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Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine learning algorithms can not estimate error directly, making them unsuitable for reliable science. Aims: We aim to train a supervised deep-learning algorithm tailored for high-resolution observational stellar spectra. This algorithm accurately infer precise estimates while providing coherent estimates of uncertainties by leveraging information from both the neural network and the spectra. Methods: We train a conditional Invertible Neural Network (cINN) on observational spectroscopic data obtained from the GIRAFFE spectrograph (HR10 and HR21 setups) within the Gaia-ESO survey. A key features of cINN is its ability to produce the Bayesian posterior distribution of parameters for each spectrum. By analyzing this distribution, we inferred parameters and their uncertainties. Several tests have been applied to study how parameters and errors are estimated. Results: We achieved an accuracy of 28K in $T_{\text{eff}}$, 0.06 dex in $\log g$, 0.03 dex in $[\text{Fe/H}]$, and between 0.05 dex and 0.17 dex for the other abundances for high quality spectra. Accuracy remains stable with low signal-to-noise ratio spectra. The uncertainties obtained are well within the same order of magnitude. The network accurately reproduces astrophysical relationships both on the scale of the Milky Way and within smaller star clusters. We created a table containing the new parameters generated by our cINN. Conclusion: This neural network represents a compelling proposition for future astronomical surveys. These coherent derived uncertainties make it possible to reuse these estimates in other works as Bayesian priors and thus present a solid basis for future work., Comment: Accepted for publication in A&A

We present spatially resolved, simple stellar population equivalent ages, stellar metallicities, and abundance ratios for 456 massive ($10.3\lesssim\log(\mathrm{M}_*/\mathrm{M}_\odot)\lesssim11.8$) quiescent galaxies at $0.6\lesssim z\lesssim1.0$ from the Large Early Galaxy Astrophysics Census, derived using full-spectrum models. Typically, we find flat age and [Mg/Fe] gradients, and negative [Fe/H] gradients, implying iron-rich cores. We also estimate intrinsic [Fe/H] gradients via forward modelling. We examine the observed gradients in three age bins. Younger quiescent galaxies typically have negative [Fe/H] gradients and positive age gradients, possibly indicating a recent central starburst. Additionally, this finding suggests that photometrically measured flat colour gradients in young quiescent galaxies are the result of the positive age and negative metallicity gradients cancelling each other. For older quiescent galaxies, the age gradients become flat and [Fe/H] gradients weaken, though remain negative. Thus, negative colour gradients at older ages are likely driven by metallicity gradients. The diminishing age gradient may result from the starburst fading. Furthermore, the persistence of the [Fe/H] gradients may suggest that the outskirts are simultaneously built up by mergers with lower metallicity satellites. On the other hand, the gradients could be inherited from the star-forming phase, in which case mergers may not be needed to explain our findings. This work illustrates the need for resolved spectroscopy, instead of just photometry, to measure stellar population gradients. Extending these measurements to higher redshift is imperative for understanding how stellar populations in quiescent galaxies are assembled over cosmic time., Comment: Accepted for publication in MNRAS; minor typesetting corrections after copyediting

The WHT Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph. This new instrument will be exploited to obtain high S/N spectra of $\sim$25000 galaxies at intermediate redshifts for the WEAVE Stellar Population Survey (WEAVE-StePS). We test machine learning methods for retrieving the key physical parameters of galaxies from WEAVE-StePS-like spectra using both photometric and spectroscopic information at various S/Ns and redshifts. We simulated $\sim$105000 galaxy spectra assuming SFH with an exponentially declining star formation rate, covering a wide range of ages, stellar metallicities, sSFRs, and dust extinctions. We then evaluated the ability of the random forest and KNN algorithms to correctly predict such parameters assuming no measurement errors. We checked how much the predictive ability deteriorates for different S/Ns and redshifts, finding that both algorithms still accurately estimate the ages and metallicities with low bias. The dispersion varies from 0.08-0.16 dex for ages and 0.11-0.25 dex for metallicity, depending on the redshift and S/N. For dust attenuation, we find a similarly low bias and dispersion. For the sSFR, we find a very good constraining power for star-forming galaxies, log sSFR$\gtrsim$ -11, where the bias is $\sim$ 0.01 dex and the dispersion is $\sim$ 0.10 dex. For more quiescent galaxies, with log sSFR$\lesssim$ -11, we find a higher bias, 0.61-0.86 dex, and a higher dispersion, $\sim$ 0.4 dex, for different S/Ns and redshifts. Generally, we find that the RF outperforms the KNN. Finally, the retrieved sSFR was used to successfully classify galaxies as part of the blue cloud, green valley, or red sequence. We demonstrate that machine learning algorithms can accurately estimate the physical parameters of simulated galaxies even at relatively low S/N=10 per angstrom spectra with available ancillary photometric information., Comment: 19 pages, 10 + 2 figures, 4 tables, accepted in A&A

The Wide-field Spectroscopic Telescope (WST) is proposed as a new facility dedicated to the efficient delivery of spectroscopic surveys. This white paper summarises the initial concept as well as the corresponding science cases. WST will feature simultaneous operation of a large field-of-view (3 sq. degree), a high multiplex (20,000) multi-object spectrograph (MOS) and a giant 3x3 sq. arcmin integral field spectrograph (IFS). In scientific capability these requirements place WST far ahead of existing and planned facilities. Given the current investment in deep imaging surveys and noting the diagnostic power of spectroscopy, WST will fill a crucial gap in astronomical capability and work synergistically with future ground and space-based facilities. This white paper shows that WST can address outstanding scientific questions in the areas of cosmology; galaxy assembly, evolution, and enrichment, including our own Milky Way; origin of stars and planets; time domain and multi-messenger astrophysics. WST's uniquely rich dataset will deliver unforeseen discoveries in many of these areas. The WST Science Team (already including more than 500 scientists worldwide) is open to the all astronomical community. To register in the WST Science Team please visit https://www.wstelescope.com/for-scientists/participate, Comment: 194 pages, 66 figures. Comments are welcome (wstelescope@gmail.com)

We test whether we can predict optical spectra from deep-field photometry of distant galaxies. Our goal is to perform a comparison in data space, highlighting the differences between predicted and observed spectra. The Large Early Galaxy Astrophysics Census (LEGA-C) provides high-quality optical spectra of thousands of galaxies at redshift $0.6

We employ a recently developed population-orbit superposition technique to simultaneously fit the stellar kinematic and age maps of 82 CALIFA spiral galaxies and obtain the ages of stars in different dynamical structures. We first evaluated the capabilities of this method on CALIFA-like mock data created from the Auriga simulations. The recovered mean ages of dynamically cold, warm, and hot components match the true values well, with an observational error of up to $20\%$ in the mock age maps. For CALIFA spiral galaxies, we find that the stellar ages of the cold, warm, and hot components all increase with the stellar mass of the galaxies, from $\overline{t_{\rm cold}}\sim2.2$ Gyr, $\overline{t_{\rm warm}}\sim2.3$ Gyr, and $\overline{t_{\rm hot}}\sim2.6$ Gyr for galaxies with stellar mass $M_*<10^{10}\,\rm M_{\odot}$, to $\overline{t_{\rm cold}}\sim4.0$ Gyr, $\overline{t_{\rm warm}}\sim5.1$ Gyr, and $\overline{t_{\rm hot}}\sim5.9$ Gyr for galaxies with $M_*>10^{11}\,\rm M_{\odot}$. About $80\%$ of the galaxies in our sample have $t_{\rm hot}>t_{\rm cold}$, and the mean values of $t_{\rm hot}-t_{\rm cold}$ also increase with stellar mass, from $0.7_{-0.2}^{+0.6}$ Gyr in low-mass galaxies ($10^{8.9}\,\rm M_{\odot}

This paper presents the third data release of the INvestigating Stellar Population In RElics (INSPIRE) project, comprising 52 ultra-compact massive galaxies (UCMGs) observed with the X-Shooter spectrograph. We measure integrated stellar velocity dispersion, [Mg/Fe] abundances, ages, and metallicities for all the INSPIRE objects. We thus infer star formation histories and confirm the existence of a degree of relicness (DoR), defined in terms of the fraction of stellar mass formed by $z=2$, the time at which a galaxy has assembled 75\% of its mass, and the final assembly time. Objects with a high DoR assembled their stellar mass at early epochs, while low-DoR objects show a non-negligible fraction of later-formed populations and hence a spread in ages and metallicities. A higher DoR correlates with larger [Mg/Fe], super-solar metallicity, and larger velocity dispersion values. The 52 UMCGs span a large range of DoR from 0.83 to 0.06, with 38 of them having formed more than 75\% of their mass by $z=2$. Of these, nine are extreme relics (DoR$>0.7$), since they formed the totality ($>99\%$) of their stellar mass by redshift $z=2$. The remaining 14 UCMGs cannot be considered relics, as they are characterised by more extended star formation histories. With INSPIRE, we built the first sizeable sample of relics outside the local Universe, up to $z\sim0.4$, increasing the number of confirmed relics by a factor of $>10$, and opening up an important window to explain the mass assembly of massive galaxies in the high-z Universe., Comment: accepted for publication on MNRAS, 20 pages, 15 figures, 3 tables

The upcoming generation of optical spectrographs on four meter-class telescopes, with their huge multiplexing capabilities, excellent spectral resolution, and unprecedented wavelength coverage, will provide high-quality spectra for thousands of galaxies. These data will allow us to examine of the stellar population properties at intermediate redshift, an epoch that remains unexplored by large and deep surveys. We assess our capability to retrieve the mean stellar metallicity in galaxies at different redshifts and S/N, while simultaneously exploiting the UV and optical rest-frame wavelength coverage. The work is based on a comprehensive library of spectral templates of stellar populations, covering a wide range of age and metallicity values and built assuming various SFHs. We simulated realistic observations of a large sample of galaxies carried out with WEAVE at the WHT at different redshifts and S/N values. We measured all the reliable indices on the simulated spectra and on the comparison library. We then adopted a Bayesian approach to obtain the probability distribution of stellar metallicity. The analysis of the spectral indices has shown how some mid-UV indices can provide reliable constraints on stellar metallicity, along with optical indicators. The analysis of the mock observations has shown that even at S/N=10, the metallicity can be derived within 0.3 dex, in particular, for stellar populations older than 2 Gyr. Our results are in good agreement with other theoretical and observational works in the literature and show how the UV indicators can be advantageous in constraining metallicities. This is very promising for the upcoming surveys carried out with new, highly multiplexed, large-field spectrographs, such as StePS at the WEAVE and 4MOST, which will provide spectra of thousands of galaxies covering large spectral ranges at relatively high S/N., Comment: 16 pages, 14 figures. Submitted 31/03/2023, Accepted 20/07/2023

We present individual star-formation histories of $\sim3000$ massive galaxies (log($\mathrm{M_*/M_{\odot}}$) > 10.5) from the Large Early Galaxy Astrophysics Census (LEGA-C) spectroscopic survey at a lookback time of $\sim$7 billion years and quantify the population trends leveraging 20hr-deep integrated spectra of these $\sim$ 1800 star-forming and $\sim$ 1200 quiescent galaxies at 0.6 < $z$ < 1.0. Essentially all galaxies at this epoch contain stars of age < 3 Gyr, in contrast with older massive galaxies today, facilitating better recovery of previous generations of star formation at cosmic noon and earlier. We conduct spectro-photometric analysis using parametric and non-parametric Bayesian SPS modeling tools - Bagpipes and Prospector to constrain the median star-formation histories of this mass-complete sample and characterize population trends. A consistent picture arises for the late-time stellar mass growth when quantified as $t_{50}$ and $t_{90}$, corresponding to the age of the universe when galaxies formed 50\% and 90\% of their total stellar mass, although the two sets of models disagree at the earliest formation times (e.g. $t_{10}$). Our results reveal trends in both stellar mass and stellar velocity dispersion as in the local universe - low-mass galaxies with shallower potential wells grow their stellar masses later in cosmic history compared to high-mass galaxies. Unlike local quiescent galaxies, the median duration of late-time star-formation ($\tau_{SF,late}$ = $t_{90}$ - $t_{50}$) does not consistently depend on the stellar mass. This census sets a benchmark for future deep spectro-photometric studies of the more distant universe., Comment: 28 pages, 12 figures, 4 tables, Accepted to ApJ

We present the first study of spatially integrated higher-order stellar kinematics over cosmic time. We use deep rest-frame optical spectroscopy of quiescent galaxies at redshifts z=0.05, 0.3 and 0.8 from the SAMI, MAGPI and LEGA-C surveys to measure the excess kurtosis $h_4$ of the stellar velocity distribution, the latter parametrised as a Gauss-Hermite series. Conservatively using a redshift-independent cut in stellar mass ($M_\star = 10^{11}\,{\rm M}_\odot$), and matching the stellar-mass distributions of our samples, we find 7 $\sigma$ evidence of $h_4$ increasing with cosmic time, from a median value of 0.019$\pm$0.002 at z=0.8 to 0.059$\pm$0.004 at z=0.06. Alternatively, we use a physically motivated sample selection, based on the mass distribution of the progenitors of local quiescent galaxies as inferred from numerical simulations; in this case, we find 10 $\sigma$ evidence. This evolution suggests that, over the last 7 Gyr, there has been a gradual decrease in the rotation-to-dispersion ratio and an increase in the radial anisotropy of the stellar velocity distribution, qualitatively consistent with accretion of gas-poor satellites. These findings demonstrate that massive galaxies continue to accrete mass and increase their dispersion support after becoming quiescent., Comment: 19 pages, 9 figures Accepted for publication in MNRAS

We present the first statistical study of spatially integrated non-Gaussian stellar kinematics spanning 7 Gyr in cosmic time. We use deep, rest-frame optical spectroscopy of massive galaxies (stellar mass $M_\star > 10^{10.5} {\rm M}_\odot$) at redshifts z = 0.05, 0.3 and 0.8 from the SAMI, MAGPI and LEGA-C surveys, to measure the excess kurtosis $h_4$ of the stellar velocity distribution, the latter parametrised as a Gauss-Hermite series. We find that at all redshifts where we have large enough samples, $h_4$ anti-correlates with the ratio between rotation and dispersion, highlighting the physical connection between these two kinematic observables. In addition, and independently from the anti-correlation with rotation-to-dispersion ratio, we also find a correlation between $h_4$ and $M_\star$, potentially connected to the assembly history of galaxies. In contrast, after controlling for mass, we find no evidence of independent correlation between $h_4$ and aperture velocity dispersion or galaxy size. These results hold for both star-forming and quiescent galaxies. For quiescent galaxies, $h_4$ also correlates with projected shape, even after controlling for the rotation-to-dispersion ratio. At any given redshift, star-forming galaxies have lower $h_4$ compared to quiescent galaxies, highlighting the link between kinematic structure and star-forming activity., Comment: 26 pages, 15 figures Accepted for publication in MNRAS

We present a nonparametric morphology analysis of the stellar continuum and nebular emission lines for a sample of local galaxies. We explore the dependence of the various morphological parameters on wavelength and morphological type. Our goal is to quantify the difference in morphology between the stellar and nebular components. We derive the nonparametric morphological indicators of 364 galaxies from the CALIFA Survey. To calculate those indicators, we apply the StatMorph package on the high-quality integral field spectroscopic data cubes, as well as to the most prominent nebular emission-line maps, namely [OIII]$\lambda$5007, H$\alpha$, and [NII]$\lambda$6583. We show that the physical size of galaxies, M$_{20}$ index, and concentration have a strong gradient from blue to red optical wavelengths. We find that the light distribution of the nebular emission is less concentrated than the stellar continuum. A comparison between the nonparametric indicators and the galaxy physical properties revealed a very strong correlation of the concentration with the specific star-formation rate and morphological type. Furthermore, we explore how the galaxy inclination affects our results. We find that edge-on galaxies show a more rapid change in physical size and concentration with increasing wavelength due to the increase in optical free path. We conclude that the apparent morphology of galaxies originates from the pure stellar distribution, but the morphology of the ISM presents differences with respect to the morphology of the stellar component. Our analysis also highlights the importance of dust attenuation and galaxy inclination in the measurement of nonparametric morphological indicators, especially in the the wavelength range 4000-5000 \r{A}.

The upcoming new generation of optical spectrographs on four-meter-class telescopes will provide valuable opportunities for forthcoming galaxy surveys through their huge multiplexing capabilities, excellent spectral resolution, and unprecedented wavelength coverage. WEAVE is a new wide-field spectroscopic facility mounted on the 4.2 m William Herschel Telescope in La Palma. WEAVE-StePS is one of the five extragalactic surveys that will use WEAVE during its first five years of operations. It will observe galaxies using WEAVE MOS (~950 fibres across a field of view of ~3 deg2 on the sky) in low-resolution mode (R~5000, spanning the wavelength range 3660-9590 AA). WEAVE-StePS will obtain high-quality spectra (S/N ~ 10 per AA at R~5000) for a magnitude-limited (I_AB = 20.5) sample of ~25,000 galaxies, the majority selected at z>=0.3. The survey goal is to provide precise spectral measurements in the crucial interval that bridges the gap between LEGA-C and SDSS data. The wide area coverage of ~25 deg2 will enable us to observe galaxies in a variety of environments. The ancillary data available in each observed field (including X-ray coverage, multi-narrow-band photometry and spectroscopic redshift information) will provide an environmental characterisation for each observed galaxy. This paper presents the science case of WEAVE-StePS, the fields to be observed, the parent catalogues used to define the target sample, and the observing strategy chosen after a forecast of the expected performance of the instrument for our typical targets. WEAVE-StePS will go back further in cosmic time than SDSS, extending its reach to encompass more than ~6 Gyr, nearly half of the age of the Universe. The spectral and redshift range covered by WEAVE-StePS will open a new observational window by continuously tracing the evolutionary path of galaxies in the largely unexplored intermediate-redshift range., Comment: 15 pages, 9 figures, A&A in press

This is the second data release (DR2) of the INvestigating Stellar Population In RElics (INSPIRE) project, comprising 21 new systems with observations completed before March 2022. For each system, we release four one-dimensional (1D) spectra to the ESO Science Archive, one spectrum for each arm of the X-Shooter spectrograph. In this paper, we focus on the line-of-sight velocity distribution, measuring integrated stellar velocity dispersions from the spectra, and assessing their robustness and the associated uncertainties. For each of the 21 new systems, we systematically investigated the effect of the parameters and set-ups of the full spectral fitting on the stellar velocity dispersion ($\sigma$) measurements. In particular, we tested how $\sigma$ changes when several parameters of the fit as well as the resolution and spectral coverage of the input spectra are varied. We found that the effect that causes the largest systematic uncertainties on $\sigma$ is the wavelength range used for the fit, especially for spectra with a lower signal-to-noise ratio (S/N $\leq$ 30). When using blue wavelengths (UVB arm) one generally underestimates the velocity dispersion (by $\sim$15 km/s). The values obtained from the near-IR (NIR) arm present a larger scatter because the quality of the spectra is lower. We finally compared our results with those in literature, finding a very good agreement overall. Joining results obtained in DR1 with those presented here, INSPIRE contains 40 ultra-compact massive galaxies, corresponding to 75% of the whole survey. By plotting these systems in a stellar mass-velocity dispersion diagram, we identify at least four highly reliable relic candidates among the new systems. Their velocity dispersion is larger than that of normal-sized galaxies of similar stellar mass., Comment: Accepted for publication, and in press on A&A

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z<0.5$ cluster galaxies; (vi) survey stellar populations and kinematics in $\sim25\,000$ field galaxies at $0.3\lesssim z \lesssim 0.7$; (vii) study the cosmic evolution of accretion and star formation using $>1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator., Comment: 41 pages, 27 figures, accepted for publication by MNRAS; updated version including information on individual grants in a revised Acknowledgements section, corrections to the affiliation list, and an updated references list

Purpose: To optimize the choice of the flip-angles of magnetization-prepared gradient echo (MP-GRE) sequences for improved accuracy, precision, and speed of 3D-T1rho mapping. Methods: We propose a new optimization approach for finding variable flip-angle (VFA) values that improve MP-GRE sequences used for 3D-T1\r{ho} mapping. This new approach can simultaneously improve the accuracy and signal-to-noise ratio (SNR) while reducing filtering effects. We demonstrate the concept in the three different versions of the MP-GRE sequences that are typically used for 3D-T1rho mapping and evaluate their performance in model agarose phantoms (n=6) and healthy volunteers (n=5) for knee joint imaging. We also tested the optimization with sequence parameters targeting faster acquisitions. Results: Our results show that optimized VFA can improve the accuracy and the precision of the sequences, seen as a reduction of the mean of normalized absolute difference (MNAD) from 6~8% to 4~5% in model phantoms and from 14~22% to 12~14% in the knee joint, and improving SNR from 12~27 to 24~35 in agarose phantoms and 5~13 to 11~16 in healthy volunteers. The optimization can also compensate for the loss in quality caused by making the sequence faster. This results in sequence configurations that acquire nearly twice more data per unit of time with similar SNR and MNAD measurements as compared to its slower versions. Conclusion: The optimization of the VFA can be used to increase accuracy and precision, and improve the speed of the typical imaging sequences used for quantitative 3D-T1rho mapping of the knee joint.

Dissecting the underlying structure of galaxies is of main importance in the framework of galaxy formation and evolution theories. While a classical bulge+disc decomposition of disc galaxies is usually taken as granted, this is only rarely solidly founded upon the full exploitation of the richness of data arising from spectroscopic studies with integral field units. In this work we describe a fully Bayesian estimation method of the global structure of disc galaxies which makes use of the wealth of photometric, kinematic, and mass-to-light ratio data, and that can be seen as a first step towards a machine-learning approach, certainly needed when dealing with larger samples of galaxies. Ours is a novel, hybrid line of action in tackling the problem of galactic parameter estimation, neither purely photometric nor orbit-based. Being rooted on a nested sampler, our code, which is available publicly as an online repository, allows for a statistical assessment of the need for multiple components in the dissecting process. As a first case-study the GPU-optimized code is applied to the S0 galaxy NGC-7683, finding that in this galaxy a pseudo-bulge, possibly the remnant of a bar-like structure, does exist in the center of the system. These results are then tested against the publicly available, orbit-based code DYNAMITE, finding substantial agreement., Comment: 14 pages, 7 figures, accepted for publication in MNRAS

The properties of the stellar populations in a galaxy are known to correlate with the amount and the distribution of stellar mass. We take advantage of the maps of light-weighted mean stellar age Agewr and metallicity Z*wr for a sample of 362 galaxies from the integral-field spectroscopic survey CALIFA (summing up to >600,000 individual regions of approximately 1 kpc linear size), produced in our previous works, to investigate how these local properties react to the local stellar-mass surface density mu* and to the global total stellar mass M* and mean stellar-mass surface density e. We establish the existence of i) a dual mu*-Agewr relation, resulting in a young sequence and an old ridge, and ii) a mu*-Z*wr relation, overall independent of the age of the regions. The global mass parameters (M* and, possibly secondarily, e) determine the distribution of mu* in a galaxy and set the maximum attainable mu*, which increases with M*. M* affects the shape and normalization of the local relations up to a threshold mass of $\sim 10^{10.3}$ MSun, above which they remain unchanged. We conclude that stellar mass is a "glocal" (i.e. simultaneously global and local) driver of the stellar population properties. We consider how the local and global mass-age and mass-metallicity relations are connected, and in particular discuss how it is possible, from a single local relation, to produce two different global mass-metallicity relations for quiescent and star-forming galaxies respectively, as reported in the literature. Structural differences in these two classes of galaxies are key to explain the duality in global scaling relations and appear as essential in modelling the baryonic cycle of galaxies., Comment: Accepted for publication on MNRAS

Purpose: To propose an alternating learning approach to learn the sampling pattern (SP) and the parameters of variational networks (VN) in accelerated parallel magnetic resonance imaging (MRI). Methods: The approach alternates between improving the SP, using bias-accelerated subset selection, and improving parameters of the VN, using ADAM with monotonicity verification. The algorithm learns an effective pair: an SP that captures fewer k-space samples generating undersampling artifacts that are removed by the VN reconstruction. The proposed approach was tested for stability and convergence, considering different initial SPs. The quality of the VNs and SPs was compared against other approaches, including joint learning methods and VN learning with fixed variable density Poisson-disc SPs, using two different datasets and different acceleration factors (AF). Results: The root mean squared error (RMSE) improvements ranged from 14.9% to 51.2% considering AF from 2 to 20 in the tested brain and knee joint datasets when compared to the other approaches. The proposed approach has shown stable convergence, obtaining similar SPs with the same RMSE under different initial conditions. Conclusion: The proposed approach was stable and learned effective SPs with the corresponding VN parameters that produce images with better quality than other approaches, improving accelerated parallel MRI applications.

We present the first comparison of observed stellar continuum spectra of high-redshift galaxies and mock galaxy spectra generated from hydrodynamical simulations. The mock spectra are produced from the IllustrisTNG TNG100 simulation combined with stellar population models and take into account dust attenuation and realistic observational effects (aperture effects and noise). We compare the simulated $D_n4000$ and EW(H$\delta$) of galaxies with $10.5 \leq \log(M_\ast/M_\odot) \leq 11.5$ at $0.6 \leq z \leq 1.0$ to the observed distributions from the LEGA-C survey. TNG100 globally reproduces the observed distributions of spectral indices, implying that the age distribution of galaxies in TNG100 is generally realistic. Yet there are small but significant differences. For old galaxies, TNG100 shows small $D_n4000$ when compared to LEGA-C, while LEGA-C galaxies have larger EW(H$\delta$) at fixed $D_n4000$. There are several possible explanations: 1) LEGA-C galaxies have overall older ages combined with small contributions (a few percent in mass) from younger ($<1$~Gyr) stars, while TNG100 galaxies may not have such young sub-populations; 2) the spectral mismatch could be due to systematic uncertainties in the stellar population models used to convert stellar ages and metallicities to observables. In conclusion, the latest cosmological galaxy formation simulations broadly reproduce the global age distribution of galaxies at $z\sim1$ and, at the same time, the high quality of the latest observed and simulated datasets help constrain stellar population synthesis models as well as the physical models underlying the simulations., Comment: 17 pages, 12 figures, accepted by AJ

The use of IoT-related technologies is growing in several areas. Applications of environmental monitoring, logistics, smart cities are examples of applications that benefit from advances in IoT. In the military context, IoT applications can support the decision-making process by delivering information collected directly from the battlefield to Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) systems. Taking the benefit of the installed IoT network in the battlefield, the use of the data collected by the IoT nodes is a way to improve resiliency and increase the survivability of networks, as well as to optimize the use of available resources. Towards improving the communication network present on the battlefield, this work presents a context-aware environmental monitoring system that uses real-time battlefield information to increase military networks' resilience and survivability. The proposed approach is validated by a proof-of-concept experiment. The obtained results show that the implementation of this system can improve the communication process even when the network is exposed to unfavorable climatic factors.

We present the third and final data release of the Large Early Galaxy Astrophysics Census (LEGA-C), an ESO/VLT public spectroscopic survey targeting $0.6 < z < 1.0$, Ks-selected galaxies. The data release contains 3528 spectra with measured stellar velocity dispersions and stellar population properties, a 25-fold increase in sample size compared to previous work. This $K_s$-selected sample probes the galaxy population down to $\sim0.3 L^*$, for all colors and morphological types. Along with the spectra we publish a value-added catalog with stellar and ionized gas velocity dispersions, stellar absorption line indices, emission line fluxes and equivalent widths, complemented with structural parameters measured from HST/ACS imaging. With its combination of high precision and large sample size, LEGA-C provides a new benchmark for galaxy evolution studies., Comment: Accepted for publication in ApJS. Data available at http://archive.eso.org/cms/eso-archive-news/Third-and-final-release-of-the-Large-Early-Galaxy-Census-LEGA-C-Spectroscopic-Public-Survey-published.html or https://users.ugent.be/\string~avdrwel/research.html\#legac

This work presents an in-depth analysis of four gravitationally lensed red galaxies at z = 1.6-3.2. The sources are magnified by factors of 2.7-30 by foreground clusters, enabling spectral and morphological measurements that are otherwise challenging. Our sample extends below the characteristic mass of the stellar mass function and is thus more representative of the quiescent galaxy population at z > 1 than previous spectroscopic studies. We analyze deep VLT/X-SHOOTER spectra and multi-band Hubble Space Telescope photometry that cover the rest-frame UV-to-optical regime. The entire sample resembles stellar disks as inferred from lensing-reconstructed images. Through stellar population synthesis analysis we infer that the targets are young (median age = 0.1-1.2 Gyr) and formed 80% of their stellar masses within 0.07-0.47 Gyr. Mg II $\lambda\lambda 2796,2803$ absorption is detected across the sample. Blue-shifted absorption and/or redshifted emission of Mg II is found in the two youngest sources, indicative of a galactic-scale outflow of warm ($T\sim10^{4}$ K) gas. The [O III] $\lambda5007$ luminosity is higher for the two young sources (median age less than 0.4 Gyr) than the two older ones, perhaps suggesting a decline in nuclear activity as quenching proceeds. Despite high-velocity ($v\approx1500$ km s$^{-1}$) galactic-scale outflows seen in the most recently quenched galaxies, warm gas is still present to some extent long after quenching. Altogether our results indicate that star formation quenching at high redshift must have been a rapid process (< 1 Gyr) that does not synchronize with bulge formation or complete gas removal. Substantial bulge growth is required if they are to evolve into the metal-rich cores of present-day slow-rotators., Comment: Accepted for publication in the Astrophysical Journal. 37 pages, 20 figures, 10 tables

The INvestigating Stellar Population In RElics is an on-going project targeting 52 ultra-compact massive galaxies at 0.12) through a short and intense star formation burst, that evolved passively and undisturbed until the present-day. Relics provide a unique opportunity to study the mechanisms of star formation at high-z. In this paper, we present the first INSPIRE Data Release, comprising 19 systems with observations completed in 2020. We use the methods already presented in the INSPIRE Pilot, but revisiting the 1D spectral extraction. For these 19 systems, we obtain an estimate of the stellar velocity dispersion, fitting separately the two UVB and VIS XSH arms at their original resolution. We estimate [Mg/Fe] abundances via line-index strength and mass-weighted integrated stellar ages and metallicities with full spectral fitting on the combined spectrum. Ages are generally old, in agreement with the photometric ones, and metallicities are almost always super-solar, confirming the mass-metallicity relation. The [Mg/Fe] ratio is also larger than solar for the great majority of the galaxies, as expected. We find that 10 objects have formed more than 75% of their stellar mass (M*) within 3 Gyr from the Big Bang and classify them as relics. Among these, we identify 4 galaxies which had already fully assembled their M* by that time. They are therefore `extreme relics' of the ancient Universe. The INSPIRE DR1 catalogue of 10 known relics to-date augment by a factor of 3.3 the total number of confirmed relics, also enlarging the redshift window. It is therefore the largest publicly available collection. Thanks to the larger number of systems, we can also better quantify the existence of a 'degree of relicness', already hinted at the Pilot Paper., Comment: (Abstract abridged) 21 pages, 12 figures and 5 tables in the main body, plus 3 figure and 1 table in the appendix, accepted for publication on A&A. The associated data are available via the ESO Phase 3 Science Portal

We examine the Fundamental Plane (FP) and mass-to-light ratio ($M/L$) scaling relations using the largest sample of massive quiescent galaxies at $1.511.26$, subset of 8 quiescent galaxies at $z>2$, from Stockmann et al. (2020), we show that they cannot passively evolve to the local Coma cluster relation alone and must undergo significant structural evolution to mimic the sizes of local massive galaxies. The evolution of the FP and $M/L$ scaling relations, from $z=2$ to present-day, for this subset are consistent with passive aging of the stellar population and minor merger structural evolution into the most massive galaxies in the Coma cluster and other massive elliptical galaxies from the MASSIVE Survey. Modeling the luminosity evolution from minor merger added stellar populations favors a history of merging with "dry" quiescent galaxies., Comment: 17 pages, 6 figures