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Eric Gawiser

Publications and source records attributed to Eric Gawiser.

At least 19 recordsLinked to original sources

ODIN: Comparison of Source Extractor and Tractor Source Detection for Lyman Alpha Emitting Galaxy Selection at z=3.1

Lyman Alpha Emitting galaxies (LAEs) are young, actively star-forming galaxies identified by their strong Lyman-alpha emission at a rest-frame wavelength of 121.6 nm, making them valuable tracers of galaxy evolution and the large-scale structure of the Universe. The One-hundred-deg^2 DECam Imaging in narrow-bands (ODIN) survey collects LAE samples during Cosmic Noon. Because LAE selection is based on photometric measurements derived from source-detection algorithms, the choice of detection method can directly affect the resulting LAE samples. We therefore compare two prominent source detection methods, Source Extractor (SE) and Tractor (Tr), to determine which is better suited for LAE selection in ODIN. We investigate differences between SE and Tr in the ODIN-COSMOS field, focusing on the z=3.1 LAE sample. We find that a significant fraction of Tr LAEs have low continuum flux measurements, increasing the inferred narrow-band excess and resulting in an LAE sample nearly twice as large as SE. However, LAEs detected by Tr but not SE exhibit equivalent width estimates indicative of potential contamination. We introduce an additional LAE selection criterion based on the expected Lyman-break behavior of LAEs at z~3 to reduce low-redshift contamination without requiring a significant detection of the break itself. Our results demonstrate that differences in source detection can significantly affect narrow-band LAE selection and motivate the use of SE photometry for ODIN LAE catalogs.

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SPAM: Survey Overview and JWST/NIRCam Multi-Band Photometry Catalog

We present the Star-formation from Photometry through the Addition of Medium-bands (SPAM) survey, a 62.9 hr JWST/NIRCam imaging program to add ten new filters, nine medium-band filters, and one broad-band filter to the CEERS legacy dataset. We describe the observation strategy, present the data, and detail the data-reduction process. We include a complete reduction of imaging in the legacy CEERS footprint, inclusive of all publicly available photometric parallel and GO observations within the legacy CEERS footprint. We present a multi-band photometric and photometric redshift catalog which includes all medium- and broad-band filters available on NIRCam. We find that adding medium bands from the SPAM and MINERVA programs improves photometric redshifts. We discuss how these data advance the SPAM survey's key science goals: better-constrained photometric redshifts, identification of high-redshift overdensity members, improved recovery of emission-line strengths, and more accurate star formation histories.

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Fisher Forecasting for the DESC with $\texttt{Augur}$

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.

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The Roman eXtreme Deep Field (RXDF)

The Roman eXtreme Deep Field (RXDF) program is one of the five General Astrophysics Survey (GAS) programs approved for observing time with the Nancy Grace Roman Space Telescope in Cycles 1 and 2. It has been allocated 386.41 hours to carry out an imaging survey to AB = 30 mag (5-sigma) over ~140x larger area than the Hubble eXtreme Deep Field (HXDF) full-depth area (ACS+WFC3/IR). The RXDF will cover the full Roman wavelength range with 7 bands, reaching AB = 30 mag in RZYJH, 29 mag in F, and 28 mag in K, over a full-depth area of 678.75 arcmin^2 embedded in a total area of 1,243 arcmin^2, and far exceeding the depths of the Roman Core Community Surveys (CCS). The RXDF is within the Euclid Ultra Deep Field (EUDF) near the North Ecliptic Pole (NEP), a strategic long-term field for generational space facilities, with a wealth of multi-wavelength data including extensive coverage from the James Webb Space Telescope (JWST) NEXUS Treasury program. The observations will cover 3 epochs at a 1-year cadence, each epoch divided into 3 sub-epochs ~10 days apart, enabling time-domain studies on time baselines from ~10 days to over ~2 years. The RXDF is uniquely positioned to address critical questions in reionization, large scale structure (LSS), growth of supermassive black holes (SMBHs), little red dots (LRDs), and high-z supernovae (SNe); the volumes probed by HST+JWST are too small at these extreme depths, and even the deepest CCS tiers are too shallow. In addition to our key objectives, a wealth of additional science will be enabled by engaging the community with our rapidly released datasets, revolutionizing a wide range of science for a lasting legacy. This short document, which is converted from the approved RXDF proposal, aims to provide the community with a summary of the program.

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ODIN: Confirmation and 3D Reconstruction of Six Massive Protoclusters at Cosmic Noon

Protoclusters represent sites of accelerated galaxy formation and extreme astrophysical activity characteristic of dense environments. Identifying massive protoclusters and mapping their spatial structures are therefore crucial first steps in understanding how the large-scale environment influences galaxy evolution. We combine wide-field Ly$α$ imaging from the ODIN survey with extensive DESI and ancillary spectroscopy across the extended COSMOS and XMM-LSS fields ($\approx$14 deg$^2$) to search for massive protoclusters. We confirm six systems at $z\approx 2.4$ and $z\approx 3.1$, reconstruct their three-dimensional structures, estimate descendant halo masses, and, for one structure at $z\approx 3.12$, demonstrate that overlapping narrowband filters ($NB497$ and $N501$) provide accurate redshift tomography for emission-line galaxies. One protocluster at $z\approx 2.45$ overlaps with one of the LATIS tomographic fields, enabling direct comparison between galaxy and H {\sc i} overdensities traced by Ly$α$ forest absorption. Another at $z\approx 3.12$ hosts a massive quiescent galaxy ($M_{\ast} \approx 1.2 \times 10^{11}M_\odot$), indicating early quenching in a dense environment. By comparing Ly$α$ emission properties across environments, we find that protocluster galaxies exhibit higher median line fluxes and a deficit of faint emitters relative to the field. The effect is strongest when both 2D and 3D density information are combined, indicating that galaxies in the densest protocluster cores are most affected by environmental processes. This effect is stronger at $z\approx3.1$ than at $z\approx2.4$, suggesting possible redshift evolution.

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ODIN: Rest-frame Optical Morphologies and Star Formation Activity of Lyα Emitters at z=2.4, 3.1, and 4.5

We analyze the rest-frame optical (~8000 Å) morphologies and star formation activity of Lyα emitters (LAEs) at redshifts $2.4$, $3.1$, and $4.5$, identified in the ODIN survey. To compare their physical properties with those of other galaxies, we construct a comparison sample of typical star-forming galaxies (SFGs) at similar redshifts from the COSMOS2025 catalog. Using the \textit{JWST}/NIRCam images from the COSMOS-Web survey, we measure the rest-frame optical sizes and Sérsic indices. We first examine their size-mass relations and find that LAEs at all three redshifts have smaller sizes than typical SFGs, with the size difference decreasing at higher redshifts. We also find that LAEs tend to have larger Sérsic indices at $z=2.4$ and $3.1$ than typical SFGs, but the difference becomes weaker at $z=4.5$. These trends are qualitatively reproduced in the Horizon Run 5 cosmological hydrodynamical simulation. We then investigate star formation activity and find that LAEs exhibit higher star formation rates than typical SFGs at all redshifts considered. Finally, we examine the connection between Lyα emission and galaxy structure, finding that the rest-frame equivalent width (REW) of the Lyα emission line has negative and positive correlations with size and Sérsic index, respectively. In addition, we find a strong positive correlation between the Lyα REW and the ratio of the instantaneous star formation rate to that averaged over the last $100\;\mathrm{Myr}$ (i.e., $\mathrm{SFR_{inst}}/\mathrm{SFR_{100 Myr}}$). These results suggest the compact and starbursting nature of LAEs, and provide important constraints on the physical mechanism for the Lyα photon escape from galaxies.

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HETDEX: Star Formation Stochasticity Diagram of Lyman Alpha Emitting Galaxies at Cosmic Noon Confirms Three Archetypes

In this work, we aim to measure the star formation stochasticity of Lyman Alpha Emitting Galaxies (LAEs) at Cosmic Noon. We identify 270 LAEs from the HETDEX Survey in the COSMOS field with rest-UV-through-NIR photometry from CANDELS\null. For each LAE, we perform non-parametric gaussian-process star formation history (SFH) reconstruction using the Dense Basis method. Our HETDEX LAE sample is described well by the three SFH archetypes defined for ODIN LAEs in Firestone et al. 2025 with comparable frequency: First Burst, Dominant Burst, and Nondominant Burst. The rapidly rising Star Formation Rates (SFRs) of First Burst LAEs are not adequately represented in traditional SFR$_{100}-M_*$ diagrams, where SFR$_{100}$ is averaged over the most recent 100Myr. This motivates the usage of SFR$_{10}-M_*$, where SFR$_{10}$ is averaged over the most recent 10Myr. We introduce the Star Formation Stochasticity Diagram, a diagnostic tool that probes variations in galaxies' SFRs across cosmic time. By eliminating the confounding factor of redshift evolution, we are able to employ a gaussian mixture model to decompose our ratio of short- vs.long-term SFR into statistically motivated sub-populations. This agnostic component decomposition reveals three populations consistent with the empirical LAE SFH archetypes. We can, therefore, summarize the overall stellar mass assembly of LAEs with this ratio, even without viewing their full star formation histories.

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ODIN: Characterizing the Three-dimensional Structure of Two Protocluster Complexes at $z = 3.1$

We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at $z=3.1$. These protocluster 'complexes', designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of $z=3.1$ Ly$α$ emitters (LAEs) identified in the COSMOS field by the One-hundred-deg$^2$ DECam Imaging in Narrowbands (ODIN) survey. These protocluster complexes have been followed up with extensive spectroscopy from Keck, Gemini, and DESI. Using a probabilistic method that combines photometrically selected and spectroscopically confirmed LAEs, we reconstruct the 3D structure of these complexes on scales of $\approx$50 cMpc. We validate our reconstruction method using the IllustrisTNG300-1 cosmological hydrodynamical simulation and show that it consistently outperforms approaches relying solely on spectroscopic data. The resulting 3D maps reveal that both complexes are irregular and elongated along a single axis, emphasizing the impact of sightline on our perception of structure morphology. The complexes consist of multiple density peaks, ten in COSMOS-z3.1-A and four in COSMOS-z3.1-C. The former is confirmed to be a proto-supercluster, similar to {\it Hyperion} at $z=2.4$ but observed at an even earlier epoch. Multiple `tails' connected to the cores of the density peaks are seen, likely representing cosmic filaments feeding into these extremely overdense regions. The 3D reconstructions further provide strong evidence that Ly$α$ blobs preferentially reside in the outskirts of the highest density regions. Descendant mass estimates of the density peaks suggest that COSMOS-z3.1-A and COSMOS-z3.1-C will evolve to become ultra-massive structures by $z=0$, with total masses $\log(M/M_\odot) \gtrsim 15.3$, exceeding that of Coma.

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A Non-parametric Method for the Inference of Halo Occupation Distributions

The galaxy-halo connection traces processes by which galaxies form and evolve. The halo occupation distribution (HOD) describes the relationship between galaxies and their host dark matter haloes. Measurements of the galaxy two-point correlation function (2PCF) allow us to extract information about the HODs of observed galaxy samples. Several parametric HOD models have been proposed in the literature, but the choice of parameterization restricts the space of possible HODs. To resolve this issue, we introduce a non-parametric HOD fitting method in which we train an emulator to learn the mappings among the galaxy 2PCF, physical properties used to select galaxy samples, and the HOD, all obtained from simulated past lightcones constructed with the Santa Cruz semi-analytic models. Implementing this emulator within a likelihood analysis framework, we derive constraints on the HOD of a galaxy sample when provided with a measurement of its 2PCF. Using the emulator to accelerate likelihood evaluations, we test the non-parametric HOD approach on a set of 2PCFs for mock galaxy samples drawn from the TNG100-1 simulation and selected above threshold values of stellar mass and star formation rate. Our framework is able to recover TNG100-1 HODs within 0.2 dex. We use the TNG100-1 mocks to tune the reported uncertainties to estimate those expected in the analysis of observations. Comparing to parametric HOD modeling routines applied to the same mock galaxy samples, our approach consistently infers the HOD with comparable or greater precision and accuracy.

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ODIN: Clustering Properties of Ly$α$ Blobs at $z$ $\sim$ 2.4 and 3.1

Spatially extended Ly$α$ nebulae, known as Ly$α$ blobs (LABs), are a rare population at $z > 2$ that are thought to trace proto-groups or the progenitors of massive galaxies in the present-day universe. However, their dark matter halo properties (e.g., halo mass) are still uncertain due to their rarity and strong field-to-field variation. The One-hundred-deg$^2$ DECam Imaging in Narrowbands (ODIN) survey has discovered 103 and 112 LABs in the extended ($\sim$9~\sqdeg) COSMOS field at $z\sim2.4$ and 3.1, respectively, enabling estimation of their bias and host halo masses through clustering analysis. We measure the angular auto-correlation functions (ACFs) of LABs and derive galaxy bias factors of $b$ = $4.0\pm0.8$ and $3.8\pm0.7$, corresponding to minimum halo masses of $2.8^{+3.0}_{-1.8}$ and $0.7^{+0.8}_{-0.5}\times10^{12}~M_\odot$ and median halo masses of $4.2^{+3.8}_{-2.5}$ and $1.1^{+1.1}_{-0.7}\times10^{12}~M_\odot$ at $z\sim2.4$ and 3.1, respectively. LABs occupy $\sim$11$^{+39}_{-8}$\% and $\sim$3$^{+9}_{-2}$\% of all dark matter halos above these minimum halo masses. These findings suggest that LABs inhabit massive dark matter halos, likely tracing proto-group environments that evolve into present-day massive halos ($\sim$10$^{13}~M_\odot$), where massive elliptical galaxies or galaxy groups reside, by $z=0$.

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Enhancing Lyα Emitter Identification in HETDEX with a Convolutional Neural Network

We present a deep learning framework to enhance the identification of Ly$α$ emitters (LAEs) in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX), an untargeted spectroscopic survey of LAEs at $1.9 < z < 3.5$ without imaging pre-selection. We primarily address the low signal-to-noise ratio (S/N) regime ($4.8 \leq \mathrm{S/N} \leq 5.5$), where LAE candidates suffer from substantial noise contamination. To distinguish LAE candidates from artifacts and sky residuals, we employ a convolutional neural network (CNN) trained on two-dimensional spectral images of single emission lines. The training sample is constructed from the HETDEX COSMOS catalog, with external validation from ancillary observations and our participatory science project, \textit{Dark Energy Explorers}. For small-format, low-resolution spectroscopic data, the model achieves a balanced accuracy, precision, and recall of $94.1\%$, $97.5\%$, and $97.5\%$, respectively, in the high-S/N regime ($\mathrm{S/N}>5.5$), and $85.1\%$, $78.2\%$, and $84.4\%$ in the low-S/N regime. Using HETDEX LAEs independently identified by DESI spectroscopy, the model recovers $99\%$ and $93\%$ of the high- and low-S/N LAEs, respectively. Visual attribution indicates that the CNN attends to smooth, spatially extended central emission in true positives and to irregular or noisy features in true negatives. Applied to the full HETDEX catalog, the CNN enables an S/N threshold down to 4.8 by suppressing spurious spikes across $z\sim 1.9$--$2.5$ in the redshift distribution. Our approach facilitates HETDEX cosmological analyses by mitigating false positives in galaxy clustering and highlights the value of domain-specific deep learning for refining low-S/N spectroscopic identification in untargeted surveys.

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Improved photometric redshift estimations through self-organising map-based data augmentation

We introduce a framework for the enhanced estimation of photometric redshifts using Self-Organising Maps (SOMs). Our method projects galaxy Spectral Energy Distributions (SEDs) onto a two-dimensional map, identifying regions that are sparsely sampled by existing spectroscopic observations. These under-sampled areas are then augmented with simulated galaxies, yielding a more representative spectroscopic training dataset. To assess the efficacy of this SOM-based data augmentation in the context of the forthcoming Legacy Survey of Space and Time (LSST), we employ mock galaxy catalogues from the OpenUniverse2024 project and generate synthetic datasets that mimic the expected photometric selections of LSST after one (Y1) and ten (Y10) years of observation. We construct 501 degraded realisations by sampling galaxy colours, magnitudes, redshifts and spectroscopic success rates, in order to emulate the compilation of a wide array of realistic spectroscopic surveys. Augmenting the degraded mock datasets with simulated galaxies from the independent CosmoDC2 catalogues has markedly improved the performance of our photometric redshift estimates compared to models lacking this augmentation, particularly for high-redshift galaxies ($z_\mathrm{true} \gtrsim 1.5$). This improvement is manifested in notably reduced systematic biases and a decrease in catastrophic failures by up to approximately a factor of 2, along with a reduction in information loss in the conditional density estimations. These results underscore the effectiveness of SOM-based augmentation in refining photometric redshift estimation, thereby enabling more robust analyses in cosmology and astrophysics for the NSF-DOE Vera C. Rubin Observatory.

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Bayesian Component Separation for DESI LAE Automated Spectroscopic Redshifts and Photometric Targeting

Lyman Alpha Emitters (LAEs) are valuable high-redshift cosmological probes traditionally identified using specialized narrow-band photometric surveys. In ground-based spectroscopy, it can be difficult to distinguish the sharp LAE peak from residual sky emission lines using automated methods, leading to misclassified redshifts. We present a Bayesian spectral component separation technique to automatically determine spectroscopic redshifts for LAEs while marginalizing over sky residuals. We use visually inspected spectra of LAEs obtained using the Dark Energy Spectroscopic Instrument (DESI) to create a data-driven prior and can determine redshift by jointly inferring sky residual, LAE, and residual components for each individual spectrum. We demonstrate this method on 881 spectroscopically observed $z = 2-4$ DESI LAE candidate spectra and determine their redshifts with $>$90% accuracy when validated against visually inspected redshifts. Using the $Δχ^2$ value from our pipeline as a proxy for detection confidence, we then explore potential survey design choices and implications for targeting LAEs with medium-band photometry. This method allows for scalability and accuracy in determining redshifts from DESI spectra, and the results provide recommendations for LAE targeting in anticipation of future high-redshift spectroscopic surveys.

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Searching Within Galaxies for the Earliest Signs of Quenching With Spatially Resolved Star Formation Histories in UVCANDELS Galaxies at z< 0.3

Understanding the complicated processes that regulate star formation and cause a galaxy to become quiescent is key to our comprehension of galaxy evolution. We used eight well resolved star-forming z$<$ 0.3 galaxies from the UVCANDELS survey, where a total of 10 HST bands including UV follow up in UVIS/F275W allow us to reconstruct the star formation histories (SFHs) of regions across each galaxy. This approach provides a powerful tool to explore the spatio-temporal connection between star formation and galaxy evolution. The spatial and temporal profiles of stellar mass and star formation rate surface density were obtained from the SFHs of these regions. We measure scaling relations and projected radial profiles of regions within each galaxy at the time of observation and at 1 Gyr lookback time, noting possible trends in the evolution. By comparing the change in star formation over time we can infer the timing and location of star formation and see early signs of star formation shut off before quenching occurs. We compared the star formation rate density -- stellar mass density scaling relations for individual galaxies as they evolve from 1 Gyr lookback time. The correlation lines pivot around a log-stellar mass surface density of 7.25 [$M_\odot$ $kpc^{-2}$] may be evidence of a self-regulating process on these scales. Radial profiles of galaxy Log sSFR show an overall decrease over 1 Gyr, but five galaxies show a greater change in Log sSFR at the outskirts than the center indicating a possible early onset of quenching in these galaxies.

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ODIN: Searching for LyC emission from Lyman-$α$ emitters at $z=4.5$ in the E-COSMOS and XMM-LSS fields

We investigated Lyman-continuum (LyC) emission from Lyman-$α$ emitters (LAEs) at $z=4.5$, identified in the One-hundred-deg$^2$ DECam Imaging in Narrowbands (ODIN) survey. Of the 7,498 LAEs (4,101 in COSMOS and 3,397 in XMM-LSS), we excluded LAEs that are either likely low-z objects or contaminated by neighboring sources. Additional background modeling process with thorough quality assessments leaves a final sample of 851 galaxies. We then performed forced photometry on $u/u^*$-band images from the CFHT large area $u$-band deep survey (CLAUDS) to measure their LyC fluxes. This represents the largest sample of $z=4.5$ LAEs searched for such a purpose. Within this sample, we identified 12 `gold' and 39 `silver' LyC-emitting candidates, with LyC fluxes detected of $>3σ$ and between $2σ$ and $3σ$, respectively, in the range of 5.16--55.29 nJy. No LyC signal is detected in the weighted mean stack of the final sample ($0.20 \pm 0.37$ nJy). Given the UVC magnitudes of LAEs in our sample, the expected LyC emission is likely below the detection limit even when stacking the full sample of ODIN LAEs. Nevertheless, having a large sample of LAEs remains valuable for identifying individual LyC leaker candidates. Among the gold and silver candidates, the LyC flux appears to correlate positively with UVC flux and negatively with Ly$α$ equivalent width, although the correlations are weak. A larger sample of LyC leakers will allow a more robust confirmation of these trends and provide better insights into their physical origins.

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ODIN: Spectroscopic Validation of Ly$α$-Emitting Galaxy Samples with DESI

The One-hundred-deg^2 DECam Imaging in Narrowbands (ODIN) survey is conducting the widest-field deep narrow-band imaging of the equatorial and southern skies. ODIN uses three custom-built narrow-band (NB) filters that sample Lya-emitting galaxies (LAEs) within thin cosmic slices centered at z=2.4, 3.1, and 4.5. In this work, we utilize extensive DESI spectroscopy of ODIN-selected galaxies in the COSMOS and XMM-LSS fields to validate our LAE selection. 2-4 hr exposures with DESI yielded redshift confirmation of 3,075 ODIN LAE candidates with NB magnitudes brighter than 26~mag. Restricting to objects that yield high-confidence redshifts, the confirmation rates are (93, 96, 92)% at z=(2.4, 3.1, 4.5). The primary contaminants consist of active galactic nuclei at the expected Lya redshift range and lower redshifts (C IV, C III]), with the remainder being star-forming galaxies ([O II] and [O III]). We find minimal contamination from [O II] emitters in our sample (<~1%), implying that our REW>20 A narrow-band excess photometry requirement is sufficient to remove them.

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Evolution of submillimeter galaxies across cosmic-web environments

Submillimeter galaxies (SMGs) provide valuable insights into galaxy formation and evolution and are likely influenced by their cosmic environment. However, their rarity makes environmental trends difficult to establish. We use the FLAMINGO simulation, which simultaneously reproduces the redshift distribution and number counts of SMGs. We use the DisPerSE to identify filamentary structures at $z=4$, 3, 2, 1.5, and 1. We define inner cluster-halo, outer cluster-halo, inner filament, outer filament, and void/wall environments at each redshift considering mass evolution of cluster-halos and density evolution of filaments. For a fixed stellar-mass cut of $M_* \geq 10^{9}$ M$_{\odot}$, the fraction of SMGs in the inner cluster-halo environment declines from $\sim30\%$ at $z=4$ to $\sim3\%$ by $z=1$, and similar trends are observed in other environments. The abundance of SMGs within a cluster-halo increases with halo mass, mirroring the increase in the total galaxy population. Consequently, the ratio of SMG halo occupation to that of all galaxies is largely insensitive to halo mass, but varies with redshift. In contrast, the ratio of the halo occupation of non-SMGs to that of all galaxies declines with halo mass and shows little redshift evolution. We show that the central and satellite SMGs form two distinct populations in inner cluster-halos. SMGs occupy the metal-rich side of the metallicity distribution, but rarely attain the highest metallicities because ongoing enrichment is limited by gas depletion. The brightest SMGs (S$_{850} > 10$ mJy) are found exclusively in inner cluster-halos, highlighting a strong connection between SMG luminosity and environmental density. Our results show that SMGs dominate star formation in dense environments, contributing up to $80\%$ of the SFR in inner cluster-halos at $z=4$, but less than $50\%$ in low-density regions.

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Imaging systematics induced by galaxy sub-sample fluctuation: new systematics at second order

Imaging systematics refers to the inhomogeneous distribution of a galaxy sample caused by varying observing conditions and astrophysical foregrounds. Current mitigation methods correct the galaxy density fluctuations caused by imaging systematics assuming that all galaxies in a sample have the same galaxy density fluctuations. Under this assumption, the corrected sample cannot perfectly recover the true correlation function. We name this effect sub-sample systematics. For a galaxy sample, even if its overall sample statistics (redshift distribution n(z), galaxy bias b(z)), are accurately measured, n(z), b(z) can still vary across the observed footprint. It makes the correlation function amplitude of galaxy clustering higher, while correlation functions for galaxy-galaxy lensing and cosmic shear do not have noticeable change. Such a combination could potentially degenerate with physical signals on small angular scales, such as the amplitude of galaxy clustering, the impact of neutrino mass on the matter power spectrum, etc. Sub-sample systematics cannot be corrected using imaging systematics mitigation approaches that rely on the cross-correlation signal between imaging systematics maps and the observed galaxy density field. In this paper, we derive formulated expressions of sub-sample systematics, demonstrating its fundamental difference with other imaging systematics. We also provide several toy models to visualize this effect. Finally, we discuss a potential method to estimate and mitigate sub-sample systematics by forward modeling its behavior using Synthetic Source Injection.

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