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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

The Swift Gamma-Ray Burst Host Galaxy Legacy Survey. I. Sample Selection and Redshift Distribution

We introduce the Swift Gamma-Ray Burst Host Galaxy Legacy Survey (SHOALS), a multi-observatory high redshift galaxy survey targeting the largest unbiased sample of long-duration gamma-ray burst (GRB) hosts yet assembled (119 in total). We describe the motivations of the survey and the development of our selection criteria, including an assessment of the impact of various observability metrics on the success rate of afterglow-based redshift measurement. We briefly outline our host galaxy observational program, consisting of deep Spitzer/IRAC imaging of every field supplemented by similarly deep, multicolor optical/near-IR photometry, plus spectroscopy of events without preexisting redshifts. Our optimized selection cuts combined with host galaxy follow-up have so far enabled redshift measurements for 110 targets (92%) and placed upper limits on all but one of the remainder. About 20% of GRBs in the sample are heavily dust obscured, and at most 2% originate from z > 5.5. Using this sample, we estimate the redshift-dependent GRB rate density, showing it to peak at z approx. 2.5 and fall by at least an order of magnitude toward low (z = 0) redshift, while declining more gradually toward high (z approx. 7) redshift. This behavior is consistent with a progenitor whose formation efficiency varies modestly over cosmic history. Our survey will permit the most detailed examination to date of the connection between the GRB host population and general star-forming galaxies, directly measure evolution in the host population over cosmic time and discern its causes, and provide new constraints on the fraction of cosmic star formation occurring in undetectable galaxies at all redshifts.

galaxies: evolution – galaxies: high-redshift â€↗
DOE OSTI2024

Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment

Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches are machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims. The goal of this work is to calculate the photo-zs for the Y3 DES Deep Fields catalogue using the DNF machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained with respect to the EAzY template fitting approach on Y3 DES Deep Fields catalogue. Methods. We have emulated -- at brighter magnitude -- the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We have used a principal component analysis to graphically assess incompleteness and to relate it with the performance parameters provided by DNF. Finally, we have applied the results about the incompleteness to the photo-z computation on Y3 DES Deep Fields with DNF and estimated its performance. Results. The photo-zs for the galaxies on DES Deep Fields have been computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. They are available at https://des.ncsa.illinois.edu/releases/y3a2/Y3deepfields. Some techniques have been developed to evaluate the performance in the absence of "true" redshift and to assess completeness. We have studied... (Partial abstract)

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

VLA observations of unidentified Leiden-Berkeley Deep-Survey sources - Luminosity and redshift dependence of spectral properties

VLA observations of a complete subset of the Leiden-Berkeley Deep Survey sources that have S(1.4 GHz) greater than 10 mJy and are not optically identified down to F=22 mag are reported. By comparing the spectral and structural properties of the sources with samples from the literature, an attempt was made to disentangle the luminosity and redshift dependence of the spectral indices of extended emission in radio galaxies and of the incidence of compact steep-spectrum sources. It is found that the fraction of compact sources among those with a steep spectrum is related primarily to redshift, being much larger at high redshifts for sources of similar radio luminosity. Only a weak and marginally significant dependence of spectral indices of the extended sources on luminosity and redshift is found in samples selected at 1.4 and 2.7 GHz. It is pointed out that the much stronger correlation of spectral indices with luminosity may be arising partly from spectral curvature, and partly due to the preferential inclusion of very steep-spectrum sources from high redshift in low-frequency surveys.

Kapahi, Vijay K.↗
DOE OSTI2024

Impact of survey spatial variability on galaxy redshift distributions and the cosmological 3 × 2-point statistics for the Rubin Legacy Survey of Space and Time (LSST)

We investigate the impact of spatial survey non-uniformity on the galaxy redshift distributions for forthcoming data releases of the Rubin Observatory Legacy Survey of Space and Time (LSST). Specifically, we construct a mock photometry data set degraded by the Rubin OpSim observing conditions, and estimate photometric redshifts of the sample using a template-fitting photo-z estimator, BPZ, and a machine learning method, FlexZBoost. We select the Gold sample, defined as $i\lt 25.3$ for 10 yr LSST data, with an adjusted magnitude cut for each year and divide it into five tomographic redshift bins for the weak lensing lens and source samples. We quantify the change in the number of objects, mean redshift, and width of each tomographic bin as a function of the coadd i-band depth for 1-yr (Y1), 3-yr (Y3), and 5-yr (Y5) data. In particular, Y3 and Y5 have large non-uniformity due to the rolling cadence of LSST, hence provide a worst-case scenario of the impact from non-uniformity. We find that these quantities typically increase with depth, and the variation can be $10\!-\!40~{{\rm per\ cent}}$ at extreme depth values. Using Y3 as an example, we propagate the variable depth effect to the weak lensing $3\times 2$ pt analysis, and assess the impact on cosmological parameters via a Fisher forecast. We find that galaxy clustering is most susceptible to variable depth, and non-uniformity needs to be mitigated below 3 per cent to recover unbiased cosmological constraints. There is little impact on galaxy–shear and shear–shear power spectra, given the expected LSST Y3 noise.

cosmology↗
DOE OSTI2024

Analysis of BOSS galaxy data with weighted skew-spectra

We present the first application of the weighted skew-spectra to analyze non-Gaussian information in galaxy survey data. Using the tree-level galaxy skew-spectra together with the one-loop power spectrum multipoles, we analyze the Sloan Digital Sky Survey (SDSS)-III Baryon Oscillation Spectroscopic Survey (BOSS) galaxy clustering data, and target our search towards the equilateral bispectrum shape of primordial non-Gaussianity. We use the Effective Field Theory model for the galaxy power spectrum and bispectrum, and account for systematic effects, such as the survey geometry. From our likelihood analysis, we find f NL equil = -34 +296 -334 at 68% CL, consistent with previous works, while systematic errors from our treatment of the survey geometry lead to an unreliable estimation of f NL ortho . As a result, we further constrain the bias and counterterm parameters, while keeping the cosmology fixed to Planck 2018 values. As a check, we also validate our analysis pipeline using theNseries simulation suite.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Quantifying the Impact of LSST u -band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies

The Vera C. Rubin Observatory will conduct the Legacy Survey of Space and Time (LSST), promising to discover billions of galaxies out to redshift 7, using six photometric bands (ugrizy) spanning the near-ultraviolet to the near-infrared. The exact number of and quality of information about these galaxies will depend on survey depth in these six bands, which in turn depends on the LSST survey strategy, i.e., how often and how long to expose in each band. u-band depth is especially important for photometric redshift (photo-z) estimation and for detection of high-redshift Lyman-break galaxies (LBGs). In this paper, we use a simulated galaxy catalog and an analytic model for the LBG population to study how recent updates and proposed changes to Rubin’s u-band throughput and LSST survey strategy impact photo-z accuracy and LBG detection. We find that proposed variations in u-band strategy have a small impact on photo-z accuracy for z < 1.5 galaxies, but the outlier fraction, scatter, and bias for higher-redshift galaxies vary by up to 50%, depending on the survey strategy considered. The number of u-band dropout LBGs at z ∼ 3 is also highly sensitive to the u-band depth, varying by up to 500%, while the number of griz-band dropouts is only modestly affected. Under the new u-band strategy recommended by the Rubin Survey Cadence Optimization Committee, we predict u-band dropout number densities of 110 deg −2 (3200 deg −2 ) in year 1 (10) of LSST. We discuss the implications of these results for LSST cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The impact of spectroscopic incompleteness in direct calibration of redshift distributions for weak lensing surveys

ABSTRACT Obtaining accurate distributions of galaxy redshifts is a critical aspect of weak lensing cosmology experiments. One of the methods used to estimate and validate redshift distributions is to apply weights to a spectroscopic sample, so that their weighted photometry distribution matches the target sample. In this work, we estimate the selection bias in redshift that is introduced in this procedure. We do so by simulating the process of assembling a spectroscopic sample (including observer-assigned confidence flags) and highlight the impacts of spectroscopic target selection and redshift failures. We use the first year (Y1) weak lensing analysis in Dark Energy Survey (DES) as an example data set but the implications generalize to all similar weak lensing surveys. We find that using colour cuts that are not available to the weak lensing galaxies can introduce biases of up to Δz ∼ 0.04 in the weighted mean redshift of different redshift intervals (Δz ∼ 0.015 in the case most relevant to DES). To assess the impact of incompleteness in spectroscopic samples, we select only objects with high observer-defined confidence flags and compare the weighted mean redshift with the true mean. We find that the mean redshift of the DES Y1 weak lensing sample is typically biased at the Δz = 0.005−0.05 level after the weighting is applied. The bias we uncover can have either sign, depending on the samples and redshift interval considered. For the highest redshift bin, the bias is larger than the uncertainties in the other DES Y1 redshift calibration methods, justifying the decision of not using this method for the redshift estimations. We discuss several methods to mitigate this bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A Unified Photometric Redshift Calibration for Weak Lensing Surveys Using the Dark Energy Spectroscopic Instrument

The effective redshift distribution n(z) of galaxies is a critical component in the study of weak gravitational lensing. Here, we introduce a new method for determining n(z) for weak lensing surveys based on high-quality redshifts and neural-network-based importance weights. Additionally, we present the first unified photometric redshift calibration of the three leading stage-III weak lensing surveys, the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS), with state-of-the-art spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We verify our method using a new, data-driven approach and obtain n(z) constraints with statistical uncertainties of the order of $σ_z$ ~ 0.01 and smaller. Our analysis is largely independent of previous photometric redshift calibrations and, thus, provides an important cross-check in light of recent cosmological tensions. Overall, we find excellent agreement with previously published results on the DES Y3 and HSC Y1 data sets, while there are some differences on the mean redshift with respect to the previously published KiDS-1000 results. We attribute the latter to mismatches in photometric noise properties in the COSMOS field compared to the wider KiDS self-organizing map-gold catalog. At the same time, the new n(z) estimates for KiDS do not significantly change estimates of cosmic structure growth from cosmic shear. Finally, we discuss how our method can be applied to future weak lensing calibrations with DESI data.

Lange, J. U. [American Univ., Washington, DC (Unit↗
DOE OSTI2025

Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim++ Lens Sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3x2pt cosmology analysis. The 3x2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection (Balrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O($10^8$) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the $n(z)$ uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. This analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

Giannini, G. [Chicago U., Astron. Astrophys. Ctr.;↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Redshift calibration of the MagLim++ lens sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3 x 2pt cosmology analysis. The 3 x 2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection ( B alrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O(10 8 ) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the n(z) uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. Here, this analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

dark energy↗
DOE OSTI2025

A comparison of effective field theory models of redshift space galaxy power spectra for DESI 2024 and future surveys

In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation theory. These models are employed in the pipelines velocileptors, PyBird, and Folpsν. While these models have been validated independently, a detailed comparison with consistent choices has not been attempted. After briefly discussing the theoretical differences between the models we describe how to provide a more apples-to-apples comparison between them. We present the results of fitting mock spectra from the AbacusSummit suite of N-body simulations provided in three redshift bins to mimic the types of dark time tracers targeted by the DESI survey. We show that the theories behave similarly and give consistent constraints in both the forward-modeling and ShapeFit compressed fitting approaches. We additionally generate (noiseless) synthetic data from each pipeline to be fit by the others, varying the scale cuts in order to show that the models agree within the range of scales for which we expect 1-loop perturbation theory to be applicable. Finally, this work lays the foundation of Full-Shape analysis with DESI Y1 galaxy samples where in the tests we performed, we found no systematic error associated with the modeling of the galaxy redshift space power spectrum for this volume.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Omega from the anisotropy of the redshift correlation function in the IRAS 2 Jansky survey

Peculiar velocities distort the correlation function of galaxies in redshift space. In the linear regime, the distortion has a characteristic quadrupole plus hexadecapole form, with amplitude depending on the cosmological density parameter Omega. I report here measurements of the anisotropy of the correlation function in the IRAS 2 Jy redshift survey. The inferred value of Omega is Omega = 0.5 + 0.5 or - 0.25.

Hamilton, A. J. S.↗
DOE OSTI2021

Dark Energy Survey Year 3 results: redshift calibration of the weak lensing source galaxies

ABSTRACT Determining the distribution of redshifts of galaxies observed by wide-field photometric experiments like the Dark Energy Survey (DES) is an essential component to mapping the matter density field with gravitational lensing. In this work we describe the methods used to assign individual weak lensing source galaxies from the DES Year 3 Weak Lensing Source Catalogue to four tomographic bins and to estimate the redshift distributions in these bins. As the first application of these methods to data, we validate that the assumptions made apply to the DES Y3 weak lensing source galaxies and develop a full treatment of systematic uncertainties. Our method consists of combining information from three independent likelihood functions: self-organizing map p(z) (sompz), a method for constraining redshifts from galaxy photometry; clustering redshifts (WZ), constraints on redshifts from cross-correlations of galaxy density functions; and shear ratios (SRs), which provide constraints on redshifts from the ratios of the galaxy-shear correlation functions at small scales. Finally, we describe how these independent probes are combined to yield an ensemble of redshift distributions encapsulating our full uncertainty. We calibrate redshifts with combined effective uncertainties of σ〈z〉 ∼ 0.01 on the mean redshift in each tomographic bin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Photo-z outlier self-calibration in weak lensing surveys

Calibrating photometric redshift errors in weak lensing surveys with external data is extremely challenging. In this work, we show that both Gaussian and outlier photo-z parameters can be self-calibrated from the data alone. This comes at no cost for the neutrino masses, curvature and dark energy equation of state w0, but with a 65% degradation when both w0 and wa are varied. We perform a realistic forecast for the Vera Rubin Observatory (VRO) Legacy Survey of Space and Time (LSST) 3× 2 analysis, combining cosmic shear, projected galaxy clustering and galaxy - galaxy lensing. We confirm the importance of marginalizing over photo-z outliers. We examine a subset of internal cross-correlations, dubbed "null correlations", which are usually ignored in 3× 2 analyses. Despite contributing only ~ 10% of the total signal-to-noise, these null correlations improve the constraints on photo-z parameters by up to an order of magnitude. Using the same galaxy sample as sources and lenses dramatically improves the photo-z uncertainties too. Together, these methods add robustness to any claim of detected new Physics, and reduce the statistical errors on cosmology by 15% and 10% respectively. Finally, including CMB lensing from an experiment like Simons Observatory or CMB-S4 improves the cosmological and photo-z posterior constraints by about 10%, and further improves the robustness to systematics. To give intuition on the Fisher forecasts, we examine in detail several toy models that explain the origin of the photo-z self-calibration. Our Fisher code LaSSI (Large-Scale Structure Information), which includes the effect of Gaussian and outlier photo-z, shear multiplicative bias, linear galaxy bias, and extensions to LCDM, is publicly available at \href{https://github.com/EmmanuelSchaan/LaSSI}{https://github.com/EmmanuelSchaan/LaSSI}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Identifying Missing Quasars from the DESI Bright Galaxy Survey

The Dark Energy Spectroscopic Instrument (DESI) cosmology survey includes a Bright Galaxy Survey (BGS), which will yield spectra for over 10 million bright galaxies (r < 20.2 AB mag). The resulting sample will be valuable for both cosmological and astrophysical studies. However, the star/galaxy separation criterion implemented in the nominal BGS target selection algorithm excludes quasar host galaxies in addition to bona fide stars. While this excluded population is comparatively rare (∼3–4 per square degrees), it may hold interesting clues regarding galaxy and quasar physics. Therefore, we present a target selection strategy that was implemented to recover these missing active galactic nuclei (AGN) from the BGS sample. The design of the selection criteria was both motivated and confirmed using spectroscopy. The resulting BGS-AGN sample is uniformly distributed over the entire DESI footprint. According to DESI survey validation data, the sample comprises 93% quasi-stellar objects (QSOs), 3% narrow-line AGN or blazars with a galaxy contamination rate of 2%, and a stellar contamination rate of 2%. Peaking around redshift z = 0.5, the BGS-AGN sample is intermediary between quasars from the rest of the BGS and those from the DESI QSO sample in terms of redshifts and AGN luminosities. The stacked spectrum is nearly identical to that of the DESI QSO targets, confirming that the sample is dominated by quasars. We highlight interesting small populations reaching z > 2, which are either faint quasars with nearby projected companions or very bright quasars with strong absorption features including the Lyα forest, metal absorbers, and/or broad absorption lines.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

All-purpose, all-sky photometric redshifts for the Legacy Imaging Surveys Data Release 8

ABSTRACT In this paper, we present photometric redshift (photo-z) estimates for the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, currently the most sensitive optical survey covering the majority of the extragalactic sky. Our photo-z methodology is based on a machine-learning approach, using sparse Gaussian processes augmented with Gaussian mixture models (GMMs) that allow regions of parameter space to be identified and trained separately in a purely data-driven way. The same GMMs are also used to calculate cost-sensitive learning weights that mitigate biases in the spectroscopic training sample. By design, this approach aims to produce reliable and unbiased predictions for all parts of the parameter space present in wide area surveys. Compared to previous literature estimates using the same underlying photometry, our photo-zs are significantly less biased and more accurate at z > 1, with negligible loss in precision or reliability for resolved galaxies at z < 1. Our photo-z estimates offer accurate predictions for rare high-value populations within the parent sample, including optically selected quasars at the highest redshifts (z > 6), as well as X-ray or radio continuum selected populations across a broad range of flux (densities) and redshift. Deriving photo-z estimates for the full Legacy Imaging Surveys Data Release 8, the catalogues provided in this work offer photo-z estimates predicted to be of high quality for ≳9 × 108 galaxies over ${\sim}19\, 400\, \text{deg}^{2}$ and spanning 0 < z ≲ 7, offering one of the most extensive samples of redshift estimates ever produced.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Impact of systematic redshift errors on the cross-correlation of the Lyman-α forest with quasars at small scales using DESI Early Data

The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-α forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Here, using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-α forest with quasars. We find evidence for a redshift dependent bias causing redshifts to be underestimated with increasing redshift, stemming from improper modeling of the Lyman-α optical depth in the templates used for redshift estimation. New templates were derived for the DESI Year 1 quasar sample at z > 1.6 and we found the redshift dependent bias, Δr ∥ , increased from -1.94 ± 0.15 h -1 Mpc to -0.08 ± 0.04 h -1 Mpc (-205 ± 15 km s -1 to -9.0 ± 4.0 km s -1 ). These new templates will be used to provide redshifts for the DESI Year 1 quasar sample.

Lyman alpha forest↗
DOE OSTI2026

Infrared-enhanced Photometric Redshifts for the Dark Energy Survey Y6 Gold catalogue

The Dark Energy Survey (DES) provides optical data across 5000 square degrees of the southern sky, enabling a broad range of extragalactic and cosmological studies. Combining DES data with infrared surveys offers the opportunity to improve its photometric redshift (photo-z) estimates. We aim to investigate improvements in photometric redshift estimation achieved by combining DES optical data with infrared measurements from the VISTA Hemisphere Survey (VHS) and the Wide-field Infrared Survey Explorer (WISE), and release an updated version of the catalogue. We performed a positional sky cross-match between the DES Y6 Gold catalogue matched to a spectroscopic dataset, the 2013 AllWISE Data Release, and VHS Data Release 5, in order to test these improvements using the Directional Neighbourhood Fitting (DNF) algorithm (Y6 Gold catalogue reference estimator). We additionally matched it to the unWISE catalogue to verify the performance against this deeper dataset. Adding infrared data reduces all the metrics (scatter, bias and outlier fraction) in photo-z estimates, particularly at higher redshifts in comparison with only using optical data from DES. The obtained results are globally better for the DES+WISE sample, with improvements that are statistically significant. On the other hand, the addition of the VHS bands to available depth is only marginal. The combined use of DES and WISE W1 and W2 data improves the photometric redshift metrics analysed here. The addition of VHS data at the DES and VHS depths explored here does not provide any further improvement at z less than 1.5, indicating that, under these constraints, WISE data may already capture the key infrared features and depth needed for accurate photo-z estimation. In addition, low signal-to-noise (less than 10) infrared data does not contribute to any improvement beyond the DES optical dataset.

Puebla, M. M. [Madrid U.; Madrid, CIEMAT]↗