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Yun-Ting Cheng

Publications and source records attributed to Yun-Ting Cheng.

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Mapping Galactic Dust Emission and Extinction with HI, HII, and H$_2$

Neutral hydrogen (HI) emission closely traces the dust column density at high Galactic latitudes and is thus a powerful tool for predicting dust extinction. However, the relation between HI column density $N_{\rm HI}$ and high-latitude dust emission observed by Planck has large-scale residuals at the level of $\lesssim 20\%$ on tens of degree scales. In this work, we improve HI-based dust templates in the north/south Galactic poles covering a sky fraction of $f_{\rm sky}=13.5\%/11.0\%$ (5577/4555\,deg$^2$) by incorporating data from ionized (HII) and molecular (H$_2$) gas phases. We make further improvements by employing a clustering analysis on the HI spectral data to identify discrete clouds with distinct dust properties. However, only a modest reduction in fitting residuals is achieved. We quantify the contributions to these residuals from variations in the dust-to-gas ratio, dust temperature and opacity, and magnetic field orientation using ancillary datasets. Although residuals in a few particular regions can be attributed to these factors, no single explanation accounts for the majority. Assuming a constant dust temperature along each line of sight, we derive an upper limit on the high-latitude dust temperature variation of $σ_T<1.28$K, lower than the temperature variation reported in previous studies. Joint analysis of multiple existing and upcoming datasets that trace Galactic gas and dust properties is needed to clarify the origins of the variation of gas and dust properties found here and to significantly improve gas-based extinction maps.

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CIBER 4th flight fluctuation analysis: Pseudo-power spectrum formalism, improved source masking and validation on mocks

Precise, unbiased measurements of extragalactic background anisotropies require careful treatment of systematic effects in fluctuation-based, broad-band intensity mapping measurements. In this paper we detail improvements in methodology for the Cosmic Infrared Background ExpeRiment (CIBER), concentrating on flat field errors and source masking errors. In order to bypass the use of field differences, which mitigate flat field errors but reduce sensitivity, we characterize and correct for the flat field on pseudo-power spectra, which includes both additive and multiplicative biases. To more effectively mask point sources at 1.1 $μ$m and 1.8 $μ$m, we develop a technique for predicting masking catalogs that utilizes optical and NIR photometry through random forest regression. This allows us to mask over two Vega magnitudes deeper than the completeness limits of 2MASS alone, with errors in the shot noise power remaining below $<10\%$ at all masking depths considered. Through detailed simulations of CIBER observations, we validate our formalism and demonstrate unbiased recovery of the sky fluctuations on realistic mocks. We demonstrate that residual flat field errors comprise $<20\%$ of the final CIBER power spectrum uncertainty with this methodology.

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CIBER 4th flight fluctuation analysis: Measurements of near-IR auto- and cross-power spectra on arcminute to sub-degree scales

We present new anisotropy measurements in the near-infrared (NIR) for angular multipoles $300<\ell<10^5$ using imaging data at 1.1 $μ$m and 1.8 $μ$m from the fourth flight of the Cosmic Infrared Background ExpeRiment (CIBER). Using improved analysis methods and higher quality fourth flight data, we detect surface brightness fluctuations on scales $\ell<2000$ with CIBER auto-power spectra at $\sim14σ$ and 18$σ$ for 1.1 and 1.8 $μ$m, respectively, and at $\sim10σ$ in cross-power spectra. The CIBER measurements pass internal consistency tests and represent a $5-10\times$ improvement in power spectrum sensitivity on several-arcminute scales relative to that of existing studies. Through cross-correlations with tracers of diffuse galactic light (DGL), we determine that scattered DGL contributes $<10\%$ to the observed fluctuation power at high confidence. On scales $θ> 5'$, the CIBER auto- and cross-power spectra exceed predictions for integrated galactic light (IGL) and integrated stellar light (ISL) by over an order of magnitude, and are inconsistent with our baseline IGL+ISL+DGL model at high significance. We cross-correlate two of the CIBER fields with 3.6 $μ$m and 4.5 $μ$m mosaics from the Spitzer Deep Wide-Field Survey and find similar evidence for departures from Poisson noise in Spitzer-internal power spectra and CIBER $\times$ Spitzer cross-power spectra. A multi-wavelength analysis indicates that the auto-power of the fluctuations at low-$\ell$ is bluer than the Poisson noise from IGL and ISL; however, for $1' <θ< 10'$, the cross-correlation coefficient $r_{\ell}$ of nearly all band combinations decreases with increasing $θ$, disfavoring astrophysical explanations that invoke a single correlated sky component.

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Bayesian Multi-line Intensity Mapping

Line intensity mapping (LIM) has emerged as a promising tool for probing the 3D large-scale structure through the aggregate emission of spectral lines. The presence of interloper lines poses a crucial challenge in extracting the signal from the target line in LIM. In this work, we introduce a novel method for LIM analysis that simultaneously extracts line signals from multiple spectral lines, utilizing the covariance of native LIM data elements defined in the spectral--angular space. We leverage correlated information from different lines to perform joint inference on all lines simultaneously, employing a Bayesian analysis framework. We present the formalism, demonstrate our technique with a mock survey setup resembling the SPHEREx deep field observation, and consider four spectral lines within the SPHEREx spectral coverage in the near infrared: H$α$, $[$\ion{O}{3}$]$, H$β$, and $[$\ion{O}{2}$]$. We demonstrate that our method can extract the power spectrum of all four lines at the $\gtrsim 10σ$ level at $z<2$. For the brightest line, H$α$, the $10σ$ sensitivity can be achieved out to $z\sim3$. Our technique offers a flexible framework for LIM analysis, enabling simultaneous inference of signals from multiple line emissions while accommodating diverse modeling constraints and parameterizations.

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Is the Radio Source Dipole from NVSS Consistent with the CMB and $Λ$CDM?

The dipole moment in the angular distribution of the cosmic microwave background (CMB) is thought to originate from the Doppler effect and our motion relative to the CMB frame. Observations of large-scale structure (LSS) should show a related ``kinematic dipole'' and help test the kinematic origin of the CMB dipole. Intriguingly, many previous LSS dipole studies suggest discrepancies with the expectations from the CMB. Here we reassess the apparent inconsistency between the CMB measurements and dipole estimates from the NVSS catalog of radio sources. We find that it is important to account for the shot noise and clustering of the NVSS sources, as well as kinematic contributions, in determining the expected dipole signal. We use the clustering redshift method and a cross-matching technique to refine estimates of the clustering term. We then derive a probability distribution for the expected NVSS dipole in a standard $Λ$CDM cosmological model including all (i.e., kinematic, shot-noise and clustering) dipole components. Our model agrees with most of the previous NVSS dipole measurements in the literature at better than $\lesssim 2σ$. We conclude that the NVSS dipole is consistent with a kinematic origin for the CMB dipole within $Λ$CDM.

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Data-driven Cosmology from Three-dimensional Light Cones

We present a data-driven technique to analyze multifrequency images from upcoming cosmological surveys mapping large sky area. Using full information from the data at the two-point level, our method can simultaneously constrain the large-scale structure (LSS), the spectra and redshift distribution of emitting sources, and the noise in the observed data without any prior assumptions beyond the homogeneity and isotropy of cosmological perturbations. In particular, the method does not rely on source detection or photometric or spectroscopic redshift estimates. Here, we present the formalism and demonstrate our technique with a mock observation from nine optical and near-infrared photometric bands. Our method can recover the input signal and noise without bias, and quantify the uncertainty on the constraints. Our technique provides a flexible framework to analyze the LSS observation traced by different types of sources, which has potential for wide application to current or future cosmological datasets such as SPHEREx, Rubin Observatory, Euclid, or the Nancy Grace Roman Space Telescope.

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Near-infrared Extragalactic Background Light Fluctuations on Nonlinear Scales

Several fluctuation studies on the near-infrared extragalactic background light (EBL) find an excess power at tens of arcminute scales ($\ell\sim10^3$). Emission from the intra-halo light (IHL) has been proposed as a possible explanation for the excess signal. In this work, we investigate the emission from the integrated galaxy light (IGL) and IHL in the power spectrum of EBL fluctuations using the simulated galaxy catalog MICECAT. We find that at $\ell\sim10^3$, the one-halo clustering from satellite galaxies has comparable power to the two-halo term in the IGL power spectrum. In some previous EBL analyses, the IGL model assumed a small one-halo clustering signal, which may result in overestimating the IHL contribution to the EBL. We also investigate the dependence of the IGL$+$IHL power spectrum on the IHL distribution as a function of redshift and halo mass, and the spatial profile within the halo. Our forecast suggests that the upcoming SPHEREx deep field survey can distinguish different IHL models considered in this work with high significance. Finally, we quantify the bias in the power spectrum from the correlation of the mask and the signal, which has not been accounted for in previous analyses.

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Cosmic Near-infrared Background Tomography with SPHEREx Using Galaxy Cross-correlations

The extragalactic background light (EBL) consists of integrated light from all sources of emission throughout the history of the universe. At near-infrared wavelengths, the EBL is dominated by stellar emission across cosmic time; however, the spectral and redshift information of the emitting sources is entangled and cannot be directly measured by absolute photometry or fluctuation measurements. Cross-correlating near-infrared maps with tracers of known redshift enables EBL redshift tomography, as EBL emission will only correlate with external tracers from the same redshift. Here, we forecast the sensitivity of probing the EBL spectral energy distribution as a function of redshift by cross-correlating the upcoming near-infrared spectro-imaging survey, SPHEREx, with several current and future galaxy redshift surveys. Using a model galaxy luminosity function, we estimate the cross power spectrum clustering amplitude on large scales, and forecast that the near-infrared EBL spectrum can be detected tomographically out to $z\sim 6$. We also predict a high-significance measurement ($\sim 10^2$-$10^4σ$) of the small-scale cross-power spectrum out to $z\sim 10$. The amplitudes of the large-scale cross power spectra can constrain the cosmic evolution of the stellar synthesis process through both continuum and the line emission, while on the nonlinear and Poisson noise scales, the high-sensitivity measurements can probe the mean spectra associated with the tracer population across redshift.

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Probing Intra-Halo Light with Galaxy Stacking in CIBER Images

We study the stellar halos of $0.2\lesssim z \lesssim 0.5$ galaxies with stellar masses spanning $M_*\sim 10^{10.5}$ to $10^{12}M_\odot$ (approximately $L_*$ galaxies at this redshift) using imaging data from the Cosmic Infrared Background Experiment (CIBER). A previous CIBER fluctuation analysis suggested that intra-halo light (IHL) contributes a significant portion of the near-infrared extragalactic background light (EBL), the integrated emission from all sources throughout cosmic history. In this work, we carry out a stacking analysis with a sample of $\sim$30,000 Sloan Digital Sky Survey (SDSS) photometric galaxies from CIBER images in two near-infrared bands (1.1 and 1.8 $μ$m) to directly probe the IHL associated with these galaxies. We stack galaxies in five sub-samples split by brightness, and detect an extended galaxy profile, beyond the instrument point spread function (PSF), derived by stacking stars. We jointly fit a model for the inherent galaxy light profile, plus large-scale one- and two-halo clustering to measure the extended galaxy IHL. We detect non-linear one-halo clustering in the 1.8 $μ$m band, at a level consistent with numerical simulations. Our results on the galaxy profile suggest that $\sim 50\%$ of the total galaxy light budget in our galaxy sample resides in the outskirts of the galaxies at $r > 10$ kpc. We describe this extended emission as IHL and and are able to study how this fraction evolves with cosmic time. These results are new in the near-infrared wavelength at the $L_*$ mass scale, and suggest that IHL has a significant contribution to the integrated galactic light, and to the amplitude of large-scale background fluctuations.

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Probing Cosmic Reionization and Molecular Gas Growth with TIME

Line intensity mapping (LIM) provides a unique and powerful means to probe cosmic structures by measuring the aggregate line emission from all galaxies across redshift. The method is complementary to conventional galaxy redshift surveys that are object-based and demand exquisite point-source sensitivity. The Tomographic Ionized-carbon Mapping Experiment (TIME) will measure the star formation rate (SFR) during cosmic reionization by observing the redshifted [CII] 158$μ$m line ($6 \lesssim z \lesssim 9$) in the LIM regime. TIME will simultaneously study the abundance of molecular gas during the era of peak star formation by observing the rotational CO lines emitted by galaxies at $0.5 \lesssim z \lesssim 2$. We present the modeling framework that predicts the constraining power of TIME on a number of observables, including the line luminosity function, and the auto- and cross-correlation power spectra, including synergies with external galaxy tracers. Based on an optimized survey strategy and fiducial model parameters informed by existing observations, we forecast constraints on physical quantities relevant to reionization and galaxy evolution, such as the escape fraction of ionizing photons during reionization, the faint-end slope of the galaxy luminosity function at high redshift, and the cosmic molecular gas density at cosmic noon. We discuss how these constraints can advance our understanding of cosmological galaxy evolution at the two distinct cosmic epochs for TIME, starting in 2021, and how they could be improved in future phases of the experiment.

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Superresolution Reconstruction of Severely Undersampled Point-spread Functions Using Point-source Stacking and Deconvolution

Point-spread function (PSF) estimation in spatially undersampled images is challenging because large pixels average fine-scale spatial information. This is problematic when fine-resolution details are necessary, as in optimal photometry where knowledge of the illumination pattern beyond the native spatial resolution of the image may be required. Here, we introduce a method of PSF reconstruction where point sources are artificially sampled beyond the native resolution of an image and combined together via stacking to return a finely sampled estimate of the PSF. This estimate is then deconvolved from the pixel-gridding function to return a superresolution kernel that can be used for optimally weighted photometry. We benchmark against the < 1% photometric error requirement of the upcoming SPHEREx mission to assess performance in a concrete example. We find that standard methods like Richardson--Lucy deconvolution are not sufficient to achieve this stringent requirement. We investigate a more advanced method with significant heritage in image analysis called iterative back-projection (IBP) and demonstrate it using idealized Gaussian cases and simulated SPHEREx images. In testing this method on real images recorded by the LORRI instrument on New Horizons, we are able to identify systematic pointing drift. Our IBP-derived PSF kernels allow photometric accuracy significantly better than the requirement in individual SPHEREx exposures. This PSF reconstruction method is broadly applicable to a variety of problems and combines computationally simple techniques in a way that is robust to complicating factors such as severe undersampling, spatially complex PSFs, noise, crowded fields, or limited source numbers.

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Phase-Space Spectral Line De-confusion in Intensity Mapping

Line intensity mapping (LIM) is a promising tool to efficiently probe the three-dimensional large-scale structure by mapping the aggregate emission of a spectral line from all sources that trace the matter density field. Spectral lines from different redshifts can fall in the same observed frequency and be confused, however, which is a major challenge in LIM. In this work, we develop a line de-confusion technique in map space capable of reconstructing the three-dimensional spatial distribution of line-emitting sources. If multiple spectral lines of a source population are observable in multiple frequencies, using the sparse approximation, our technique iteratively extracts sources along a given line of sight by fitting the LIM data to a set of spectral templates. We demonstrate that the technique successfully extracts sources with emission lines present at a few $σ$ above the noise level, taking into account uncertainties in the source modeling and presence of continuum foreground contamination and noise fluctuations. As an example, we consider a TIME/CONCERTO-like survey targeting [C II] at the epoch of reionization, and reliably reconstruct the 3D spatial distribution of the CO interlopers at $0.5\lesssim z\lesssim 1.5$. We also demonstrate a successful de-confusion for the SPHEREx mission in the near-infrared wavelengths. Potentially, the reconstructed maps can be further cross-correlated with a (galaxy) tracer population to estimate the total interloper power in the linear clustering regime. This technique is a general framework to extract the phase-space distribution of low-redshift interlopers, without the need of external information, for any line de-confusion problem.

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Optimally Mapping Large-Scale Structures with Luminous Sources

Intensity mapping has emerged as a promising tool to probe the three-dimensional structure of the universe. The traditional approach of galaxy redshift surveys is based on individual galaxy detection, typically performed by thresholding and digitizing large-scale intensity maps. By contrast, intensity mapping uses the integrated emission from all sources in a 3D pixel (or voxel) as an analog tracer of large-scale structure. In this work, we develop a formalism to quantify the performance of both approaches when measuring large-scale structures. We compute the Fisher information of an arbitrary observable, derive the optimal estimator, and study its performance as a function of source luminosity function, survey resolution, instrument sensitivity, and other survey parameters. We identify regimes where each approach is advantageous and discuss optimal strategies for different scenarios. To determine the best strategy for any given survey, we develop a metric that is easy to compute from the source luminosity function and the survey sensitivity, and we demonstrate the application with several planned intensity mapping surveys.

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Tomography of the Cosmic Dawn and Reionization Eras with Multiple Tracers

The Cosmic Dawn and Reionization epochs remain a fundamental but challenging frontier of astrophysics and cosmology. We advocate a large-scale, multi-tracer approach to develop a comprehensive understanding of the physics that led to the formation and evolution of the first stars and galaxies. We highlight the line intensity mapping technique to trace the multi-phase reionization topology on large scales, and measure reionization history in detail. Besides 21cm, we advocate for Lya tomography mapping during the epoch of Wouthuysen-Field coupling as an additional probe of the cosmic dawn era.

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A Foreground Masking Strategy for [CII] Intensity Mapping Experiments Using Galaxies Selected by Stellar Mass and Redshift

Intensity mapping provides a unique means to probe the epoch of reionization (EoR), when the neutral intergalactic medium was ionized by the energetic photons emitted from the first galaxies. The [CII] 158$μ$m fine-structure line is typically one of the brightest emission lines of star-forming galaxies and thus a promising tracer of the global EoR star-formation activity. However, [CII] intensity maps at $6 \lesssim z \lesssim 8$ are contaminated by interloping CO rotational line emission ($3 \leq J_{\rm upp} \leq 6$) from lower-redshift galaxies. Here we present a strategy to remove the foreground contamination in upcoming [CII] intensity mapping experiments, guided by a model of CO emission from foreground galaxies. The model is based on empirical measurements of the mean and scatter of the total infrared luminosities of galaxies at $z < 3$ and with stellar masses $M_{*} > 10^{8}\,\rm M_{\rm \odot}$ selected in $K$-band from the COSMOS/UltraVISTA survey, which can be converted to CO line strengths. For a mock field of the Tomographic Ionized-carbon Mapping Experiment (TIME), we find that masking out the "voxels" (spectral-spatial elements) containing foreground galaxies identified using an optimized CO flux threshold results in a $z$-dependent criterion $m^{\rm AB}_{\rm K} \lesssim 22$ (or $M_{*} \gtrsim 10^{9} \,\rm M_{\rm \odot}$) at $z < 1$ and makes a [CII]/CO$_{\rm tot}$ power ratio of $\gtrsim 10$ at $k=0.1$ $h$/Mpc achievable, at the cost of a moderate $\lesssim 8\%$ loss of total survey volume.

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Line-Intensity Mapping: 2017 Status Report

Following the first two annual intensity mapping workshops at Stanford in March 2016 and Johns Hopkins in June 2017, we report on the recent advances in theory, instrumentation and observation that were presented in these meetings and some of the opportunities and challenges that were identified looking forward. With preliminary detections of CO, [CII], Lya and low-redshift 21cm, and a host of experiments set to go online in the next few years, the field is rapidly progressing on all fronts, with great anticipation for a flood of new exciting results. This current snapshot provides an efficient reference for experts in related fields and a useful resource for nonspecialists. We begin by introducing the concept of line-intensity mapping and then discuss the broad array of science goals that will be enabled, ranging from the history of star formation, reionization and galaxy evolution to measuring baryon acoustic oscillations at high redshift and constraining theories of dark matter, modified gravity and dark energy. After reviewing the first detections reported to date, we survey the experimental landscape, presenting the parameters and capabilities of relevant instruments such as COMAP, mmIMe, AIM-CO, CCAT-p, TIME, CONCERTO, CHIME, HIRAX, HERA, STARFIRE, MeerKAT/SKA and SPHEREx. Finally, we describe recent theoretical advances: different approaches to modeling line luminosity functions, several techniques to separate the desired signal from foregrounds, statistical methods to analyze the data, and frameworks to generate realistic intensity map simulations.

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Spectral Line De-confusion in an Intensity Mapping Survey

Spectral line intensity mapping has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, line intensity mapping makes use of all available photons and measures the integrated light in the source confusion limit, to efficiently map the three-dimensional matter distribution on large scales as traced by a given emission line. One particular challenge is the separation of desired signals from astrophysical continuum foregrounds and line interlopers. Here we present a technique to extract large-scale structure information traced by emission lines from different redshifts, embedded in a three-dimensional intensity mapping data cube. The line redshifts are distinguished by the anisotropic shape of the power spectra when projected onto a common coordinate frame. We consider the case where high-redshift [CII] lines are confused with multiple low-redshift CO rotational lines. We present a semi-analytic model for [CII] and CO line estimates based on the cosmic infrared background measurements, and show that with a modest instrumental noise level and survey geometry, the large-scale [CII] and CO power spectrum amplitudes can be successfully extracted from a confusion-limited data set, without external information. We discuss the implications and limits of this technique for possible line intensity mapping experiments.

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