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Forecasting the cross correlation of Terahertz Intensity Mapper [CII] line intensity maps with Euclid galaxies

Justin S. Bracks, Ryan P. Keenan, Shubh Agrawal, Garrett K. Keating, James E. Aguirre, Adam Lidz, Charles M. Bradford, Brockton Brendal, Jeffrey Filippini, Jianyang Fu, Karolina Garcia, Christopher Groppi, Steven Hailey-Dunsheath, Reinier M. J. Janssen, Wooseok Kang, Lun-Jun Liu, Ian Lowe, Alex Manduca, Daniel P. Marrone, Philip Mauskopf, Evan C. Mayer, Sydnee O'Donnell, Talia Saeid, Simon Tartakovsky, Mathilde Cuyck, Joaquin D. Vieira, Jessica A. Zebrowski

Abstract

We forecast that the Terahertz Intensity Mapper (TIM) cross-correlated with Euclid's Fornax deep field (EDF-F), TIM$\times$EDF-F, will detect the [CII]-galaxy cross-power spectrum at a median redshift of 1.1 with $\gtrsim 7 σ$ confidence. The Poisson component of the cross-power spectrum at $0.1 \leq k \leq 10$ hMpc$^{-1}$ (i.e. cross-shot noise) will be detected at $\gtrsim 3 σ$ in 4 bins spanning $0.5 < z< 1.7$. This measurement will constrain the mean [CII] specific intensity over half of cosmic history and assess the degree to which Euclid-selected galaxies account for the [CII] intensity observed by TIM. We find that TIM can detect the cross-power spectrum across a wide range of [CII] intensity models.

Forecasting the cross correlation of Terahertz Intensity Mapper [CII] line intensity maps with Euclid galaxies

Abstract

We forecast that the Terahertz Intensity Mapper (TIM) cross-correlated with Euclid's Fornax deep field (EDF-F), TIMEDF-F, will detect the [CII]-galaxy cross-power spectrum at a median redshift of 1.1 with confidence. The Poisson component of the cross-power spectrum at hMpc (i.e. cross-shot noise) will be detected at in 4 bins spanning . This measurement will constrain the mean [CII] specific intensity over half of cosmic history and assess the degree to which Euclid-selected galaxies account for the [CII] intensity observed by TIM. We find that TIM can detect the cross-power spectrum across a wide range of [CII] intensity models.
Paper Structure (16 sections, 15 equations, 7 figures, 3 tables)

This paper contains 16 sections, 15 equations, 7 figures, 3 tables.

Figures (7)

  • Figure 1: The specific intensity of select FIR line species (left y-axis) versus observed frequency. The dotted lines (using right y-axis) represent the thermal atmospheric background brightness at the ALMA site (dark) and at typical scientific ballooning altitudes (light). The color bar denotes the redshift corresponding to line emission at a given observed frequency. The white region shows TIM's range of operation. Predicted line intensities for CO are based on models from keating20, calibrated on data from Kamenetzky16. Line intensity predictions for ${\mathrm{ [C{\normalfont\textsc{ii}}] }}$ , $[\rm NII]_{\rm 122}$, $[\rm NII]_{\rm 205}$, $[\rm OI]_{\rm 63}$, and $[\rm OIII]_{\rm 52}$ are based on empirical models from the SimIM modeling framework keenan20keenan22keating20. Line intensity predictions for $[\rm OI]_{\rm 145}$ and $[\rm OIII]_{\rm 88}$ are based on models from bonato19. The atmospheric brightness is derived using the AM software package atmospheric_model.
  • Figure 2: Top Nominal NEI for the TIM detector focal planes. We present the averaged NEI for TIM's 4 redshift bins separately in purple, blue, yellow and red, depicting increasing redshift. Gray-filled areas denote the wavelength bands for TIM's SWA (upward hashed) and LWA (downward hashed). TIM's band-averaged NEI is shown by dashed (SWA) and dash-dotted (LWA) horizontal lines. The NEI for the current TIM instrument is dominated by the Poisson noise imparted by the warm primary mirror. Bottom We include equivalent curves for both a stratospheric atmosphere- (orange) and zodiacal-background-light (green) limited version of the TIM optics.
  • Figure 3: Redshift-dependent linear clustering bias models using separate model classes. The colored bars are the fiducial biases from this work, with the individual colors bearing the same meaning as in figure \ref{['fig:NEIs']}. Grey fill region display forecasts using similar models, effectively serving as a literature-based uncertainty on our assumed biases. Dot-dashed gray line: padmanabhan+19, dashed gray line: yang+22, dotted grey line: keenan20.
  • Figure 4: left: $\overline{B}(k)$, the transfer coefficient for each individual k mode measured by TIM in each of its 4 redshift bins. center: Projection of each mode $\textbf{k}$ in the transverse ($k_\perp$) and line-of-sight ($k_\parallel$) directions for TIM's lowest redshift ($0.52 < z < 0.77$) bin. right: The linear average of $\overline{B}(k)$ within logarithmically spaced, spherical shells in $k$-space denoted $\mathcal{B}(k)$.
  • Figure 5: Top: Forecast TIM $P_{{\mathrm{ [C{\normalfont\textsc{ii}}] }} \times \rm EDF-F}$ sensitivity curves in 4 redshift bins. Upward-facing arrows represent the $1\sigma$ sensitivity; blue solid line represents TIM as designed with a 1 $\mathrm{deg}^2$ field; orange solid line the $P_{{\mathrm{ [C{\normalfont\textsc{ii}}] }} \times \rm EDF-F}$ forecast from this work. Grey fill regions display analogous forecasts using parameters from alternative models in the current literature. Dot-dashed gray line: padmanabhan+19, Dashed gray line: yang+22, dotted grey line: keenan20. Bottom: SNR per $k$ bin, with total expected per-redshift-bin SNR presented in the upper left of each SNR subfigure. Dotted and dashed grey lines present 1$\sigma$ and 3$\sigma$ thresholds respectively.
  • ...and 2 more figures