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We study the dynamical properties of the bosonic quantum East model at low temperature. We show that a naive generalization of the corresponding spin-1/2 quantum East model does not posses analogous slow dynamical properties. In particular, conversely to the spin case, the bosonic ground state turns out to be not localized. We restore localization by introducing a repulsive interaction term. The bosonic nature of the model allows us to construct rich families of many-body localized states, including coherent, squeezed and cat states. We formalize this finding by introducing a set of superbosonic creation-annihilation operators which satisfy the bosonic commutation relations and, when acting on the vacuum, create excitations exponentially localized around a certain site of the lattice. Given the constrained nature of the model, these states retain memory of their initial conditions for long times. Even in the presence of dissipation, we show that quantum information remains localized within decoherence times tunable with the parameters of the system. We propose an implementation of the bosonic quantum East model based on state-of-the-art superconducting circuits, which could be used in the near future to explore dynamical properties of kinetically constrained models in modern platforms., Comment: 26 pages, 18 figures; improved Sec. IV, V and VI

In this work, we have implemented a detailed physical model of galaxy chemical enrichment into the ${\it Astraeus}$ (semi-numerical rAdiative tranSfer coupling of galaxy formaTion and Reionization in N-body dark matter simUlationS) framework which couples galaxy formation and reionization in the first billion years. Simulating galaxies spanning over 2.5 orders of magnitude in halo mass with $M_h \sim 10^{8.9-11.5} M_\odot$ ($M_h \sim 10^{8.9-12.8} M_\odot$) at $z \sim 10 ~ (5)$, we find: (i) smooth-accretion of metal-poor gas from the intergalactic medium (IGM) plays a key role in diluting the interstellar medium (ISM) metallicity which is effectively restored due to self-enrichment from star formation; (ii) a redshift averaged gas-mass loading factor that depends on the stellar mass as $\eta_g \approx 1.38 ({M_*}/{10^{10} M_\odot})^{-0.43}$; (iii) the mass-metallicity relation is already in place at $z \sim 10$ and shows effectively no redshift evolution down to $z \sim 5$; (iv) for a given stellar mass, the metallicity decreases with an increase in the star formation rate (SFR); (v) the key properties of the gas-phase metallicity (in units of 12+log(O/H), stellar mass, SFR and redshift are linked through a high-redshift fundamental plane of metallicity (HFPZ) for which we provide a functional form; (vi) the mass-metallicity-SFR relations are effectively independent of the reionization radiative feedback model for $M_* \geq 10^{6.5} M_\odot$ galaxies; (vii) while low-mass galaxies ($M_h \leq 10^9 M_\odot$) are the key contributors to the metal budget of the IGM at early times, higher mass halos provide about 50% of the metal budget at lower-redshifts., Comment: Accepted to MNRAS

Next generation large sky surveys will observe up to billions of galaxies for which basic structural parameters are needed to study their evolution. This is a challenging task that, for ground-based observations, is complicated by seeing limited point-spread function (PSF). To perform a fast and accurate analysis of galaxy surface brightness, we have developed a family of supervised Convolutional Neural Networks (CNN) to derive Sersic profile parameters of galaxies. This work presents the first two Galaxy Light profile convolutional neural Networks (GaLNets) of this family. The first one is trained using galaxy images only (GaLNet-1), and the second is trained with both galaxy images and the local PSF (GaLNet-2). We have compared the results from the GaLNets with structural parameters (total magnitude, effective radius, Sersic index etc.) derived on a set of galaxies from the Kilo-Degree Survey (KiDS) by 2DPHOT, as a representative of "standard" PSF convolved Sersic fitting tools. The comparison shows that GaLNet-2 can reach an accuracy as high as 2DPHOT, while GaLNet-1 performs worse because it misses the information on the local PSF. Both GaLNets are three orders of magnitude faster than standard methods in terms of computational speed. This first application of CNNs to ground-based galaxy surface photometry shows that they are promising tools to perform parametric analyses of very large galaxy samples, like the ones expected from Vera Rubin/LSST surveys. However, the GaLNets can be easily modified for space observations from Euclid and the China Space Station Telescope., Comment: Accepted for publication by APJ

The quantum interference between the decays of entangled neutral kaons is studied in the process $\phi\rightarrow K_S K_L \rightarrow\pi^+\pi^-\pi^+\pi^-$, which exhibits the characteristic Einstein--Podolsky--Rosen correlations that prevent both kaons to decay into $\pi^+\pi^-$ at the same time. This constitutes a very powerful tool for testing at the utmost precision the quantum coherence of the entangled kaon pair state, and to search for tiny decoherence and CPT violation effects, which may be justified in a quantum gravity framework. The analysed data sample was collected with the KLOE detector at DA$\Phi$NE, the Frascati $\phi$-factory, and corresponds to an integrated luminosity of about 1.7 fb$^{-1}$, i.e. to about $1.7 \times 10^9$ $\phi\rightarrow K_S K_L$ decays produced. From the fit of the observed $\Delta t$ distribution, being $\Delta t$ the difference of the kaon decay times, the decoherence and CPT violation parameters of various phenomenological models are measured with a largely improved accuracy with respect to previous analyses. The results are consistent with no deviation from quantum mechanics and CPT symmetry, while for some parameters the precision reaches the interesting level at which -- in the most optimistic scenarios -- quantum gravity effects might show up. They provide the most stringent limits up to date on the considered models., Comment: 17 pages 6 figures

Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our understanding of the galaxy evolution and the unresolved nature of dark matter (DM). At galaxy scales, the density distribution of DM is strongly affected by the astrophysical feedback processes, which are difficult to fully account for in classical techniques to derive mass models. In this work, we explore the capability of supervised learning algorithms to predict the DM content of galaxies from luminous observational-like parameters, using the public catalog of the TNG100 simulation. In particular, we use Photometric, Structural and Kinematic parameters to predict the total DM mass, DM half-mass radius, DM mass inside one and two stellar half-mass radii. We adopt the coefficient of determination, $R^2$, as a reference metric to evaluate the accuracy of these predictions. We find that the Photometric features alone are able to predict the total DM mass with fair accuracy, while Structural and Photometric features together are more effective to determine the DM inside the stellar half mass radius, and the DM within twice the stellar half mass radius. However, using all observational quantities together (Photometry, Structural and Kinematics) incredibly improves the overall accuracy for all DM quantities. This first test shows that Machine Learning tools are promising approaches to derive predictions of the DM in real galaxies. The next steps will be to improve observational realism of the training sets, by closely select samples which accurately reproduce the typical observed luminous scaling relations. The trained pipelines will be suitable for real galaxy data collected from the next-generation surveys like Rubin/LSST, Euclid, CSST, 4MOST, DESI, to derive, e.g., the properties of their central DM fractions., Comment: 19 pages, 11 figures, 3 tables. Submitted to MNRAS. Comments are welcome

Context. The assembly history of the stellar component of a massive elliptical galaxy is closely related to that of its dark matter halo. Measuring how the properties of galaxies correlate with their halo mass can help understand their evolution. Aims. We investigate how the dark matter halo mass of elliptical galaxies varies as a function of their properties, using weak gravitational lensing observations. To minimise the chances of biases, we focus on galaxy properties that can be determined robustly: the surface brightness profile and the colour. Methods. We selected 2409 central massive elliptical galaxies from the SDSS spectroscopic sample. We first measured their surface brightness profile and colours by fitting Sersic models to photometric data from the Kilo-Degree Survey (KiDS). We fitted their halo mass distribution as a function of redshift, rest-frame $r-$band luminosity, half-light radius and rest-frame $u-g$ colour, using KiDS weak lensing data and a Bayesian hierarchical approach. For the sake of robustness to assumptions on the large-radii behaviour of the surface brightness, we repeated the analysis replacing total luminosity and half-light radius with the luminosity within a 10~kpc aperture, $L_{r,10}$, and the light-weighted surface brightness slope, $\Gamma_{10}$. Results. We did not detect any correlation between halo mass and either half-light radius or colour, at fixed redshift and luminosity. Conclusions. Our results indicate that the average star formation efficiency of massive elliptical galaxies has little dependence on their final size or colour. This suggests that the origin of the diversity in the size and colour distribution of these objects lies with properties other than halo mass., Comment: In press on Astronomy & Astrophysics. A short summary video is available at https://youtu.be/LlvwQNjLT7k

Radio occultations are commonly used to assess remotely the thermodynamic properties of planets or satellites' atmospheres within the solar system. The data processing usually involves the so-called Abel inversion method or the numerical ray-tracing technique. Both these approaches are now well established, however, they do not allow to easily determine the uncertainty profiles in the atmospheric properties, and this makes the results difficult to interpret statistically. Recently, a purely analytical approach based on the time transfer functions formalism was proposed for modeling radio occultation data. Using this formulation, we derive uncertainty relationships between the frequency shift and the thermodynamic properties of the neutral atmosphere such as the temperature, pressure, and neutral number density. These expressions are important for interpreting previous results from past radio occultation experiments. They are especially relevant for deriving the system requirements for future missions in a rigorous manner and consistently with the scientific requirements about the atmospheric properties retrieval., Comment: 18 pages, 5 figures, 1 table

The central dark-matter fraction of galaxies is sensitive to feedback processes during galaxy formation. Strong gravitational lensing has been effective in the precise measurement of the dark-matter fraction inside massive early-type galaxies. Here, we compare the projected dark-matter fraction of early-type galaxies inferred from the SLACS strong-lens survey, with those obtained from the EAGLE, Illustris, and IllustrisTNG hydro-dynamical simulations. Previous comparisons with some simulations revealed a large discrepancy, with considerably higher inferred dark-matter fractions -- by factors 2-3 -- inside half of the effective radius in observed strong-lens galaxies as compared to simulated galaxies. Here, we report good agreement between EAGLE and SLACS for the dark-matter fractions inside both half of the effective radius and the effective radius as a function of the galaxy's stellar mass, effective radius, and total mass-density slope. However, for IllustrisTNG and Illustris, the dark-matter fractions are lower than observed. This work consistently assumes a Chabrier IMF, which suggests that a different IMF (although not excluded) is not necessary to resolve this mismatch. The differences in the stellar feedback model between EAGLE and Illustris and IllustrisTNG, are likely the dominant cause of the difference in their dark-matter fraction, and density slope., Comment: Matches with the published version. Fixed an error in Fig 2. Updated reference. Conclusions unchanged. 7 pages, 4 figures

Gas accretion and stellar feedback processes link metal content, star formation, and gas and stellar mass (and the potential depth) in star-forming galaxies. Constraining this hypersurface has been challenging because of the need for measurements of HI and HII gas masses spanning a broad parameter space. A recent step forward has been achieved through the "Metallicity And Gas for Mass Assembly" (MAGMA) sample of local star-forming galaxies, which consists of homogeneously-determined parameters and a significant quantity of dwarf galaxies, with stellar masses as low as $\sim 10^5 - 10^{6}\, M_{\odot}$. Here, we adopt a "standard" galactic chemical evolution model, with which we can quantify stellar-driven outflows. In particular, we constrain the difference between the mass-loading in accretion and outflows and the wind metal-loading factor. The resulting model reproduces very well the local mass-metallicity relation, and the observed trends of metallicity with gas fraction. Although the difference in mass loading between accreted and expelled gas is extremely difficult to constrain, we find indications that, on average, the amount of gas acquired through accretion is roughly the same as the gas lost through bulk stellar outflows, corresponding to a "gas equilibrium" scenario. In agreement with previous work, the wind metal-loading factor shows a steep increase toward lower mass and circular velocity, indicating that low-mass galaxies are more efficient at expelling metals, thus shaping the mass-metallicity relation. Effective yields are found to increase with mass up to an inflection mass threshold, with a mild decline at larger masses and circular velocities. A comparison of our results for metal loading in outflows with the expectations for their mass loading favors momentum-driven winds at low masses, rather than energy-driven ones. (abridged), Comment: 21 pages, 13 figures, accepted for publication on A&A

We present 97 new high-quality strong lensing candidates found in the final $\sim 350\,\rm deg^2$, that completed the full $\sim 1350\,\rm deg^2$ area of the Kilo-Degree Survey (KiDS). Together with our previous findings, the final list of high-quality candidates from KiDS sums up to 268 systems. The new sample is assembled using a new Convolutional Neural Network (CNN) classifier applied to $r$-band (best seeing) and $g,~r,~i$ color-composited images separately. This optimizes the complementarity of the morphology and color information on the identification of strong lensing candidates. We apply the new classifiers to a sample of luminous red galaxies (LRGs) and a sample of bright galaxies (BGs) and select candidates that received a high probability to be a lens from the CNN ($P_{\rm CNN}$). In particular, setting $P_{\rm CNN}>0.8$ for the LRGs, the $1$-band CNN predicts 1213 candidates, while the $3$-band classifier yields 1299 candidates, with only $\sim$30\% overlap. For the BGs, in order to minimize the false positives, we adopt a more conservative threshold, $P_{\rm CNN} >0.9$, for both CNN classifiers. This results in 3740 newly selected objects. The candidates from the two samples are visually inspected by 7 co-authors to finally select 97 "high-quality" lens candidates which received mean scores larger than 6 (on a scale from 0 to 10). We finally discuss the effect of the seeing on the accuracy of CNN classification and possible avenues to increase the efficiency of multi-band classifiers, in preparation of next-generation surveys from ground and space., Comment: Published by APJ

The COld STream finder Algorithm (COSTA) is a novel algorithm to find streams in the phase space of planetary nebulae (PNe) and globular cluster (GCs) populations. COSTA isolates groups of particles with small velocity dispersion, using an iterative sigma-clipping over a defined number of neighbor particles. We have applied COSTA to a catalog of about 2000 PNe and GCs from the Fornax Cluster VLT Spectroscopic Survey (FVSS), within 200 kpc from the cluster core, to detect cold substructures and characterize their kinematics. We have found 13 cold substructures, with velocity dispersion ranging from 20 to 100 kms^{-1}, which are likely associated either to large galaxies or to ultra-compact dwarf (UCD) galaxies in the Fornax core. These streams show a clear correlation of their luminosity with the internal velocity dispersion, and their surface brightness with size and distance from the cluster center that are compatible with dissipative processes producing them. However, we cannot exclude that some of these substructures have formed by violent relaxation of massive satellites finally merged into the central galaxy. Among these substructures we have: a stream connecting NGC1387 to the central galaxy, NGC1399, previously reported in literature; a new giant stream produced by the interaction of NGC1382 with NGC1380 and possibly NGC1381; a series of streams kinematically connected to nearby ultra compact dwarf galaxies; clumps of tracers with no clear kinematical association to close cluster members. We show evidence for a variety of cold substructure predicted in simulations. Most of the streams are kinematically connected to UCDs, supporting the scenario that they can be remnants of disrupted dwarf systems. [abridged], Comment: 27 Pages, 15 Figures. Accepted for publication in Astronomy and Astrophysics

We derived surface brightness profiles in the \emph{g} band for 170 Small Magellanic Cloud (SMC) star clusters (SCs) mainly located in the central region of the galaxy. We provide a set of homogeneous structural parameters obtained by fitting Elson, Fall \& Freeman (EFF) and King models. Through a careful analysis of their colour-magnitude diagrams (CMDs) we also supply the ages for a subsample of 134 SCs. For the first time, such a large sample of SCs in the SMC is homogeneously characterized in terms of their sizes, luminosities and masses, widening the probed region of the parameter space, down to hundreds of solar masses. We used these data to explore the evolution of the SC's structural parameters with time. In particular, we confirm the existence of a physical mechanism that induces an increase of the core radius after 0.3-1.0 Gyr. We suggest that cluster mass could be the main parameter driving the inner expansion, as none of the SCs having $\log (M/M_{\odot}) \leq 3.5$~dex analysed in this work undergoes to such an expansion. We also detected a mass-size relationship almost over the entire range of SCs masses investigated here. Finally, our data suggest that globally the SMC SC system is dynamically evolved., Comment: 24 pages, 14 figures. Accepted for publication by MNRAS

We report the possible discovery of a new stellar system (YMCA-1), identified during a search for small scale overdensities in the photometric data of the YMCA survey. The object's projected position lies on the periphery of the Large Magellanic Cloud about $13^\circ$ apart from its center. The most likely interpretation of its color-magnitude diagram, as well as of its integrated properties, is that YMCA-1 may be an old and remote star cluster of the Milky Way at a distance of 100 kpc from the Galactic center. If this scenario could be confirmed, then the cluster would be significantly fainter and more compact than most of the known star clusters residing in the extreme outskirts of the Galactic halo, but quite similar to Laevens~3. However, much deeper photometry is needed to firmly establish the actual nature of the cluster and the distance to the system., Comment: 5 Pages, 3 figures. Published on Research Notes of the AAS

We systematically explore the self-assembly of semi-flexible polymers in deformable spherical confinement across a wide regime of chain stiffness, contour lengths and packing fractions by means of coarse-grained molecular dynamics simulations. Compliant, DNA-like filaments are found to undergo a continuous crossover from two distinct surface-ordered quadrupolar states, both characterized by tetrahedral patterns of topological defects, to either longitudinal or latitudinal bipolar structures with increasing polymer concentrations. These transitions, along with the intermediary arrangements that they involve, may be attributed to the combination of an orientational wetting phenomenon with subtle density- and contour-length-dependent variations in the elastic anisotropies of the corresponding liquid crystal phases. Conversely, the organization of rigid, microtubule-like polymers evidences a progressive breakdown of continuum elasticity theory as chain dimensions become comparable to the equilibrium radius of the encapsulating membrane. In this case, we observe a gradual shift from prolate, tactoid-like morphologies to oblate, erythrocyte-like structures with increasing contour lengths, which is shown to arise from the interplay between nematic ordering, polymer and membrane buckling. We further provide numerical evidence of a number of yet-unidentified, self-organized states in such confined systems of stiff achiral filaments, including spontaneous spiral smectic assemblies, faceted polyhedral and twisted bundle-like arrangements. Our results are quantified through the introduction of several order parameters and an unsupervised learning scheme for the localization of surface topological defects, and are in excellent agreement with field-theoretical predictions as well as classical elastic theories of thin rods and spherical shells.