arXiv subjects

Lorenzo Betti

Publications and source records attributed to Lorenzo Betti.

10 recordsLinked to original sources

arXiv2026

AT 2016blu: Accretion-Powered Outbursts in a Luminous Blue Variable and Compact Object Binary

We present the first X-ray detection of the supernova (SN) impostor AT 2016blu in NGC 4559. AT 2016blu exhibited 27 detected quasiperiodic (~113 day) outbursts between 2012 and June 2026, presumably triggered by periastron passages in an eccentric binary system in which the primary is a $\gtrsim 33~M_{\odot}$ luminous blue variable (LBV). AT 2016blu was serendipitously observed by Chandra in 2001-2002, prior to its first documented outburst in 2012, but the stacked archival data show no X-ray detection. We monitored the source's visual-wavelength variability around its predicted outburst time and triggered a Chandra Target of Opportunity program in March 2026, obtaining observations with detections over five closely spaced epochs. These data indicate an X-ray luminosity of $\log L_{\rm X} \approx 38.64 \pm 0.11$~erg~s$^{-1}$ and an accretion rate of $\dot{M} \gtrsim 8\times10^{-8}~M_{\odot}~\mathrm{yr^{-1}}$, consistent with the presence of a compact companion. We therefore conclude that AT 2016blu is the first known case of an LBV SN impostor whose outbursts are driven by intermittent accretion onto a compact object. Given that the system consists of a massive star and a compact companion, AT 2016blu is a high-mass X-ray binary, similar to SN 2010da, although the donor star in SN 2010da is a red supergiant.

astro-ph.HE↗

arXiv2026

Students using GenAI lag behind in problem-solving competence: an agent-based study of classroom networks

The development of problem-solving competence (PSC) among high school students is foundational for preparing resilient and adaptive citizens. Generative artificial intelligence (GenAI) can support this process, but it may also encourage students to offload part of the cognitive work that is necessary for deep learning. While the individual effects of GenAI use are increasingly studied, its collective consequences for competence development within classroom environments remain underexplored. In this study, we use an agent-based model to simulate the evolution of PSC in a high school physics classroom, where students complete tasks individually, in collaboration with peers, or with the support of GenAI. By comparing classrooms with and without access to GenAI across different peer-network structures, we show that GenAI use can diminish competence development and increase the share of students remaining in lower competence tiers. These results suggest that the educational impact of GenAI should be assessed not only through individual learning outcomes but also through its effects on collective competence dynamics.

physics.soc-ph↗

arXiv2026

Hypergraphx-data: a repository for higher-order network data

The availability of network datasets advances research in network science, machine learning and related fields by enabling empirical analyses and their reproducibility, algorithm development, model validation and benchmarking. Existing repositories, such as SNAP and Netzschleuder, have made traditional network datasets widely accessible with metadata, metrics, and basic visualizations. However, they primarily focus on pairwise interactions, limiting data access to systems with many-body interactions. To address this gap, we created hypergraphx-data, a repository of real-world hypergraph datasets for higher-order network analysis, spanning different domains from social networks to biology and finance, and supporting configurations such as weighted, directed, temporal, and multiplex hypergraphs. Each dataset includes relational information and metadata, provided in an open JSON format and a binarized format for Hypergraphx. We provide a user-friendly interface to facilitate browsing, filtering, and accessing the datasets, while also ensuring integrity and reproducibility through hash-based verification and data versioning. The repository is available at https://hgx-team.github.io/hypergraphx-data

physics.soc-ph↗

arXiv2024

Spot Modeling through Multiband Photometry Analysis of V1298 Tau

Context. Stellar activity consists of different phenomena, mainly spots and faculae, and it is one of the main sources of noise in exoplanetary observations because it affects both spectroscopic and photometric observations. If we want to study young active planetary systems we need to model the activity of the host stars in order to remove astrophysical noise from our observational data. Aims. We modelled the contribution of stellar spots in photometric observations. Through the use of multiband photometry, we aim to extract the geometric properties of the spots and constrain their temperature. Methods. We analyzed multiband photometric observations acquired with the 80 cm Marcon telescope of the Osservatorio Polifunzionale del Chianti of V1298 Tau, assuming that the photometric modulation observed in different bands should be due to cold spots. Results. We constrained the effective temperature of the active regions present on the surface of V1298 Tau, which is composed by the contemporary presence of spots and faculae. We tested our hypothesis on solar data, verifying that we measure the size of the dominant active region and its averaged effective temperature.

astro-ph.SR↗

arXiv2024

Moral Judgments in Online Discourse are not Biased by Gender

The interaction between social norms and gender roles prescribes gender-specific behaviors that influence moral judgments. Here, we study how moral judgments are biased by the gender of the protagonist of a story. Using data from r/AITA, a Reddit community with 17 million members who share first-hand experiences seeking community judgment on their behavior, we employ machine learning techniques to match stories describing similar situations that differ only by the protagonist's gender. We find no direct causal effect of the protagonist's gender on the received moral judgments, except for stories about ``friendship and relationships'', where male protagonists receive more negative judgments. Our findings complement existing correlational studies and suggest that gender roles may exert greater influence in specific social contexts. These results have implications for understanding sociological constructs and highlight potential biases in data used to train large language models.

cs.CY↗

arXiv2024

Receding contact line dynamics on superhydrophobic surfaces

We have explored receding contact line dynamics on superhydrophobic surfaces, composed of micropillars arrays. We present here dynamic receding contact angle measurements of water on such surfaces, covering contact line speeds spanning over five decades. We have studied the effect of pillars fraction on dynamical receding contact angles. We compared these measurements to those on smooth surfaces with the same chemical nature and also with similar systems reported in the literature. We show that superhydrophobic surfaces exhibit a significantly lower dependence of contact angle on contact line speed compared to smooth surfaces. Additionally, we observed that a higher surface fraction of pillars leads to a greater dependence of the contact angle on contact line speed, approaching the dependence of the angle on smooth surface. Interestingly, we show that the exact texuration of the surface does not play a fundamental role in the angle-velocity relationships as long as microtextures present the same type of periodic pattern (pillar arrays or microgrid). These results are interpreted in terms of viscous friction reduction on superhydrophobic surfaces, shedding light on the underlying mechanisms governing their unique dynamic behavior. In addition we show that contact angles follow same laws for two different geometries (milimetric sessile drop and a centimetric capillary bridge).

cond-mat.soft↗

arXiv2024

The dynamics of leadership and success in software development teams

From science to industry, teamwork plays a crucial role in knowledge production and innovation. Most studies consider teams as static groups of individuals, thereby failing to capture how the micro-dynamics of collaborative processes and organizational changes determine team success. Here, we leverage fine-grained temporal data on software development teams from three software ecosystems -- Rust, JavaScript, and Python -- to gain insights into the dynamics of online collaborative projects. Our analysis reveals an uneven workload distribution in teams, with stronger heterogeneity correlated with higher success, and the early emergence of a lead developer carrying out the majority of work. Moreover, we find that a sizeable fraction of projects experience a change of lead developer, with such a transition being more likely in projects led by inexperienced users. Finally, we show that leadership change is associated with faster success growth. Our work contributes to a deeper understanding of the link between team evolution and success in collaborative processes.

physics.soc-ph↗

arXiv2023

Large scale analysis of gender bias and sexism in song lyrics

We employ Natural Language Processing techniques to analyse 377808 English song lyrics from the "Two Million Song Database" corpus, focusing on the expression of sexism across five decades (1960-2010) and the measurement of gender biases. Using a sexism classifier, we identify sexist lyrics at a larger scale than previous studies using small samples of manually annotated popular songs. Furthermore, we reveal gender biases by measuring associations in word embeddings learned on song lyrics. We find sexist content to increase across time, especially from male artists and for popular songs appearing in Billboard charts. Songs are also shown to contain different language biases depending on the gender of the performer, with male solo artist songs containing more and stronger biases. This is the first large scale analysis of this type, giving insights into language usage in such an influential part of popular culture.

cs.CY↗

arXiv2022

Identifying maximal sets of significantly interacting nodes in higher-order networks

Filtering methods are fundamental tools for extracting the backbone of complex networks. Systems displaying group interactions, however, open the way to new types of filtering approaches. Here, we introduce a statistical filtering method for higher-order networks that identifies statistically validated maximal interacting sets -- maximal sets of nodes that consistently interact together within group interactions. Using properly designed benchmarks, we show that our approach is highly effective in systems where the maximal sets are likely to be diluted into interactions of larger sizes that include occasional participants. Applications to real-world data reveal that the identified sets of nodes are characterized by higher levels of similarity and topical coherence, highlighting the ability of our method to provide new insights on the organization of real-world higher-order networks.

physics.soc-ph↗

arXiv2020

Lunar Gravitational-Wave Antenna

Monitoring of vibrational eigenmodes of an elastic body excited by gravitational waves was one of the first concepts proposed for the detection of gravitational waves. At laboratory scale, these experiments became known as resonant-bar detectors first developed by Joseph Weber in the 1960s. Due to the dimensions of these bars, the targeted signal frequencies were in the kHz range. Weber also pointed out that monitoring of vibrations of Earth or Moon could reveal gravitational waves in the mHz band. His Lunar Surface Gravimeter experiment deployed on the Moon by the Apollo 17 crew had a technical failure rendering the data useless. In this article, we revisit the idea and propose a Lunar Gravitational-Wave Antenna (LGWA). We find that LGWA could become an important partner observatory for joint observations with the space-borne, laser-interferometric detector LISA, and at the same time contribute an independent science case due to LGWA's unique features. Technical challenges need to be overcome for the deployment of the experiment, and development of inertial vibration sensor technology lays out a future path for this exciting detector concept.

gr-qc↗