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A key hurdle to the success of quantum computers is the ability to initialize qubits into a pure state, which can be achieved by cooling qubits down to very low temperatures. Computational cooling of qubits, whereby a subset of the qubits is cooled at the expense of heating the other qubits via the application of special sets of logic gates, offers a route to effectively cool qubits. Here, we present QuL, a programming library which can be used to generate, analyze, and test quantum circuits for various computational cooling protocols. In its most basic usage, QuL enables a novice user to easily produce cooling circuits with minimal input or knowledge required. The programming library, however, offers flexibility to more advanced users to finely tune the cooling protocol used to generate the quantum circuit. Finally, QuL offers methods to assess and compare various cooling protocols for users interested in studying optimal implementation of computational cooling in general, or on specific quantum backends. It is our hope that QuL will not only facilitate the execution of computational cooling on current quantum computers, but also serve as a tool to investigate open questions in the optimal implementation of computational cooling., Comment: 14 pages, 7 figures

Timeseria is an object-oriented time series processing library implemented in Python, which aims at making it easier to manipulate time series data and to build statistical and machine learning models on top of it. Unlike common data analysis frameworks, it builds up from well defined and reusable logical units (objects), which can be easily combined together in order to ensure a high level of consistency. Thanks to this approach, Timeseria can address by design several non-trivial issues often underestimated, such as handling data losses, non-uniform sampling rates, differences between aggregated data and punctual observations, time zones, daylight saving times, and more. Timeseria comes with a comprehensive set of base data structures, common data manipulation operations, and extensible models for data reconstruction, forecasting and anomaly detection. It also integrates a powerful plotting engine capable of handling even millions of data points.

Continued fractions have been generalized over the field of $p$-adic numbers, where it is still not known an analogue of the famous Lagrange's Theorem. In general, the periodicity of $p$-adic continued fractions is well studied and addressed as a hard problem. In this paper, we show a strong connection between periodic $p$--adic continued fractions and the convergence to real quadratic irrationals. In particular, in the first part we prove that the convergence in $\mathbb{R}$ is a necessary condition for the periodicity of the continued fractions of a quadratic irrational in $\mathbb{Q}_p$. Moreover, we leave several conjectures on the converse, supported by experimental computations. In the second part of the paper, we exploit these results to develop a probabilistic argument for the non-periodicity of Browkin's $p$-adic continued fractions. The probabilistic results are conditioned under the assumption of uniform distribution of the $p$-adic digits of a quadratic irrational, that holds for almost all $p$-adic numbers.

Binaries with a Wolf-Rayet star and a compact object (WR-COs), either a black hole (BH) or a neutron star (NS), have been proposed as possible progenitors for the binary compact object mergers (BCOs) observed with the gravitational wave (GW) detectors. In this work, we use the open-source population synthesis code SEVN to investigate the role of WR-COs as BCO progenitors. We consider an initial population of $5 \times 10^6$ binaries and we evolve it across 96 combinations of metallicities, common envelope efficiencies, core-collapse supernova models and natal kick distributions. We find that WR-COs are the progenitors of most BCOs, especially at high and intermediate metallicity. At $Z=0.02,\,{}0.014,$ and $0.0014$, more than $\gtrsim 99 \%$ of all the BCOs in our simulations evolved as WR-COs. At $Z = 0.00014$, inefficient binary-stripping lowers the fraction of BCOs with WR-CO progenitors to $\approx 83-95 \%$. Despite their key role in BCO production, only $\approx 5-30 \%$ of WR-COs end their life as BCOs. We find that Cyg X-3, the only WR-CO candidate observed in the Milky Way, is a promising BCO progenitor, especially if it hosts a BH. In our simulations, about $\approx 70-100 \%$ of the Cyg X-3 - like systems in the WR-BH configuration (BH mass $ \leq 10 \rm ~ M_\odot$) are BCO progenitors, in agreement with the literature. Future observations of WR-COs similar to Cyg X-3 may be the Rosetta stone to interpret the formation of BCOs., Comment: 16 pages, 13 figures, 1 table. Submitted to A&A, comments welcome

We study how stronger noise can enhance the entanglement in inhomogeneously monitored quantum systems. We consider a free fermions model composed of two coupled chains - a system chain and an ancilla chain, each subject to its own different noise - and explore the dynamics of entanglement within the system chain under different noise intensities. Our results demonstrate that, contrary to the detrimental effects typically associated with noise, certain regimes of noise on the ancilla can significantly enhance entanglement within the system. Numerical simulations demonstrate the robustness of such entanglement enhancement across various system sizes and noise parameters. This enhancement is found to be highly dependent on the hopping strength in the ancilla, suggesting that the interplay between unitary dynamics and noise can be tuned to optimize the entanglement of a quantum system., Comment: 17 pages, 9 figures

First order phase transitions in the early universe may have left a variety of experimentally accessible imprints. The dynamics of such transitions is governed by the density perturbations caused by the propagation of the bubble wall in the false vacuum plasma, conveniently described by a Boltzmann equation. The determination of the bubble wall expansion velocity is crucial to determine the experimental signatures of the transition. We report on the first full (numerical) solution to the Boltzmann equation. Differently from traditional ones, our approach does not rely on any ansatz. The results significantly differ from the ones obtained within the fluid approximation and large differences for the friction acting on the bubble wall are found. The wall velocity is calculated in a singlet extension of the Standard Model, including out-of-equilibrium contributions from both the top quark and the electroweak gauge bosons., Comment: 7 pages, 3 figures, presented at QCD@Work International Workshop on QCD Theory and Experiment 2024

Recently, AI systems have made remarkable progress in various tasks. Deep Reinforcement Learning(DRL) is an effective tool for agents to learn policies in low-level state spaces to solve highly complex tasks. Researchers have introduced Intrinsic Motivation(IM) to the RL mechanism, which simulates the agent's curiosity, encouraging agents to explore interesting areas of the environment. This new feature has proved vital in enabling agents to learn policies without being given specific goals. However, even though DRL intelligence emerges through a sub-symbolic model, there is still a need for a sort of abstraction to understand the knowledge collected by the agent. To this end, the classical planning formalism has been used in recent research to explicitly represent the knowledge an autonomous agent acquires and effectively reach extrinsic goals. Despite classical planning usually presents limited expressive capabilities, PPDDL demonstrated usefulness in reviewing the knowledge gathered by an autonomous system, making explicit causal correlations, and can be exploited to find a plan to reach any state the agent faces during its experience. This work presents a new architecture implementing an open-ended learning system able to synthesize from scratch its experience into a PPDDL representation and update it over time. Without a predefined set of goals and tasks, the system integrates intrinsic motivations to explore the environment in a self-directed way, exploiting the high-level knowledge acquired during its experience. The system explores the environment and iteratively: (a) discover options, (b) explore the environment using options, (c) abstract the knowledge collected and (d) plan. This paper proposes an alternative approach to implementing open-ended learning architectures exploiting low-level and high-level representations to extend its knowledge in a virtuous loop.

Online platforms for social interactions are an essential part of modern society. With the advance of technology and the rise of algorithms and AI, content is now filtered systematically and facilitates the formation of filter bubbles. This work investigates the social consensus under limited visibility in a two-state majority-vote model on Barab\'asi-Albert scale-free networks. In the consensus evolution, each individual assimilates the opinion of the majority of their neighbors with probability $1-q$ and disagrees with chance $q$, known as the noise parameter. We define the visibility parameter $V$ as the probability of an individual considering the opinion of a neighbor at a given interaction. The parameter $V$ enables us to model the limited visibility phenomenon that produces synthetic neighborhoods in online interactions. We employ Monte Carlo simulations and finite-size scaling analysis to obtain the critical noise parameter as a function of the visibility $V$ and the growth parameter $z$. We find the critical exponents $\beta/\bar{\nu}$, $\gamma/\bar{\nu}$ and $1/\bar{\nu}$ of and validate their unitary relation for complex networks. Our analysis shows that installing and manipulating synthetic influence groups critically undermines consensus robustness., Comment: 10 pages, 9 figures, 1 table

Context. Computational astronomy has reached the stage where running a gravitational N-body simulation of a stellar system, such as a Milky Way star cluster, is computationally feasible, but a major limiting factor that remains is the ability to set up physically realistic initial conditions. Aims. We aim to obtain realistic initial conditions for N-body simulations by taking advantage of machine learning, with emphasis on reproducing small-scale interstellar distance distributions. Methods. The computational bottleneck for obtaining such distance distributions is the hydrodynamics of star formation, which ultimately determine the features of the stars, including positions, velocities, and masses. To mitigate this issue, we introduce a new method for sampling physically realistic initial conditions from a limited set of simulations using Gaussian processes. Results. We evaluated the resulting sets of initial conditions based on whether they meet tests for physical realism. We find that direct sampling based on the learned distribution of the star features fails to reproduce binary systems. Consequently, we show that physics-informed sampling algorithms solve this issue, as they are capable of generating realisations closer to reality., Comment: Accepted to A&A (4th Sep 2024)

To capture the dynamics of macroscopic non-relativistic fluids consisting of very many atoms, it is typically sufficient to truncate the gradient expansion at order zero, leading to ideal fluid dynamics, or at order one, leading to the Navier-Stokes theory. For mesoscopic fluids consisting of a small number of atoms, second-order corrections can become significant. We investigate here specifically superfluids at vanishing temperature, and identify relevant second-order terms of quantum origin that contribute already in a static situation. The general form of these terms arises from an extension of the Gross-Pitaevskii theory. In the context of density functional theory, they are named after C. von Weizs\"acker. We assess the influence of these terms on numerical solutions of second-order fluid dynamic equations for the expansion of a mesoscopic ultra-cold Fermi gas released from an anisotropic harmonic trap in two spatial dimensions.

Classical machine learning has proven remarkably useful in post-processing quantum data, yet typical learning algorithms often require prior training to be effective. In this work, we employ a tensorial kernel support vector machine (TK-SVM) to analyze experimental data produced by trapped-ion quantum computers. This unsupervised method benefits from directly interpretable training parameters, allowing it to identify the non-trivial string-order characterizing symmetry-protected topological (SPT) phases. We apply our technique to two examples: a spin-1/2 model and a spin-1 model, featuring the cluster state and the AKLT state as paradigmatic instances of SPT order, respectively. Using matrix product states, we generate a family of quantum circuits that host a trivial phase and an SPT phase, with a sharp phase transition between them. For the spin-1 case, we implement these circuits on two distinct trapped-ion machines based on qubits and qutrits. Our results demonstrate that the TK-SVM method successfully distinguishes the two phases across all noisy experimental datasets, highlighting its robustness and effectiveness in quantum data interpretation., Comment: 16 pages, 11 figures

This work utilizes the Immersed Boundary Conformal Method (IBCM) to analyze Kirchhoff-Love and Reissner-Mindlin shell structures within an immersed domain framework. Immersed boundary methods involve embedding complex geometries within a background grid, which allows for great flexibility in modeling intricate shapes and features despite the simplicity of the approach. The IBCM method introduces additional layers conformal to the boundaries, allowing for the strong imposition of Dirichlet boundary conditions and facilitating local refinement. In this study, the construction of boundary layers is combined with high-degree spline-based approximation spaces to further increase efficiency. The Nitsche method, employing non-symmetric average operators, is used to couple the boundary layers with the inner patch, while stabilizing the formulation with minimal penalty parameters. High-order quadrature rules are applied for integration over cut elements and patch interfaces. Numerical experiments demonstrate the efficiency and accuracy of the proposed formulation, highlighting its potential for complex shell structures modeled through Kirchhoff-Love and Reissner-Mindlin theories. These tests include the generation of conformal interfaces, the coupling of Kirchhoff-Love and Reissner-Mindlin theories, and the simulation of a damaged shell.

Large autoregressive generative models have emerged as the cornerstone for achieving the highest performance across several Natural Language Processing tasks. However, the urge to attain superior results has, at times, led to the premature replacement of carefully designed task-specific approaches without exhaustive experimentation. The Coreference Resolution task is no exception; all recent state-of-the-art solutions adopt large generative autoregressive models that outperform encoder-based discriminative systems. In this work,we challenge this recent trend by introducing Maverick, a carefully designed - yet simple - pipeline, which enables running a state-of-the-art Coreference Resolution system within the constraints of an academic budget, outperforming models with up to 13 billion parameters with as few as 500 million parameters. Maverick achieves state-of-the-art performance on the CoNLL-2012 benchmark, training with up to 0.006x the memory resources and obtaining a 170x faster inference compared to previous state-of-the-art systems. We extensively validate the robustness of the Maverick framework with an array of diverse experiments, reporting improvements over prior systems in data-scarce, long-document, and out-of-domain settings. We release our code and models for research purposes at https://github.com/SapienzaNLP/maverick-coref., Comment: Accepted at main conference of ACL 2024. 15 pages

Large Language Models (LLMs) show promising potential in Software Engineering, especially for code-related tasks like code completion and code generation. LLMs' evaluation is generally centred around general metrics computed over benchmarks. While painting a macroscopic view of the benchmarks and of the LLMs' capacity, it is unclear how each programming task in these benchmarks assesses the capabilities of the LLMs. In particular, the difficulty level of the tasks in the benchmarks is not reflected in the score used to report the performance of the model. Yet, a model achieving a 90% score on a benchmark of predominantly easy tasks is likely less capable than a model achieving a 90% score on a benchmark containing predominantly difficult tasks. This paper devises a framework, HardEval, for assessing task difficulty for LLMs and crafting new tasks based on identified hard tasks. The framework uses a diverse array of prompts for a single task across multiple LLMs to obtain a difficulty score for each task of a benchmark. Using two code generation benchmarks, HumanEval+ and ClassEval, we show that HardEval can reliably identify the hard tasks within those benchmarks, highlighting that only 21% of HumanEval+ and 27% of ClassEval tasks are hard for LLMs. Through our analysis of task difficulty, we also characterize 6 practical hard task topics which we used to generate new hard tasks. Orthogonal to current benchmarking evaluation efforts, HardEval can assist researchers and practitioners in fostering better assessments of LLMs. The difficulty score can be used to identify hard tasks within existing benchmarks. This, in turn, can be leveraged to generate more hard tasks centred around specific topics either for evaluation or improvement of LLMs. HardEval generalistic approach can be applied to other domains such as code completion or Q/A.

The proliferation of human-AI ecosystems involving human interaction with algorithms, such as assistants and recommenders, raises concerns about large-scale social behaviour. Despite evidence of such phenomena across several contexts, the collective impact of GPS navigation services remains unclear: while beneficial to the user, they can also cause chaos if too many vehicles are driven through the same few roads. Our study employs a simulation framework to assess navigation services' influence on road network usage and CO2 emissions. The results demonstrate a universal pattern of amplified conformity: increasing adoption rates of navigation services cause a reduction of route diversity of mobile travellers and increased concentration of traffic and emissions on fewer roads, thus exacerbating an unequal distribution of negative externalities on selected neighbourhoods. Although navigation services recommendations can help reduce CO2 emissions when their adoption rate is low, these benefits diminish or even disappear when the adoption rate is high and exceeds a certain city- and service-dependent threshold. We summarize these discoveries in a non-linear function that connects the marginal increase of conformity with the marginal reduction in CO2 emissions. Our simulation approach addresses the challenges posed by the complexity of transportation systems and the lack of data and algorithmic transparency.

Peculiar phenomena have been observed in analyses of anisotropic flow ($v_n$) fluctuations in ultracentral nucleus-nucleus collisions: The fourth-order cumulant of the elliptic flow ($v_2$) distribution changes sign. In addition, the ATLAS collaboration has shown that cumulants of $v_n$ fluctuations of all orders depend significantly on the centrality estimator. We show that these peculiarities are due to the fact that the impact parameter $b$ always spans a finite range for a fixed value of the centrality estimator. We provide a quantitative determination of this range through a simple Bayesian analysis. We obtain excellent fits of STAR and ATLAS data, with a few parameters, by assuming that the probability distribution of $v_n$ solely depends on $b$ at a given centrality. This probability distribution is almost Gaussian, and its parameters depend smoothly on $b$, in a way that is constrained by symmetry and scaling laws. We reconstruct, thus, the impact parameter dependence of the mean elliptic flow in the reaction plane in a model-independent manner, and assess the robustness of the extraction using Monte Carlo simulations of the collisions where the impact parameter is known. We argue that the non-Gaussianity of $v_n$ fluctuations gives direct information on the hydrodynamic response to initial anisotropies, ATLAS data being consistent with a smaller response for $n=4$ than for $n=2$ and $n=3$, in agreement with hydrodynamic calculations., Comment: 18 pages, 8 figures

SOXS (Son Of X-Shooter) is the new single object spectrograph for the ESO New Technology Telescope (NTT) at the La Silla Observatory, able to cover simultaneously both the UV-VIS and NIR bands (350-2000 nm). The instrument is currently in the integration and test phase, approaching the Preliminary Acceptance in Europe (PAE) before shipment to Chile for commissioning. After the assembly and preliminary test of the control electronics at INAF - Astronomical Observatory of Capodimonte (Napoli), the two main control cabinets of SOXS are now hosted in Padova, connected to the real hardware. This contribution describes the final electronic cabinets layout, the control strategy and the different integration phases, waiting for the Preliminary Acceptance in Europe and the installation of the instrument in Chile.

The Son Of X-Shooter (SOXS) will be the specialized facility to observe any transient event with a flexible scheduler at the ESO New Technology Telescope (NTT) at La Silla, Chile. SOXS is a single object spectrograph offering simultaneous spectral coverage in UV-VIS (350-850 nm) and NIR (800-2000 nm) wavelength regimes with an average of R~4500 for a 1arcsec slit. SOXS also has imaging capabilities in the visible wavelength regime. Currently, SOXS is being integrated at the INAF-Astronomical Observatory of Padova. Subsystem- and system-level tests and verification are ongoing to ensure and confirm that every requirement and performance are met. In this paper, we report on the integration and verification of SOXS as the team and the instrument prepare for the Preliminary Acceptance Europe (PAE).

The Son Of X-Shooter (SOXS) is a single object spectrograph, built by an international consortium for the 3.58-m ESO New Technology Telescope at the La Silla Observatory [1]. It offers a simultaneous spectral coverage over 350-2000 nm, with two separate spectrographs. In this paper we present the status of the Near InfraRed (NIR) cryogenic echelle cross-dispersed spectrograph [1], in the range 0.80-2.00 {\mu}m with 15 orders, equipped with an 2k x 2k Hawaii H2RG IR array from Teledyne, working at 40K, that is currently assembled and tested on the SOXS instrument, in the premises of INAF in Padova. We describe the different tests and results of the cryo, vacuum, opto-mechanics and detector subsystems that finally will be part of the PAE by ESO., Comment: 8 Pages, 7 Figures, Astronomical Telescopes and Instrumentation, SPIE Proceedings 2024

We present the advancements in the development of the scheduler for the Son Of X-shooter instrument at the ESO-NTT 3.58-m telescope in La Silla, Chile. SOXS is designed as a single-object spectroscopic facility and features a high-efficiency spectrograph with two arms covering the spectral range of 350-2000 nm and a mean resolving power of approximately R=4500. It will conduct UV-visible and near-infrared follow-up observations of astrophysical transients, drawing from a broad pool of targets accessible through the streaming services of wide-field telescopes, both current and future, as well as high-energy satellites. The instrument will cater to various scientific objectives within the astrophysical community, each entailing specific requirements for observation planning. SOXS will operate at the European Southern Observatory (ESO) in La Silla, without the presence of astronomers on the mountain. This poses a unique challenge for the scheduling process, demanding a fully automated algorithm that is autonomously interacting with the appropriate databases and the La Silla Weather API, and is capable of presenting the operator not only with an ordered list of optimal targets (in terms of observing constraints) but also with optimal backups in the event of changing weather conditions. This imposes the necessity for a scheduler with rapid-response capabilities without compromising the optimization process, ensuring the high quality of observations and best use of the time at the telescope. We thus developed a new highly available and scalable architecture, implementing API Restful applications like Docker Containers, API Gateway, and Python-based Flask frameworks. We provide an overview of the current state of the scheduler, which is now ready for the approaching on-site testing during Commissioning phase, along with insights into its web interface and preliminary performance tests.

The Instrument Control Software of SOXS (Son Of X-Shooter), the forthcoming spectrograph for the ESO New Technology Telescope at the La Silla Observatory, has reached a mature state of development and is approaching the crucial Preliminary Acceptance in Europe phase. Now that all the subsystems have been integrated in the laboratories of the Padova Astronomical Observatory, the team operates for testing purposes with the whole instrument at both engineering and scientific level. These activities will make use of a set of software peculiarities that will be discussed in this contribution. In particular, we focus on the synoptic panel, the co-rotator system special device, on the Active Flexure Compensation system which controls two separate piezo tip-tilt devices., Comment: 6 pages, 3 figures, SPIE conference

We consider anyonic quasiparticles with charge e/2 described by the {\nu} = 1/2 chiral Luttinger liquid, which collide in a Hong-Ou-Mandel-like interferometer. These colliding anyonic channels can be formally viewed as hosting Laughlin-like fractional {\nu} = 1/2 quasiparticles. More specifically, two possible geometries are considered: (i) a two-edge-channel setup where anyons originate from equilibrium reservoirs; (ii) a four-edge-channel setup where nonequilibrium anyons arrive at the collider in the form of diluted beams. For both setups, we calculate the tunneling current and the current correlations. For setup (i), our results provide analytically exact expressions for the tunneling current, tunneling-current noise, and cross-correlation noise, The exact relation between conductance and noise is demonstrated. For setup (ii), we show that the tunneling current and the generalized Fano factor [defined in B. Rosenow et al. (2016)] are finite for diluted streams of {\nu} = 1/2 anyons. This is due to the processes where nonequilibrium anyons, supplied via either source edge, directly tunnel at the central QPC. Thus, to obtain meaningful results in this case, one should go beyond the so-called time-domain braiding processes, where nonequilibrium anyons do not tunnel at the collider, but rather indirectly influence the tunneling by braiding with the quasiparticle-quasihole pairs created at the collider. This suggests that the effect of direct tunneling and collisions of diluted anyons in the Hong-Ou-Mandel interferometer can be important for various observables in physical quantum-Hall edges at Laughlin filling fractions., Comment: 39 pages, 10 figures

The logico-algebraic study of Lewis's hierarchy of variably strict conditional logics has been essentially unexplored, hindering our understanding of their mathematical foundations, and the connections with other logical systems. This work aims to fill this gap by providing a comprehensive logico-algebraic analysis of Lewis's logics. We begin by introducing novel finite axiomatizations for varying strengths of Lewis's logics, distinguishing between global and local consequence relations on Lewisian sphere models. We then demonstrate that the global consequence relation is strongly algebraizable in terms of a specific class of Boolean algebras with a binary operator representing the counterfactual implication; in contrast, we show that the local consequence relation is generally not algebraizable, although it can be characterized as the degree-preserving logic over the same algebraic models. Further, we delve into the algebraic semantics of Lewis's logics, developing two dual equivalences with respect to particular topological spaces. In more details, we show a duality with respect to the topological version of Lewis's sphere models, and also with respect to Stone spaces with a selection function; using the latter, we demonstrate the strong completeness of Lewis's logics with respect to sphere models. Finally, we draw some considerations concerning the limit assumption over sphere models.

We introduce a cyclic quantum battery model, based on an interacting bipartite system, weakly coupled to a thermal bath. The working cycle of the battery consists of four strokes: system thermalization, disconnection of subsystems, ergotropy extraction, and reconnection. The thermal bath acts as a charger in the thermalization stroke, while ergotropy extraction is possible because the ensuing thermal state is no longer passive after the disconnection stroke. Focusing on the case of two interacting qubits, we show that phase coherence, in the presence of non-trivial correlations between the qubits, can be exploited to reach working regimes with efficiency higher than 50% while providing finite ergotropy. Our protocol is illustrated through a simple and feasible circuit model of a cyclic superconducting quantum battery. Furthermore, we simulate the considered cycle on superconducting IBM quantum machines. The good agreement between the theoretical and simulated results strongly suggests that our scheme for cyclic quantum batteries can be successfully realized in superconducting quantum hardware., Comment: 20 pages, 9 figures

The Fornax dwarf spheroidal galaxy (dSph) represents a challenge for some globular cluster (GC) formation models, because an exceptionally high fraction of its stellar mass is locked in its GC system. In order to shed light on our understanding of GC formation, we aim to constrain the amount of stellar mass that Fornax has lost via tidal interaction with the Milky Way (MW). Exploiting the flexibility of effective multi-component $N$-body simulations and relying on state-of-the-art estimates of Fornax's orbital parameters, we study the evolution of the mass distribution of the Fornax dSph in observationally justified orbits in the gravitational potential of the MW over 12 Gyr. We find that, though the dark-matter mass loss can be substantial, the fraction of stellar mass lost by Fornax to the MW is always negligible, even in the most eccentric orbit considered. We conclude that stellar-mass loss due to tidal stripping is not a plausible explanation for the unexpectedly high stellar mass of the GC system of the Fornax dSph and we discuss quantitatively the implications for GC formation scenarios., Comment: 15 pages, 12 figures. Version accepted in A&A

Recommendation systems and assistants (in short, recommenders) are ubiquitous in online platforms and influence most actions of our day-to-day lives, suggesting items or providing solutions based on users' preferences or requests. This survey analyses the impact of recommenders in four human-AI ecosystems: social media, online retail, urban mapping and generative AI ecosystems. Its scope is to systematise a fast-growing field in which terminologies employed to classify methodologies and outcomes are fragmented and unsystematic. We follow the customary steps of qualitative systematic review, gathering 144 articles from different disciplines to develop a parsimonious taxonomy of: methodologies employed (empirical, simulation, observational, controlled), outcomes observed (concentration, model collapse, diversity, echo chamber, filter bubble, inequality, polarisation, radicalisation, volume), and their level of analysis (individual, item, model, and systemic). We systematically discuss all findings of our survey substantively and methodologically, highlighting also potential avenues for future research. This survey is addressed to scholars and practitioners interested in different human-AI ecosystems, policymakers and institutional stakeholders who want to understand better the measurable outcomes of recommenders, and tech companies who wish to obtain a systematic view of the impact of their recommenders.

International trade and logistics are subject to factors including geopolitical instability, climate change, and black swan events such as the unforeseen closure of the Suez Canal. The problem of predicting local price change under modification of an underlying transport network or change in supply characteristics unites elements of game theory, network theory and transport. The Cournot Oligopoly models economic actors as rational players attempting to maximise profit by optimising supply quantities with analytical results now consolidated about equilibrium characteristics where transport conditions are fixed. Similarly, where supply and demand are fixed, the routing of goods in a transport network can be analytically solved through a traffic assignment problem. Hence we can solve the coupled Cournot-congestion problem by means of a 2-layer network. Where the layers are linked, inter-layer feedback wherein players attempt to maximise their utility occurs. In this respect we find players benefit from taking advantage of non-simultaneous responses to the market rather than moving to a new equilibrium. We draw conclusions about the nature of equilibria, finding that the concave utility curve property results in unique and stable equilibrium for each uncoupled layer, while linked layers have a non-unique stable equilibria for which general solutions are stated., Comment: 27 pages, 11 figures

We present the discovery and early observations of the nearby Type II supernova (SN) 2024ggi in NGC 3621 at 6.64 +/- 0.3 Mpc. The SN was caught 5.8 (+1.9 -2.9) hours after its explosion by the ATLAS survey. Early-phase, high-cadence, and multi-band photometric follow-up was performed by the Kinder (Kilonova Finder) project, collecting over 1000 photometric data points within a week. The combined o- and r-band light curves show a rapid rise of 3.3 magnitudes in 13.7 hours, much faster than SN 2023ixf (another recent, nearby, and well-observed SN II). Between 13.8 and 18.8 hours after explosion SN 2024ggi became bluer, with u-g colour dropping from 0.53 to 0.15 mag. The rapid blueward evolution indicates a wind shock breakout (SBO) scenario. No hour-long brightening expected for the SBO from a bare stellar surface was detected during our observations. The classification spectrum, taken 17 hours after the SN explosion, shows flash features of high-ionization species such as Balmer lines, He I, C III, and N III. Detailed light curve modeling reveals critical insights into the properties of the circumstellar material (CSM). Our favoured model has an explosion energy of 2 x 10^51 erg, a mass-loss rate of 10^-3 solar_mass/yr (with an assumed 10 km/s wind), and a confined CSM radius of 6 x 10^14 cm. The corresponding CSM mass is 0.4 solar_mass. Comparisons with SN 2023ixf highlight that SN 2024ggi has a smaller CSM density, resulting in a faster rise and fainter UV flux. The extensive dataset and the involvement of citizen astronomers underscore that a collaborative network is essential for SBO searches, leading to more precise and comprehensive SN characterizations., Comment: 11 pages, 5 figures in manuscript, 6 pages in appendix, submitted to ApJL

Alternative routing is crucial to minimize the environmental impact of urban transportation while enhancing road network efficiency and reducing traffic congestion. Existing methods neglect information about road popularity, possibly leading to unintended consequences such as increasing emissions and congestion. This paper introduces Polaris, an alternative routing algorithm that exploits road popularity to optimize traffic distribution and reduce CO2 emissions. Polaris leverages the novel concept of K-road layers, which mitigates the feedback loop effect where redirecting vehicles to less popular roads could increase their popularity in the future. We conduct experiments in three cities to evaluate Polaris against state-of-the-art alternative routing algorithms. Our results demonstrate that Polaris significantly reduces the overuse of highly popular road edges and traversed regulated intersections, showcasing its ability to generate efficient routes and distribute traffic more evenly. Furthermore, Polaris achieves substantial CO2 reductions, outperforming existing alternative routing strategies. Finally, we compare Polaris to an algorithm that coordinates vehicles centrally to distribute them more evenly on the road network. Our findings reveal that Polaris performs comparably well, even with much less information, highlighting its potential as an efficient and sustainable solution for urban traffic management.

The System for Measuring Overlap with Gas (SMOG2) at the LHCb detector enables the study of fixed-target ion-ion collisions at relativistic energies ($\sqrt{s_{\rm NN}}\sim100$ GeV in the centre-of-mass). With input from \textit{ab initio} calculations of the structure of $^{16}$O and $^{20}$Ne, we compute 3+1D hydrodynamic predictions for the anisotropic flow of Pb+Ne and Pb+O collisions, to be tested with upcoming LHCb data. This will allow the detailed study of quark-gluon plasma (QGP) formation as well as experimental tests of the predicted nuclear shapes. Elliptic flow ($v_2$) in Pb+Ne collisions is greatly enhanced compared to the Pb+O baseline due to the shape of $^{20}$Ne, which is deformed in a bowling-pin geometry. Owing to the large $^{208}$Pb radius, this effect is seen in a broad centrality range, a unique feature of this collision configuration. Larger elliptic flow further enhances the quadrangular flow ($v_4$) of Pb+Ne collisions via non-linear coupling, and impacts the sign of the kurtosis of the elliptic flow vector distribution ($c_2\{4\}$). Exploiting the shape of $^{20}$Ne proves thus an ideal method to investigate the formation of QGP in fixed-target experiments at LHCb, and demonstrates the power of SMOG2 as a tool to image nuclear ground states.

Most stripped envelope supernova progenitors are formed through binary interaction, losing hydrogen and/or helium from their outer layers. An emerging class of supernovae with the highest degree of envelope-stripping are thought to be the product of stripping by a NS companion. However, relatively few examples are known and the outcomes of such systems can be diverse and are poorly understood at present. Here, we present spectroscopic observations and high cadence multi-band photometry of SN 2023zaw, a low ejecta mass and rapidly evolving supernova. SN 2023zaw was discovered in a nearby spiral galaxy at D = 39.7 Mpc, with significant Milky Way extinction, $E(B-V) = 0.21$, and significant (but uncertain) host extinction. Bayesian evidence comparison reveals that nickel is not the only power source and an additional energy source is required to explain our observations. Our models suggest an ejecta mass of $M_{\rm ej} \sim 0.07\,\rm M_\odot$ and a synthesised nickel mass of $M_{\rm ej} \sim 0.007\,\rm M_\odot$ is required to explain the explosion. However an additional heating from a magnetar or interaction with circumstellar material is required to power the early light curve.

The Material Point Method (MPM) is widely used to analyse coupled (solid-water) problems under large deformations/displacements. However, if not addressed carefully, MPM u-p formulations for poro-mechanics can be affected by two major sources of instability. Firstly, inf-sup condition violation can arise when the spaces for the displacement and pressure fields are not chosen correctly, resulting in an unstable pressure field. Secondly, the intrinsic nature of particle-based discretisation makes the MPM an unfitted mesh-based method, which can affect the system's condition number and solvability, particularly when background mesh elements are poorly populated. This work proposes a solution to both problems. The inf-sup condition is avoided using two overlapping meshes, a coarser one for the pressure and a finer one for the displacement. This approach does not require stabilisation of the primary equations since it is stable by design and is particularly valuable for low-order shape functions. As for the system's poor condition number, a face ghost penalisation method is added to both the primary equations, which constitutes a novelty in the context of MPM mixed formulations. This study frequently makes use of the theories of functional analysis or the unfitted Finite Element Method (FEM). Although these theories may not directly apply to the MPM, they provide a robust and logical basis for the research. These rationales are further supported by three numerical examples, which encompass both elastic and elasto-plastic cases and drained and undrained conditions., Comment: 37 pages, 11 figures, 3 tables

In application as hyperthermia and nanowarming, power dissipation arises when the time-dependent magnetization $M(t)$ of an out-of-equilibrium system of nanoparticles lags behind the applied field $H(t)$. The key parameter governing this process is the relaxation time $\tau$ of the system, which induces a phase shift $\phi_n$ between $H(t)$ and every nth harmonic component of $M(t)$. In this work, we present an expression for $M(t)$ in terms of $\tau$ and the equilibrium magnetization, valid for any magnetic system exhibiting odd equilibrium response. From this calculation, we obtain a method for determining the effective $\tau$ of a MNPs sample directly from the experimental measurement of $M(t)$. Additionally, we demonstrate that the power dissipation (SAR: Specific Absorption Rate) of any magnetic sample under a sinusoidal field can be obtained from the first harmonic component of $M(t)$. As an illustrative application, we explore the variation of $\tau$ for magnetic MNPs in aqueous suspension during the melting process of the matrix. In this case, the change in $\tau$ can be understood as a result of the reorientation of the MNPs in the direction of the applied field as the matrix becomes liquid.

This paper investigates the asymptotic behavior of the extremes of a sequence of generalized Oppenheim random variables. Particularly, we establish conditions under which some normalized extremes of sequences arising from Oppenheim expansions belong to the maximum domain of attraction of the Frechet distribution. Additionally, we identify conditions under which the maxima and minima of Oppenheim random variables demonstrate some kind of asymptotic independence. Finally, we prove an Extreme Types theorem for Oppenheim expansions with unknown dependent structure.

The surfaces of icy moons are primarily composed of water ice that can be mixed with other compounds, such as carbon dioxide. The carbon dioxide (CO$_2)$ stretching fundamental band observed on Europa and Ganymede appears to be a combination of several bands that are shifting location from one moon to another. We investigate the cause of the observed shift in the CO$_2$ stretching absorption band experimentally. We also explore the spectral behaviour of CO$_2$ ice by varying the temperature and concentration.} %H$_2$O:CO$_2$ deposition ratios. We analyzed pure CO$_2$ ice and ice mixtures deposited at 10 K under ultra-high vacuum conditions using Fourier-transform infrared (FTIR) spectroscopy and temperature programmed desorption (TPD) experiments. Laboratory ice spectra were compared to JWST observation of Europa's and Ganymede's leading hemispheres. The simulated IR spectra were calculated using density functional theory (DFT) methods, exploring the effect of porosity in CO$_2$ ice. Pure CO$_2$ and CO$_2$-water ice show distinct spectral changes and desorption behaviours at different temperatures, revealing intricate CO$_2$ and H$_2$O interactions. The number of discernible peaks increases from two in pure CO$_2$ to three in CO$_2$-water mixtures., Comment: Accepted for publication in Astronomy & Astrophysics

Binary black holes (BBHs) born from the evolution of Population III (Pop. III) stars are one of the main high-redshift targets for next-generation ground-based gravitational-wave (GW) detectors. Their predicted initial mass function and lack of metals make them the ideal progenitors of black holes above the upper edge of the pair-instability mass gap, i.e. with a mass higher than $\approx{}134$ (241) M$_\odot$ for stars that become (do not become) chemically homogeneous during their evolution. Here, we investigate the effects of cluster dynamics on the mass function of BBHs born from Pop. III stars, by considering the main uncertainties on Pop. III star mass function, orbital properties of binary systems, star cluster's mass and disruption time. In our dynamical models, at least $\sim$5% and up to 100% BBH mergers in Pop. III star clusters have primary mass $m_1$ above the upper edge of the pair-instability mass gap. In contrast, only $\lesssim {} 3$% isolated BBH mergers have primary mass above the gap, unless their progenitors evolved as chemically homogeneous stars. The lack of systems with primary and/or secondary mass inside the gap defines a zone of avoidance with sharp boundaries in the primary mass - mass ratio plane. Finally, we estimate the merger rate density of BBHs and, in the most optimistic case, we find a maximum of $\mathcal{R}\approx200\,{\rm Gpc^{-3}\,yr^{-1}}$ at $z\sim15$ for BBHs formed via dynamical capture. For comparison, the merger rate density of isolated Pop. III BBHs is $\mathcal{R}\leq{}10\,{\rm Gpc^{-3}\,yr^{-1}}$, for the same model of Pop. III star formation history., Comment: 17 pages, 12 figures, 4 tables. Comments welcome

In the fully-anonymous (shared-memory) model, inspired by a biological setting, processors have no identifiers and memory locations are anonymous. This means that there is no pre-existing agreement among processors on any naming of the memory locations. In this work, we ask fundamental questions about the fully-anonymous model in the hope to obtain a better understanding of the role of naming and anonymity in distributed computing. First, we ask what it means to solve a task under processor anonymity. With tasks such as renaming, the traditional notion obviously does not apply. Instead of restricting ourselves to colorless tasks, we propose using the notion of group solvability, which allows transferring any task to processor-anonymous models. Second, the difficulty with anonymity is that processors can hardly avoid covering and then overwriting each other's writes, erasing information written by their predecessors. To get to the bottom of this phenomenon, we ask what system configurations are stable when processors keep reading and writing ad infinitum. Resolving this question leads us to a wait-free solution to the snapshot task, which then allows us to solve renaming and obstruction-free consensus.

This paper presents TetraBFT, a novel unauthenticated Byzantine fault tolerant protocol for solving consensus in partial synchrony, eliminating the need for public key cryptography and ensuring resilience against computationally unbounded adversaries. TetraBFT has several compelling features: it necessitates only constant local storage, has optimal communication complexity, satisfies optimistic responsiveness -- allowing the protocol to operate at actual network speeds under ideal conditions -- and can achieve consensus in just 5 message delays, which outperforms all known unauthenticated protocols achieving the other properties listed. We validate the correctness of TetraBFT through rigorous security analysis and formal verification. Furthermore, we extend TetraBFT into a multi-shot, chained consensus protocol, making a pioneering effort in applying pipelining techniques to unauthenticated protocols. This positions TetraBFT as a practical and deployable solution for blockchain systems aiming for high efficiency., Comment: The full version of the PODC 2024 paper

In this paper we present a new formulation of the Beurling-Malliavin density (Proposition 1). Then we consider the upper Polya density and show how its existence is connected with the concept of subadditivity; moreover, by means of some quantities introduced for proving Proposition 1, a theorem is presented that clarifies the connection between the upper Polya and the Beurling-Malliavin densities. In the last section we discuss the classical definition of the upper Polya density and we prove a result which seems to be new., Comment: 20 pages

We consider a non-relativistic particle in a one-dimensional box with all possible quantum boundary conditions that make the kinetic-energy operator selfadjoint. We determine the Wigner functions of the corresponding eigenfunctions and analyze in detail their classical limit in the high-energy regime. We show that the quantum boundary conditions split into two classes: all local and regular boundary conditions collapse to the same classical boundary condition, while singular non-local boundary conditions slightly persist in the classical limit., Comment: 25 pages, 12 figures

Gaia BH3 is the first observed dormant black hole (BH) with a mass of $\approx{30}$ M$_\odot$ and represents the first confirmation that such massive BHs are associated with metal-poor stars. Here, we explore the isolated binary formation channel for Gaia BH3 focusing on the old and metal-poor stellar population of the Milky Way halo. We use the MIST stellar models and our open-source population synthesis code SEVN to evolve $5.6 \times 10^8$ binaries exploring 20 sets of parameters. We find that systems like Gaia BH3 form preferentially from binaries initially composed of a massive star ($40-60$ M$_\odot$) and a low mass companion ($<1$ M$_\odot$) in a wide ($P>10^3$ days) and eccentric orbit ($e>0.6$). Such progenitor binary stars do not undergo any Roche-lobe overflow episode during their entire evolution, so that the final orbital properties of the BH-star system are determined at the core collapse of the primary star. Low natal kicks ($\lesssim$ 10~km/s) significantly favour the formation of Gaia BH3-like systems, but high velocity kicks up to $\approx 220$ km/s are also allowed. We estimate the formation efficiency for Gaia BH3-like systems in old ($t>10$ Gyr) and metal-poor ($Z<0.01$) populations to be $\sim 4 \times 10^{-8}$ M$_\odot^{-1}$ (for our fiducial model), representing $\sim 3\%$ of the whole simulated BH-star population. We expect up to $\approx 4000$ BH-star systems in the Galactic halo formed through isolated evolution, of which $\approx 100$ are compatible with Gaia BH3-like. Given the density profile of the Galactic halo we do not expect more than one at the observed distance of Gaia BH3. Our models show that, even if it was born inside a stellar cluster, Gaia BH3 is compatible with a primordial binary star that escaped from its parent cluster without experiencing significant dynamical interactions., Comment: Accepted for publication in A&A. The produced datasets are publicly available in Zenodo. I Initiail conditions and run scripts: https://zenodo.org/records/11617742; IIA simulation outcomes: https://zenodo.org/records/11992265; IIB simulation outcomes, different metallicities: https://zenodo.org/records/12188369; IIC simulation outcomes, fiducial 1E8, https://zenodo.org/records/12189734

Fluctuations affect the functionality of nanodevices. Thermodynamic uncertainty relations (TURs), derived within the framework of stochastic thermodynamics, show that a minimal amount of dissipation is required to obtain a given relative energy current dispersion, that is, current precision has a thermodynamic cost. It is therefore of great interest to explore the possibility that TURs are violated, particularly for quantum systems, leading to accurate currents at lower cost. Here, we show that two quantum harmonic oscillators are synchronized by coupling to a common thermal environment, at strong dissipation and low temperature. In this regime, periodically modulated couplings to a second thermal reservoir, breaking time-reversal symmetry and taking advantage of non-Markovianity of this latter reservoir, lead to strong violation of TURs for local work currents, while maintaining finite output power. Our results pave the way for the use of synchronization in the thermodynamics of precision., Comment: 15 pages, 10 figures. This is the Accepted Manuscript version of an article accepted for publication in "Quantum Science and Technology". IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://www.doi.org/10.1088/2058-9565/ad6fc9

Third-generation (3G) gravitational-wave (GW) detectors like the Einstein Telescope (ET) will observe binary black hole (BBH) mergers at redshifts up to $z\sim 100$. However, unequivocal determination of the origin of high-redshift sources will remain uncertain, due to the low signal-to-noise ratio (SNR) and poor estimate of their luminosity distance. This study proposes a machine learning approach to infer the origins of high-redshift BBHs, specifically differentiating those arising from Population III (Pop. III) stars - likely the first progenitors of stellar-born BBH mergers in the Universe - and those originated from Population I-II (Pop. I-II) stars. We have considered a wide range of state-of-the-art models encompassing current uncertainties on Pop. III BBH mergers. We then estimate parameter errors of detected sources with ET using the Fisher-information-matrix formalism, followed by classification using XGBoost, a machine learning algorithm based on decision trees. For a set of mock observed BBHs, we provide the probability that they belong to the Pop. III class while considering the parameter errors of each source. In our fiducial model, we accurately identify ~10% of detected BBHs originating from Pop. III stars with > 90% precision. Our study demonstrates how machine learning enables to achieve some pivotal aspects of ET science case by exploring the origin of individual high-redshift GW observations. We set the basis for further studies, which will integrate additional simulated populations and account for population modeling uncertainties, Comment: Submitted to Astronomy & Astrophysics. 13 pages, 9 Figures and 5 tables. Comments are welcome

This work focuses on the coupling of trimmed shell patches using Isogeometric Analysis, based on higher continuity splines that seamlessly meet the $C^1$ requirement of Kirchhoff-Love-based discretizations. Weak enforcement of coupling conditions is achieved through the symmetric interior penalty method, where the fluxes are computed using their correct variationally consistent expression that was only recently proposed and is unprecedentedly adopted herein in the context of coupling conditions. The constitutive relationships account for generically laminated materials, although the proposed tests are conducted under the assumption of uniform thickness and lamination sequence. Numerical experiments assess the method for an isotropic and a laminated plate, as well as an isotropic hyperbolic paraboloid shell from the new shell obstacle course. The boundary conditions and domain force are chosen to reproduce manufactured analytical solutions, which are taken as reference to compute rigorous convergence curves in the $L^2$, $H^1$, and $H^2$ norms, that closely approach optimal ones predicted by theory. Additionally, we conduct a final test on a complex structure comprising five intersecting laminated cylindrical shells, whose geometry is directly imported from a STEP file. The results exhibit excellent agreement with those obtained through commercial software, showcasing the method's potential for real-world industrial applications., Comment: Engineering with Computers. 2024

Investigating nucleon-nucleon correlations inherent to the strong nuclear force is one of the core goals in nuclear physics research. We showcase the unique opportunities offered by collisions of $^{16}$O nuclei at high-energy facilities to reveal detailed many-body properties of the nuclear ground state. We interface existing knowledge about the geometry of $^{16}$O coming from \textit{ab-initio} calculations of nuclear structure with transport simulations of high-energy $^{16}$O+$^{16}$O collisions. Bulk observables in these processes, such as the elliptic flow or the fluctuations of the mean transverse momentum, are found to depend significantly on the input nuclear model and to be sensitive to realistic clustering and short-range repulsive correlations, effectively opening a new avenue to probe these features experimentally. This finding demonstrates collisions of oxygen nuclei as a tool to elucidate initial conditions of small collision systems while fostering connections with effective field theories of nuclei rooted in quantum chromodynamics (QCD).

This paper presents a comprehensive framework designed to facilitate the widespread deployment of the Internet of Things (IoT) for enhanced monitoring and optimization of Water Distribution Systems (WDSs). The framework aims to investigate the utilization of massive IoT in monitoring and optimizing WDSs, with a particular focus on leakage detection, energy consumption and wireless network performance assessment in real-world water networks. The framework integrates simulation environments at both the application level (using EPANET) and the radio level (using NS-3) within the LoRaWAN network. The paper culminates with a practical use case, alongside evaluation results concerning power consumption in a large-scale LoRaWAN network and strategies for optimal gateway positioning., Comment: This is a pre-print paper submitted to IFIP/IEEE Networking 2024 - The International Federation for Information Processing (IFIP) Networking 2024 Conference (NETWORKING 2024) for consideration