaxy shapes over 1000 square degrees to H ~ 25. The galaxy spectra over the same area form a baryon oscillation survey to z ~ 4. Priors Assumed for Dark Energy Constraints: (1) For all three methods: assumed a flat universe, Wm is known to 1% (or 3%) from CMB data from Planck (or WMAP). (2) For the baryon oscillation method, assumed Wmh2 is known to 3% fractional error, Wbh2 is known to 10%, the sound horizon at recombination is known to 1-2% from CMB data from Planck and WMAP. Measuring cosmic expansion history H(z) to ≤ 5% accuracy using supernovae as standard candles Uncorrelated measurement of H(z) from simulated supernova data (systematics included), with Wm assumed to be known. Assuming a Gaussian prior on Wm would introduce some correlations in the estimated H(z) in different z bins, but would change the size of the error bars little. JEDI SNe only. h(z)=H(z)/100 km/s Mpc-1 Wang & Tegmark (2005) Measuring cosmic expansion history H(z) to ≤ 2% accuracy using baryon oscillation scale as a standard ruler Assuming that the sound horizon at recombination is measured to 1.36% accuracy (WMAP, Spergel et al. 2003). Not sensitive to values of Wm and Wb assumed. Data: JEDI 10,000 square degree galaxy redshift survey. Blake (2005) Note that the errors go opposite way of the SN case. Measuring baryon oscillations as a standard ruler The Power of Three Independent Methods Supernovae as standard candles: luminosity distances dL(zi) Baryon acoustic oscillation as standard ruler: cosmic expansion rate H(zi) angular diameter distance dA(zi) Weak lensing cosmography: ratios of dA(zi)/dA(zj) The three independent methods will provide a powerful cross-check, and allow JEDI to place precise constraints on dark energy (+growth of structure via cluster counts+ strong lens delay timings+LSS Alcock-Paczynski+…) Measuring w0 to better than 2%, and w’ to better than 5% accuracies w(z)=w0+w’z (with a cutoff at z=2 such that w(z>2) = w0+2w’), and a Gaussian prior on Wm with (Wm)=0.01 (from Planck). SN constraints (systematics included) are derived using Fisher matrix & including 300 SNe Ia with 0.1 < z < 0.08 from Nearby SN Factory. Weak lensing constraints are scaled from Zhang, Hui, & Stebbins (2003, Fisher matrix) for a survey with median redshift 1, and photometric redshift accuracy of z=0.05. Baryon oscillation constraints are derived using Glazebrook & Blake’s (2005) conservative Monte Carlo method. Necessity of Space Observations Supernovae as standard candles: 1) Higher sensitivity: z > 1 SNe Ia tightens constraints on w’, tracker solutions. 2) H(z) measured as a continuous free function allows robust testing of DE models. 3) Rest J lightcurves for all SNe Ia (better standard candles – Krisciunas et al. 2004). 4) Smaller extinction corrections. Baryon acoustic oscillation as standard ruler: 1) H(z) across redshift desert z = 1.5-2.5 significantly tightens constraints on w, w’. 2) H(z) measured as a continuous free function allows robust testing of DE models. Weak lensing cosmography: 1) Stable and smaller point spread function a big plus over ground observations. 2) More galaxies and smaller shape noise by including red, quiescent populations Result: Continuous H(z) to better than 2% in Dz~0.2 bins. Comparison of JEDI and ground-based BO survey Required Supernova Data • Supernova observations: 146 detection periods (5 days each) over 2 years • ~ 5,000 type Ia supernovae over 12 deg2 • Photometric precision: ~ 2% • Quality of spectra: S/N 10 with a dispersion of 20-40Å per pixel Required Galaxy Data • Baryon acoustic oscillation measurements: – ~30-100 million galaxy redshifts (z2) over 10000 deg2 ; ~10 million galaxy redshifts (z4) over 1000 deg2 – Redshift precision: σz /(1+z) =0.2% or better • Weak lensing measurements (1000 deg2 ): – Photometric precision: ~ 1-2% – PSF stability: pointing stability < 0’’.02 Observational Capability • Observing modes: simultaneous imaging and multi-slit spectroscopy • Imaging: FOV: ~ 0.15 deg2; wavelength: 0.8-4.2μm resolution: ~ 0".14 at 1μm • Spectroscopy: FOV: ~ 0.35 deg2; wavelength: 0.8-3.2μm resolution: R ≥ 200-300 multiplexing: ~ 50 supernova and 3000 galaxy spectra simultaneously • Data rate: ≤ 30 Gbyte/day with compression and onboard processing JEDI focal plane Strawman Mission Architecture • Aperture of the telescope: ~1.5m • Mission duration: 3 years • Detectors: 32 2048x2048 HgCdTe detectors for imaging (0.8-4.2μm) and spectra (0.8-3.2 μm) plus eight 1024x1024 HdCdTe detectors for longer-wavelength imaging • Spectrograph slit mask: each spectrograph field consists of a 175x384 microshutter array, with a slit size 3"x6" • Orbit: L2 • Telescope temperature: ~100 K (passive cooling achieved using sunshields) JEDI Satellite Microshutter Arrays: AAS 205, [5.07] Microshutter Arrays for JWST NIRSpec., S. H. Moseley et al. Each shutter consists of a shutter blade suspended on a torsion beam (from a support grid) that allows for a rotation of 90°. A motor opens the shutters with a specially formed magnet as a remote controlling tool. 2D programmable slit mask Strawman JEDI optical design (Hawaii-1 detectors at reimaged focus are suppressed for clarity) Dominic Benford (NASA GSFC) (Hawaii-1 detectors at reimaged focus are suppressed for clarity) Dominic Benford (NASA GSFC) Simulated JEDI spectrum of a SN Ia at z=1.7 S/N ~ 10 JEDI Mission Summary • 1.5m-class, simultaneous imaging & multiple object spectroscopy, FOV: 0.5 square degree. • Simultaneous slit spectra for ~50 supernovae and ~3000 galaxies • Imaging in five bands (0.8-4.2 microns, spaced evenly in log ) • 4 spectrograph fields (0.8-3.2 microns), 175x384 microshutters each • Total of 32 HAWAII-2 2048x2048 Rockwell HgCdTe detectors + eight HAWAII-1 1024x1024 detectors • L2 orbit, sunshields for passive cooling • JEDI would benefit from coordinated ground-based, optical surveys • First two years: 7,000 type Ia supernovae (a deep galaxy survey over 12 square degrees as a by-product) • 3rd year: a 1000 square degree survey of galaxy redshifts (to z~4) and weak lensing measurements, imbedded in 10,000 square degree survey (redshifts measured to z~2) • Launch scheduled for 2017 Relaxing the prior on Wm As before, except gaussian prior of (Wm)=0.03 (from WMAP). Fine point: also (Wm h2)/Wm h2 =0.03 for baryon oscillations.
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