Redshift Survey Research Articles

The SRG/eROSITA All-Sky Survey

Superclusters of galaxies mark the large-scale overdense regions in the Universe. Superclusters provide an ideal environment to study structure formation and to search for the emission of the intergalactic medium such as cosmic filaments and WHIM. In this work, we present the largest-to-date catalog of X-ray-selected superclusters identified in the first SRG/eROSITA All-Sky Survey (eRASS1). By applying the Friends-of-Friends (FoF) method on the galaxy clusters detected in eRASS1, we identified 1338 supercluster systems in the western Galactic hemisphere up to redshift 0.8, including 818 cluster pairs and 520 rich superclusters with ≥3 members. The most massive and richest supercluster system is the Shapley supercluster at redshift 0.05 with 45 members and a total mass of 2.58 ± 0.51 × 1016M⊙. The most extensive system has a projected length of 127 Mpc. The sizes of the superclusters we identified in this work are comparable to the structures found with galaxy survey data. We also found a good association between the eRASS1 superclusters and the large-scale structures formed by optical galaxies. We note that 3948 clusters, corresponding to 45% of the cluster sample, were identified as supercluster members. The reliability of each supercluster was estimated by considering the uncertainties in the redshifts of the galaxy clusters and the peculiar velocities of clusters. Furthermore, 63% of the systems have a reliability larger than 0.7. The eRASS1 supercluster catalog provided in this work represents the most extensive sample of superclusters selected in the X-ray band in terms of the unprecedented sample volume, sky coverage, redshift range, the availability of X-ray properties, and the well-understood selection function of the parent cluster sample, which enables direct comparisons with numerical simulations. This legacy catalog will greatly advance our understanding of superclusters and the cosmic large-scale structure.

The DESI One-percent Survey: Evidence for Assembly Bias from Low-redshift Counts-in-cylinders Measurements

We explore the galaxy-halo connection information that is available in low-redshift samples from the early data release of the Dark Energy Spectroscopic Instrument (DESI). We model the halo occupation distribution (HOD) from z = 0.1 to 0.3 using Survey Validation 3 (SV3; a.k.a., the One-Percent Survey) data of the DESI Bright Galaxy Survey. In addition to more commonly used metrics, we incorporate counts-in-cylinders (CiC) measurements, which drastically tighten HOD constraints. Our analysis is aided by the Python package, galtab, which enables the rapid, precise prediction of CiC for any HOD model available in halotools. This methodology allows our Markov chains to converge with much fewer trial points, and enables even more drastic speedups due to its GPU portability. Our HOD fits constrain characteristic halo masses tightly and provide statistical evidence for assembly bias, especially at lower luminosity thresholds: the HOD of central galaxies in z ∼ 0.15 samples with limiting absolute magnitude M r < −20.0 and M r < −20.5 samples is positively correlated with halo concentration with a significance of 99.9% and 99.5%, respectively. Our models also favor positive central assembly bias for the brighter M r < −21.0 sample at z ∼ 0.25 (94.8% significance), but there is no significant evidence for assembly bias with the same luminosity threshold at z ∼ 0.15. We provide our constraints for each threshold sample’s characteristic halo masses, assembly bias, and other HOD parameters. These constraints are expected to be significantly tightened with future DESI data, which will span an area 100 times larger than that of SV3.

The cosmic web from perturbation theory

Context. Analysing the large-scale structure (LSS) in the Universe with galaxy surveys demands accurate structure formation models. Such models should ideally be fast and have a clear theoretical framework in order to rapidly scan a variety of cosmological parameter spaces without requiring large training data sets. Aims. This study aims to extend Lagrangian perturbation theory (LPT), including viscosity and vorticity, to reproduce the cosmic evolution from dark matter N-body calculations at the field level. Methods. We extend LPT to a Eulerian framework, which we dub eALPT. An ultraviolet regularisation through the spherical collapse model provided by Augmented LPT turns out to be crucial at low redshifts. This iterative method enables modelling of the stress tensor and introduces vorticity. The eALPT model has two free parameters apart from the choice of cosmology, redshift snapshots, cosmic volume, and the number of particles. Results. We find that compared to N-body solvers, the cross-correlation of the dark matter distribution increases at k = 1 h Mpc−1 and z = 0 from ∼55% with the Zel’dovich approximation (∼70% with ALPT), to ∼95% with the three-timestep eALPT, and the power spectra show percentage accuracy up to k ≃ 0.3 h Mpc−1.

PROVABGS: The Probabilistic Stellar Mass Function of the BGS One-percent Survey

We present the probabilistic stellar mass function (pSMF) of galaxies in the DESI Bright Galaxy Survey (BGS), observed during the One-percent Survey. The One-percent Survey was one of DESI’s survey validation programs conducted from 2021 April to May, before the start of the main survey. It used the same target selection and similar observing strategy as the main survey and successfully observed the spectra and redshifts of 143,017 galaxies in the r < 19.5 magnitude-limited BGS Bright sample and 95,499 galaxies in the fainter surface-brightness- and color-selected BGS Faint sample over z < 0.6. We derive pSMFs from posteriors of stellar mass, M *, inferred from DESI photometry and spectroscopy using the Hahn et al. PRObabilistic Value-Added BGS (PROVABGS) Bayesian spectral energy distribution modeling framework. We use a hierarchical population inference framework that statistically and rigorously propagates the M * uncertainties. Furthermore, we include correction weights that account for the selection effects and incompleteness of the BGS observations. We present the redshift evolution of the pSMF in BGS, as well as the pSMFs of star-forming and quiescent galaxies classified using average specific star formation rates from PROVABGS. Overall, the pSMFs show good agreement with previous stellar mass function measurements in the literature. Our pSMFs showcase the potential and statistical power of BGS, which in its main survey will observe >100 × more galaxies. Moreover, we present the statistical framework for subsequent population statistics measurements using BGS, which will characterize the global galaxy population and scaling relations at low redshifts with unprecedented precision.

Detecting Anomalous Images in Astronomical Datasets

Environmental and instrumental conditions can cause anomalies in astronomical images, which can potentially bias all kinds of measurements if not excluded. Detection of the anomalous images is usually done by human eyes, which is slow and sometimes not accurate. This is an important issue in weak lensing studies, particularly in the era of large-scale galaxy surveys, in which image qualities are crucial for the success of galaxy shape measurements. In this work we present two automatic methods for detecting anomalous images in astronomical data sets. The anomalous features can be divided into two types: one is associated with the source images, and the other appears on the background. Our first method, called the entropy method, utilizes the randomness of the orientation distribution of the source shapes and the background gradients to quantify the likelihood of an exposure being anomalous. Our second method involves training a neural network (autoencoder) to detect anomalies. We evaluate the effectiveness of the entropy method on the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) and Dark Energy Camera Legacy Survey (DECaLS DR3) data. In CFHTLenS, with 1171 exposures, the entropy method outperforms human inspection by detecting 12 of the 13 anomalous exposures found during human inspection and uncovering 10 new ones. In DECaLS DR3, with 17112 exposures, the entropy method detects a significant number of anomalous exposures while keeping a low false-positive rate. We find that although the neural network performs relatively well in detecting source anomalies, its current performance is not as good as the entropy method.

Topological bias: how haloes trace structural patterns in the cosmic web

ABSTRACT We trace the connectivity of the cosmic web as defined by haloes in the Planck-Millennium simulation using a persistence and Betti curve analysis. We normalize clustering up to the second-order correlation function and use our systematic topological analysis to correlate local information and properties of haloes with their multiscale geometrical environment of the cosmic web (elongated filamentary bridges and sheetlike walls). We capture the multiscale topology traced by the halo distribution through filtrations of the corresponding Delaunay tessellation. The resulting nested alpha shapes are sensitive to the local density, perfectly outline the local geometry, and contain the complete information on the multiscale topology. We find a remarkable linear relationship between halo masses and topology: haloes of different mass trace environments with different topological signature. This is a topological bias, an environmental structure bias independent of the halo clustering bias associated with the two-point correlation function. This mass-dependent linear scaling relation allows us to take clustering into account and determine the overall connectivity from a limited sample of galaxies. The presence of topological bias has major implications for the study of voids and filaments in the observed distribution of galaxies. The (infra)structure and shape of these key cosmic web components will strongly depend on the underlying galaxy sample. Their use as cosmological probes, with their properties influenced by cosmological parameters, will have to account for the subtleties of topological bias. This is of particular relevance with the large upcoming galaxy surveys such as DESI, Euclid, and the Vera Rubin telescope surveys.

Shining light on the hosts of the nano-Hertz gravitational wave sources: a theoretical perspective

ABSTRACT The formation of supermassive black holes (SMBHs) in the Universe and its role in the properties of the galaxies is one of the open questions in astrophysics and cosmology. Though, traditionally, electromagnetic waves have been instrumental in direct measurements of SMBHs, significantly influencing our comprehension of galaxy formation, gravitational waves (GW) bring an independent avenue to detect numerous binary SMBHs in the observable Universe in the nano-Hertz range using the pulsar timing array observation. This brings a new way to understand the connection between the formation of binary SMBHs and galaxy formation if we can connect theoretical models with multimessenger observations namely GW data and galaxy surveys. Along these lines, we present here the first paper on this series based on romulus25 cosmological simulation on the properties of the host galaxies of SMBHs and propose on how this can be used to connect with observations of nano-Hertz GW signal and galaxy surveys. We show that the most dominant contribution to the background will arise from sources with high chirp masses which are likely to reside in low-redshift early-type galaxies with high stellar mass, largely old stellar population, and low star formation rate, and that reside at centres of galaxy groups and manifest evidence of recent mergers. The masses of the sources show a correlation with the halo mass and stellar mass of the host galaxies. This theoretical study will help in understanding the host properties of the GW sources and can help in establishing a connection with observations.

Predicting the ages of galaxies with an artificial neural network

ABSTRACT We present a new method of predicting the ages of galaxies using a machine learning (ML) algorithm with the goal of providing an alternative to traditional methods. We aim to match the ability of traditional models to predict the ages of galaxies by training an artificial neural network (ANN) to recognize the relationships between the equivalent widths of spectral indices and the mass-weighted ages of galaxies estimated by the magphys model in data release 3 (DR3) of the Galaxy and Mass Assembly (GAMA) survey. We discuss the optimization of our hyperparameters extensively and investigate the application of a custom loss function to reduce the influence of errors in our input data. To quantify the quality of our predictions we calculate the mean squared error (MSE), mean absolute error (MAE) and R2 score for which we find MSE = 0.020, MAE = 0.108 and R2 = 0.530. We find our predicted ages have a similar distribution with standard deviation σp = 0.182 compared with the GAMA true ages σt = 0.207. This is achieved in approximately 23 s to train our ANN on an 11th Gen Intel Core i9-11900H running at 2.50 GHz using 32 GB of RAM. We report our results for when light-weighted ages are used to train the ANN, which improves the accuracy of the predictions. Finally, we detail an evaluation of our method relating to physical properties and compare with other ML techniques to encourage future applications of ML techniques in astronomy.

Cosmological evolution of metallicity correlation functions from the Auriga simulations

ABSTRACT We study the cosmological evolution of the two-point correlation functions of galactic gas-phase metal distributions using the 28 simulated galaxies from the Auriga Project. Using mock observations of the z = 0 snapshots to mimic our past work, we show that the correlation functions of the simulated mock observations are well matched to the correlation functions measured from local galaxy surveys. This comparison suggests that the simulations capture the processes important for determining metal correlation lengths, the key parameter in metallicity correlation functions. We investigate the evolution of metallicity correlations over cosmic time using the true simulation data, showing that individual galaxies undergo no significant systematic evolution in their metal correlation functions from z ∼ 3 to today. In addition, the fluctuations in metal correlation length are correlated with but lag ahead fluctuations in star formation rate. This suggests that re-arrangement of metals within galaxies occurs at a higher cadence than star formation activity, and is more sensitive to the changes of environment, such as galaxy mergers, gas inflows/outflows, and fly-bys.

The SAMI galaxy survey: predicting kinematic morphology with logistic regression

ABSTRACT We use the SAMI (Sydney-AAO Multi-object Integral field spectrograph) galaxy survey to study the the kinematic morphology–density relation: the observation that the fraction of slow rotator galaxies increases towards dense environments. We build a logistic regression model to quantitatively study the dependence of kinematic morphology (whether a galaxy is a fast or slow rotator) on a wide range of parameters, without resorting to binning the data. Our model uses a combination of stellar mass, star formation rate (SFR), r-band half-light radius, and a binary variable based on whether the galaxy’s observed ellipticity (ϵ) is less than 0.4. We show that, at fixed mass, size, SFR, and ϵ, a galaxy’s local environmental surface density (log10(Σ5/Mpc−2)) gives no further information about whether a galaxy is a slow rotator, that is, the observed kinematic–morphology density relation can be entirely explained by the well-known correlations between environment and other quantities. We show how our model can be applied to different galaxy surveys to predict the fraction of slow rotators which would be observed and discuss its implications for the formation pathways of slow rotators.

Resolving cosmic star formation histories of present-day bulges, discs, and spheroids with ProFuse

ABSTRACT We present the first look at star formation histories of galaxy components using ProFuse, a new technique to model the 2D distribution of light across multiple wavelengths using simultaneous spectral and spatial fitting of purely imaging data. We present a number of methods to classify galaxies structurally/morphologically, showing the similarities and discrepancies between these schemes. We show the variation in componentwise mass functions that can occur simply due to the use of a different classification method, which is most dramatic in separating bulges and spheroids. Rather than identifying the best-performing scheme, we use the spread of classifications to quantify uncertainty in our results. We study the cosmic star formation history (CSFH), forensically derived using ProFuse with a sample of ∼7000 galaxies from the Galaxy And Mass Assembly survey. Remarkably, the forensic CSFH recovered via both our method (ProFuse) and traditional Spectral Energy Distribution (SED) fitting (ProSpect) are not only exactly consistent with each other over the past 8 Gyr, but also with the in situ CSFH measured using ProSpect. Furthermore, we separate the CSFH by contributions from spheroids, bulges, and discs. While the vast majority (70 per cent) of present-day star formation takes place in the disc population, we show that 50 per cent of the stars that formed at cosmic noon (8–12 Gyr ago) now reside in spheroids, and present-day bulges are composed of stars that were primarily formed in the very early Universe, with half their stars already formed ∼12 Gyr ago.

The SAMI Galaxy Survey: using tidal streams and shells to trace the dynamical evolution of massive galaxies

ABSTRACT Slow rotator galaxies are distinct amongst galaxy populations, with simulations suggesting that a mix of minor and major mergers are responsible for their formation. A promising path to resolve outstanding questions on the type of merger responsible, is by investigating deep imaging of massive galaxies for signs of potential merger remnants. We utilize deep imaging from the Subaru-Hyper Suprime Cam Wide data to search for tidal features in massive [log10(M*/M⊙) &amp;gt; 10] early-type galaxies (ETGs) in the SAMI Galaxy Survey. We perform a visual check for tidal features on images where the galaxy has been subtracted using a Multi-Gauss Expansion (MGE) model. We find that 31$^{+2}_{-2}$ per cent of our sample show tidal features. When comparing galaxies with and without features, we find that the distributions in stellar mass, light-weighted mean stellar population age, and H${\alpha}$ equivalent width are significantly different, whereas spin ($\lambda _{R_{\rm {e}}}$), ellipticity, and bulge-to-total ratio have similar distributions. When splitting our sample in age, we find that galaxies below the median age (10.8 Gyr) show a correlation between the presence of shells and lower $\lambda _{R_{\rm {e}}}$, as expected from simulations. We also find these younger galaxies which are classified as having ‘strong’ shells have lower $\lambda _{R_{\rm {e}}}$. However, simulations suggest that merger features become undetectable within ∼2–4 Gyr post-merger. This implies that the relationship between tidal features and merger history disappears for galaxies with older stellar ages, i.e. those that are more likely to have merged long ago.

Radio-optical synergies at high redshift to constrain primordial non-Gaussianity

We apply the multi-tracer technique to test the possibility of improved constraints on the amplitude of local primordial non-Gaussianity, f_NL, in the cosmic large-scale structure. A precise measurement of f_NL is difficult because the effects of non-Gaussianity mostly arise on the largest scales, which are heavily affected by the low statistical sampling commonly referred to as cosmic variance. The multi-tracer approach suppresses cosmic variance and we implement it by combining the information from next-generation galaxy surveys in the optical/near-infrared band and neutral hydrogen (Hi) intensity mapping surveys in the radio band. High-redshift surveys enhance the precision on f_NL, due to the larger available volume, and Hi intensity mapping surveys can naturally reach high redshifts. In order to extend the redshift coverage of a galaxy survey, we consider different emission-line galaxy populations, focusing on the Hα line at low redshift and on oxygen lines at higher redshift. By doing so, we cover a wide redshift range 1≲ z≲4. To assess the capability of our approach, we implement a synthetic-data analysis by means of Markov chain Monte Carlo sampling of the (cosmological+nuisance) parameter posterior, to evaluate the constraints on f_NL obtained in different survey configurations. We find significant improvements from the multi-tracer technique: the full data set leads to a precision of σ(f_NL)<1.

Taming assembly bias for primordial non-Gaussianity

Primordial non-Gaussianity of the local type induces a strong scale-dependent bias on the clustering of halos in the late-time Universe. This signature is particularly promising to provide constraints on the non-Gaussianity parameter f NL from galaxy surveys, as the bias amplitude grows with scale and becomes important on large, linear scales. However, there is a well-known degeneracy between the real prize, the f NL parameter, and the (non-Gaussian) assembly bias i.e., the halo formation history-dependent contribution to the amplitude of the signal, which could seriously compromise the ability of large-scale structure surveys to constrain f NL. We show how the assembly bias can be modeled and constrained, thus almost completely recovering the power of galaxy surveys to competitively constrain primordial non-Gaussianity. In particular, studying hydrodynamical simulations, we find that a proxy for the halo properties that determine assembly bias can be constructed from photometric properties of galaxies. Using a prior on the assembly bias guided by this proxy degrades the statistical errors on f NL only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on f NL that the proxy induces can be safely kept under control.

The Halos and Environments of Nearby Galaxies (HERON) survey

The shapes of galaxies, their outer regions in particular, are important guideposts to their formation and evolution. In this work, we report on the discovery of strongly box-shaped morphologies of the otherwise well-studied elliptical and lenticular galaxies NGC 720 and NGC 2768 from deep imaging. The boxiness is strongly manifested in the parameter shape A4/a of −0.04 in both objects, and significant center shifts of the isophotes of ∼2–4 kpc are also seen. One reason for such asymmetries commonly stated in the literature is a merger origin, although the number of such cases is still sparse, and the exact properties of the individual boxy objects are highly diverse. Indeed, for NGC 2768, we identify a progenitor candidate (dubbed “Pelops”) in the residual images, which appears to be a dwarf satellite that is currently merging with NGC 2768. At its absolute magnitude of Mr of −12.2 mag, the corresponding Sersic radius of 2.4 kpc is more extended than those of typical dwarf galaxies from the literature. However, systematically larger radii are known to occur in systems that are in tidal disruption. This finding is bolstered by the presence of a tentative tidal stream feature on archival GALEX data. Finally, further structures in the fascinating host galaxy include rich dust lanes and a vestigial X-shaped bulge component.

The Atacama Cosmology Telescope: A Measurement of the DR6 CMB Lensing Power Spectrum and Its Implications for Structure Growth

We present new measurements of cosmic microwave background (CMB) lensing over 9400 deg2 of the sky. These lensing measurements are derived from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) CMB data set, which consists of five seasons of ACT CMB temperature and polarization observations. We determine the amplitude of the CMB lensing power spectrum at 2.3% precision (43σ significance) using a novel pipeline that minimizes sensitivity to foregrounds and to noise properties. To ensure that our results are robust, we analyze an extensive set of null tests, consistency tests, and systematic error estimates and employ a blinded analysis framework. Our CMB lensing power spectrum measurement provides constraints on the amplitude of cosmic structure that do not depend on Planck or galaxy survey data, thus giving independent information about large-scale structure growth and potential tensions in structure measurements. The baseline spectrum is well fit by a lensing amplitude of A lens = 1.013 ± 0.023 relative to the Planck 2018 CMB power spectra best-fit ΛCDM model and A lens = 1.005 ± 0.023 relative to the ACT DR4 + WMAP best-fit model. From our lensing power spectrum measurement, we derive constraints on the parameter combination S8CMBL≡σ8Ωm/0.30.25 of S8CMBL=0.818±0.022 from ACT DR6 CMB lensing alone and S8CMBL=0.813±0.018 when combining ACT DR6 and Planck NPIPE CMB lensing power spectra. These results are in excellent agreement with ΛCDM model constraints from Planck or ACT DR4 + WMAP CMB power spectrum measurements. Our lensing measurements from redshifts z ∼ 0.5–5 are thus fully consistent with ΛCDM structure growth predictions based on CMB anisotropies probing primarily z ∼ 1100. We find no evidence for a suppression of the amplitude of cosmic structure at low redshifts.

The Atacama Cosmology Telescope: DR6 Gravitational Lensing Map and Cosmological Parameters

We present cosmological constraints from a gravitational lensing mass map covering 9400 deg2 reconstructed from measurements of the cosmic microwave background (CMB) made by the Atacama Cosmology Telescope (ACT) from 2017 to 2021. In combination with measurements of baryon acoustic oscillations and big bang nucleosynthesis, we obtain the clustering amplitude σ 8 = 0.819 ± 0.015 at 1.8% precision, S8≡σ8(Ωm/0.3)0.5=0.840±0.028 , and the Hubble constant H 0 = (68.3 ± 1.1) km s−1 Mpc−1 at 1.6% precision. A joint constraint with Planck CMB lensing yields σ 8 = 0.812 ± 0.013, S8≡σ8(Ωm/0.3)0.5=0.831±0.023 , and H 0 = (68.1 ± 1.0) km s−1 Mpc−1. These measurements agree with ΛCDM extrapolations from the CMB anisotropies measured by Planck. We revisit constraints from the KiDS, DES, and HSC galaxy surveys with a uniform set of assumptions and find that S 8 from all three are lower than that from ACT+Planck lensing by levels ranging from 1.7σ to 2.1σ. This motivates further measurements and comparison, not just between the CMB anisotropies and galaxy lensing but also between CMB lensing probing z ∼ 0.5–5 on mostly linear scales and galaxy lensing at z ∼ 0.5 on smaller scales. We combine with CMB anisotropies to constrain extensions of ΛCDM, limiting neutrino masses to ∑m ν < 0.13 eV (95% c.l.), for example. We describe the mass map and related data products that will enable a wide array of cross-correlation science. Our results provide independent confirmation that the universe is spatially flat, conforms with general relativity, and is described remarkably well by the ΛCDM model, while paving a promising path for neutrino physics with lensing from upcoming ground-based CMB surveys.

The EDGE-CALIFA Survey: Molecular Gas and Star Formation Activity across the Green Valley

We present a 12CO(J = 2−1) survey of 60 local galaxies using data from the Atacama Compact Array as part of the Extragalactic Database for Galaxy Evolution: the ACA EDGE survey. These galaxies all have integral field spectroscopy from the CALIFA survey. Compared to other local galaxy surveys, ACA EDGE is designed to mitigate selection effects based on CO brightness and morphological type. Of the 60 galaxies in ACA EDGE, 36 are on the star formation main sequence, 13 are on the red sequence, and 11 lie in the “green valley” transition between these sequences. We test how star formation quenching processes affect the star formation rate (SFR) per unit molecular gas mass, SFEmol = SFR/M mol, and related quantities in galaxies with stellar masses 10 ≤ log[M ⋆/M ⊙] ≤ 11.5 covering the full range of morphological types. We observe a systematic decrease of the molecular-to-stellar mass fraction ( R⋆mol ) with a decreasing level of star formation activity, with green valley galaxies also having lower SFEmol than galaxies on the main sequence. On average, we find that the spatially resolved SFEmol within the bulge region of green valley galaxies is lower than in the bulges of main-sequence galaxies if we adopt a constant CO-to-H2 conversion factor, α CO. While efficiencies in main-sequence galaxies remain almost constant with galactocentric radius, in green valley galaxies, we note a systematic increase of SFEmol, R⋆mol , and specific SFR with increasing radius. As shown in previous studies, our results suggest that although gas depletion (or removal) seems to be the most important driver of the star formation quenching in galaxies transiting through the green valley, a reduction in star formation efficiency is also required during this stage.

Accurate Fourier-space statistics for line intensity mapping: Cartesian grid sampling without aliased power

ABSTRACT Estimators for n-point clustering statistics in Fourier-space demand that modern surveys of large-scale structure be transformed to Cartesian coordinates to perform Fast Fourier Transforms (FFTs). In this work, we explore this transformation in the context of pixelized line intensity maps (LIM), highlighting potential biasing effects on power-spectrum measurements. Current analyses often avoid a complete resampling of the data by approximating survey geometry as rectangular in Cartesian space, an increasingly inaccurate assumption for modern wide-sky surveys. Our simulations of a $20\, {\times }\, 20\, \text{deg}^2$ 21 cm LIM survey at $0.34\, {\lt }\, z\, {\lt }\, 0.54$ show this assumption biases power-spectrum measurements by ${\gt }\, 20~{{\ \rm per\ cent}}$ across all scales. We therefore present a more robust framework for regridding the voxel intensities on to a 3D FFT field by coordinate transforming large numbers of Monte-Carlo sampling particles. Whilst this unbiases power-spectrum measurements on large scales, smaller scale discrepancies remain, caused by structure smoothing and aliasing from separations unresolved by the grid. To correct these effects, we introduce modelling techniques, higher order particle assignments, and interlaced FFT grids to suppress the aliased power. Using a piecewise cubic spline (PCS) particle assignment and an interlaced FFT field, we achieve sub-per cent accuracy up to 80 per cent of the Nyquist frequency for our 21 cm LIM simulations. We find a more subtle hierarchical improvement in results for higher order assignment schemes, relative to the gains made for galaxy surveys, which we attribute to the extra complexity in LIM from additional discretizing steps. python code accompanying this paper is available at github.com/stevecunnington/gridimp.

Classifying Intermediate-redshift Galaxies in SDSS: Alternative Diagnostic Diagrams

We select a sample of 1437 active galactic nuclei (AGN) from the catalog of the Sloan Digital Sky Survey galaxy properties from the Portsmouth group by detection of the high-ionization [Ne v] 3426 Å emission line. We compare the fluxes of [Ne III] 3869 Å, [O III] 5007 Å, [O II] 3726, 3728 Å, and [O i] 6300 Å to that of [Ne v]. All four lines show a strong linear correlation with [Ne v], although lines from ions with lower ionization potentials have a lower correlation coefficient. We investigate the use of two forbidden line ratio diagnostic diagrams that do not rely on Hα in order to classify high-redshift galaxies. These use the [Ne III]/[O II] line ratio plotted against [O III]/[O i] and [O III]/[O II], respectively. We use photoionization modeling to characterize the behavior of the narrow-line region in AGN and star-forming regions and test the validity of our diagnostic diagrams. We also use a luminosity cutoff of log L [O III] [erg s−1] = 42, which lowers the contamination of the AGN region by star-forming galaxies down to 10% but does not remove green pea and purple grape galaxies from the AGN region. We also investigate the OHNO diagram, which uses [Ne III]/[O II] plotted against [O III]/Hβ. Using our new diagnostic diagrams, we are able to reliably classify AGN up to a redshift of z ≤ 1.06 and add more than 822 new AGN to the [Ne v]-selected AGN sample.