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The framework of Partial Information Decomposition (PID) unveils complex nonlinear interactions in network systems by dissecting the mutual information (MI) between a target variable and several source variables. While PID measures have been formulated mostly for discrete variables, with only recent extensions to continuous systems, the case of mixed variables where the target is discrete and the sources are continuous is not yet covered properly. Here, we introduce a PID scheme whereby the MI between a specific state of the discrete target and (subsets of) the continuous sources is expressed as a Kullback-Leibler divergence and is estimated through a data-efficient nearest-neighbor strategy. The effectiveness of this PID is demonstrated in simulated systems of mixed variables and showcased in a physiological application. Our approach is relevant to many scientific problems, including sensory coding in neuroscience and feature selection in machine learning.

Robotic systems for manipulation tasks are increasingly expected to be easy to configure for new tasks or unpredictable environments, while keeping a transparent policy that is readable and verifiable by humans. We propose the method BEhavior TRee eXPansion with Large Language Models (BETR-XP-LLM) to dynamically and automatically expand and configure Behavior Trees as policies for robot control. The method utilizes an LLM to resolve errors outside the task planner's capabilities, both during planning and execution. We show that the method is able to solve a variety of tasks and failures and permanently update the policy to handle similar problems in the future., Comment: Submitted to ICRA 2025

We introduce a general concept of layered computation model, of which neural networks are a particular example, and combine tools of topological dynamics and model theory to study asymptotics of such models. We prove that, as the number of layers of a computation grows, the computation reaches a state of ``deep equilibrium" which amounts to a single, self-referential layer. After proving the existence of deep equilibria under fairly general hypotheses, we characterize their computability.

The spectrum of the quasinormal modes of the gravitational waves emitted during the ringdown phase following the merger of two black holes is of primary importance in gravitational astronomy. However, the spectrum is extremely sensitive to small disturbances of the system, thus potentially jeopardizing the predictions of the gravitational wave observables. We offer an analytical and intuitive explanation of such an instability and its properties based on the transfer matrix approach of quantum mechanics. We also give a simple interpretation of the fact that the prompt ringdown response in the time domain and the black hole greybody factor receive parametrically small corrections, thus being robust observables., Comment: 5 pages, 2 figures, supplementary material available

Travel Recommender Systems TRSs have been proposed to ease the burden of choice in the travel domain by providing valuable suggestions based on user preferences Despite the broad similarities in functionalities and data provided by TRSs these systems are significantly influenced by the diverse and heterogeneous contexts in which they operate This plays a crucial role in determining the accuracy and appropriateness of the travel recommendations they deliver For instance in contexts like smart cities and natural parks diverse runtime informationsuch as traffic conditions and trail status respectivelyshould be utilized to ensure the delivery of pertinent recommendations aligned with user preferences within the specific context However there is a trend to build TRSs from scratch for different contexts rather than supporting developers with configuration approaches that promote reuse minimize errors and accelerate timetomarket To illustrate this gap in this paper we conduct a systematic mapping study to examine the extent to which existing TRSs are configurable for different contexts The conducted analysis reveals the lack of configuration support assisting TRSs providers in developing TRSs closely tied to their operational context Our findings shed light on uncovered challenges in the domain thus fostering future research focused on providing new methodologies enabling providers to handle TRSs configurations, Comment: Accepted at the 50th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) 2024

Sizeable primordial curvature perturbations needed to seed a population of primordial black holes (PBHs) will be accompanied by a scalar-induced gravitational wave signal that can be detectable by pulsar timing arrays (PTA). We derive conservative bounds on the amplitude of the scalar power spectrum at the PTA frequencies and estimate the implied constraints on the PBH abundance. We show that only a small fraction of dark matter can consist of stellar mass PBHs when the abundance is calculated using threshold statistics. The strength and the shape of the constraint depend on the shape of the power spectrum and the nature of the non-Gaussianities. We find that constraints on the PBH abundance arise in the mass range $0.1-10^3\, M_{\odot}$, with the sub-solar mass range being constrained only for narrow curvature power spectra. These constraints are softened when positive non-Gaussianity is introduced and can be eliminated when $f_{\rm NL} \gtrsim 5$. On the other hand, if the PBH abundance is computed via the theory of peaks, the PTA constraints on PBHs are significantly relaxed, signalling once more the theoretical uncertainties in assessing the PBH abundance. We further discuss how strong positive non-Gaussianites can allow for heavy PBHs to potentially seed supermassive BHs., Comment: 16 pages and 7 figures. V2 matches JCAP published version

Model-Driven Engineering (MDE) is a software engineering methodology focusing on models as primary artifacts. In the last years, the emergence of Web technologies has led to the development of Web-based modeling tools and model-based approaches for the Web that offer a web-based environment to create and edit models or model-based low-code solutions. A common requirement when developing Web-based modeling tools is to provide a fast and efficient way for model management, and this is particularly a hot topic in model-based system engineering. However, the number of approaches offering RESTful services for model management is still limited. Among the alternatives for developing distributed services, there is a growing interest in the use of RESTful services. In this paper, we present an approach to provide RESTful services for model management that can be used to interact with any kind of model and can be used to build a modeling platform providing modeling-as-a-service. The approach follows the REST principles to provide a stateless and scalable service., Comment: 3 pages, 1 figure, 1 table

The WHT Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph. This new instrument will be exploited to obtain high S/N spectra of $\sim$25000 galaxies at intermediate redshifts for the WEAVE Stellar Population Survey (WEAVE-StePS). We test machine learning methods for retrieving the key physical parameters of galaxies from WEAVE-StePS-like spectra using both photometric and spectroscopic information at various S/Ns and redshifts. We simulated $\sim$105000 galaxy spectra assuming SFH with an exponentially declining star formation rate, covering a wide range of ages, stellar metallicities, sSFRs, and dust extinctions. We then evaluated the ability of the random forest and KNN algorithms to correctly predict such parameters assuming no measurement errors. We checked how much the predictive ability deteriorates for different S/Ns and redshifts, finding that both algorithms still accurately estimate the ages and metallicities with low bias. The dispersion varies from 0.08-0.16 dex for ages and 0.11-0.25 dex for metallicity, depending on the redshift and S/N. For dust attenuation, we find a similarly low bias and dispersion. For the sSFR, we find a very good constraining power for star-forming galaxies, log sSFR$\gtrsim$ -11, where the bias is $\sim$ 0.01 dex and the dispersion is $\sim$ 0.10 dex. For more quiescent galaxies, with log sSFR$\lesssim$ -11, we find a higher bias, 0.61-0.86 dex, and a higher dispersion, $\sim$ 0.4 dex, for different S/Ns and redshifts. Generally, we find that the RF outperforms the KNN. Finally, the retrieved sSFR was used to successfully classify galaxies as part of the blue cloud, green valley, or red sequence. We demonstrate that machine learning algorithms can accurately estimate the physical parameters of simulated galaxies even at relatively low S/N=10 per angstrom spectra with available ancillary photometric information., Comment: 19 pages, 10 + 2 figures, 4 tables, accepted in A&A

Star-galaxy separation is a crucial step in creating target catalogues for extragalactic spectroscopic surveys. A classifier biased towards inclusivity risks including spurious stars, wasting fibre hours, while a more conservative classifier might overlook galaxies, compromising completeness and hence survey objectives. To avoid bias introduced by a training set in supervised methods, we employ an unsupervised machine learning approach. Using photometry from the Wide Area VISTA Extragalactic Survey (WAVES)-Wide catalogue comprising 9-band $u-K_s$ data, we create a feature space with colours, fluxes, and apparent size information extracted by ${\rm P{\scriptsize RO} F{\scriptsize OUND}}$. We apply the non-linear dimensionality reduction method UMAP (Uniform Manifold Approximation and Projection) combined with the classifier ${\rm{\scriptsize HDBSCAN}}$ to classify stars and galaxies. Our method is verified against a baseline colour and morphological method using a truth catalogue from Gaia, SDSS, GAMA, and DESI. We correctly identify 99.72% of galaxies within the AB magnitude limit of $Z = 21.2$, with an F1 score of 0.9970 across the entire ground truth sample, compared to 0.9871 from the baseline method. Our method's higher purity (0.9966) compared to the baseline (0.9780) increases efficiency, identifying 11% fewer galaxy or ambiguous sources, saving approximately 70,000 fibre hours on the 4MOST instrument. We achieve reliable classification statistics for challenging sources including quasars, compact galaxies, and low surface brightness galaxies, retrieving 95.1%, 84.6%, and 99.5% of them respectively. Angular clustering analysis validates our classifications, showing consistency with expected galaxy clustering, regardless of the baseline classification., Comment: Submitted to MNRAS; 17 pages, 11 figures

Behavior Trees (BTs) were first conceived in the computer games industry as a tool to model agent behavior, but they received interest also in the robotics community as an alternative policy design to Finite State Machines (FSMs). The advantages of BTs over FSMs had been highlighted in many works, but there is no thorough practical comparison of the two designs. Such a comparison is particularly relevant in the robotic industry, where FSMs have been the state-of-the-art policy representation for robot control for many years. In this work we shed light on this matter by comparing how BTs and FSMs behave when controlling a robot in a mobile manipulation task. The comparison is made in terms of reactivity, modularity, readability, and design. We propose metrics for each of these properties, being aware that while some are tangible and objective, others are more subjective and implementation dependent. The practical comparison is performed in a simulation environment with validation on a real robot. We find that although the robot's behavior during task solving is independent on the policy representation, maintaining a BT rather than an FSM becomes easier as the task increases in complexity., Comment: Submitted to IEEE Transactions on Robotics (T-RO). arXiv admin note: text overlap with arXiv:2209.07392

Primordial black holes (PBH) can efficiently form black hole binaries in the early universe. We update the resulting constraints on PBH abundance using data from the third observational run (O3) of LIGO-Virgo-KAGRA. To capture a wide range of PBH scenarios, we consider a variety of mass functions, including critical collapse in the QCD epoch in the presence of non-Gaussianities. Applying hierarchical Bayesian analysis to a population binaries consisting of primordial and astrophysical black holes, we find that, in every scenario, the PBHs can make up at most $f_{\rm PBH} \lesssim 10^{-3}$ of dark matter in the mass range $1-200~M_\odot$. The shape and strength of the constraints are insensitive to the type of non-Gaussianities, the modifications to the mass function during the QCD epoch, or the modelling of the astrophysical PBH population.

How the quiescent galaxies evolve with redshift and the factors that impact their evolution are still debated. It is still unclear what the dominant mechanisms of passive galaxy growth are and what role is played by the environment in shaping their evolutionary paths over cosmic time. Our aim is to study the mass-size relation (MSR) of the quiescent population and to understand how the environment shapes the MSR at intermediate redshift. We used the VIPERS, a large spectroscopic survey of $\sim$90~000 galaxies in the redshift range $0.5\le z \le 1.2$. We selected a mass-complete sample of 4786 passive galaxies based on the NUVrK diagram and refined it using the $D_n4000$ spectral index to study the MSR of the passive population over $0.5\le z \le 0.9$. The impact of the environment on the MSR and on the growth of the quiescent population is studied through the density contrast. The slope and the intercept of the MSR, $\alpha=0.62\pm 0.04$ and $\textrm{log}(A)=0.52\pm 0.01$, agree well with values from the literature at the same redshift. The intercept decreases with redshift, $R_e(z)=8.20\times (1+z)^{-1.70}$, while the slope remains roughly constant, and the same trend is observed in the low-density (LD) and high-density (HD) environments. We find that the average size of the quiescent population in the LD and HD environments are identical within $3\sigma$ and this result is robust against a change in the definition of the LD and HD environments or a change in the selection of quiescent galaxies. In the LD and HD environments, $\sim$30 and $\sim$40% of the population have experienced a minor merger process between $0.5\le z \le 0.9$. However, minor mergers account only for 30 to 40% of the size evolution in this redshift range, the remaining evolution likely being due to the progenitor bias., Comment: 23 pages, 17 figures, accepted for publication in A&A

We provide evidence for a correspondence between the formation of black holes and the stability of circular null geodesics around the collapsing perturbation. We first show that the critical threshold of the compaction function to form a black hole in radiation is well approximated by the critical threshold for the appearance of the first unstable circular orbit in a spherically symmetric background. We also show that the critical exponent in the scaling law of the primordial black hole mass close to the threshold is set by the inverse of the Lyapunov coefficient of the unstable orbits when a self-similar stage is developed close to criticality., Comment: 5 pages, 4 figures v2: Updated version matching the PRL published version

In industrial applications Finite State Machines (FSMs) are often used to implement decision making policies for autonomous systems. In recent years, the use of Behavior Trees (BT) as an alternative policy representation has gained considerable attention. The benefits of using BTs over FSMs are modularity and reusability, enabling a system that is easy to extend and modify. However, there exists few published studies on successful implementations of BTs for industrial applications. This paper contributes with the lessons learned from implementing BTs in a complex industrial use case, where a robotic system assembles explosive charges and places them in holes on the rock face. The main result of the paper is that even if it is possible to model the entire system as a BT, combining BTs with FSMs can increase the readability and maintainability of the system. The benefit of such combination is remarked especially in the use case studied in this paper, where the full system cannot run autonomously but human supervision and feedback are needed.

We show that the abundance of primordial black holes, if formed through the collapse of large fluctuations generated during inflation and unless the power spectrum of the curvature perturbation is very peaked, is always dominated by the broadest profile of the compaction function, even though statistically it is not the most frequent. The corresponding threshold is therefore 2/5. This result exacerbates the tension when combining the primordial black hole abundance with the signal seen by pulsar timing arrays and originated from gravitational waves induced by the same large primordial perturbations., Comment: V2, Published version on PRD. Minor changes respect V1

We used 5487 star-forming galaxies at redshift z~0.63 extracted from the VIPERS and 143774 comparison galaxies in the local Universe from the GSWLC catalog. We employed two families of methods: parametric and non-parametric. In the former approaches, we compared the FMR projections plagued by observational biases on differently constructed control samples at various redshifts. Then, the metallicity difference between different redshifts in M*-SFR bins. In the latter approach, we related the metallicity and the normalized sSFR. The methodologies implemented to construct fair, complete samples for studying the MZR and the FMR produced consistent results showing a small, but still statistically significant evolution of both relations up to z~0.63. In particular, we observed a systematic trend where the median metallicity of the sample at z=0.63 is lower than that of the local sample at the same M* and SFR. The average difference in the metallicity of the low and intermediate redshifts is approximately 1.8 times the metallicity standard deviation of the median, of the intermediate redshift sample, in M*-SFR bins. We confirmed this result using the Kolmogorov-Smirnov test. When we applied the M*-completeness criterion to catalogs, the metallicity difference in redshifts decreased to approximately 0.96 times the metallicity standard deviation of the median, thus not statistically significant. This result may be dominated by the limited parameter space, being the lower M* galaxies where the difference is larger out from the analysis. A careful reading of the results, and their underlying selection criteria, are crucial in studies of the mass-metallicity and FMRs., Comment: Accepted for publication in A&A, 22 pages, 20 figures

VANDELS is a deep spectroscopic survey, performed with the VIMOS instrument at VLT, aimed at studying in detail the physical properties of high-redshift galaxies. VANDELS targeted about 2100 sources at 1

The most conservative interpretation of the nHz stochastic gravitational wave background (SGWB) discovered by NANOGrav and other Pulsar Timing Array (PTA) Collaborations is astrophysical, namely that it originates from supermassive black hole (SMBH) binaries. However, alternative cosmological models have been proposed, including cosmic strings, phase transitions, domain walls, primordial fluctuations and "audible" axions. We perform a multi-model analysis (MMA) to compare how well these different hypotheses fit the NANOGrav data, both in isolation and in combination with SMBH binaries, and address the questions: Which interpretations fit the data best, and which are disfavoured? We also discuss experimental signatures that can help discriminate between different sources of the PTA GW signal, including fluctuations in the signal strength between frequency bins, individual sources and how the PTA signal extends to higher frequencies., Comment: 15 pages, 17 figures, 1 table

The upcoming generation of optical spectrographs on four meter-class telescopes, with their huge multiplexing capabilities, excellent spectral resolution, and unprecedented wavelength coverage, will provide high-quality spectra for thousands of galaxies. These data will allow us to examine of the stellar population properties at intermediate redshift, an epoch that remains unexplored by large and deep surveys. We assess our capability to retrieve the mean stellar metallicity in galaxies at different redshifts and S/N, while simultaneously exploiting the UV and optical rest-frame wavelength coverage. The work is based on a comprehensive library of spectral templates of stellar populations, covering a wide range of age and metallicity values and built assuming various SFHs. We simulated realistic observations of a large sample of galaxies carried out with WEAVE at the WHT at different redshifts and S/N values. We measured all the reliable indices on the simulated spectra and on the comparison library. We then adopted a Bayesian approach to obtain the probability distribution of stellar metallicity. The analysis of the spectral indices has shown how some mid-UV indices can provide reliable constraints on stellar metallicity, along with optical indicators. The analysis of the mock observations has shown that even at S/N=10, the metallicity can be derived within 0.3 dex, in particular, for stellar populations older than 2 Gyr. Our results are in good agreement with other theoretical and observational works in the literature and show how the UV indicators can be advantageous in constraining metallicities. This is very promising for the upcoming surveys carried out with new, highly multiplexed, large-field spectrographs, such as StePS at the WEAVE and 4MOST, which will provide spectra of thousands of galaxies covering large spectral ranges at relatively high S/N., Comment: 16 pages, 14 figures. Submitted 31/03/2023, Accepted 20/07/2023

We study whether the signal seen by pulsar timing arrays (PTAs) may originate from gravitational waves (GWs) induced by large primordial perturbations. Such perturbations may be accompanied by a sizeable primordial black hole (PBH) abundance. We improve existing analyses and show that PBH overproduction disfavors Gaussian scenarios for scalar-induced GWs at 2{\sigma} and single-field inflationary scenarios, accounting for non-Gaussianity, at 3{\sigma} as the explanation of the most constraining NANOGrav 15-year data. This tension can be relaxed in models where non-Gaussianites suppress the PBH abundance. On the flip side, the PTA data does not constrain the abundance of PBHs., Comment: V3: Version published on PRL. 15 pages and 8 figures. Full article + supplementary materials. V1 appeared on Thu, 29 Jun 2023

We revise primordial black holes (PBHs) production in the axion-curvaton model, in light of recent developments in the computation of their abundance accounting for non-gaussianities (NGs) in the curvature perturbation up to all orders. We find that NGs intrinsically generated in such scenarios have a relevant impact on the phenomenology associated to PBHs and, in particular, on the relation between the abundance and the signal of second-order gravitational waves. We show that this model could explain both the totality of dark matter in the asteroid mass range and the tentative signal reported by the NANOGrav and IPTA collaborations in the nano-Hz frequency range. En route, we provide a new, explicit computation of the power spectrum of curvature perturbations going beyond the sudden-decay approximation., Comment: 25 pages, 11 figures, V2: additional references, matches version to appear in JCAP

A major issue for many applications of blockchain technology is the tension between immutability and compliance to regulations. For instance, the GDPR in the EU requires to guarantee, under some circumstances, the right to be forgotten. This could imply that at some point one might be forced to delete some data from a locally stored blockchain, therefore irreparably hurting the security and transparency of such decentralized platforms. Motivated by such data protection and consistency issues, in this work we design and implement a mechanism for securely deleting data from Bitcoin blockchain. We use zero-knowledge proofs to allow any node to delete some data from Bitcoin transactions, still preserving the public verifiability of the correctness of the spent and spendable coins. Moreover, we specifically use STARK proofs to exploit the transparency that they provide. Our solution, unlike previous approaches, avoids the complications of asking nodes to reach consensus on the content to delete. In particular, our design allows every node to delete some specific data without coordinating this decision with others. In our implementation, data removal can be performed (resp., verified) in minutes (resp., seconds) on a standard laptop rather than in days as required in previous designs based on consensus.

We discuss the issue of perturbativity in single-field inflationary models with a phase of ultra slow-roll (USR) tailor suited to generate an order-one abundance of primordial black holes (PBHs). More in detail, we impose the condition that loop corrections made up of short-wavelength modes enhanced by the USR dynamics do not alter the tree-level power spectrum of curvature perturbations. In our analysis, the USR phase is preceded and followed by two stages of ordinary slow-roll (SR), and we model the resulting SR/USR/SR dynamics using both instantaneous and smooth transitions. Focusing on scales relevant for CMB observations, we find that it is not possible, with these arguments, to rule out the scenario of PBH formation via USR, not even in the limit of instantaneous transition. However, we also find that loop corrections of short modes on the power spectrum of long modes, even though not large enough to violate perturbativity requirements, remain appreciable and, most importantly, are not tamed in realistic realisations of smooth SR/USR/SR transitions. This makes perturbativity a powerful theoretical tool to constrain USR dynamics. We extend the analysis at any scale beyond those relevant for CMB observations. We find that loop corrections of short modes remain within the few percent if compared to the tree-level power spectrum. However, we also find one notable exception of phenomenological relevance: we show that the so-called dip in the power spectrum of curvature perturbation is an artifact of the tree-level computation., Comment: 31 pages, 12 figures. V2 published version on PRD. minor changes respect V1

In modern industrial collaborative robotic applications, it is desirable to create robot programs automatically, intuitively, and time-efficiently. Moreover, robots need to be controlled by reactive policies to face the unpredictability of the environment they operate in. In this paper we propose a framework that combines a method that learns Behavior Trees (BTs) from demonstration with a method that evolves them with Genetic Programming (GP) for collaborative robotic applications. The main contribution of this paper is to show that by combining the two learning methods we obtain a method that allows non-expert users to semi-automatically, time-efficiently, and interactively generate BTs. We validate the framework with a series of manipulation experiments. The BT is fully learnt in simulation and then transferred to a real collaborative robot., Comment: Submitted to IEEE 19th Conference on Automation Science and Engineering (CASE) 2023

The upcoming new generation of optical spectrographs on four-meter-class telescopes will provide valuable opportunities for forthcoming galaxy surveys through their huge multiplexing capabilities, excellent spectral resolution, and unprecedented wavelength coverage. WEAVE is a new wide-field spectroscopic facility mounted on the 4.2 m William Herschel Telescope in La Palma. WEAVE-StePS is one of the five extragalactic surveys that will use WEAVE during its first five years of operations. It will observe galaxies using WEAVE MOS (~950 fibres across a field of view of ~3 deg2 on the sky) in low-resolution mode (R~5000, spanning the wavelength range 3660-9590 AA). WEAVE-StePS will obtain high-quality spectra (S/N ~ 10 per AA at R~5000) for a magnitude-limited (I_AB = 20.5) sample of ~25,000 galaxies, the majority selected at z>=0.3. The survey goal is to provide precise spectral measurements in the crucial interval that bridges the gap between LEGA-C and SDSS data. The wide area coverage of ~25 deg2 will enable us to observe galaxies in a variety of environments. The ancillary data available in each observed field (including X-ray coverage, multi-narrow-band photometry and spectroscopic redshift information) will provide an environmental characterisation for each observed galaxy. This paper presents the science case of WEAVE-StePS, the fields to be observed, the parent catalogues used to define the target sample, and the observing strategy chosen after a forecast of the expected performance of the instrument for our typical targets. WEAVE-StePS will go back further in cosmic time than SDSS, extending its reach to encompass more than ~6 Gyr, nearly half of the age of the Universe. The spectral and redshift range covered by WEAVE-StePS will open a new observational window by continuously tracing the evolutionary path of galaxies in the largely unexplored intermediate-redshift range., Comment: 15 pages, 9 figures, A&A in press