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At least 343 records · Page 19

The SAGA Survey. II. Building a Statistical Sample of Satellite Systems around Milky Way–like Galaxies

In this work, we present the Stage II results from the ongoing Satellites Around Galactic Analogs (SAGA) Survey. Upon completion, the SAGA Survey will spectroscopically identify satellite galaxies brighter than M r,o = -12.3 around 100 Milky Way (MW) analogs at z ~ 0.01. In Stage II, we have more than quadrupled the sample size of Stage I, delivering results from 127 satellites around 36 MW analogs with an improved target selection strategy and deep photometric imaging catalogs from the Dark Energy Survey and the Legacy Surveys. We have obtained 25,372 galaxy redshifts, peaking around z = 0.2. These data significantly increase spectroscopic coverage for very low redshift objects in 17 < r o < 20.75 around SAGA hosts, creating a unique data set that places the Local Group in a wider context. The number of confirmed satellites per system ranges from zero to nine and correlates with host galaxy and brightest satellite luminosities. We find that the number and luminosities of MW satellites are consistent with being drawn from the same underlying distribution as SAGA systems. The majority of confirmed SAGA satellites are star-forming, and the quenched fraction increases as satellite stellar mass and projected radius from the host galaxy decrease. Overall, the satellite quenched fraction among SAGA systems is lower than that in the Local Group. We compare the luminosity functions and radial distributions of SAGA satellites with theoretical predictions based on cold dark matter simulations and an empirical galaxy–halo connection model and find that the results are broadly in agreement.

79 ASTRONOMY AND ASTROPHYSICS↗

Transient Radio Emission from Low-redshift Galaxies at z < 0.3 Revealed by the VLASS and FIRST Surveys

We present the discovery of a sample of 18 low-redshift (z < 0.3) galaxies with transient nuclear radio emission. These galaxies are not detected or are weakly detected in the Faint Images of the Radio Sky at Twenty cm survey, performed from 1993–2009, but have brightened significantly in radio flux (by a factor of ≳5) in the epoch I (2017–2019) observations of the Very Large Array Sky Survey (VLASS). All 18 galaxies have been detected in VLASS epoch II observations, from 2020–2021, from which the radio flux has been found to evolve slowly (with variability amplitudes of ≳40%) over a period of about 3 yr. 15 galaxies have been observed in the Rapid ASKAP Continuum Survey, and a flat or inverted spectral slope between 888 MHz and 3 GHz is found. Based on the Sloan Digital Sky Survey spectra taken before the radio brightening, 14 of the 18 galaxies can be classified as LINERs or normal galaxies with weak or no nuclear activity. Most galaxies are red and massive, with more than half having central black hole masses above 10 8 M ⊙ . We find that only one galaxy in our sample displays an optical flare lasting for at least two months, with a long decay in the infrared light curve that can be explained as the dust-heated echo emission of a central optical flare, such as a stellar tidal disruption event. We discuss several possibilities for the transient radio emission and conclude that it is likely associated with a newborn radio jet triggered by short sporadic fueling of a supermassive black hole. Such a scenario can be tested with further multifrequency radio observations of these sources, via measuring their radio flux variability and spectral evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Tuning the Legacy Survey of Space and Time (LSST) Observing Strategy for Solar System Science

Abstract The Vera C. Rubin Observatory is expected to start the Legacy Survey of Space and Time (LSST) in early to mid-2025. This multiband wide-field synoptic survey will transform our view of the solar system, with the discovery and monitoring of over five million small bodies. The final survey strategy chosen for LSST has direct implications on the discoverability and characterization of solar system minor planets and passing interstellar objects. Creating an inventory of the solar system is one of the four main LSST science drivers. The LSST observing cadence is a complex optimization problem that must balance the priorities and needs of all the key LSST science areas. To design the best LSST survey strategy, a series of operation simulations using the Rubin Observatory scheduler have been generated to explore the various options for tuning observing parameters and prioritizations. We explore the impact of the various simulated LSST observing strategies on studying the solar system’s small body reservoirs. We examine what are the best observing scenarios and review what are the important considerations for maximizing LSST solar system science. In general, most of the LSST cadence simulations produce ±5% or less variations in our chosen key metrics, but a subset of the simulations significantly hinder science returns with much larger losses in the discovery and light-curve metrics.

79 ASTRONOMY AND ASTROPHYSICS↗

PSTN-053: Survey Cadence Optimization Committee's Phase 1 Recommendations

This document is authored by the Survey Cadence Optimization Committee (SCOC), guided by the community input, and it will serve as a roadmap for the concluding round of survey cadence simulations. These simulations, to be delivered during early calendar year 2022, will inform the phase 2 survey strategy recommendation which will define the baseline strategy for starting the Rubin Observatory's Legacy Survey of Space and Time (LSST). The phase 2 SCOC recommendation will be delivered to the Rubin Observatory Operations Director before the end of calendar year 2022.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models: Preprint

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.

backsheet↗

The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration

We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low-redshift surveys, retraining the salt3 light-curve model and fixing a numerical approximation in the host-galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises ~1600 likely Type Ia SNe from DES and ~200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain Ω m = 0.330 ± 0.015 in flat Lambda-cold dark matter (⁠ΛCDM) which changes Ω m by –0.022 compared to DES-SN5YR. Combining DES-Dovekie with cosmic microwave background data from Planck, Atacama Cosmology Telescope, and South Pole Telescope and the DESI DR2 measurements in a flat CDM cosmology, we find ω 0 = –0.803 ± 0.054 and ω a = –0.72 ± 0.21⁠. Our results hold a significance of 3.2σ, reduced from 4.2σ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the flat ω 0 ω a CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.

dark energy↗

Workforce Development Survey Results: Industry, Government Laboratories, Academia, and Recent Graduates

Herein, we describe the results of the survey from the TMS Education committee. The committee designated a subcommittee on Workforce Development to survey professionals in industry/government laboratories (I/G), academia (A), and recent graduates (RG) to gain insights into the alignment of materials science curricula with workforce needs. The survey project began with a charter to explore any disconnects that might exist between university materials curriculum and workforce knowledge, skill, and ability needs for MSE-related careers, and also highlight critical areas of excellence that should be preserved. Focused surveys for each category were developed and received over 150 responses, including 83 responses from industry/government, 40 responses from recent graduates, 29 responses from academia.

99 GENERAL AND MISCELLANEOUS↗

StarHorse results for spectroscopic surveys and Gaia DR3: Chrono-chemical populations in the solar vicinity, the genuine thick disk, and young alpha-rich stars

The Gaia mission has provided an invaluable wealth of astrometric data for more than a billion stars in our Galaxy. The synergy between Gaia astrometry, photometry, and spectroscopic surveys gives us comprehensive information about the Milky Way. Using the Bayesian isochrone-fitting code StarHorse, we derive distances and extinctions for more than 10 million unique stars listed in both Gaia Data Release 3 and public spectroscopic surveys: 557 559 in GALAH+ DR3, 4 531 028 in LAMOST DR7 LRS, 347 535 in LAMOST DR7 MRS, 562 424 in APOGEE DR17, 471 490 in RAVE DR6, 249 991 in SDSS DR12 (optical spectra from BOSS and SEGUE), 67 562 in the Gaia-ESO DR5 survey, and 4 211 087 in the Gaia RVS part of the Gaia DR3 release. StarHorse can increase the precision of distance and extinction measurements where Gaia parallaxes alone would be uncertain. We used StarHorse for the first time to derive stellar ages for main-sequence turnoff and subgiant branch stars, around 2.5 million stars, with age uncertainties typically around 30%; the uncertainties drop to 15% for subgiant-branch-only stars, depending on the resolution of the survey. With the derived ages in hand, we investigated the chemical-age relations. In particular, the α and neutron-capture element ratios versus age in the solar neighbourhood show trends similar to previous works, validating our ages. We used the chemical abundances from local subgiant samples of GALAH DR3, APOGEE DR17, and LAMOST MRS DR7 to map groups with similar chemical compositions and StarHorse ages, using the dimensionality reduction technique t-SNE and the clustering algorithm HDBSCAN. We identify three distinct groups in all three samples, confirmed by their kinematic properties: the genuine chemical thick disk, the thin disk, and a considerable number of young alpha-rich stars (427) that are also a part of the delivered catalogues. We confirm that the genuine thick disk’s kinematics and age properties are radically different from those of the thin disk and compatible with high-redshift (z ≈ 2) star-forming disks with high dispersion velocities. We also find a few extra chemical populations in GALAH DR3 thanks to the availability of neutron-capture element information.

79 ASTRONOMY AND ASTROPHYSICS↗

MHONGOOSE: A MeerKAT nearby galaxy H I survey

The MHONGOOSE (MeerKAT H IObservations of Nearby Galactic Objects: Observing Southern Emitters) survey maps the distribution and kinematics of the neutral atomic hydrogen (H I) gas in and around 30 nearby star-forming spiral and dwarf galaxies to extremely low H Icolumn densities. The H Icolumn density sensitivity (3σover 16 km s −1 ) ranges from ∼5 × 10 17 cm −2 at 90″ resolution to ∼4 × 10 19 cm −2 at the highest resolution of 7″. The H Imass sensitivity (3σover 50 km s −1 ) is ∼5.5 × 10 5 M ⊙ at a distance of 10 Mpc (the median distance of the sample galaxies). The velocity resolution of the data is 1.4 km s −1 . One of the main science goals of the survey is the detection of cold accreting gas in the outskirts of the sample galaxies. The sample was selected to cover a range in H Imasses from 10 7 M ⊙ to almost 10 11 M ⊙ in order to optimally sample possible accretion scenarios and environments. The distance to the sample galaxies ranges from 3 to 23 Mpc. In this paper, we present the sample selection, survey design, and observation and reduction procedures. We compared the integrated H Ifluxes based on the MeerKAT data with those derived from single-dish measurement and find good agreement, indicating that our MeerKAT observations are recovering all flux. We present H Imoment maps of the entire sample based on the first ten percent of the survey data, and find that a comparison of the zeroth- and second-moment values shows a clear separation in the physical properties of the H Ibetween areas with star formation and areas without related to the formation of a cold neutral medium. Finally, we give an overview of the H I-detected companion and satellite galaxies in the 30 fields, five of which have not previously been cataloged. We find a clear relation between the number of companion galaxies and the mass of the main target galaxy.

Astronomy & Astrophysics↗

The SRG/eROSITA All-Sky Survey: Constraints on the structure growth from cluster number counts

Recent advancements in methods used in wide-area surveys have demonstrated the reliability of the number density of galaxy clusters as a viable tool for precision cosmology. Beyond testing the current cosmological paradigm, cluster number counts can also be used to investigate the discrepancies currently affecting cosmological measurements. In particular, cosmological studies based on cosmic shear and other large-scale structure probes routinely find a value for the amplitude of the fluctuations in the universe S​ 8 = σ 8 (Ω m /0.3) 0.5 smaller than the one inferred from the primary cosmic microwave background. In this work, we investigate this tension by measuring structure evolution across cosmic time as probed by the number counts of massive halos with the first SRG/eROSITA All-Sky Survey cluster catalog in the western Galactic hemisphere, complemented with the overlapping Dark Energy Survey Year-3, Kilo-Degree Survey, and Hyper Suprime-Cam data for weak lensing mass calibration, by implementing two different parameterizations and a model-agnostic method. In the first model, we measured the cosmic linear growth index as γ = 1.19 ± 0.21, which is in tension with the standard value of γ = 0.55 but in good statistical agreement with other large-scale structure probes. The second model is a phenomenological scenario in which we rescale the linear matter power spectrum at low redshift to investigate a potential reduction of structure formation, and it provided similar results. Finally, in a third strategy, we considered a standard ΛCDM cosmology, but we separated the cluster catalog into five redshift bins, measuring the cosmological parameters in each and inferring the evolution of the structure formation, finding hints of a reduction. Interestingly, the S ​8 value inferred from the number counts of the cluster eRASS1 when we add a degree of freedom to the matter power spectrum recovers the value inferred by cosmic shear studies. The observed reduction in the growth rate or systematic uncertainties associated with various measurements may account for the discrepancy in the S 8 ​ values suggested between cosmic shear probes and eROSITA cluster number counts and Planck CMB measurements.

cosmological parameters↗

The SRG/eROSITA All-Sky Survey: Constraints on ultralight axion dark matter through galaxy cluster number counts

Ultralight axions are hypothetical scalar particles that influence the evolution of large-scale structures of the Universe. Depending on their mass, they can potentially be part of the dark matter component of the Universe as candidates commonly referred to as fuzzy dark matter. While strong constraints have been established for pure fuzzy dark matter models, the more general scenario where ultralight axions constitute only a fraction of the dark matter has been limited to only a few observational probes. In this work, we use the galaxy cluster number counts obtained from the first All-Sky Survey (eRASS1) of the SRG/eROSITA mission together with gravitational weak lensing data from the Dark Energy Survey, the Kilo-Degree Survey, and the Hyper Suprime-Cam to constrain the fraction of ultralight axions in the mass range 10 −32 eV to 10 −24 eV. We put upper bounds on the ultralight axion relic density Ω a in independent logarithmic axion mass bins by performing a full cosmological parameter inference. We find an exclusion region in the intermediate ultralight axion mass regime with the tightest bounds reported so far in the mass bins around m a = 10 −27 eV with Ω a < 0.0035 and m a = 10 −26 eV with Ω a < 0.0079; both are at a 95% confidence level. When combined with cosmic microwave background probes, these bounds are tightened to Ω a < 0.0030 in the m a = 10 −27 eV mass bin and Ω a < 0.0058 in the m a = 10 −26 eV mass bin, with both at a 95% confidence level. This is the first time that constraints on ultralight axions have been obtained using the growth of structure measured by galaxy cluster number counts. These results pave the way for large surveys, which can be utilized to obtain tight constraints on the mass and relic density of ultralight axions with better theoretical modeling of the abundance of halos.

cosmological parameters↗

Mock data sets for the Eboss and DESI Lyman-α forest surveys

We present a publicly-available code to generate sets of mock Lyman-α (Lyα) forest data that have realistic large-scale correlations including those due to the Baryonic Acoustic Oscillations (BAO). The primary purpose of these mocks is to test the analysis procedures of the Extended Baryon Oscillation Survey (eBOSS) and the Dark Energy Spectroscopy Instrument (DESI) surveys. The transmitted flux fraction, F(λ), of background quasars due to Lyα absorption in the intergalactic medium (IGM) is simulated using the Fluctuating Gunn-Petterson Approximation (FGPA) applied to Gaussian random fields produced through the use of fast Fourier transforms (FFT). The output includes the IGM-Lyα transmitted flux fraction along quasar lines of sight and a catalog of high-column-density systems appropriately placed at high-density regions of the IGM. This output serves as input to additional code that superimposes the IGM tranmission on realistic quasar spectra, adds absorption by high-column-density systems and metals, and simulates instrumental transmission and noise. Redshift space distortions (RSD) of the flux correlations are implemented by including the large-scale velocity-gradient field in the FGPA resulting in a correlation function of F(λ) that can be accurately predicted. One hundred realizations have been produced over the 14,000 deg 2 DESI survey footprint with 100 quasars per deg 2 . The analysis of these realizations shows that the correlations of F(λ) follows the prediction within the accuracy of eBOSS survey. Here, the most time-consuming part of the mock production occurs before application of the FGPA, and the existing pre-FGPA forests can be used to easily produce new mock sets with modified redshift-dependent bias parameters or observational conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

Light fields during inflation from BOSS and future galaxy surveys

Abstract Primordial non-Gaussianity generated by additional fields present during inflation offers a compelling observational target for galaxy surveys. These fields are of significant theoretical interest since they offer a window into particle physics in the inflaton sector. They also violate the single-field consistency conditions and induce a scale-dependent bias in the galaxy power spectrum. In this paper, we explore this particular signal for light scalar fields and study the prospects for measuring it with galaxy surveys. We find that the sensitivities of current and future surveys are remarkably stable for different configurations, including between spectroscopic and photometric redshift measurements. This is even the case at non-zero masses where the signal is not obviously localized on large scales. For realistic galaxy number densities, we demonstrate that the redshift range and galaxy bias of the sample have the largest impact on the sensitivity in the power spectrum. These results additionally motivated us to explore the potentially enhanced sensitivity of Vera Rubin Observatory's LSST through multi-tracer analyses. Finally, we apply this understanding to current data from the last data release of the Baryon Oscillation Spectroscopic Survey (BOSS DR12) and place new constraints on light fields coupled to the inflaton.

Astronomy & Astrophysics↗

Applied Machine-Learning Models to Identify Spectral Sub-Types of M Dwarfs from Photometric Surveys

M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is one of the parameters that is used for the characterization and it is traditionally derived from the observed spectra. However, obtaining the spectra of M dwarfs is expensive in terms of observation time and resources due to their intrinsic faintness. We study the performance of four machine-learning (ML) models—K-Nearest Neighbor (KNN), Random Forest (RF), Probabilistic Random Forest (PRF), and Multilayer Perceptron (MLP)—in identifying the spectral sub-types of M dwarfs at a grand scale by deploying broadband photometry in the optical and near-infrared. We trained the ML models by using the spectroscopically identified M dwarfs from the Sloan Digital Sky Survey (SDSS) Data Release (DR) 7, together with their photometric colors that were derived from the SDSS, Two-Micron All-Sky Survey, and Wide-field Infrared Survey Explorer. We found that the RF, PRF, and MLP give a comparable prediction accuracy, 74%, while the KNN provides slightly lower accuracy, 71%. We also found that these models can predict the spectral sub-type of M dwarfs with ~99% accuracy within ±1 sub-type. The five most useful features for the prediction are r - z, r - i, r - J, r - H , and g - z, and hence lacking data in all SDSS bands substantially reduces the prediction accuracy. However, we can achieve an accuracy of over 70% when the r and i magnitudes are available. Since the stars in this study are nearby (d ≲ 1300 pc for 95% of the stars), the dust extinction can reduce the prediction accuracy by only 3%. Finally, we used our optimized RF models to predict the spectral sub-types of M dwarfs from the Catalog of Cool Dwarf Targets for the Transiting Exoplanet Survey Satellite, and we provide the optimized RF models for public use.

79 ASTRONOMY AND ASTROPHYSICS↗

Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.

79 ASTRONOMY AND ASTROPHYSICS↗

LAMOST Time-Domain survey: first results of four K2 plates

From Oct. 2019 to Apr. 2020, LAMOST performed a time-domain (TD) spectroscopic survey of four K2 plates with both low- and medium-resolution observations. The low-resolution spectroscopic survey acquired 282 exposures ( ≈ 46.6 h) over 25 nights, yielding a total of about 767 000 spectra, and the medium-resolution survey took 177 exposures ( ≈ 49.1 h) over 27 nights, collecting about 478 000 spectra. More than 70%/50% of low-resolution/medium-resolution spectra have signal-to-noise ratio higher than 10. We determine stellar parameters (e.g., T eff , log g, [Fe/H]) and radial velocity (RV) with different methods, including LASP, DD-Payne and SLAM. In general, these parameter estimations from different methods show good agreement, and the stellar parameter values are consistent with those of APOGEE. We use the Gaia DR2 RV values to calculate a median RV zero point (RVZP) for each spectrograph exposure by exposure, and the RVZP-corrected RVs agree well with the APOGEE data. The stellar evolutionary and spectroscopic masses are estimated based on the stellar parameters, multi-band magnitudes, distances and extinction values. Finally, we construct a binary catalog including about 2700 candidates by analyzing their light curves, fitting the RV data, calculating the binarity parameters from medium-resolution spectra and cross-matching the spatially resolved binary catalog from Gaia EDR3. In conclusion, the LAMOST TD survey is expected to represent a breakthrough in various scientific topics, such as binary systems, stellar activity, stellar pulsation, etc.

79 ASTRONOMY AND ASTROPHYSICS↗

Supernova host galaxies in the dark energy survey: I. Deep coadds, photometry, and stellar masses

ABSTRACT The 5-yr Dark Energy Survey Supernova Programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterizing the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimized coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other four seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order ∼27 in g band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multiband photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high-mass hosts at high-redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects.

79 ASTRONOMY AND ASTROPHYSICS↗

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic power spectrum between redshifts 0.6 and 1.0

ABSTRACT We analyse the clustering of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 luminous red galaxy sample (DR16 eBOSS LRG) in combination with the high redshift tail of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey Data Release 12 (DR12 BOSS CMASS). We measure the redshift space distortions (RSD) and also extract the longitudinal and transverse baryonic acoustic oscillation (BAO) scale from the anisotropic power spectrum signal inferred from 377 458 galaxies between redshifts 0.6 and 1.0, with the effective redshift of zeff = 0.698 and effective comoving volume of $2.72\, {\rm Gpc}^3$. After applying reconstruction, we measure the BAO scale and infer DH(zeff)/rdrag = 19.30 ± 0.56 and DM(zeff)/rdrag = 17.86 ± 0.37. When we perform an RSD analysis on the pre-reconstructed catalogue on the monopole, quadrupole, and hexadecapole we find, DH(zeff)/rdrag = 20.18 ± 0.78, DM(zeff)/rdrag = 17.49 ± 0.52 and fσ8(zeff) = 0.454 ± 0.046. We combine both sets of results along with the measurements in configuration space and report the following consensus values: DH(zeff)/rdrag = 19.77 ± 0.47, DM(zeff)/rdrag = 17.65 ± 0.30 and fσ8(zeff) = 0.473 ± 0.044, which are in full agreement with the standard ΛCDM and GR predictions. These results represent the most precise measurements within the redshift range 0.6 ≤ z ≤ 1.0 and are the culmination of more than 8 yr of SDSS observations.

Gil-Marín, Héctor↗