arXiv subjects

L. Bonavera

Publications and source records attributed to L. Bonavera.

At least 19 recordsLinked to original sources

arXiv2026

Methodological refinement of the submillimeter galaxy cross-correlation function measurements and their uncertainty estimation

In this study, we aim to develop a new methodology to estimate the cross-correlation function and uncertainties and apply it to the analysis of magnification bias in galaxy surveys. We adopt a new methodological framework that uses a statistically rigorous approach to obtain more robust measurements for constraining cosmological parameters. This strategy involves using the full field area to count the number of different pairs for each field and combine them into a single estimation, reducing statistical uncertainty and accounting for the full information available in the data. The covariance matrix was estimated internally using an oversampled bootstrap method. We divided each field into at least five patches, that were defined automatically using a k-mean clustering algorithm. We investigate the robustness of the new methodology by comparing the results from a spectroscopic lens sample with those from a photometric lens sample, finding them to be compatible. We also analyse the cross-correlation function and auto-correlation function for individual fields in the three GAMA fields, comparing both samples. The G15 field was found to have a stronger signal compared to the other fields, suggesting that the stronger cross-correlation is produced by the rare combination of two excesses of large-scale structure in both the foreground and background samples. Our results demonstrate the robustness of the new methodology and suggest that the differences with respect to the mini-tile previously used approached may be due to physical properties of the samples themselves. The identified G15 anomalous signal warrants further investigation into its impact on cosmological parameters.

astro-ph.CO↗

arXiv2025

Surveying Galaxy Clusters (in formation) in the Distant Universe

Present-day galaxy clusters are the largest virialized structures in the Universe, yet their early assembly remains poorly understood. At z$>$2, clusters in formation span tens of Mpc and host gas-rich, dust-obscured galaxies embedded in extended, low-surface-brightness gaseous environments. Current (sub-)millimeter facilities lack the mapping speed, sensitivity, and contiguous field of view needed to trace the cold gas and dust driving rapid galaxy growth across such scales. A future large single-dish observatory with degree-scale coverage, broad spectral access, and high-multiplex capability would enable comprehensive and uniform mapping of entire protoclusters, revealing where star formation is triggered or quenched, and quantifying the cold gas budget, thus providing information on gas cooling within protocluster environments. In synergy with wide-sky optical/NIR surveys such as Euclid, LSST, and Roman, this facility would provide the missing multi-scale and multiphase submillimeter view needed to uncover how the stellar, gaseous, and dark-matter components assemble in protoclusters, completing our view of early structure formation.

astro-ph.GA↗

arXiv2025

Cosmic magnification on multi-catalogue Herschel submillimetre galaxies

{Submillimetre galaxies (SMGs) are excellent background sources for magnification-bias studies, but the limited sky coverage in the submillimetre (sub-mm) band constrains their statistical power. Beyond H-ATLAS, Herschel produced additional sub-mm catalogues, though not optimised for spatial statistical lensing analyses.} {Our goal is to refine cosmological constraints from SMG magnification bias by exploiting the full sub-mm sky surveyed by Herschel.} {We expanded the SMG sample by incorporating other Herschel catalogues overlapping SDSS spectroscopic lenses. Random catalogues were generated via kernel density estimation to compute cross-correlations, and Markov Chain Monte Carlo methods were applied to infer astrophysical and cosmological parameters for each catalogue and for the combined dataset.} {We report the first detection of magnification bias in SMGs beyond H-ATLAS, reinforcing the robustness of this observable. Individual Herschel catalogues yield reasonable central values for $Ω_m$ and $σ_8$, although with large uncertainties. The combined analysis, dominated by the more powerful H-ATLAS sample, gives results consistent with $Λ$CDM: $Ω_m = 0.30^{+0.05}_{-0.07}$, $σ_8 = 0.80 (+/- 0.07)$, and $h < 0.80$, in better agreement with \textit{Planck} 2018 than previous non-tomographic studies.} {SMGs are promising tracers for magnification bias, but the narrow sub-mm coverage remains a major limitation. Wider surveys optimised for lensing would enable cross-correlations on larger scales, yielding tighter cosmological constraints.}

astro-ph.CO↗

arXiv2025

Spatial Variations of Polarized Synchrotron Emission in the QUIJOTE MFI Data using Neural Networks

Polarized synchrotron emission from ultra-relativistic electrons spiraling the Galactic magnetic field has become one of the most relevant emissions in the Interstellar medium these last years due to the improvement in the quality of low-frequency observations. One of the recent experiments designed to explore this emission is the QUIJOTE experiment. We aim to study the spatial variations of the synchrotron emission in the QUIJOTE MFI data, by dividing the sky into physically separated regions. For such task, we firstly use a novel component separation method based on artificial neural networks to clean the synchrotron maps. After training the network with simulations, we fit both $EE$ and $BB$ spectra by assuming a power-law model. Then, we give estimations for the index $\alpha_{S}$, the amplitude, and the ratio between $B$ and $E$ amplitudes. When analyzing the real data, we found a clear spatial variation of the synchrotron properties along the sky at 11 GHz, obtaining a steeper index in the Galactic plane of $\alpha_{S}^{EE} = -3.1 \pm 0.3$ and $\alpha_{S}^{BB} = -3.10 \pm 0.28$ and a flatter one at high Galactic latitudes of $\alpha_{S}^{EE} = -3.05 \pm 0.16$ and $\alpha_{S}^{B} = -2.98 \pm 0.23$. We found average values at all sky of $\alpha_{S}^{EE} = -3.04 \pm 0.18$ and $\alpha_{S}^{BB} = -3.00 \pm 0.26$. Furthermore, after obtaining an average value of $A_{S}^{EE} = 3.31 \pm 0.17$ $\mu K^{2}$ and $A_{S}^{BB} = 0.93 \pm 0.04$ $\mu K^{2}$, we estimate a ratio between $B$ and $E$ amplitudes of $A_{S}^{BB}/A_{S}^{EE} = 0.28 \pm 0.06$. Based on the results we conclude that, although neural networks seem to be valuable methods to apply on real ISM observations, combined analyses with Planck, WMAP and/or CBASS data are mandatory to reduce the contamination from QUIJOTE maps and then improve the accuracy of the estimations.

astro-ph.GA↗

arXiv2025

Recovering CMB polarization maps with neural networks: Performance in realistic simulations

Recovering the polarized cosmic microwave background (CMB) is essential for shedding light on the exponential expansion of the very early Universe, known as cosmic inflation. Achieving this goal requires not only improved instrumental sensitivity but also the development of robust and diverse data analysis techniques. In this work, we explore a novel component separation approach based on neural networks to reconstruct the Stokes $Q$ and $U$ polarization maps. To validate the method, we first test the network on realistic \textit{Planck} sky simulations, finding a mean absolute error of $0.1 \pm 0.3~μK^{2}$ for the $E$-mode and $-0.1 \pm 0.3~μK^{2}$ for the $B$-mode. We then apply the trained network to public \textit{Planck} observations, with results consistent with those obtained using the Commander method. Based on these findings, we conclude that neural network-based methods show potential as component separation techniques in polarization CMB experiments. However, substantial improvements and more comprehensive analyses are necessary before these methods can provide reliable high-precision cosmological estimates.

astro-ph.CO↗

arXiv2025

The dust emissivity index beta in infrared-bright galaxies at 1.5 < z < 4.2

We have measured the dust emissivity index beta for 21 infrared-bright sources (including several gravitationally lensed galaxies) at 1.5 < z < 4.2 using Atacama Large Millimeter/submillimeter Array (ALMA) 101-199 GHz data sampling the Rayleigh-Jeans side of the SED. These data are largely insensitive to temperature variations and therefore should provide robust measurements of beta. We obtain a mean beta of 2.2 with a standard deviation of 0.6 that is at the high end of the range of values that had previously been measured in many galactic and extragalactic sources. We find no systematic variation in beta versus redshift. We also demonstrate with a subset of our sources that these higher beta values have significant implications for modelling dust emission and in particular for calculating dust masses or the wavelength at which dust becomes optically thick.

astro-ph.GA↗

arXiv2025

Recovering the CMB signal with neural networks

Component separation is the process of extracting one or more emission sources in astrophysical maps. It is therefore crucial to develop models that can accurately clean the cosmic microwave background (CMB) in current and future experiments. In this work, we present a new methodology based on neural networks which operates on realistic temperature and polarization simulations. We assess its performance by comparing the power spectra of the output maps with those of the input maps and other emissions. For temperature, we obtain residuals of $20 \pm μK^{2}$. For polarization, we analyze the $E$ and $B$ modes, which are related to density (scalar) and primordial gravitational waves (tensorial) perturbations occurring in the first second of the Universe, obtaining residuals of $10^{-2} μK^{2}$ at $l>200$ and $10^{-2}$ and $10^{-3} μK^{2}$ for $E$ and $B$, respectively.

astro-ph.CO↗

arXiv2024

A Novel high-z submm Galaxy Efficient Line Survey in ALMA bands 3 through 8 -- An ANGELS Pilot

We use the Atacama Large sub/Millimetre Array (ALMA) to efficiently observe spectral lines across Bands 3, 4, 5, 6, 7, and 8 at high-resolution (0.5" - 0.1") for 16 bright southern Herschel sources at $1.5 < z < 4.2$. With only six and a half hours of observations, we reveal 66 spectral lines in 17 galaxies. These observations detect emission from CO (3-2) to CO(18-17), as well as atomic ([CI](1-0), (2-1), [OI] 145 $μ$m and [NII] 205 $μ$m) lines. Additional molecular lines are seen in emission (${\rm H_2O}$ and ${\rm H_2O^+}$) and absorption (OH$^+$ and CH$^+$). The morphologies based on dust continuum ranges from extended sources to strong lensed galaxies with magnifications between 2 and 30. CO line transitions indicate a diverse set of excitation conditions with a fraction of the sources ($\sim 35$%) showcasing dense, warm gas. The resolved gas to star-formation surface densities vary strongly per source, and suggest that the observed diversity of dusty star-forming galaxies could be a combination of lensed, compact dusty starbursts and extended, potentially-merging galaxies. The predicted gas depletion timescales are consistent with 100 Myr to 1 Gyr, but require efficient fueling from the extended gas reservoirs onto the more central starbursts, in line with the Doppler-shifted absorption lines that indicate inflowing gas for two out of six sources. This pilot paper explores a successful new method of observing spectral lines in large samples of galaxies, supports future studies of larger samples, and finds that the efficiency of this new observational method will be further improved with the planned ALMA Wideband Sensitivity Upgrade.

astro-ph.GA↗

arXiv2024

Toward the measurement of neutrino masses: Performance of cosmic magnification with submillimeter galaxies

The phenomenon of magnification bias can induce a non-negligible angular correlation between two samples of galaxies with nonoverlapping redshift distributions. This signal is particularly clear when background submillimeter galaxies are used, and has been shown to constitute an independent cosmological probe. This work extends prior studies on the submillimeter galaxy magnification bias to the massive neutrino scenario, with the aim being to assess its sensitivity as a cosmological observable to the sum of neutrino masses. The measurements of the angular cross-correlation function between moderate redshift GAMA galaxies and high-redshift submillimeter H-ATLAS galaxies are fit to the weak lensing prediction down to the arcmin scale. The signal is interpreted under the halo model, which is modified to accommodate massive neutrinos. We discuss the impact of the choice of cosmological parametrization on the sensitivity to neutrino masses. The currently available data on the magnification bias affecting submillimeter galaxies are sensitive to neutrino masses when a cosmological parametrization in terms of the primordial amplitude of the power spectrum $(A_s$) is chosen over the local root mean square of smoothed linear density perturbations $(σ_8$). A clear upper limit on the sum of neutrino masses can be derived if the value of $A_s$ is either fixed or assigned a narrow Gaussian prior, a behavior that is robust against changes to the chosen value.

astro-ph.CO↗

arXiv2024

Methodological refinement of the submillimeter galaxy magnification bias. II. Cosmological analysis with tomography

This paper is the third in a series on submillimeter galaxy magnification bias, focusing on the tomographic scenario. It refines the methodology used to constrain the halo occupation distribution model and cosmological parameters within a flat $Λ$CDM model, using updated data. The study aims to optimize CPU time, explore strategies for analyzing different redshift bins, and assess the impact of excluding the GAMA15 field. The tomographic approach involves dividing the redshift range into bins and analyzing cross-correlation measurements between submillimeter and foreground galaxies. The results show good agreement between the mean-redshift and full model cases, with an increase in the minimum mass of lenses at higher redshifts. The inferred cosmological parameters have narrower posterior distributions, indicating reduced measurement uncertainties compared to previous studies. Excluding the GAMA15 field reduces the cross-correlation signal, suggesting sample variance within the large-scale structure. Extending the redshift range improves robustness against sample variance and produces similar but tighter constraints. The study highlights the importance of sample variance and redshift binning in tomographic analyses, and suggests using additional wide-area fields and updated foreground catalogues for more effective implementation.

astro-ph.CO↗

arXiv2024

Mass density profiles at kiloparsec scales using the sub-millimetre galaxies magnification bias

Gravitational lensing is a powerful tool for studying the distribution of mass in the Universe. Understanding the magnification bias effect in gravitational lensing and its impact on the flux of sub-millimetre galaxies (SMGs) is crucial for accurate interpretations of observational data. This study aims to investigate the magnification bias effect and analyse the mass density profiles of different types of foreground lenses, including quasi-stellar objects, galaxies, and clusters. The specific goals are to compare the lens types, assess the impact of angular resolution on the analysis, and determine the adequacy of theoretical mass density profiles in explaining the observed data, using four different theoretical mass density profiles. The magnification bias was estimated using the cross-correlation function between the positions of background SMGs and foreground lens samples. Stacking techniques were employed to enhance the signal at smaller angular separations, and the more precise positions from the WISE catalogue were utilised to improve positional accuracy. The cross-correlation measurements revealed distinctive central excess and outer power-law profiles, with a lack of signal in the intermediate region. The analysis of mass density profiles indicated limitations in the selected profiles' ability to explain the observed data, highlighting the need for additional considerations. The results suggest the presence of isolated galactic halos and the importance of considering environmental factors and close satellites in future investigations. The derived masses and best-fit parameters contribute to our understanding of lensing systems and provide constraints on the nature of central galaxies. Notably, the intriguing lack of signal around 10 arcsec challenges current understanding and calls for further quantitative analysis and confirmation of the observed feature.

astro-ph.GA↗

arXiv2023

Constraining the polarisation flux density and angle of point sources by training a convolutional neural network

Constraining the polarisation properties of extragalactic point sources is a relevant task not only because they are one of the main contaminants for primordial cosmic microwave background B-mode detection if the tensor-to-scalar ratio is lower than r = 0.001, but also for a better understanding of the properties of radio-loud active galactic nuclei. We develop and train a machine learning model based on a convolutional neural network to learn how to estimate the polarisation flux density and angle of point sources embedded in cosmic microwave background images knowing only their positions. To train the neural network, we use realistic simulations of patches of area 32x32 pixels at the 217 GHz Planck channel with injected point sources at their centres. The patches also contain a realistic background composed by dust, the CMB and instrumental noise. Firstly, we study the comparison between true and estimated polarisation flux densities for P, Q and U. Secondly, we analyse the comparison between true and estimated polarisation angles. Finally, we study the performance of our model with real data and we compare our results against the PCCS2. We obtain that our model is reliable to constrain the polarisation flux above 80 mJy. For this limit, we obtain errors lower than 30%. Training the same network with Q and U, the reliability limit is above +-250 mJy for determining the polarisation angle of both Q and U sources with a 1sigma uncertainty of +-29deg and +-32deg for Q and U sources respectively. We obtain similar results to the PCCS2 for some sources, although we also find discrepancies in the 300-400 mJy flux density range with respect to the Planck catalogue. Based on these results, our model seems to be a promising tool to give estimations of the polarisation flux densities and angles of point sources above 80 mJy in any catalogue with practically null computational time.

astro-ph.CO↗

arXiv2022

Quasi-stellar objects and galaxy mass density profiles derived using the submillimetre galaxies magnification bias

In this work, we want to exploit the magnification bias of the SMGs using two different foreground samples, quasi-stellar objects (QSOs) and galaxies. Our aim is to study and compare their mass density profiles and estimate their masses and concentrations. The background SMG sample consists of objects observed by \textit{Herschel} with 1.2<z<4.0. The foreground samples are QSOs and massive galaxies with spectroscopic redshifts between 0.2 and 1.0. The cross-correlation measurements are estimated with the Davis-Peebles estimator by stacking the SMG-QSO and SMG-galaxy pairs for the two analysed cases, respectively. This approach allows us to study the mass density profile from $\sim2$ to $\sim250$ arcsec. Moreover, the analysis is carried out by combining two of the most common theoretical mass density profiles in order to fit the cross-correlation measurements. The measurements are correctly fitted after splitting the available angular scales into an inner and an outer part using independent mass density profiles for each region. For the QSOs, we obtain masses and concentrations of $\log_{10}(M/M_{\odot})=13.51\pm0.04; C=6.85\pm0.34$ for the inner part and $\log_{10}(M/M_{\odot})=13.44\pm0.17; C=0.36\pm0.18$ for outer parts. For the galaxy sample are $\log_{10}(M/M_{\odot})=13.32\pm0.08; C=8.23\pm0.77$ and $\log_{10}(M/M_{\odot})=12.78\pm0.21; C=1.21\pm1.01$ for the inner and outer parts, respectively. In both samples, the inner part has an excess in the mass density profile and much higher concentration with respect to the outer part. We obtain similar values for the central mass with both samples, in agreement with those of galaxy clusters results. However, the estimated masses for the outer region and the concentrations of the inner region both vary with lens sample. This could be related to the probability of galactic interactions and/or the different evolutionary stages.

astro-ph.GA↗

arXiv2022

CENN: A fully convolutional neural network for CMB recovery in realistic microwave sky simulations

Component separation is the process with which emission sources in astrophysical maps are generally extracted by taking multi-frequency information into account. It is crucial to develop more reliable methods for component separation for future CMB experiments. We aim to develop a new method based on fully convolutional neural networks called the Cosmic microwave background Extraction Neural Network (CENN) in order to extract the CMB signal in total intensity. The frequencies used are the Planck channels 143, 217 and 353 GHz. We validate the network at all sky, and at three latitude intervals: lat1=0^{\circ}<b<5^{\circ}, lat2=5^{\circ}<b<30^{\circ} and lat3=30^{\circ}<b<90^{\circ}, without using any Galactic or point source masks. For training, we make realistic simulations in the form of patches of area 256 pixels, which contain the CMB, Dust, CIB and PS emissions, Sunyaev-Zel'dovich effect and the instrumental noise. After validate the network, we compare the power spectrum from input and output maps. We analyse the power spectrum from the residuals at each latitude interval and at all sky and we study the performance of our model dealing with high contamination at small scales. We obtain a power spectrum with an error of 13{\pm}113 μK^2 for multipoles up to above 4000. For residuals, we obtain 700{\pm}60 μK^2 for lat1, 80{\pm}30 μK^2 for lat2 and 30{\pm}20 μK^2 for lat3. For all sky, we obtain 20{\pm}10 μK^2. We validate the network in a patch with strong contamination at small scales, obtaining an error of 50{\pm}120 μK^2 and residuals of 40{\pm}10 μK^2. Therefore, fully convolutional neural networks are promising methods to perform component separation in future CMB experiments. Particularly, CENN is reliable against different levels of contamination from Galactic and point source foregrounds at both large and small scales.

astro-ph.CO↗

arXiv2022

Selecting a complete sample of blazars in sub-millimetre catalogues

The \textit{Herschel} Astrophysical Terahertz Large Area Survey (H-ATLAS), that has covered about 642 sq. deg. in 5 bands from 100 to 500 $μ\rm m$, allows a blind flux-limited selection of blazars at sub-mm wavelengths. However, blazars constitute a tiny fraction of H-ATLAS sources and therefore identifying them is not a trivial task. Using the data on known blazars detected by the H-ATLAS we have defined a locus for 500\,$μ$m selected blazars and exploited it to select blazar candidates in the H-ATLAS fields. Candidates and known blazars in the H-ATLAS equatorial and South Galactic Pole fields were followed up with the Australia Telescope Compact Array (ATCA) or with the Karl G. Jansky Very Large Array (VLA), and matched with existing radio- and mm-catalogues to reconstruct the spectral behaviour over at least 6 orders of magnitude in frequency. We identified a selection approach that, combining the information in the sub-mm and radio domains, efficiently singles out genuine blazars. In this way, we identified a sample of 39 blazars brighter than $S_{500μ\rm m} = 35\,$mJy in the H-ATLAS fields. Tests made cross-matching the H-ATLAS catalogues with large catalogues of blazar candidates indicate that the sample is complete. The derived counts are compared with model predictions finding good consistency with the C2Ex model and with estimates based on ALMA data.

astro-ph.GA↗

arXiv2022

Tomography-based observational measurements of the halo mass function via the submillimeter magnification bias

Aims. The main goal of this paper is to derive observational constraints on the halo mass fuction (HMF) by performing a tomographic analysis of the magnification bias signal on a sample of background submillimeter galaxies. The results can then be compared with those from a non-tomographic study. Methods. We measure the cross-correlation function between a sample of foreground GAMA galaxies with spectroscopic redshifts in the range $0.1 < z < 0.8$ (and divided up into four bins) and a sample of background submillimeter galaxies from H-ATLAS with photometric redshifts in the range $1.2 < z < 4.0$. We model the weak lensing signal within the halo model formalism and carry out a Markov chain Monte Carlo algorithm to obtain the posterior distribution of all HMF parameters, which we assume to follow the Sheth and Tormen (ST) three-parameter and two-parameter fits. Results. While the observational constraints on the HMF from the non-tomographic analysis are not stringent, there is a remarkable improvement in terms of uncertainty reduction when tomography is adopted. Moreover, with respect to the traditional ST triple of values from numerical simulations, the results from the three-parameter fit predict a higher number density of halos at masses below $10^{12}M_{\odot}/h$ at 95% credibility. The two-parameter fit yields even more restricting results, with a larger number density of halos below $10^{13}M_{\odot}/h$ and a lower one above $10^{14}M_{\odot}/h$, this time at more than 3$σ$ credibility. Our results are therefore in disagreement with the standard N-body values for the ST fit at 2$σ$ and 3$σ$, respectively.

astro-ph.CO↗

arXiv2021

Multi-frequency point source detection with fully convolutional networks: Performance in realistic microwave sky simulations

Point Source (PS) detection is an important issue for future Cosmic Microwave Background (CMB) experiments since they are one of the main contaminants to the recovery of CMB signal at small scales. Improving its multifrequency detection would allow to take into account valuable information otherwise neglected when extracting PS using a channel-by-channel approach. We develop a method based on Neural Networks (NNs) to detect PS in multifrequency realistic simulations and compare its performance against one of the most popular methods, the matrix filters. The frequencies used are 143, 217 and 353 GHz and we impose a Galactic cut of 30 degrees. We produce simulations by adding contaminating signals to the PS maps as the CMB, the Cosmic Infrared Background, the Galactic thermal emission, the thermal Sunyaev-Zel'dovich effect and the instrumental noise. These simulations are used to train two NNs called Flat and Spectral MultiPoSeIDoN. The first one considers PS with a flat spectrum and the second one is more realistic because it takes into account the spectral behavior of the PS. Using a detection limit of 60 mJy, Flat MultiPoSeIDoN reachs the 90% of completeness level at 58 mJy and at 79, 71 and 60 for the spectral case at 143, 217 and 353 GHz respectively, while the matrix filters reach it at 84, 79 and 123 mJy. Using safer 4σ detection limit does not help to improve these results. In all cases, MultiPoSeIDoN obtain a much lower number of spurious sources than the filter. The NNs recover the flux density of the detections with a relative error of 10% above 100 mJy, while the filter above 150 mJy. Based on the results, NNs are the perfect candidates to substitute filters to detect multifrequency PS in future CMB experiments. Moreover, we have shown that a multifrequency approach can detect sources with higher accuracy than single-frequency approaches also based on NNs.

astro-ph.IM↗

arXiv2021

Cosmological and astrophysical results exploiting magnification bias with high-z sub-millimetre galaxies

The high-z submillimeter galaxies (SMGs) can be used as background sample for gravitational lensing studies thanks to their magnification bias, which can manifest itself through a non-negligible measurement of the cross-correlation function between a background and a foreground source sample with non-overlapping redshift distributions. In particular, the choice of SMGs as background sample enhances the cross-correlation signal so as to provide an alternative and independent observable for cosmological studies regarding the probing of mass distribution. In particular the magnification bias can be exploited in order to constrain the free astrophysical parameters of a Halo Occupation Distribution model and some of the main cosmological parameters. Urged by the improvements obtained when adopting a pseudo-tomographic analysis, It has been adopted a tomographic set-up to explore not only a $Λ$CDM scenario, but also the possible time evolution of the dark energy density in the $ω_0$CDM and $ω_0ω_a$CDM frameworks.

astro-ph.CO↗