Near-IR Background Fluctuation Results from the Cosmic Infrared Background Experiment

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Near-IR Background Fluctuation Results from the Cosmic Infrared Background Experiment Michael Zemcov The Near- IR Background II: From Reionization to the Present Epoch Max- Planck- Gesellschaft, June 2, 2015 Closing in on the Cosmological Model Aspen, CO M. Zemcov, March 13 2014

The CIBER Collaboration John Battle Jamie Bock Viktor Hristov Alicia Lanz Phil Korngut Peter Mason Gael Roudier Michael Zemcov Asantha Cooray Yan Gong Chang Feng Joseph Smidt Toshiaki Arai Shuji Matsuura Yosuki Onishi Takehiko Wada Kohji Tsumura Toshio Matsumoto Mai Shirahata Min Gyu Kim Dae Hee Lee

A Near-IR Application: Searching for the Sources Responsible for Reionization HST JWST Bouwens et al. (2010,2014) Salvaterra et al. (2010) Galaxy counts miss faint sources that may dominate the reionization budget. Estimates of the SFRD at high redshift require huge extrapolations of UV luminosity function to explain reionization. Courtesy T. Abel IM studies are sensitive to the total luminosity emitted by all galaxies -> Intensity Mapping offers an advantage.

Searching for the Sources Responsible for Reionization We know: (1) UV photons redshifted into near- IR (2) there should be plenty of photons, if we can find them. 1) Need large area 180 Mpc, 1.2 HST UDF 2) and to mitigate atmospheric emission 3) and bands to discriminate between high redshift and local emission. Lidz et al. (2009) H-band 9x9 degree 2 image over 45 minutes at Kitt Peak, Courtesy 2MASS Airglow Project Cooray et al. (2012)

The Cosmic Infrared Background Experiment (CIBER) I-band λ=1.1 μm, δλ/λ= 0.5 7 pixels, 2 x2 FOV H-band λ=1.6 μm, δλ/λ= 0.5 Tuned to measure low redshift signal. 7 pixels, 2 x2 FOV Tuned to peak of reionization signal. Zemcov et al. (2013)

The Cosmic Infrared Background Experiment (CIBER)

Imager Data Analysis Laboratory Flat Fields Raw Images Responsivity Correction PSF Generation Differenced & Masked Images Annularized PSF Masking Bock et al. (2013) Zemcov et al. (2014)

Imager Noise Properties Raw Time Ordered Data Dark Image Single Output PSD Noise Ripple Bock et al. (2013)

Power Spectra & Noise Model B l N ll M ll Zemcov et al. (2014)

CIBER Images Measured 5 good fields in two flights. Form 4 difference-field combinations to reduce flat field error, 2 of which are independent. Hurt/CIBER Masked images smoothed with an l=3000 Gaussian kernel show correlated fluctuations between bands. 1.1 μm 1.6 μm Zemcov et al. (2014)

Imager Results Auto Cross CIBER power spectra follow galaxies to scales of a few arcmin, and then strongly deviate. Behavior is well matched by Spitzer data at longer wavelengths. CIBER Data Points / Spitzer Reanalysis Cross Auto Previous Analyses (HST 1.1/1.6 μm, Thompson et al. 2008; Spitzer 3.6 μm, Cooray et al. 2012) Zemcov et al. (2014)

Imager Results CIBER is plotted with previous measurements from Spitzer & AKARI. The EM spectrum of combined data is very blue and too bright to be reionization. Not explained by scaled foregrounds. Evidence for the beginning of a turn over at 1.1 μm? Zemcov et al. (2014)

CIBER is Robust to Systematic Errors Systematic Error Zodiacal Smoothness Mitigation Observe same sky in two different seasons. Flat Field Errors Use field difference images, laboratory flat field, Season 1 x Season 2. 1/f noise from HAWAII-1 Detector Assess using sky differences, create detailed noise model, remove in x-correlations. Unmasked Galaxies Astrophysical Foregrounds Anything else? Large l separation from signal. Careful checks using ancillary data. Cross-correlate with Spitzer.

Astrophysical Foregrounds Could all this be caused by local sources of emission? 1.Dust in the solar system (Zodiacal light) very smooth on the angular scales we measure, previous limits exist. 2.Residual stars can measure this from deep surveys, this contributes 10% of the small angle power but goes as shot noise. 3.Diffuse galactic light we measure a correlation between CIBER and 100 μm, smaller than the measured fluctuations. 4.Residual galaxies most recent models do not explain power at l~10 3. Zemcov et al. (2014)

Intra-Halo Light An intra-halo light model has been used to explain the 3.6 μm near IR fluctuation measurements. From Science Magazine News and Reviews by H. Moseley on Zemcov et al. Hurt/Zemcov/CIBER IHL Component 1 and 2-Halo Components Reionization Component BRITT GRISWOLD/MASLOW MEDIA GROUP/NASA'S GODDARD SPACE FLIGHT CENTER Cooray et al. (2012)

Imager Results DGL Component IHL Component 1 and 2-Halo Components Reionization Component Auto Cross Cross Auto Zemcov et al. (2014)

Band-Band Correlation

Detecting a Large Fraction of Star Formation Is A Big Deal Fluctuation power at 1.1 and 1.6 μm is extremely bright. Applying a notional 10% contrast factor, total brightness is ~15 nw m -2 sr -1. More detailed modeling implies an IHL brightness of ~10 nw m -2 sr -1, as bright as the IGL at these wavelengths. These measurements call for a new, significant component of the near IR energy budget. Does this require modification to cosmic structure formation theories? Zemcov et al. (2014)

CIBER-2 CIBER-2 improves on CIBER-1 with 6 bands and ~5x greater AΩ which maximizes sensitivity to l-modes of interest. f esc =6% CIBER2 combined analysis expected 1 error f esc =20% CIBER Collaboration (2015) Aperture 28.5 cm Pixel Size 4 arcsec FOV 1.1x2.3 for imager bands, 0.4 for LVF degrees Coverage In the optical is critical to separate IHL from EOR. Array 3x 2048 2 H2RG CIBER Collaboration (2015) λ (Δλ/λ) 600 800 1030 1280 1550 1850 μm νi (sky) 525 450 400 380 320 224 nw m -2 sr -1

CIBER-2 3 H2RG detectors have been procured and read out electronics are being integrated. Optics currently being fabricated in Korea and Japan by collaborators. NSROC fabricating rocket components. Ready to begin integration this spring. CIBER Collaboration (2014)

SPHEREx: An All Sky Spectral Survey Optical-IR imaging spectrometer λ= 0.75-4.1 μm R=41.5 λ= 4.1-4.8 μm R=150 20cm telescope Passively cooled 6.2 x6.2 pixels SPHEREx Collaboration (2014) 2x(3.5x7) sq. deg. FOV Spatial Spectral Spatial SPHEREx Collaboration (2014) Redshift

SPHEREx: An All Sky Spectral Survey SPHEREx Collaboration (2014) SPHEREx is an Intensity Mapping Machine

Summary CIBER fluctuation measurements have detected a signal that is very bright and close to flat between 1.1 and 1.6 μm. The CIBER signal is strongly correlated with 3.6 μm measurements. Color and energetics disfavor a high-redshift interpretation, but instead favor diffuse emission at low redshifts. This would represent a new population of emitters about which we know very little that represents a significant contributor to the cosmic photon energy budget and, if due to stars, a large amount of baryonic mass. Upcoming experiments like CIBER-2 and SPHEREx are critical to our understanding of these mysterious fluctuations. THANK YOU