Early Epochs Research Articles

Structure formation in non-local bouncing models

In this study, we investigate the growth of structures within the Deser-Woodard nonlocal theory and extend it to various bouncing cosmology scenarios. Our findings show that the observable structure growth rate, fσ 8, in a vacuum-dominated universe is finite within the redshift range of 0 < z < 2, contrary to previous literature. Although fσ 8 exhibits no divergences, we observe a slight difference between the evolution of the ΛCDM and the non-local DW II models. Regarding structure formation in bouncing cosmologies, we evaluate the evolution of fσ 8 near the bouncing point. Among the different bouncing cases we explore, the oscillatory bounce and pre-inflationary asymmetrical bounce demonstrate a physical profile where the growth rate begins as a small perturbation in the early epoch and increases with inflation, which can be regarded as the seeds of large-scale structures. These findings are significant because they shed light on the growth of seed fluctuations into cosmic structures resulting from non-local effects.

A unified model of inflation and dark energy based on the holographic spacetime foam

I present a model of inflation and dark energy in which the inflaton potential is constructed by imposing that a scalar field representing the classical energy of the spacetime foam inside the Hubble horizon is an exact solution to the cosmological equations. The resulting potential has the right properties to describe both the early and late expansion epochs of the universe in a unified picture.

Methodological Principles of the Study of Marriage and Family Relations in Islam

The article is devoted to the problem of studying the issues of marriage and family relations in the Muslim theological discourse. Theologians have paid special attention to the institution of the family since the early epoch of the Fiqh, and their works bear witness to this. They contain concise principles with the help of which they justified theological conclusions aimed at solving marital and family problems. A deep analysis of these works helped to identify these principles, the study of which will help modern theologians to understand the goals of Sharia in the field of family relations and will effectively resolve the problems of marriage and family relations.

Benthic foraminiferal morphogroups at the end-Guadalupian extinction in eastern Sichuan Basin, China

Benthic foraminiferal morphogroups near the Permian Guadalupian-Lopingian (GLB) reveal their responses to palaeoenvironmental and palaeoecological changes in the eastern Sichuan Basin, China. According to the shell forms, coiling modes, and life positions linked to the life styles and feeding strategies, seven types of benthic foraminiferal morphogroups were recognized in Guadalupian and lower Wuchiapingian carbonate rocks from four lithological profiles. During the Guadalupian Epoch, highly diversified and large number of benthic foraminifera and their various feeding strategies indicated sufficient trophic resources for food. However, the foraminiferal assemblages dropped dramatically after the end-Guadalupian extinction event, reflecting remarkable changes in the nutrient sources and oxygen conditions in the ocean. In the early Wuchiapingian Epoch, nutrient input and plant debris decreased rapidly, while terrigenous detritus increased. As a result, the number of herbivores significantly declined, and suspension feeders and detritivores dominated. Changes in foraminiferal morphogroups in the eastern Sichuan Basin confirmed the existence of a end-Guadalupian extinction event. Surviving benthic foraminifera in Wuchiapiangian, such as Codonofusiella and Eotuberitina, prefer epiphytism, multiple feeding strategies, and low oxygen concentrations, which helped them sustain in a severe ecological environment. The dominant Wuchiapingian foraminifera has changed to other genera, which had to alter their living habits by enlarging the bottom contact area to resist waves and expanding semi-shells to increase feeding capacity. Benthic foraminiferal assemblages from adjacent regions (south China, Tibet, Iran, and Greece) were consistent with our investigation of the morphogroups and showed a similar response to the end-Guadalupian extinction event.

Chasing the impact of the Gaia-Sausage-Enceladus merger on the formation of the Milky Way thick disc

ABSTRACT We employ our Bayesian Machine Learning framework BINGO (Bayesian INference for Galactic archaeOlogy) to obtain high-quality stellar age estimates for 68 360 red giant and red clump stars present in the 17th data release of the Sloan Digital Sky Survey, the APOGEE-2 high-resolution spectroscopic survey. By examining the denoised age-metallicity relationship of the Galactic disc stars, we identify a drop in metallicity with an increase in [Mg/Fe] at an early epoch, followed by a chemical enrichment episode with increasing [Fe/H] and decreasing [Mg/Fe]. This result is congruent with the chemical evolution induced by an early-epoch gas-rich merger identified in the Milky Way-like zoom-in cosmological simulation Auriga. In the initial phase of the merger of Auriga 18 there is a drop in metallicity due to the merger diluting the metal content and an increase in the [Mg/Fe] of the primary galaxy. Our findings suggest that the last massive merger of our Galaxy, the Gaia-Sausage-Enceladus, was likely a significant gas-rich merger and induced a starburst, contributing to the chemical enrichment and building of the metal-rich part of the thick disc at an early epoch.

Inferencing Progenitor and Explosion Properties of Evolving Core-collapse Supernovae from Zwicky Transient Facility Light Curves

We analyze a sample of 45 Type II supernovae from the Zwicky Transient Facility public survey using a grid of hydrodynamical models in order to assess whether theoretically driven forecasts can intelligently guide follow-up observations supporting all-sky survey alert streams. We estimate several progenitor properties and explosion physics parameters, including zero-age main-sequence (ZAMS) mass, mass-loss rate, kinetic energy, 56Ni mass synthesized, host extinction, and the time of the explosion. Using complete light curves we obtain confident characterizations for 34 events in our sample, with the inferences of the remaining 11 events limited either by poorly constraining data or the boundaries of our model grid. We also simulate real-time characterization of alert stream data by comparing our model grid to various stages of incomplete light curves (Δt < 25 days, Δt < 50 days, all data), and find that some parameters are more reliable indicators of true values at early epochs than others. Specifically, ZAMS mass, time of the explosion, steepness parameter β, and host extinction are reasonably constrained with incomplete light-curve data, whereas mass-loss rate, kinetic energy, and 56Ni mass estimates generally require complete light curves spanning >100 days. We conclude that real-time modeling of transients, supported by multi-band synthetic light curves tailored to survey passbands, can be used as a powerful tool to identify critical epochs of follow-up observations. Our findings are relevant to identifying, prioritizing, and coordinating efficient follow-up of transients discovered by the Vera C. Rubin Observatory.

Taste-Odor Association Learning Alters the Dynamics of Intraoral Odor Responses in the Posterior Piriform Cortex of Awake Rats.

How an odor is perceived is to a large extent dependent on the context in which that odor is (or has been) experienced. For example, experiencing an odor in mixture with taste during consumption can instill taste qualities in the percept of that odor (e.g., vanilla, an odor, has a gustatory quality: sweet). How associative features of odors are encoded in the brain remains unknown, but previous work suggests an important role for ongoing interactions between piriform cortex and extraolfactory systems. Here, we tested the hypothesis that piriform cortex dynamically encodes taste associations of odors. Rats were trained to associate one of two odors with saccharin; the other odor remained neutral. Before and after training, we tested preferences for the saccharin-associated odor versus the neutral odor, and recorded spiking responses from ensembles of neurons in posterior piriform cortex (pPC) to intraoral delivery of small drops of the same odor solutions. The results show that animals successfully learned taste-odor associations. At the neural level, single pPC neuron responses to the saccharin-paired odor were selectively altered following conditioning. Altered response patterns appeared after 1 s following stimulus delivery, and successfully discriminated between the two odors. However, firing rate patterns in the late epoch appeared different from firing rates early in the early epoch (<1 s following stimulus delivery). That is, in different response epoch, neurons used different codes to represent the difference between the two odors. The same dynamic coding scheme was observed at the ensemble level.

The growth of brightest cluster galaxies in the TNG300 simulation: dissecting the contributions from mergers andin situstar formation

ABSTRACTWe investigate the formation of brightest cluster galaxies (BCGs) in the TNG300 cosmological simulation of the IllustrisTNG project. Our cluster sample consists of 700 haloes with $M_{\rm 200}\ge 5 \times 10^{13} \, {\rm M}_{\odot }$ at z = 0, along with their progenitors at earlier epochs. This includes 280 systems with $M_{\rm 200}\ge 10^{14} \, {\rm M}_{\odot }$ at z = 0, as well as three haloes with $M_{\rm 200}\ge 10^{15} \, {\rm M}_{\odot }$. We find that the stellar masses and star formation rates of our simulated BCGs are in good agreement with observations at z ≲ 0.4, and that they have experienced, on average, ∼2 (∼3) major mergers since z = 1 (z = 2). Separating the BCG from the intracluster light (ICL) by means of a fixed 30 kpc aperture, we find that the fraction of stellar mass contributed by ex situ (i.e. accreted) stars at z = 0 is approximately 70, 80, and 90 per cent for the BCG, BCG + ICL, and ICL, respectively. Tracking our simulated BCGs back in time using the merger trees, we find that they became dominated by ex situ stars at z ∼1–2, and that half of the stars that are part of the BCG at z = 0 formed early (z ∼ 3) in other galaxies, but ‘assembled’ onto the BCG until later times (z ≈ 0.8 for the whole sample, z ≈ 0.5 for BCGs in $M_{\rm 200}\ge 5 \times 10^{14} \, {\rm M}_{\odot }$ haloes). Finally, we show that the stellar mass profiles of BCGs are often dominated by ex situ stars at all radii, with stars from major mergers being found closer to the centre, while stars that were tidally stripped from other galaxies dominate the outer regions.

FedDdrl: Federated Double Deep Reinforcement Learning for Heterogeneous IoT with Adaptive Early Client Termination and Local Epoch Adjustment.

Federated learning (FL) is a technique that allows multiple clients to collaboratively train a global model without sharing their sensitive and bandwidth-hungry data. This paper presents a joint early client termination and local epoch adjustment for FL. We consider the challenges of heterogeneous Internet of Things (IoT) environments including non-independent and identically distributed (non-IID) data as well as diverse computing and communication capabilities. The goal is to strike the best tradeoff among three conflicting objectives, namely global model accuracy, training latency and communication cost. We first leverage the balanced-MixUp technique to mitigate the influence of non-IID data on the FL convergence rate. A weighted sum optimization problem is then formulated and solved via our proposed FL double deep reinforcement learning (FedDdrl) framework, which outputs a dual action. The former indicates whether a participating FL client is dropped, whereas the latter specifies how long each remaining client needs to complete its local training task. Simulation results show that FedDdrl outperforms the existing FL scheme in terms of overall tradeoff. Specifically, FedDdrl achieves higher model accuracy by about 4% while incurring 30% less latency and communication costs.

Origin of multiwavelength emission from flaring high redshift blazar PKS 0537−286

ABSTRACT The high redhsift blazars powered by supermassive black holes with masses exceeding 109 M⊙ have the highest jet power and luminosity and are important probes to test the physics of relativistic jets at the early epochs of the Universe. We present a multifrequency spectral and temporal study of high redshift blazar PKS 0537−286 by analysing data from Fermi-LAT, NuSTAR Swift XRT, and UVOT. Although the time averaged γ-ray spectrum of the source is relatively soft (indicating the high-energy emission peak is below the GeV range), several prominent flares were observed when the spectrum hardened and the luminosity increased above 1049 erg s−1. The X-ray emission of the source varies in different observations and is characterized by a hard spectrum ≤1.38 with a luminosity of &amp;gt;1047 erg s−1. The broad-band spectral energy distribution in the quiescent and flaring periods was modelled within a one-zone leptonic scenario assuming different locations of the emission region and considering both internal (synchrotron radiation) and external (from the disc, broad-line region, and dusty torus) photon fields for the inverse Compton scattering. The modelling shows that the most optimistic scenario, from the energy requirement point of view, is when the jet energy dissipation occurs within the broad-line region. The comparison of the model parameters obtained for the quiescent and flaring periods suggests that the flaring activities are most likely caused by the hardening of the emitting electron spectral index and shifting of the cut-off energy to higher values.

Technical note: Progressive deep learning: An accelerated training strategy for medical image segmentation.

Recent advancements in Deep Learning (DL) methodologies have led to state-of-the-art performance in a wide range of applications especially in object recognition, classification, and segmentation of medical images. However, training modern DL models requires a large amount of computation and long training times due to the complex nature of network structures and the large number of training datasets involved. Moreover, it is an intensive, repetitive manual process to select the optimized configuration of hyperparameters for a given DL network. In this study, we present a novel approach to accelerate the training time of DL models via the progressive feeding of training datasets based on similarity measures for medical image segmentation. We term this approach Progressive Deep Learning (PDL). The two-stage PDL approach was tested on the auto-segmentation task for two imaging modalities: CT and MRI. The training datasets were ranked according to similarity measures between each sample based on Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and the Universal Quality Image Index (UQI) values. At the start of the training process, a relatively coarse sampling of training datasets with higher ranks was used to optimize the hyperparameters of the DL network. Following this, the samples with higher ranks were used in step 1 to yield accelerated loss minimization in early training epochs and the total dataset was added in step 2 for the remainder of training. Our results demonstrate that the PDL approach can reduce the training time by nearly half (∼49%) and can predict segmentations (CT U-net/DenseNet dice coefficient: 0.9506/0.9508, MR U-net/DenseNet dice coefficient: 0.9508/0.9510) without major statistical difference (Wilcoxon signed-rank test) compared to the conventional DL approach. The total training times with a fixed cutoff at 0.95 DSC for the CT dataset using DenseNet and U-Net architectures, respectively, were 17h, 20 min and 4h, 45 min in the conventional case compared to 8h, 45 min and 2h, 20 min with PDL. For the MRI dataset, the total training times using the same architectures were 2h, 54 min and 52 min in the conventional case and 1h, 14 min and 25 min with PDL. The proposed PDL training approach offers the ability to substantially reduce the training time for medical image segmentation while maintaining the performance achieved in the conventional case.

Spherical symmetry in the kilonova AT2017gfo/GW170817.

The mergers of neutron stars expel a heavy-element enriched fireball that can be observed as a kilonova1-4. The kilonova's geometry is a key diagnostic of the merger and is dictated by the properties of ultra-dense matter and the energetics of the collapse to a black hole. Current hydrodynamical merger models typically show aspherical ejecta5-7. Previously, Sr+ was identified in the spectrum8 of the only well-studied kilonova9-11 AT2017gfo12, associated with the gravitational wave event GW170817. Here we combine the strong Sr+ P Cygni absorption-emission spectral feature and the blackbody nature of kilonova spectrum to determine that the kilonova is highly spherical at early epochs. Line shape analysis combined with the known inclination angle of the source13 also show the same sphericity independently. We conclude that energy injection by radioactive decay is insufficient to make the ejecta spherical. A magnetar wind or jet from the black-hole disk could inject enough energy to induce a more spherical distribution in the overall ejecta; however, an additional process seems necessary to make the element distribution uniform.

JWST unveils the brown dwarf sequence of 47 Tucanæ

ABSTRACT We have developed a technique to restore scientific usage in compromised (publicly available) images collected with the JWST of the Galactic globular cluster NGC 104 (47 Tucanæ). In spite of the degradation and limited data, we were able to recover photometry and astrometry for the coolest stellar objects ever observed within a globular cluster, possibly unveiling the brightest part of the brown dwarf (BD) sequence. This is supported by (i) proper motion membership, derived by the comparison with positions obtained from Hubble Space Telescope archival early epochs, (ii) the predicted location of the BD sequence, and (iii) the mass function for low-mass stars derived from models. Future JWST observations will provide the necessary deep and precise proper motions to confirm the nature of the here-identified BD candidates belonging to this globular cluster.

Exploring Structural Sparsity of Deep Networks Via Inverse Scale Spaces.

The great success of deep neural networks is built upon their over-parameterization, which smooths the optimization landscape without degrading the generalization ability. Despite the benefits of over-parameterization, a huge amount of parameters makes deep networks cumbersome in daily life applications. On the other hand, training neural networks without over-parameterization faces many practical problems, e.g., being trapped in the local optimal. Though techniques such as pruning and distillation are developed, they are expensive in fully training a dense network as backward selection methods; and there is still a void on systematically exploring forward selection methods for learning structural sparsity in deep networks. To fill in this gap, this paper proposes a new approach based on differential inclusions of inverse scale spaces. Specifically, our method can generate a family of models from simple to complex ones along the dynamics via coupling a pair of parameters, such that over-parameterized deep models and their structural sparsity can be explored simultaneously. This kind of differential inclusion scheme has a simple discretization, dubbed Deep structure splitting Linearized Bregman Iteration (DessiLBI), whose global convergence in learning deep networks could be established under the Kurdyka-Łojasiewicz framework. Particularly, we explore several applications of DessiLBI, including finding sparse structures of networks directly via the coupled structure parameter and growing networks from simple to complex ones progressively. Experimental evidence shows that our method achieves comparable and even better performance than the competitive optimizers in exploring the sparse structure of several widely used backbones on the benchmark datasets. Remarkably, with early stopping, our method unveils "winning tickets" in early epochs: the effective sparse network structures with comparable test accuracy to fully trained over-parameterized models, that are further transferable to similar alternative tasks. Furthermore, our method is able to grow networks efficiently with adaptive filter configurations, demonstrating the good performance with much less computational cost. Codes and models can be downloaded at https://github.com/DessiLBI2020/DessiLBI.

Hubble tension as a guide for refining the early Universe: Cosmologies with explicit local Lorentz and diffeomorphism violation

This paper is dedicated to assessing modified cosmological settings based on the gravitational Standard-Model Extension (SME). Our analysis rests upon the Hubble tension (HT), which is a discrepancy between the observational determination of the Hubble parameter via data from the Cosmic Microwave Background (CMB) and Type Ia supernovae, respectively. While the latter approach is model-independent, the former highly depends on the model used to describe the physics of the early Universe. Motivated by the HT, we take into account two recently introduced cosmological models as test frameworks of the pre-CMB era. These settings involve local Lorentz and diffeomorphism violation parameterized by nondynamical SME background fields $s_{00}$ and $s^{ij}$, respectively. We aim at explaining the tension in the measured results of the cosmic expansion rate in early and late epochs by resorting to these two modified cosmologies as potential descriptions of the pre-CMB era. As long as the HT does not turn out to be a merely systematic effect, it can serve as a criterion for exploring regions of the parameter space in certain pre-CMB new-physics candidates such as SME cosmologies. By setting extracted limits on SME coefficients into perspective with already existing bounds in the literature, we infer that none of the aforementioned models are suitable pre-CMB candidates for fixing the HT. In this way, new physics arising from the particular realizations of Lorentz and diffeomorphism violation studied in this paper does not explain the HT. Our paper exemplifies how to exploit this discrepancy as a novel possibility of refining our description of the early Universe.

Re-Evaluating Botryosphaeriales: Ancestral State Reconstructions of Selected Characters and Evolution of Nutritional Modes.

Botryosphaeriales (Dothideomycetes, Ascomycota) occur in a wide range of habitats as endophytes, saprobes, and pathogens. The order Botryosphaeriales has not been subjected to evaluation since 2019 by Phillips and co-authors using phylogenetic and evolutionary analyses. Subsequently, many studies introduced novel taxa into the order and revised several families separately. In addition, no ancestral character studies have been conducted for this order. Therefore, in this study, we re-evaluated the character evolution and taxonomic placements of Botryosphaeriales species based on ancestral character evolution, divergence time estimation, and phylogenetic relationships, including all the novel taxa that have been introduced so far. Maximum likelihood, maximum parsimony, and Bayesian inference analyses were conducted on a combined LSU and ITS sequence alignment. Ancestral state reconstruction was carried out for conidial colour, septation, and nutritional mode. Divergence times estimates revealed that Botryosphaeriales originated around 109 Mya in the early epoch of the Cretaceous period. All six families in Botryosphaeriales evolved in the late epoch of the Cretaceous period (66-100 Mya), during which Angiosperms also appeared, rapidly diversified and became dominant on land. Families of Botryosphaeriales diversified during the Paleogene and Neogene periods in the Cenozoic era. The order comprises the families Aplosporellaceae, Botryosphaeriaceae, Melanopsaceae, Phyllostictaceae, Planistromellaceae and Saccharataceae. Furthermore, current study assessed two hypotheses; the first one being "All Botryosphaeriales species originated as endophytes and then switched into saprobes when their hosts died or into pathogens when their hosts were under stress"; the second hypothesis states that "There is a link between the conidial colour and nutritional mode in botryosphaerialean taxa". Ancestral state reconstruction and nutritional mode analyses revealed a pathogenic/saprobic nutritional mode as the ancestral character. However, we could not provide strong evidence for the first hypothesis mainly due to the significantly low number of studies reporting the endophytic botryosphaerialean taxa. Results also showed that hyaline and aseptate conidia were ancestral characters in Botryosphaeriales and supported the relationship between conidial pigmentation and the pathogenicity of Botryosphaeriales species.

Deep Spitzer/IRAC Data for z ∼ 10 Galaxies Reveal Blue Balmer Break Colors: Young Stellar Populations at ∼500 Myr of Cosmic Time

We present the deepest constraints yet on the median rest-UV+optical spectral energy distribution (SED) of z ∼ 10 galaxies prior to James Webb Space Telescope science operations. We constructed stacks based on four robust J 125 dropouts, previously identified across the GOODS fields. We used archival Hubble Space Telescope/Wide Field Camera 3 data and the full-depth Spitzer/IRAC mosaics from the GREATS program, the deepest coverage at ∼3–5 μm to date. The most remarkable feature of the SED is a blue IRAC [3.6]–[4.5] = −0.18 ± 0.25 mag color. We also find a nearly flat H 160 − [3.6] = 0.07 ± 0.22 mag color, corresponding to a UV slope β = −1.92 ± 0.25. This is consistent with previous studies and indicative of minimal dust absorption. The observed blue IRAC color and SED fitting suggest that z ∼ 10 galaxies have very young (few × 10 Myr) stellar populations, with 80% of stars being formed in the last ≲160 Myr (2σ). While an exciting result, the uncertainties on the SED are too large to allow us to place strong constraints on the presence of a nebular continuum in z ∼ 10 galaxies (as might be suggested by the blue [3.6]–[4.5] < 0 mag color). The resulting sSFR is consistent with the specific accretion rate of dark matter halos, indicative of a star formation efficiency showing quite limited evolution at such early epochs.

Cosmic Evolution of Gas and Star Formation * * 2022 AAS Russell Lecture by Scoville. We provide the science background behind the Russell Lecture and draw extensively on previous work in Scoville et al. ().

Atacama Large Millimeter/submillimeter Array (ALMA) observations of the long-wavelength dust continuum are used to estimate the gas masses in a sample of 708 star-forming galaxies at z = 0.3−4.5. We determine the dependence of gas masses and star formation efficiencies (SFEs; SFR per unit gas mass) on redshift (z), M *, and star formation rate (SFR) relative to the main sequence (MS). We find that 70% of the increase in SFRs of the MS is due to the increased gas masses at earlier epochs, while 30% is due to increased efficiency of star formation (SF). For galaxies above the MS this is reversed—with 70% of the increased SFR relative to the MS being due to elevated SFEs. Thus, the major evolution of star formation activity at early epochs is driven by increased gas masses, while the starburst activity taking galaxies above the MS is due to enhanced triggering of star formation (likely due to galactic merging). The interstellar gas peaks at z = 2 and dominates the stellar mass down to z = 1.2. Accretion rates needed to maintain continuity of the MS evolution reach >100 M ⊙ yr−1 at z > 2. The galactic gas contents are likely the driving determinant for both the rise in SF and AGN activity from z = 5 to their peak at z = 2 and subsequent fall at lower z. We suggest that for self-gravitating clouds with supersonic turbulence, cloud collisions and the filamentary structure of the clouds regulate the star formation activity.

The McDonald Accelerating Stars Survey: Architecture of the Ancient Five-planet Host System Kepler-444

We present the latest and most precise characterization of the architecture for the ancient (≈11 Gyr) Kepler-444 system, which is composed of a K0 primary star (Kepler-444 A) hosting five transiting planets and a tight M-type spectroscopic binary (Kepler-444 BC) with an A–BC projected separation of 66 au. We have measured the system’s relative astrometry using the adaptive optics imaging from Keck/NIRC2 and Kepler-444 A’s radial velocities from the Hobby-Eberly Telescope and reanalyzed relative radial velocities between BC and A from Keck/HIRES. We also include the Hipparcos-Gaia astrometric acceleration and all published astrometry and radial velocities in an updated orbit analysis of BC’s barycenter. These data greatly extend the time baseline of the monitoring and lead to significant updates to BC’s barycentric orbit compared to previous work, including a larger semimajor axis ( au), a smaller eccentricity (e = 0.55 ± 0.05), and a more precise inclination (). We have also derived the first dynamical masses of B and C components. Our results suggest that Kepler-444 A’s protoplanetary disk was likely truncated by BC to a radius of ≈8 au, which resolves the previously noticed tension between Kepler-444 A’s disk mass and planet masses. Kepler-444 BC’s barycentric orbit is likely aligned with those of A’s five planets, which might be primordial or a consequence of dynamical evolution. The Kepler-444 system demonstrates that compact multiplanet systems residing in hierarchical stellar triples can form at early epochs of the universe and survive their secular evolution throughout cosmic time.

The star formation history and the nature of the mass–metallicity relation of passive galaxies at 1.0 &amp;lt;z&amp;lt; 1.4 from VANDELS

ABSTRACTWe derived stellar ages and metallicities [Z/H] for ∼70 passive early-type galaxies (ETGs) selected from VANDELS survey over the redshift range 1.0 &amp;lt; z &amp;lt; 1.4 and stellar mass range 10 &amp;lt; log(M*/M⊙) &amp;lt; 11.6. We find significant systematics in their estimates depending on models and wavelength ranges considered. Using the full-spectrum fitting technique, we find that both [Z/H] and age increase with mass as for local ETGs. Age and metallicity sensitive spectral indices independently confirm these trends. According to EMILES models, for 67 per cent of the galaxies we find [Z/H] &amp;gt; 0.0, a percentage which rises to ∼90 per cent for log(M*/M⊙) &amp;gt; 11 where the mean metallicity is [Z/H] = 0.17 ± 0.1. A comparison with homogeneous measurements at similar and lower redshift does not show any metallicity evolution over the redshift range 0.0 &amp;lt; z &amp;lt; 1.4. The derived star formation (SF) histories show that the stellar mass fraction formed at early epoch increases with the mass of the galaxy. Galaxies with log(M*/M⊙) &amp;gt; 11.0 host stellar populations with [Z/H] &amp;gt; 0.05, formed over short time-scales (Δt50 &amp;lt; 1 Gyr) at early epochs (tform &amp;lt; 2 Gyr), implying high star formation rates (SFR &amp;gt; 100 M⊙ yr−1) in high-mass density regions (log(Σ1kpc) &amp;gt; 10 M⊙/kpc2). This sharp picture tends to blur at lower masses: log(M*/M⊙) ∼ 10.6 galaxies can host either old stars with [Z/H] &amp;lt; 0.0 or younger stars with [Z/H] &amp;gt; 0.0, depending on the duration (Δt50) of the SF. The relations between galaxy mass, age, and metallicities are therefore largely set up ab initio as part of the galaxy formation process. Mass, SFR, and SF time-scale all contribute to shape up the stellar mass–metallicity relation with the mass that modulates metals retention.