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Base station densification is one of the key approaches for delivering high capacity in radio access networks. However, current static deployments are often impractical and financially unsustainable, as they increase both capital and operational expenditures of the network. An alternative paradigm is the moving base stations (MBSs) approach, by which part of base stations are installed on vehicles. However, to the best of our knowledge, it is still unclear if and up to which point MBSs allow decreasing the number of static base stations (BSs) deployed in urban settings. In this work, we start tackling this issue by proposing a modeling approach for a first-order evaluation of potential infrastructure savings enabled by the MBSs paradigm. Starting from a set of stochastic geometry results, and a traffic demand profile over time, we formulate an optimization problem for the derivation of the optimal combination of moving and static BSs which minimizes the overall amount of BSs deployed, while guaranteeing a target mean QoS for users. Initial results on a two-district scenario with measurement-based network traffic profiles suggest that substantial infrastructure savings are achievable. We show that these results are robust against different values of user density.

We present rest-frame optical spectra from Keck/MOSFIRE and Keck/NIRES of 16 candidate ultramassive galaxies targeted as part of the Massive Ancient Galaxies at $z>3$ Near-Infrared (MAGAZ3NE) Survey. These candidates were selected to have photometric redshifts $3\lesssim z_{\rm phot}<4$, photometric stellar masses log($M$/M$_\odot$)$>11.7$, and well-sampled photometric spectral energy distributions (SEDs) from the UltraVISTA and VIDEO surveys. In contrast to previous spectroscopic observations of blue star-forming and post-starburst ultramassive galaxies, candidates in this sample have very red SEDs implying significant dust attenuation, old stellar ages, and/or active galactic nuclei (AGN). Of these galaxies, eight are revealed to be heavily dust-obscured $2.03$, one is a $z\sim1.2$ dusty galaxy, and four galaxies do not have a confirmed spectroscopic redshift. In fact, none of the sample has |$z_{\rm spec}-z_{\rm phot}$|$<0.5$, suggesting difficulties for photometric redshift programs in fitting similarly red SEDs. The prevalence of these red interloper galaxies suggests that the number densities of high-mass galaxies are overestimated at $z\gtrsim3$ in large photometric surveys, helping to resolve the `impossibly early galaxy problem' and leading to much better agreement with cosmological galaxy simulations. A more complete spectroscopic survey of ultramassive galaxies is required to pin down the uncertainties on their number densities in the early universe., Comment: Submitted to ApJ. Comments welcome!

We present spectroscopic confirmation of an ultra-massive galaxy (UMG) with $\log(M_\star/M_\odot) = 10.98 \pm 0.07$ at $z_\mathrm{spec} = 4.8947$ in the Extended Groth Strip (EGS), based on deep observations of Ly$\alpha$ emission with Keck/DEIMOS. The ultra-massive galaxy (UMG-28740) is the most massive member in one of the most significant overdensities in the EGS, with four additional photometric members with $\log(M_\star/M_\odot) > 10.5$ within $R_\mathrm{proj} \sim 1$ cMpc. The Ly$\alpha$ profile is highly asymmetric ($A_f = 3.56$), suggesting the presence of neutral gas within the interstellar medium, circumgalactic medium, or via AGN-driven outflows. Spectral energy distribution (SED) fitting using a large suite of star formation histories and two sets of high-quality photometry from ground- and space-based facilities consistently estimates the stellar mass of UMG-28740 to be $\log(M_\star/M_\odot) \sim 11$ with a small standard deviation between measurements ($\sigma = 0.07$). While the best-fit SED models agree on stellar mass, we find discrepancies in the estimated star formation rate for UMG-28740, resulting in either a star-forming or quiescent system. JWST/NIRCam photometry of UMG-28740 strongly favors a quiescent scenario, demonstrating the need for high-quality mid-IR observations. Assuming the galaxy to be quiescent, UMG-28740 formed the bulk of its stars at $z > 10$ and is quenching at $z \sim 8$, resulting in a high star formation efficiency at high redshift ($\epsilon \sim 0.2$ at $z \sim 5$ and $\epsilon \gtrsim 1$ at $z \gtrsim 8$). As the most massive galaxy in its protocluster environment, UMG-28740 is a unique example of the impossibly early galaxy problem., Comment: 11 pages, 6 figures, 2 tables, Accepted to OJA

Fully distributed learning schemes such as Gossip Learning (GL) are gaining momentum due to their scalability and effectiveness even in dynamic settings. However, they often imply a high utilization of communication and computing resources, whose energy footprint may jeopardize the learning process, particularly on battery-operated IoT devices. To address this issue, we present Optimized Gossip Learning (OGL)}, a distributed training approach based on the combination of GL with adaptive optimization of the learning process, which allows for achieving a target accuracy while minimizing the energy consumption of the learning process. We propose a data-driven approach to OGL management that relies on optimizing in real-time for each node the number of training epochs and the choice of which model to exchange with neighbors based on patterns of node contacts, models' quality, and available resources at each node. Our approach employs a DNN model for dynamic tuning of the aforementioned parameters, trained by an infrastructure-based orchestrator function. We performed our assessments on two different datasets, leveraging time-varying random graphs and a measurement-based dynamic urban scenario. Results suggest that our approach is highly efficient and effective in a broad spectrum of network scenarios., Comment: IEEE AIIOT 2024

The allocation of computing tasks for networked distributed services poses a question to service providers on whether centralized allocation management be worth its cost. Existing analytical models were conceived for users accessing computing resources with practically indistinguishable (hence irrelevant for the allocation decision) delays, which is typical of services located in the same distant data center. However, with the rise of the edge-cloud continuum, a simple analysis of the sojourn time that computing tasks observe at the server misses the impact of diverse latency values imposed by server locations. We therefore study the optimization of computing task allocation with a new model that considers both distance of servers and sojourn time in servers. We derive exact algorithms to optimize the system and we show, through numerical analysis and real experiments, that differences in server location in the edge-cloud continuum cannot be neglected. By means of algorithmic game theory, we study the price of anarchy of a distributed implementation of the computing task allocation problem and unveil important practical properties such as the fact that the price of anarchy tends to be small -- except when the system is overloaded -- and its maximum can be computed with low complexity., Comment: Edge-Cloud Continuum; Network servers; Optimization; Next generation networking; Game Theory; Price of Anarchy

We define the notion of stochastic stability, already present in the literature in the context of smooth dynamical systems, for invariant measures of cellular automata perturbed by a random noise, and the notion of strongly stochastically stable cellular automaton. We study these notions on basic examples (nilpotent cellular automata, spreading symbols) using different methods inspired by those presented in \cite{MST19}. We then show that this notion of stability is not trivial by proving that a Turing machine cannot decide if a given invariant measure of a cellular automaton is stable under a uniform perturbation., Comment: 9 figure

Sequences of aftershocks following Omori's empirical law are observed after most major earthquakes, as well as in laboratory-scale fault-mimicking experiments. Nevertheless, the origin of this memory effect is still unclear. In this letter, we present an analytical framework for treating labquake and earthquake catalogs on an equal footing. Using this analysis method, we show that when memory is considered to be in deformation and not in time, all data collapse onto a single master curve, showing that the timescale is entirely fixed by the inverse of the strain rate.

The resolved mass assembly of Milky-Way-mass galaxies has been previously studied in simulations, the local universe, and at higher redshifts using infrared (IR) light profiles. To better characterize the mass assembly of Milky Way Analogues (MWAs), as well as their changes in star-formation rate and color gradients, we construct resolved stellar mass and star-formation rate maps of MWA progenitors selected with abundance matching techniques up to z $\sim$ 2 using deep, multi-wavelength imaging data from the Hubble Frontier Fields. Our results using stellar mass profiles agree well with previous studies that utilize IR light profiles, showing that the inner 2 kpc of the galaxies and the regions beyond 2 kpc exhibit similar rates of stellar mass growth. This indicates the progenitors of MWAs from $z\sim 2$ to the present do not preferentially grow their bulges or their disks. The evolution of the star-formation rate (SFR) profiles indicate greater decrease in SFR density in the inner regions versus the outer regions. S\'ersic parameters indicate modest growth in the central regions at lower redshifts, perhaps indicating slight bulge growth. However, the S\'ersic index does not rise above $n \sim 2$ until $z < 0.5$, meaning these galaxies are still disk dominated systems. We find that the half-mass radii of the MWA progenitors increase between $1.5 < z < 2$, but remain constant at later epochs ($z < 1.5$). This implies mild bulge growth since $z\sim 2$ in MWA progenitors, in line with previous MWA mass assembly studies., Comment: 19 Pages, 12 figures, accepted by ApJ

We present the construction of a deep multi-wavelength PSF-matched photometric catalog in the UDS field following the final UKIDSS UDS DR11 release. The catalog includes photometry in 24 filters, from the MegaCam-uS (0.38 microns) band to the Spitzer-IRAC (8 microns) band, over ~ 0.9 sq. deg. and with a 5-sigma depth of 25.3 AB in the K-band detection image. The catalog, containing approximately 188,564 (136,235) galaxies at 0.2 < z < 8.0 with stellar mass > 10$^{8}$ solar masses and K-band total magnitude K < 25.2 (24.3) AB, enables a range of extragalactic studies. We also provide photometric redshifts, corresponding redshift probability distributions, and rest-frame absolute magnitudes and colors derived using the template-fitting code eazy-py. Photometric redshift errors are less than 3 to 4 percent at z < 4 across the full brightness range in K-band and stellar mass range 10$^{8}$-10$^{12}$ solar masses. Stellar population properties (e.g., stellar mass, star-formation rate, dust extinction) are derived from the modeling of the spectral energy distributions (SEDs) using the codes FAST and Dense Basis., Comment: 26 pages, 18 figures, accepted in ApJ. Photometric Catalog, catalogs of stellar population properties derived using Eazy and Dense Basis and other high-level products available for public use at the following webpage - https://www.zaidikumail.com/feniks-uds-catalogs (DOI:10.5281/zenodo.11002298)

Internet of Things (IoT) devices often come with batteries of limited capacity that are not easily replaceable or rechargeable, and that constrain significantly the sensing, computing, and communication tasks that they can perform. The Simultaneous Wireless Information and Power Transfer (SWIPT) paradigm addresses this issue by delivering power wirelessly to energy-harvesting IoT devices with the same signal used for information transfer. For their peculiarity, these networks require specific energy-efficient planning and management approaches. However, to date, it is not clear what are the most effective strategies for managing a SWIPT network for energy efficiency. In this paper, we address this issue by developing an analytical model based on stochastic geometry, accounting for the statistics of user-perceived performance and base station scheduling. We formulate an optimization problem for deriving the energy optimal configuration as a function of the main system parameters, and we propose a genetic algorithm approach to solve it. Our results enable a first-order evaluation of the most effective strategies for energy-efficient provisioning of power and communications in a SWIPT network. We show that the service capacity brought about by users brings energy-efficient dynamic network provisioning strategies that radically differ from those of networks with no wireless power transfer., Comment: The manuscript has already been submitted to Journal on 7-12-2023

Documenting the interplay between slow deformation and seismic ruptures is essential to understand the physics of earthquakes nucleation. However, slow deformation is often difficult to detect and characterize. The most pervasive seismic markers of slow slip are low-frequency earthquakes (LFEs) that allow resolving deformations at minute-scale. Detecting LFEs is hard, due to their emergent onsets and low signal-to-noise ratios, usually requiring region-specific template matching approaches. These approaches suffer from low flexibility and might miss LFEs as they are constrained to sources identified a priori. Here, we develop a deep learning-based workflow for LFE detection, modeled after classical earthquake detection with phase picking, phase association, and location. Across three regions with known LFE activity, we detect LFEs from both previously cataloged sources and newly identified sources. Furthermore, the approach is transferable across regions, enabling systematic studies of LFEs in regions without known LFE activity.

The formation of galaxies by gradual hierarchical co-assembly of baryons and cold dark matter halos is a fundamental paradigm underpinning modern astrophysics and predicts a strong decline in the number of massive galaxies at early cosmic times. Extremely massive quiescent galaxies (stellar masses $>10^{11}$ M$_\odot$) have now been observed as early as 1-2 billions years after the Big Bang; these are extremely constraining on theoretical models as they form 300-500 Myr earlier and only some models can form massive galaxies this early. Here we report on the spectroscopic observations with the James Webb Space Telescope of a massive quiescent galaxy ZF-UDS-7329 at redshift 3.205 $\pm$ 0.005 that eluded deep ground-based spectrscopy, is significantly redder than typical and whose spectrum reveals features typical of much older stellar populations. Detailed modelling shows the stellar population formed around 1.5 billion years earlier in time (z ~ 11) at an epoch when dark matter halos of sufficient hosting mass have not yet assembled in the standard scenario. This observation may point to the presence of undetected populations of early galaxies and the possibility of significant gaps in our understanding of early stellar populations, galaxy formation and/or the nature of dark matter., Comment: 21 pages, 6 figures, updated to reflect accepted version. v3 with figure caption clarified

Motivated by spectroscopic confirmation of three overdense regions in the COSMOS field at $z\sim3.35$, we analyze the uniquely deep multi-wavelength photometry and extensive spectroscopy available in the field to identify any further related structure. We construct a three dimensional density map using the Voronoi tesselation Monte Carlo method and find additional regions of significant overdensity. Here we present and examine a set of six overdense structures at $3.205\sigma$ overdensity separated by up to 70 cMpc, suggestive of a proto-supercluster similar to the Hyperion system at $z\sim2.45$. Upcoming photometric surveys with JWST such as COSMOS-Web, and further spectroscopic follow-up will enable more extensive analysis of the evolutionary effects that such an environment may have on its component galaxies at these early times., Comment: Accepted for publication in MNRAS. 7 pages, 3 figures, 3 tables

The measured ages of massive, quiescent galaxies at $z\sim 3-4$ imply that massive galaxies quench as early as $z\sim 6$. While the number of spectroscopic confirmations of quiescent galaxies at $z < 3$ has increased over the years, there are only a handful at $z > 3.5$. We report spectroscopic redshifts of one secure ($z=3.757$) and two tentative ($z = 3.336$, $z=4.673$) massive ($\log(M_\ast/M_\odot) > 10.3$) quiescent galaxies with 11 hours of Keck/MOSFIRE $K$-band observations. Our candidates were selected from the FENIKS survey, which uses deep Gemini/Flamingos-2 $K_b$ $K_r$ imaging optimized for increased sensitivity to the characteristic red colors of galaxies at $z > 3$ with strong Balmer/4000 \AA\ breaks. The rest-frame $UVJ$ and $(ugi)_s$ colors of 3/4 quiescent candidates are consistent with $1-2$ Gyr old stellar populations. This places these galaxies as the oldest objects at these redshifts, and challenges the notion that quiescent galaxies at $z > 3$ are all recently-quenched, "post-starburst" galaxies. Our spectroscopy shows that the other quiescent-galaxy candidate is a broad-line AGN ($z = 3.594$) with strong, redshifted $H\beta$+[O III] emission with a velocity offset $>1000$ km/s, indicative of a powerful outflow. The star-formation history of our highest redshift candidate suggests that its progenitor was already in place by $z \sim 7-11$, reaching $\sim$ 10$^{11} M_{\odot}$ by $z \simeq 8$. These observations reveal the limit of what is possible with deep near-infrared photometry and targeted spectroscopy from the ground and demonstrate that secure spectroscopic confirmation of quiescent galaxies at $z > 4$ is only feasible with JWST., Comment: 20 pages, 11 figures, submitted to ApJ

Slow slip events (SSEs) originate from a slow slippage on faults that lasts from a few days to years. A systematic and complete mapping of SSEs is key to characterizing the slip spectrum and understanding its link with coeval seismological signals. Yet, SSE catalogues are sparse and usually remain limited to the largest events, because the deformation transients are often concealed in the noise of the geodetic data. Here we present the first multi-station deep learning SSE detector applied blindly to multiple raw geodetic time series. Its power lies in an ultra-realistic synthetic training set, and in the combination of convolutional and attention-based neural networks. Applied to real data in Cascadia over the period 2007-2022, it detects 78 SSEs, that compare well to existing independent benchmarks: 87.5% of previously catalogued SSEs are retrieved, each detection falling within a peak of tremor activity. Our method also provides useful proxies on the SSE duration and may help illuminate relationships between tremor chatter and the nucleation of the slow rupture. We find an average day-long time lag between the slow deformation and the tremor chatter both at a global- and local-temporal scale, suggesting that slow slip may drive the rupture of nearby small asperities.

In this paper we investigate the limit performance of Floating Gossip, a new, fully distributed Gossip Learning scheme which relies on Floating Content to implement location-based probabilistic evolution of machine learning models in an infrastructure-less manner. We consider dynamic scenarios where continuous learning is necessary, and we adopt a mean field approach to investigate the limit performance of Floating Gossip in terms of amount of data that users can incorporate into their models, as a function of the main system parameters. Different from existing approaches in which either communication or computing aspects of Gossip Learning are analyzed and optimized, our approach accounts for the compound impact of both aspects. We validate our results through detailed simulations, proving good accuracy. Our model shows that Floating Gossip can be very effective in implementing continuous training and update of machine learning models in a cooperative manner, based on opportunistic exchanges among moving users.

Here we present a sample of 12 massive quiescent galaxy candidates at z~3-4 observed with the James Webb Space Telescope (JWST) Near Infrared Spectrograph (NIRSpec). These galaxies were pre-selected from the Hubble Space Telescope imaging and 10 of our sources were unable to be spectroscopically confirmed by ground based spectroscopy. By combining spectroscopic data from NIRSpec with multi-wavelength imaging data from the JWST Near Infrared Camera (NIRCam), we analyse their stellar populations and their formation histories. We find that all of our galaxies classify as quiescent based on the reconstruction of their star formation histories but show a variety of quenching timescales and ages. All our galaxies are massive ($\sim0.1-1.2 \times 10^{11} M\odot$), with masses comparable to massive galaxies in the local Universe. We find that the oldest galaxy in our sample formed $\sim1.0\times10^{11} M\odot$ of mass within the first few hundred million years of the Universe and has been quenched for more than a billion years by the time of observation at z$\sim$3.2 ($\sim$2 billion years after the Big Bang). Our results point to very early formation of massive galaxies requiring a high conversion rate of baryons to stars in the early Universe., Comment: Published in Nature Scientific Reports

In this work we publish stellar velocity dispersions, sizes, and dynamical masses for 8 ultra-massive galaxies (UMGs; log($M$/M$_\odot>11$, $z\gtrsim3$) from the Massive Ancient Galaxies At $z>3$ NEar-infrared (MAGAZ3NE) Survey, more than doubling the number of such galaxies with velocity dispersion measurements at this epoch. Using the deep Keck/MOSFIRE and Keck/NIRES spectroscopy of these objects in the $H$- and $K$-bandpasses, we obtain large velocity dispersions of $\sim400$ km s$^{-1}$ for most of the objects, which are some of the highest stellar velocity dispersions measured, and $\sim40$\% larger than those measured for galaxies of similar mass at $z\sim1.7$. The sizes of these objects are also smaller by a factor of 1.5-3 compared to this same $z\sim1.7$ sample. We combine these large velocity dispersions and small sizes to obtain dynamical masses. The dynamical masses are similar to the stellar masses of these galaxies, consistent with a Chabrier initial mass function (IMF). Considered alongside previous studies of massive quiescent galaxies across $0.2

In this study, we aim to offer linguistically motivated solutions to resolve the issues of the lack of representation of null morphemes, highly productive derivational processes, and syncretic morphemes of Turkish in the BOUN Treebank without diverging from the Universal Dependencies framework. In order to tackle these issues, new annotation conventions were introduced by splitting certain lemmas and employing the MISC (miscellaneous) tab in the UD framework to denote derivation. Representational capabilities of the re-annotated treebank were tested on a LSTM-based dependency parser and an updated version of the BoAT Tool is introduced., Comment: This is a peer reviewed article that has been presented in The International Conference on Agglutinative Language Technologies as a challenge of Natural Language Processing (ALTNLP) 2022

We present a new rest-frame color-color selection method using "synthetic $u_s-g_s$ and $g_s-i_s$'', $(ugi)_s$ colors to identify star-forming and quiescent galaxies. Our method is similar to the widely-used $U-V$ versus $V-J$ ($UVJ$) diagram. However, $UVJ$ suffers known systematics. Spectroscopic campaigns have shown that $UVJ$-selected quiescent samples at $z \gtrsim 3$ include $\sim 10-30\%$ contamination from galaxies with dust-obscured star formation and strong emission lines. Moreover, at $z>3$, $UVJ$ colors are extrapolated because the rest-frame J-band shifts beyond the coverage of the deepest bandpasses at $< 5~\mu m$ (typically $Spitzer$/IRAC 4.5 $\mu m$ or future $JWST$/NIRCam observations). We demonstrate that $(ugi)_s$ offers improvements to $UVJ$ at $z>3$, and can be applied to galaxies in the $JWST$ era. We apply $(ugi)_s$ selection to galaxies at $0.5

The value of quality treebanks is steadily increasing due to the crucial role they play in the development of natural language processing tools. The creation of such treebanks is enormously labor-intensive and time-consuming. Especially when the size of treebanks is considered, tools that support the annotation process are essential. Various annotation tools have been proposed, however, they are often not suitable for agglutinative languages such as Turkish. BoAT v1 was developed for annotating dependency relations and was subsequently used to create the manually annotated BOUN Treebank (UD_Turkish-BOUN). In this work, we report on the design and implementation of a dependency annotation tool BoAT v2 based on the experiences gained from the use of BoAT v1, which revealed several opportunities for improvement. BoAT v2 is a multi-user and web-based dependency annotation tool that is designed with a focus on the annotator user experience to yield valid annotations. The main objectives of the tool are to: (1) support creating valid and consistent annotations with increased speed, (2) significantly improve the user experience of the annotator, (3) support collaboration among annotators, and (4) provide an open-source and easily deployable web-based annotation tool with a flexible application programming interface (API) to benefit the scientific community. This paper discusses the requirements elicitation, design, and implementation of BoAT v2 along with examples., Comment: Presented in The International Conference and Workshop on Agglutinative Language Technologies as a challenge of Natural Language Processing (ALTNLP), June 7-8, 2022, Koper, Slovenia

One of the challenges in understanding the quenching processes for galaxies is connecting progenitor star-forming populations to their descendant quiescent populations over cosmic time. Here we attempt a novel approach to this challenge by assuming that the underlying stellar mass distribution of galaxies is not significantly altered during environmental quenching processes that solely affect the gas content of cluster galaxies, such as strangulation and ram-pressure stripping. Using the deep, high-resolution photometry of the Hubble Frontier Fields, we create resolved stellar mass maps for both cluster and field galaxies, from which we determine 2D S\'ersic profiles, and obtain S\'ersic indices and half-mass radii. We classify the quiescent cluster galaxies into disk-like and bulge-like populations based on their S\'ersic indices, and find that bulge-like quiescent galaxies dominate the quiescent population at higher masses ($M_\star > 10^{9.5}M_\odot$), whereas disk-like quiescent galaxies dominate at lower masses ($10^{8.5}M_\odot< M_\star < 10^{9.5}M_\odot$). Using both the S\'ersic indices and half-mass radii, we identify a population of quiescent galaxies in clusters that are "morphological analogues" of field star-forming galaxies. These analogues are interpreted to be star-forming galaxies that had been environmentally quenched. We use these morphological analogues to compute the environmental-quenching efficiency, and we find that the efficiency decreases with increasing stellar mass. This demonstrates that environmental quenching is more effective on less massive galaxies and that the effect of environment on quenching galaxies is not completely separable from the effect of mass on quenching galaxies., Comment: 25 pages, 14 figures, accepted for publication in ApJ Revision ver. 1: Replaced title, fixed link to section 3

Compact star-forming clumps observed in distant galaxies are often suggested to play a crucial role in galaxy assembly. In this paper, we use a novel approach of applying finite resolution deconvolution on ground-based images of the COSMOS field to resolve 20,185 star-forming galaxies (SFG) at 0.5