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The characterization of the dynamical state of galaxies up to z~7 is crucial for constraining the mechanisms driving the mass assembly in the early Universe. However, it is unclear whether the data quality of current and future observations is sufficient to perform a solid dynamical analysis. This paper defines the angular resolution and S/N required for a robust characterization of the dynamical state of galaxies up to the EoR. The final aim is to help design spatially-resolved surveys targeting emission lines of primeval galaxies. We investigate the [CII]-158um emission from z~6-7 LBGs from the SERRA cosmological simulation, covering a range of dynamical states: from disks to major mergers. We create ALMA mock observations with various data quality and apply the kinematic classification methods used in the literature. These tests allow us to quantify the performances of such methods as a function of angular resolution and S/N. We find that barely-resolved observations do not allow the correct dynamical characterization of a galaxy, resulting in the misclassification of all disks in our sample. However, even when using spatially-resolved observations with data quality typical of high-z galaxies, the standard kinematic classification methods, based on the analysis of the moment maps, fail to distinguish a merger from a disk. The high angular resolution and S/N needed to apply these standard methods successfully can be achieved with current data only for a handful of bright galaxies. We propose a new classification method, called PVsplit, that quantifies the asymmetries and morphological features in position-velocity diagrams using three empirical parameters. We test PVsplit on our mock data concluding that it can predict whether a galaxy is a disk or a merger provided that S/N $\gtrsim10$, and the major axis is covered by $\gtrsim3$ independent resolution elements., Comment: Submitted to Astronomy and Astrophysics (A&A) Journal. Comments are welcome

Thanks to its capability to provide a uniform service rate for the User Equipments (UEs), Cell-free (CF) massive Multiple-Input, Multiple-Output (mMIMO), has recently attracted considerable attention, both in academia and in industry, and so is considered as one of the potential technologies for beyond-5G and 6G. However, the reuse of the same pilot signals by multiple users can create the so-called pilot contamination problem, which can hinder the CF mMIMO from unlocking its full performance. In this paper, we address the challenge by formulating the pilot assignment as a maximally diverse clustering problem and propose an efficient yet straightforward repulsive clustering-based pilot assignment scheme to mitigate the effects of pilot contamination on CF mMIMO. The numerical results show the superiority of the proposed technique compared to some other methods with respect to the achieved uplink per-user rate.

We investigate the fine-structure [C${\rm \scriptsize II}$] line at $158\,\mu$m as a molecular gas tracer by analyzing the relationship between molecular gas mass ($M_{\rm mol}$) and [C${\rm \scriptsize II}$] line luminosity ($L_{\rm [CII]}$) in 11,125 $z\simeq 6$ star-forming, main sequence galaxies from the SIMBA simulations, with line emission modeled by S\'IGAME. Though most ($\sim 50-100\,\%$) of the gas mass in our simulations is ionized, the bulk ($> 50\,\%$) of the [C${\rm \scriptsize II}$] emission comes from the molecular phase. We find a sub-linear (slope $0.78\pm 0.01$) $\log L_{\rm [CII]}-\log M_{\rm mol}$ relation, in contrast with the linear relation derived from observational samples of more massive, metal-rich galaxies at $z \lesssim 6$. We derive a median [C${\rm \scriptsize II}$]-to-$M_{\rm mol}$ conversion factor of $\alpha_{\rm [CII]} \simeq 18\,{\rm M_{\rm \odot}/L_{\rm \odot}}$. This is lower than the average value of $\simeq 30\,{\rm M_{\rm \odot}/L_{\rm \odot}}$ derived from observations, which we attribute to lower gas-phase metallicities in our simulations. Thus, a lower, luminosity-dependent, conversion factor must be applied when inferring molecular gas masses from [C${\rm \scriptsize II}$] observations of low-mass galaxies. For our simulations, [C${\rm \scriptsize II}$] is a better tracer of the molecular gas than CO $J=1-0$, especially at the lowest metallicities, where much of the gas is 'CO-dark'. We find that $L_{\rm [CII]}$ is more tightly correlated with $M_{\rm mol}$ than with star-formation rate (${\rm SFR}$), and both the $\log L_{\rm [CII]}-\log M_{\rm mol}$ and $\log L_{\rm [CII]}-\log {\rm SFR}$ relations arise from the Kennicutt-Schmidt relation. Our findings suggest that $L_{\rm [CII]}$ is a promising tracer of the molecular gas at the earliest cosmic epochs., Comment: 13 pages, 9 figures. Accepted for publication in ApJ

Fake news spreading, with the aim of manipulating individuals' perceptions of facts, is now recognized as a major problem in many democratic societies. Yet, to date, little has been understood about how fake news spreads on social networks, what the influence of the education level of individuals is, when fake news is effective in influencing public opinion, and what interventions might be successful in mitigating their effect. In this paper, starting from the recently introduced kinetic multi-agent model with competence by the first two authors, we propose to derive reduced-order models through the notion of social closure in the mean-field approximation that has its roots in the classical hydrodynamic closure of kinetic theory. This approach allows to obtain simplified models in which the competence and learning of the agents maintain their role in the dynamics and, at the same time, the structure of such models is more suitable to be interfaced with data-driven applications. Examples of different Twitter-based test cases are described and discussed., Comment: Minor changes to align the manuscript to its published version

We study the physical properties (size, stellar mass, luminosity, star formation rate) and scaling relations for a sample of 166 star-forming clumps with redshift $z \sim 2-6.2$. They are magnified by the Hubble Frontier Field galaxy cluster MACS~J0416 and have robust lensing magnification ($2\lesssim \mu \lesssim 82$) computed by using our high-precision lens model, based on 182 multiple images. Our sample extends by $\sim 3$ times the number of spectroscopically-confirmed lensed clumps at $z \gtrsim 2$. We identify clumps in ultraviolet continuum images and find that, whenever the effective spatial resolution (enhanced by gravitational lensing) increases, they fragment into smaller entities, likely reflecting the hierarchically-organized nature of star formation. Kpc-scale clumps, most commonly observed in field, are not found in our sample. The physical properties of our sample extend the parameter space typically probed by $z \gtrsim 1$ field observations and simulations, by populating the low mass (M$_\star \lesssim 10^7$ M$_\odot$), low star formation rate (SFR $\lesssim 0.5$ M$_\odot$ yr$^{-1}$), and small size (R$_\mathrm{eff} \lesssim 100$ pc) regime. The new domain probed by our study approaches the regime of compact stellar complexes and star clusters. In the mass-size plane, our sample spans the region between galaxies and globular clusters, with a few clumps in the region populated by young star clusters and globular-clusters. For the bulk of our sample, we measure star-formation rates which are higher than those observed locally in compact stellar systems, indicating different conditions for star formation at high redshift than in the local Universe., Comment: 25 pages, 20 figures, 3 table. Accepted to publication in MNRAS

The worldwide commercialization of fifth generation (5G) wireless networks and the exciting possibilities offered by connected and autonomous vehicles (CAVs) are pushing toward the deployment of heterogeneous sensors for tracking dynamic objects in the automotive environment. Among them, Light Detection and Ranging (LiDAR) sensors are witnessing a surge in popularity as their application to vehicular networks seem particularly promising. LiDARs can indeed produce a three-dimensional (3D) mapping of the surrounding environment, which can be used for object detection, recognition, and topography. These data are encoded as a point cloud which, when transmitted, may pose significant challenges to the communication systems as it can easily congest the wireless channel. Along these lines, this paper investigates how to compress point clouds in a fast and efficient way. Both 2D- and a 3D-oriented approaches are considered, and the performance of the corresponding techniques is analyzed in terms of (de)compression time, efficiency, and quality of the decompressed frame compared to the original. We demonstrate that, thanks to the matrix form in which LiDAR frames are saved, compression methods that are typically applied for 2D images give equivalent results, if not better, than those specifically designed for 3D point clouds., Comment: 6 pages, 5 figures, 1 table. This paper has been accepted for presentation at IEEE Wireless Communications and Networking Conference (WCNC) 2022. Please cite it as: F. Nardo, D. Peressoni, P. Testolina, M. Giordani, and A. Zanella, "Point cloud compression for efficient data broadcasting: A performance comparison," IEEE Wireless Communications and Networking Conference (WCNC), Austin, USA, 2022

In this paper, we focus on the construction of a hybrid scheme for the approximation of non-Maxwellian kinetic models with uncertainties. In the context of multiagent systems, the introduction of a kernel at the kinetic level is useful to avoid unphysical interactions. The methods here proposed, combine a direct simulation Monte Carlo (DSMC) in the phase space together with stochastic Galerkin (sG) methods in the random space. The developed schemes preserve the main physical properties of the solution together with accuracy in the random space. The consistency of the methods is tested with respect to surrogate Fokker-Planck models that can be obtained in the quasi-invariant regime of parameters. Several applications of the schemes to non-Maxwellian models of multiagent systems are reported., Comment: 28 pages, 8 figures

Cool gas (T$\sim$10$^{4}$~K) traced by hydrogen Ly$\alpha$ emission is now routinely detected around $z\sim3$ quasars, but little is known about their molecular gas reservoirs. Here, we present an APEX spectroscopic survey of the CO(6-5), CO(7-6) and [CI](2-1) emission lines for 9 quasars from the QSO MUSEUM survey which have similar UV luminosities, but very diverse Ly$\alpha$ nebulae. These observations ($\langle~\rm rms~\rangle=2.6$~mJy in 300~km~s$^{-1}$) detected three CO(6-5) lines with 3.4$\leq I_{\rm CO(6-5)} \leq$5.1~Jy~km~s$^{-1}$, 620$\leq$FWHM$\leq$707~km~s$^{-1}$, and three [CI](2-1) lines with 2.3$\leq I_{\rm [CI](2-1)} \leq$15.7~Jy~km~s$^{-1}$, 329$\leq$FWHM$\leq$943~km~s$^{-1}$. For the CO and [CI] detected sources, we constrain the molecular gas reservoirs to be $\rm M_{H_{2}} = (0.4-6.9) \times 10^{11} M_{\odot}$, while the non-detections imply $\rm M_{H_{2}} < 1.1\times 10^{11} M_{\odot}$. We compare our observations with the extended Ly$\alpha$ properties to understand the link between the cool and the molecular gas phases. We find large velocity shifts between the bulk of Ly$\alpha$ and the molecular gas systemic redshift in five sources (from $\sim$-400 to $\sim+$1200~km~s$^{-1}$). The sources with the largest shifts have the largest Ly$\alpha$ line widths in the sample, suggesting more turbulent gas conditions and/or large-scale inflows/outflows around these quasars. We also find that the brightest ($I_{\rm[CI](2-1)}=15.7\pm3.7~\rm Jy~km~s^{-1}$) and the widest (FWHM$\sim$900~km~s$^{-1}$) lines are detected for the smallest and dimmest Ly$\alpha$ nebulae. From this, we speculate that host galaxy obscuration can play an important role in reducing the ionizing and Ly$\alpha$ photons able to escape to halo scales, and/or that these systems are hosted by more massive halos., Comment: Accepted on January 3, MNRAS. 25 pages, 17 figures

Over the past few years, eXtended Reality (XR) has attracted increasing interest thanks to its extensive industrial and commercial applications, and its popularity is expected to rise exponentially over the next decade. However, the stringent Quality of Service (QoS) constraints imposed by XR's interactive nature require Network Slicing (NS) solutions to support its use over wireless connections: in this context, quasi-Constant Bit Rate (CBR) encoding is a promising solution, as it can increase the predictability of the stream, making the network resource allocation easier. However, traffic characterization of XR streams is still a largely unexplored subject, particularly with this encoding. In this work, we characterize XR streams from more than 4 hours of traces captured in a real setup, analyzing their temporal correlation and proposing two prediction models for future frame size. Our results show that even the state-of-the-art H.264 CBR mode can have significant frame size fluctuations, which can impact the NS optimization. Our proposed prediction models can be applied to different traces, and even to different contents, achieving very similar performance. We also show the trade-off between network resource efficiency and XR QoS in a simple NS use case., Comment: 10 pages, 10 figures. The paper has been submitted to IEEE WoWMoM 2022. Copyright may change without notice

Spectrum scarcity is one of the main challenges of future wireless technologies. When looking at vehicle-to-everything (V2X), this is amplified as spectrum sharing could impact road safety and traffic efficiency. It is therefore of particular importance to study solutions that allow the coexistence, in the same geographical area and in the same channels, of what are today the main V2X access technologies, namely IEEE 802.11p and sidelink LTE-V2X Mode 4. In this work, in addition to investigating the impact of the reciprocal interference, which we demonstrate to have a strong impact especially on the first and in congested channel conditions, a mitigation solution is extensively studied, which is based on the insertion of the IEEE 802.11p preamble at the beginning of the LTE-V2X sidelink transmission. The proposal, which is also under discussion within the standardization bodies, requires no modifications to the IEEE 802.11p protocol stack and minor changes to LTE-V2X sidelink. This solution is directly applicable to upcoming IEEE 802.11bd and extendable to NR-V2X sidelink. The paper shows, through analysis and simulations in free-flow and dense scenarios, that the proposal allows for a mitigation of collisions caused by co-channel coexistence under low to high-load channel conditions and that the improvement is also granted in congested cases when combined with additional countermeasures. Regarding the latter aspect, in particular, different approaches are compared, demonstrating that acting on the congestion control mechanisms is a simple but effective solution.

The spreading of Covid-19 pandemic has highlighted the close link between economics and health in the context of emergency management. A widespread vaccination campaign is considered the main tool to contain the economic consequences. This paper will focus, at the level of wealth distribution modelling, on the economic improvements induced by the vaccination campaign in terms of its effectiveness rate. The economic trend during the pandemic is evaluated resorting to a mathematical model joining a classical compartmental model including vaccinated individuals with a kinetic model of wealth distribution based on binary wealth exchanges. The interplay between wealth exchanges and the progress of the infectious disease is realized by assuming on the one hand that individuals in different compartments act differently in the economic process and on the other hand that the epidemic affects risk in economic transactions. Using the mathematical tools of kinetic theory, it is possible to identify the equilibrium states of the system and the formation of inequalities due to the pandemic in the wealth distribution of the population. Numerical experiments highlight the importance of the vaccination campaign and its positive effects in reducing economic inequalities in the multi-agent society., Comment: 22 pages, 20 figures

We study the class of first-order locally-balanced Metropolis--Hastings algorithms introduced in Livingstone & Zanella (2021). To choose a specific algorithm within the class the user must select a balancing function $g:\mathbb{R} \to \mathbb{R}$ satisfying $g(t) = tg(1/t)$, and a noise distribution for the proposal increment. Popular choices within the class are the Metropolis-adjusted Langevin algorithm and the recently introduced Barker proposal. We first establish a universal limiting optimal acceptance rate of 57% and scaling of $n^{-1/3}$ as the dimension $n$ tends to infinity among all members of the class under mild smoothness assumptions on $g$ and when the target distribution for the algorithm is of the product form. In particular we obtain an explicit expression for the asymptotic efficiency of an arbitrary algorithm in the class, as measured by expected squared jumping distance. We then consider how to optimise this expression under various constraints. We derive an optimal choice of noise distribution for the Barker proposal, optimal choice of balancing function under a Gaussian noise distribution, and optimal choice of first-order locally-balanced algorithm among the entire class, which turns out to depend on the specific target distribution. Numerical simulations confirm our theoretical findings and in particular show that a bi-modal choice of noise distribution in the Barker proposal gives rise to a practical algorithm that is consistently more efficient than the original Gaussian version., Comment: 24 pages, 4 figures

We propose AnonyGAN, a GAN-based solution for face anonymisation which replaces the visual information corresponding to a source identity with a condition identity provided as any single image. With the goal to maintain the geometric attributes of the source face, i.e., the facial pose and expression, and to promote more natural face generation, we propose to exploit a Bipartite Graph to explicitly model the relations between the facial landmarks of the source identity and the ones of the condition identity through a deep model. We further propose a landmark attention model to relax the manual selection of facial landmarks, allowing the network to weight the landmarks for the best visual naturalness and pose preservation. Finally, to facilitate the appearance learning, we propose a hybrid training strategy to address the challenge caused by the lack of direct pixel-level supervision. We evaluate our method and its variants on two public datasets, CelebA and LFW, in terms of visual naturalness, facial pose preservation and of its impacts on face detection and re-identification. We prove that AnonyGAN significantly outperforms the state-of-the-art methods in terms of visual naturalness, face detection and pose preservation., Comment: 21st International Conference on Image analysis and Processing

We use a sample of 706 galaxies, selected as [OII]$\lambda$3727 ([OII]) emitters in the Survey for High-$z$ Absorption Red and Dead Sources (SHARDS) on the CANDELS/GOODS-N field, to study the differential attenuation of the nebular emission with respect to the stellar continuum. The sample includes only galaxies with a counterpart in the infrared and $\mathrm{log}_{10}(M_{*}/\mathrm{M}_{\odot})$ $>$ 9, over the redshift interval 0.3 $\lesssim$ $z$ $\lesssim$ 1.5. Our methodology consists in the comparison of the star formation rates inferred from [OII] and H$\alpha$ emission lines with a robust quantification of the total star-forming activity (${SFR}_{\mathrm{TOT}}$) that is independently estimated based on both infrared and ultraviolet (UV) luminosities. We obtain $f$$=$$E(B-V)_{\mathrm{stellar}}$/$E(B-V)_{\mathrm{nebular}}$ $=$ 0.69$^{0.71}_{0.69}$ and 0.55$^{0.56}_{0.53}$ for [OII] and H$\alpha$, respectively. Our resulting $f$-factors display a significant positive correlation with the UV attenuation and shallower or not-significant trends with the stellar mass, the $SFR_{\mathrm{TOT}}$, the distance to the main sequence, and the redshift. Finally, our results favour an average nebular attenuation curve similar in shape to the typical dust curve of local starbursts., Comment: 23 pages, 10 figures, 3 tables; accepted for publication in MNRAS

The systematic targeting of extended Ly$\alpha$ emission around high-redshift quasars resulted in the discovery of rare and bright Enormous Ly$\alpha$ Nebulae (ELANe) associated with multiple active galactic nuclei (AGN). We here initiate "a multiwavelength study of ELAN environments" (AMUSE$^2$) focusing on the ELAN around the $z\sim3$ quasar SDSS J1040+1020, a.k.a. the Fabulous ELAN. We report on VLT/HAWK-I, APEX/LABOCA, JCMT/SCUBA-2, SMA/850$\mu$m, ALMA/CO(5-4) and 2mm observations and compare them to previously published VLT/MUSE data. The continuum and line detections enable a first estimate of the star-formation rates, dust, stellar and molecular gas masses in four objects associated with the ELAN (three AGNs and one Ly$\alpha$ emitter), confirming that the quasar host is the most star-forming (${\rm SFR}\sim500$ M$_\odot$ yr$^{-1}$) and massive galaxy ($M_{\rm star}\sim10^{11}$ M$_{\odot}$) in the system, and thus can be assumed as central. All four embedded objects have similar molecular gas reservoirs ($M_{\rm H_2}\sim10^{10}$ M$_{\odot}$), resulting in short depletion time scales. This fact together with the estimated total dark-matter halo mass, $M_{\rm DM}=(0.8-2)\times10^{13}$ M$_{\odot}$, implies that this ELAN will evolve into a giant elliptical galaxy. Consistently, the constraint on the baryonic mass budget for the whole system indicates that the majority of baryons should reside in a massive warm-hot reservoir (up to $10^{12}$ M$_{\odot}$), needed to complete the baryons count. Additionally, we discuss signatures of gas infall on the compact objects as traced by Ly$\alpha$ radiative transfer effects and the evidence for the alignment between the satellites' spins and their directions to the central., Comment: 26 pages, 19 figures, 4 appendix; submitted to ApJ

Over the last few years, the DRL paradigm has been widely adopted for 5G and beyond network optimization because of its extreme adaptability to many different scenarios. However, collecting and processing learning data entail a significant cost in terms of communication and computational resources, which is often disregarded in the networking literature. In this work, we analyze the cost of learning in a resource-constrained system, defining an optimization problem in which training a DRL agent makes it possible to improve the resource allocation strategy but also reduces the number of available resources. Our simulation results show that the cost of learning can be critical when evaluating DRL schemes on the network edge and that assuming a cost-free learning model can lead to significantly overestimating performance., Comment: 6 pages, 4 figures, 2 tables. This paper has been submitted to IEEE ICC 2022. Copyright IEEE 2021

We study the impact of contact heterogeneity on epidemic dynamics. A system characterized by multiple susceptible populations is considered. The description of the spread of an infectious disease is obtained through the study of a system of Boltzmann-type equations for the number densities of social contacts of the introduced compartments. A macroscopic system of equations characterizing observable effects of the epidemic is then derived to assess the impact of contact heterogeneity., Comment: 10 pages, 3 figures