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Evaluating the accuracy and calibration of the redshift posteriors produced by photometric redshift (photo-z) estimators is vital for enabling precision cosmology and extragalactic astrophysics with modern wide-field photometric surveys. Evaluating photo-z posteriors on a per-galaxy basis is difficult, however, as real galaxies have a true redshift but not a true redshift posterior. We introduce PZFlow, a Python package for the probabilistic forward modeling of galaxy catalogs with normalizing flows. For catalogs simulated with PZFlow, there is a natural notion of "true" redshift posteriors that can be used for photo-z validation. We use PZFlow to simulate a photometric galaxy catalog where each galaxy has a redshift, noisy photometry, shape information, and a true redshift posterior. We also demonstrate the use of an ensemble of normalizing flows for photo-z estimation. We discuss how PZFlow will be used to validate the photo-z estimation pipeline of the Dark Energy Science Collaboration (DESC), and the wider applicability of PZFlow for statistical modeling of any tabular data., Comment: 19 pages, 13 figures, submitted to AJ

A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data from other telescopes. This white paper focuses in particular on the compelling benefits of ground-based spectroscopic and photometric observations to complement the Vera C. Rubin Observatory, as well as smaller programs in aid of a DESI-2 experiment and CMB-S4. These additional data sets will both improve dark energy constraints from these flagship projects beyond what would possible on their own and open completely new windows into fundamental physics. For example, additional photometry and single-object spectroscopy will provide necessary follow-up information for supernova and strong lensing cosmology, while highly-multiplexed spectroscopy both from smaller facilities over wide fields and from larger facilities over narrower regions of sky will yield more accurate photometric redshift estimates for weak lensing and galaxy clustering measurements from the Rubin Observatory, provide critical spectroscopic host galaxy redshifts for supernova Hubble diagrams, provide improved understanding of limiting astrophysical systematic effects, and enable new measurements that probe the nature of gravity. A common thread is that access to complementary data from a range of telescopes/instruments would have a substantial impact on the rate of advance of dark energy science in the coming years., Comment: White paper submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021)

Upcoming deep imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time will be confronted with challenges that come with increased depth. One of the leading systematic errors in deep surveys is the blending of objects due to higher surface density in the more crowded images; a considerable fraction of the galaxies which we hope to use for cosmology analyses will overlap each other on the observed sky. In order to investigate these challenges, we emulate blending in a mock catalogue consisting of galaxies at a depth equivalent to 1.3 yr of the full 10-yr Rubin Observatory that includes effects due to weak lensing, ground-based seeing, and the uncertainties due to extraction of catalogues from imaging data. The emulated catalogue indicates that approximately 12 per cent of the observed galaxies are ``unrecognized'' blends that contain two or more objects but are detected as one. Using the positions and shears of half a billion distant galaxies, we compute shear--shear correlation functions after selecting tomographic samples in terms of both spectroscopic and photometric redshift bins. We examine the sensitivity of the cosmological parameter estimation to unrecognized blending employing both jackknife and analytical Gaussian covariance estimators. An $\sim0.025$ decrease in the derived structure growth parameter $S_8 = \sigma_8 (\Omega_{\rm m}/0.3)^{0.5}$ is seen due to unrecognized blending in both tomographies with a slight additional bias for the photo-$z$-based tomography. This bias is greater than the $2\sigma$ statistical error in measuring $S_8$., Comment: Published version with a typo fixed

Recent works have shown that weak lensing magnification must be included in upcoming large-scale structure analyses, such as for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), to avoid biasing the cosmological results. In this work we investigate whether including magnification has a positive impact on the precision of the cosmological constraints, as well as being necessary to avoid bias. We forecast this using an LSST mock catalog and a halo model to calculate the galaxy power spectra. We find that including magnification has little effect on the precision of the cosmological parameter constraints for an LSST galaxy clustering analysis, where the halo model parameters are additionally constrained by the galaxy luminosity function. In particular, we find that for the LSST gold sample ($i < 25.3$) including weak lensing magnification only improves the galaxy clustering constraint on $\Omega_{\rm{m}}$ by a factor of 1.03, and when using a very deep LSST mock sample ($i<26.5$) by a factor of 1.3. Since magnification predominantly contributes to the clustering measurement and provides similar information to that of cosmic shear, this improvement would be reduced for a combined galaxy clustering and shear analysis. We also confirm that not modelling weak lensing magnification will catastrophically bias the cosmological results from LSST. Magnification must therefore be included in LSST large-scale structure analyses even though it does not significantly enhance the precision of the cosmological constraints., Comment: v2: Version accepted in MNRAS. Minor clarifications, conclusions unchanged

Systematic errors in the galaxy redshift distribution $n(z)$ can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy-galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter $S_8 \equiv \sigma_8 (\Omega_m/.3)^{1/2}$ goes from $.841^{+0.062}_{-.061}$ to $.739^{+.054}_{-.050}$ upon correcting the n(z) errors in the second method., Comment: 13 pages, 9 figures

In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg$^2$ simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository., Comment: 25 pages, 3 figures; 9 tables. A detailed changelog can be found in Appendix A. To obtain data, visit the DESC Data Portal at https://data.lsstdesc.org/

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology., Comment: 39 pages, 19 figures, version accepted for publication in ApJS

Accurate photometric redshift (photo-$z$) estimates are essential to the cosmological science goals of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). In this work we use simulated photometry for mock galaxy catalogs to explore how LSST photo-$z$ estimates can be improved by the addition of near-infrared (NIR) and/or ultraviolet (UV) photometry from the Euclid, WFIRST, and/or CASTOR space telescopes. Generally, we find that deeper optical photometry can reduce the standard deviation of the photo-$z$ estimates more than adding NIR or UV filters, but that additional filters are the only way to significantly lower the fraction of galaxies with catastrophically under- or over-estimated photo-$z$. For Euclid, we find that the addition of ${JH}$ $5{\sigma}$ photometric detections can reduce the standard deviation for galaxies with $z>1$ ($z>0.3$) by ${\sim}20\%$ (${\sim}10\%$), and the fraction of outliers by ${\sim}40\%$ (${\sim}25\%$). For WFIRST, we show how the addition of deep ${YJHK}$ photometry could reduce the standard deviation by ${\gtrsim}50\%$ at $z>1.5$ and drastically reduce the fraction of outliers to just ${\sim}2\%$ overall. For CASTOR, we find that the addition of its ${UV}$ and $u$-band photometry could reduce the standard deviation by ${\sim}30\%$ and the fraction of outliers by ${\sim}50\%$ for galaxies with $z<0.5$. We also evaluate the photo-$z$ results within sky areas that overlap with both the NIR and UV surveys, and when spectroscopic training sets built from the surveys' small-area deep fields are used., Comment: 21 pages, 16 figures, 4 tables, accepted to AJ

Community access to deep (i ~ 25), highly-multiplexed optical and near-infrared multi-object spectroscopy (MOS) on 8-40m telescopes would greatly improve measurements of cosmological parameters from LSST. The largest gain would come from improvements to LSST photometric redshifts, which are employed directly or indirectly for every major LSST cosmological probe; deep spectroscopic datasets will enable reduced uncertainties in the redshifts of individual objects via optimized training. Such spectroscopy will also determine the relationship of galaxy SEDs to their environments, key observables for studies of galaxy evolution. The resulting data will also constrain the impact of blending on photo-z's. Focused spectroscopic campaigns can also improve weak lensing cosmology by constraining the intrinsic alignments between the orientations of galaxies. Galaxy cluster studies can be enhanced by measuring motions of galaxies in and around clusters and by testing photo-z performance in regions of high density. Photometric redshift and intrinsic alignment studies are best-suited to instruments on large-aperture telescopes with wider fields of view (e.g., Subaru/PFS, MSE, or GMT/MANIFEST) but cluster investigations can be pursued with smaller-field instruments (e.g., Gemini/GMOS, Keck/DEIMOS, or TMT/WFOS), so deep MOS work can be distributed amongst a variety of telescopes. However, community access to large amounts of nights for surveys will still be needed to accomplish this work. In two companion white papers we present gains from shallower, wide-area MOS and from single-target imaging and spectroscopy., Comment: Science white paper submitted to the Astro2020 decadal survey. A table of time requirements is available at http://d-scholarship.pitt.edu/36036/

LSST will open new vistas for cosmology in the next decade, but it cannot reach its full potential without data from other telescopes. Cosmological constraints can be greatly enhanced using wide-field ($>20$ deg$^2$ total survey area), highly-multiplexed optical and near-infrared multi-object spectroscopy (MOS) on 4-15m telescopes. This could come in the form of suitably-designed large surveys and/or community access to add new targets to existing projects. First, photometric redshifts can be calibrated with high precision using cross-correlations of photometric samples against spectroscopic samples at $0 < z < 3$ that span thousands of sq. deg. Cross-correlations of faint LSST objects and lensing maps with these spectroscopic samples can also improve weak lensing cosmology by constraining intrinsic alignment systematics, and will also provide new tests of modified gravity theories. Large samples of LSST strong lens systems and supernovae can be studied most efficiently by piggybacking on spectroscopic surveys covering as much of the LSST extragalactic footprint as possible (up to $\sim20,000$ square degrees). Finally, redshifts can be measured efficiently for a high fraction of the supernovae in the LSST Deep Drilling Fields (DDFs) by targeting their hosts with wide-field spectrographs. Targeting distant galaxies, supernovae, and strong lens systems over wide areas in extended surveys with (e.g.) DESI or MSE in the northern portion of the LSST footprint or 4MOST in the south could realize many of these gains; DESI, 4MOST, Subaru/PFS, or MSE would all be well-suited for DDF surveys. The most efficient solution would be a new wide-field, highly-multiplexed spectroscopic instrument in the southern hemisphere with $>6$m aperture. In two companion white papers we present gains from deep, small-area MOS and from single-target imaging and spectroscopy., Comment: Submitted to the call for Astro2020 science white papers; tables with estimates of telescope time needed for a supernova host survey can be seen at http://d-scholarship.pitt.edu/id/eprint/36041

We develop an improved sky background estimator which employs optimal filters for both spatial and pixel intensity distributions. It incorporates growth of masks around detected objects and a statistical estimate of the flux from undetected faint galaxies in the remaining sky pixels. We test this algorithm for underlying sky estimation and compare its performance with commonly used sky estimation codes on realistic simulations which include detected galaxies, faint undetected galaxies, and sky noise. We then test galaxy surface brightness recovery using GALFIT 3, a galaxy surface brightness profile fitting optimizer, yielding fits to S\'{e}rsic profiles. This enables robust sky background estimates accurate at the 4 parts-per-million level. This background sky estimator is more accurate and is less affected by surface brightness profiles of galaxies and the local image environment compared with other methods., Comment: 16 pages, 7 figures, 1 table, accepted by PASP

The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of galaxies, dark matter, and black holes over cosmic time. The LSST Galaxies Science Collaboration has identified a host of preparatory research tasks required to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. This Galaxies Science Roadmap provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The Galaxies Science Roadmap will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era., Comment: For more information, see https://galaxies.science.lsst.org

In this paper we present and characterize a nearest-neighbors color-matching photometric redshift estimator that features a direct relationship between the precision and accuracy of the input magnitudes and the output photometric redshifts. This aspect makes our estimator an ideal tool for evaluating the impact of changes to LSST survey parameters that affect the measurement errors of the photometry, which is the main motivation of our work (i.e., it is not intended to provide the "best" photometric redshifts for LSST data). We show how the photometric redshifts will improve with time over the 10-year LSST survey and confirm that the nominal distribution of visits per filter provides the most accurate photo-$z$ results. The LSST survey strategy naturally produces observations over a range of airmass, which offers the opportunity of using an SED- and $z$-dependent atmospheric affect on the observed photometry as a color-independent redshift indicator. We show that measuring this airmass effect and including it as a prior has the potential to improve the photometric redshifts and can ameliorate extreme outliers, but that it will only be adequately measured for the brightest galaxies, which limits its overall impact on LSST photometric redshifts. We furthermore demonstrate how this airmass effect can induce a bias in the photo-$z$ results, and caution against survey strategies that prioritize high-airmass observations for the purpose of improving this prior. Ultimately, we intend for this work to serve as a guide for the expectations and preparations of the LSST science community with regards to the minimum quality of photo-$z$ as the survey progresses., Comment: 25 pages, 16 figures, 2 tables, accepted to AJ

We present The-wiZZ, an open source and user-friendly software for estimating the redshift distributions of photometric galaxies with unknown redshifts by spatially cross-correlating them against a reference sample with known redshifts. The main benefit of The-wiZZ is in separating the angular pair finding and correlation estimation from the computation of the output clustering redshifts allowing anyone to create a clustering redshift for their sample without the intervention of an "expert". It allows the end user of a given survey to select any sub-sample of photometric galaxies with unknown redshifts, match this sample's catalog indices into a value-added data file, and produce a clustering redshift estimation for this sample in a fraction of the time it would take to run all the angular correlations needed to produce a clustering redshift. We show results with this software using photometric data from the Kilo-Degree Survey (KiDS) and spectroscopic redshifts from the Galaxy and Mass Assembly (GAMA) survey and the Sloan Digital Sky Survey (SDSS). The results we present for KiDS are consistent with the redshift distributions used in a recent cosmic shear analysis from the survey. We also present results using a hybrid machine learning-clustering redshift analysis that enables the estimation of clustering redshifts for individual galaxies. The-wiZZ can be downloaded at http://github.com/morriscb/The-wiZZ/., Comment: 16 pages, 8 figures, accepted to MNRAS

We apply clustering-based redshift inference to all extended sources from the Sloan Digital Sky Survey photometric catalogue, down to magnitude r = 22. We map the relationships between colours and redshift, without assumption of the sources' spectral energy distributions (SED). We identify and locate star-forming, quiescent galaxies, and AGN, as well as colour changes due to spectral features, such as the 4000 \AA{} break, redshifting through specific filters. Our mapping is globally in good agreement with colour-redshift tracks computed with SED templates, but reveals informative differences, such as the need for a lower fraction of M-type stars in certain templates. We compare our clustering-redshift estimates to photometric redshifts and find these two independent estimators to be in good agreement at each limiting magnitude considered. Finally, we present the global clustering-redshift distribution of all Sloan extended sources, showing objects up to z ~ 0.8. While the overall shape agrees with that inferred from photometric redshifts, the clustering redshift technique results in a smoother distribution, with no indication of structure in redshift space suggested by the photometric redshift estimates (likely artifacts imprinted by their spectroscopic training set). We also infer a higher fraction of high redshift objects. The mapping between the four observed colours and redshift can be used to estimate the redshift probability distribution function of individual galaxies. This work is an initial step towards producing a general mapping between redshift and all available observables in the photometric space, including brightness, size, concentration, and ellipticity., Comment: 12 pages, 9 figures, accepted to MNRAS

This white paper summarizes the conclusions of the Snowmass White Paper "Spectroscopic Needs for Imaging Dark Energy Experiments" (arXiv:1309.5384) which are relevant to the calibration of LSST photometric redshifts; i.e., the accurate characterization of biases and uncertainties in photo-z's. Any significant miscalibration will lead to systematic errors in photo-z's, impacting nearly all extragalactic science with LSST. As existing deep redshift samples have failed to yield highly-secure redshifts for a systematic 20%-60% of their targets, it is a strong possibility that future deep spectroscopic samples will not solve the calibration problem on their own. The best options in this scenario are provided by cross-correlation methods that utilize clustering with objects from spectroscopic surveys (which need not be fully representative) to trace the redshift distribution of the full sample. For spectroscopy, the eBOSS survey would enable a basic calibration of LSST photometric redshifts, while the expected LSST-DESI overlap would be more than sufficient for an accurate calibration at z>0.2. A DESI survey of nearby galaxies conducted in bright time would enable accurate calibration down to z~0. The expanded areal coverage provided by the transfer of the DESI instrument (or duplication of it at the Blanco Telescope) would enable the best possible calibration from cross-correlations, in addition to other science gains., Comment: White paper submitted to the National Research Council Committee on a Strategy Optimize the U.S. O/IR System in the Era of the LSST, 4 pages

This white paper summarizes those conclusions of the Snowmass White Paper "Spectroscopic Needs for Imaging Dark Energy Experiments" (arXiv:1309.5384) which are relevant to the training of LSST photometric redshifts; i.e., the use of spectroscopic redshifts to improve algorithms and reduce photo-z errors. The larger and more complete the available training set is, the smaller the RMS error in photo-z estimates should be, increasing LSST's constraining power. Among the better US-based options for this work are the proposed MANIFEST fiber feed for the Giant Magellan Telescope or (with lower survey speed) the WFOS spectrograph on the Thirty Meter Telescope (TMT). Due to its larger field of view and higher multiplexing, the PFS spectrograph on Subaru would be able to obtain a baseline training sample faster than TMT; comparable performance could be achieved with a highly-multiplexed spectrograph on Gemini with at least a 20 arcmin diameter field of view., Comment: White paper submitted to the National Research Council Committee on a Strategy Optimize the U.S. O/IR System in the Era of the LSST, 5 pages

We investigate the potential and accuracy of clustering-based redshift estimation using the method proposed by M\'enard et al. (2013). This technique enables the inference of redshift distributions from measurements of the spatial clustering of arbitrary sources, using a set of reference objects for which redshifts are known. We apply it to a sample of spectroscopic galaxies from the Sloan Digital Sky Survey and show that, after carefully controlling the sampling efficiency over the sky, we can estimate redshift distributions with high accuracy. Probing the full colour space of the SDSS galaxies, we show that we can recover the corresponding mean redshifts with an accuracy ranging from $\delta$z=0.001 to 0.01. We indicate that this mapping can be used to infer the redshift probability distribution of a single galaxy. We show how the lack of information on the galaxy bias limits the accuracy of the inference and show comparisons between clustering redshifts and photometric redshifts for this dataset. This analysis demonstrates, using real data, that clustering-based redshift inference provides a powerful data-driven technique to explore the redshift distribution of arbitrary datasets, without any prior knowledge on the spectral energy distribution of the sources., Comment: 13 pages. Submitted to MNRAS. Comments welcome

Cross-correlating the Planck High Frequency Instrument (HFI) maps against quasars from the Sloan Digital Sky Survey (SDSS) DR7, we estimate the intensity distribution of the Cosmic Infrared Background (CIB) over the redshift range 0 < z < 5.We detect redshift-dependent spatial cross-correlations between the two datasets using the 857, 545 and 353 GHz channels and we obtain upper limits at 217 GHz consistent with expectations. At all frequencies with detectable signal we infer a redshift distribution peaking around z ~ 1.2 and find the recovered spectrum to be consistent with emission arising from star forming galaxies. By assuming simple modified blackbody and Kennicutt relations, we estimate dust and star formation rate density as a function of redshift, finding results consistent with earlier multiwavelength measurements over a large portion of cosmic history. However, we note that, lacking mid-infrared coverage, we are not able to make an accurate determination of the mean temperature for the dust responsible for the CIB. Our results demonstrate that clustering-based redshift inference is a valuable tool for measuring the entire evolution history of the cosmic star formation rate from a single and homogeneous dataset., Comment: 14 pages, 10 figures, published in MNRAS. Some revisions and an additional figure added since version 1

Wide, deep photometric surveys require robust photometric redshift estimates (photo-z's) for studies of large-scale structure. These estimates depend critically on accurate photometry. We describe the improvements to the photometric calibration and the photo-z estimates in the Deep Lens Survey (DLS) from correcting three of the inputs to the photo-z calculation: the system response as a function of wavelength, the spectral energy distribution templates, and template prior probabilities as a function of magnitude. We model the system response with a physical model of the MOSAIC camera's CCD, which corrects a 0.1 magnitude discrepancy in the colours of type M2 and later stars relative to the SDSS z-band photometry. We provide our estimated z-band response function for the use of other surveys that used MOSAIC before its recent detector upgrade. The improved throughput curve, template set, and Bayesian prior lead to a 20 per cent reduction in photo-z scatter and a reduction of the bias by a factor of more than two. This paper serves as both a photo-z data release description for DLS and a guide for testing the quality of photometry and resulting photo-z's generally., Comment: 13 pages, 10 figures, submitted to MNRAS. Updated MOSAIC z-band filter curve available as an electronic attachment (MOSAIC_z_Thorman.txt). To retrieve filter, download and extract the gzipped tar source file listed under "Other formats"

We examine the projected correlation of galaxies with mass from small scales (

Using about 450,000 galaxies in the Deep Lens Survey, we present a detection of the gravitational magnification of z > 4 Lyman Break Galaxies by massive foreground galaxies with 0.4 < z < 1.0, grouped by redshift. The magnification signal is detected at S/N greater than 20, and rigorous checks confirm that it is not contaminated by any galaxy sample overlap in redshift. The inferred galaxy mass profiles are consistent with earlier lensing analyses at lower redshift. We then explore the tomographic lens magnification signal by splitting our foreground galaxy sample into 7 redshift bins. Combining galaxy-magnification cross-correlations and galaxy angular auto-correlations, we develop a bias-independent estimator of the tomographic signal. As a diagnostic of magnification tomography, the measurement of this estimator rejects a flat dark matter dominated Universe at > 7.5{\sigma} with a fixed \sigma_8 and is found to be consistent with the expected redshift-dependence of the WMAP7 {\Lambda}CDM cosmology., Comment: 12 pages, 9 figures, Accepted to MNRAS

We present the results of a study of a sample of 375 Extremely Red Galaxies (ERGs) in the Phoenix Deep Survey, 273 of which constitute a subsample which is 80% complete to K_s = 18.5 over an area of 1160 arcmin^2. The angular correlation function for ERGs is estimated, and the association of ERGs with faint radio sources explored. We find tentative evidence that ERGs and faint radio sources are associated at z > 0.5. A new overdensity-mapping algorithm has been used to characterize the ERG distribution, and identify a number of cluster candidates, including a likely cluster containing ERGs at 0.5 < z < 1. Our algorithm is also used in an attempt to probe the environments in which faint radio sources and ERGs are associated. We find limited evidence that the I - K_s > 4 criterion is more efficient than R - K_s > 5 at selecting dusty star-forming galaxies, rather than passively evolving ERGs., Comment: 14 emulateapj pages, 15 figures, 1 table, accepted for publication in Astronomical Journal. A version with full resolution figures is available at http://www.physics.usyd.edu.au/~asmith/research/ERGpaper.pdf

We analyze the photometric information contained in individual pixels of galaxies in the Hubble Deep Field North (HDFN) using a new technique, _pixel-z_, that combines predictions of evolutionary synthesis models with photometric redshift template fitting. Each spectral energy distribution template is a result of modeling of the detailed physical processes affecting gas properties and star formation efficiency. The criteria chosen to generate the SED templates is that of sampling a wide range of physical characteristics such as age, star formation rate, obscuration and metallicity. A key feature of our method is the sophisticated use of error analysis to generate error maps that define the reliability of the template fitting on pixel scales and allow for the separation of the interplay among dust, metallicity and star formation histories. This technique offers a number of advantages over traditional integrated color studies. As a first application, we derive the star formation and metallicity histories of galaxies in the HDFN. Our results show that the comoving density of star formation rate, determined from the UV luminosity density of sources in the HDFN, increases monotonically with redshift out to at least redshift of 5. This behavior can plausibly be explained by a smooth increase of the UV luminosity density with redshift coupled with an increase in the number of star forming regions as a function of redshift. We also find that the information contained in individual pixels in a galaxy can be linked to its morphological history. Finally, we derive the metal enrichment rate history of the universe and find it in good agreement with predictions based on the evolving HI content of Lyman-alpha QSO absorption line systems., Comment: Accepted for publication in the Astronomical Journal. Full resolution figures available at http://www.stsci.edu/~aconti/pixelz.html