Showing 1–50 of 60 results for author: Mei, A

The ultra-fast afterglow of GRB 260226A

Authors: Biswajit Banerjee, Alessio Mei, Annarita Ierardi, Samanta Macera, Gor Oganesyan, Shraddha Mohnani, Elias Kammoun, Pawan Tiwari, Stefano Ascenzi, Samuele Ronchini, Ansh Chopra, Alessio Ludovico De Santis, Stefano Covino, Paolo D'Avanzo, Andrea Melandri, Silvia Piranomonte

Abstract: Long-duration gamma-ray bursts are typically powered by relativistic jets launched after the core collapse of some rapidly rotating massive stars. Internal dissipation releases part of the jet energy as highly variable MeV prompt emission, while the remaining kinetic energy drives an external shock into the surrounding medium and produces the so-called afterglow. During the first minutes of the af… ▽ More Long-duration gamma-ray bursts are typically powered by relativistic jets launched after the core collapse of some rapidly rotating massive stars. Internal dissipation releases part of the jet energy as highly variable MeV prompt emission, while the remaining kinetic energy drives an external shock into the surrounding medium and produces the so-called afterglow. During the first minutes of the afterglow, the unsteady jet transfers energy to the external shock. The early afterglow emission in MeV-GeV energies is rarely observed because the emergence of afterglow can be overshined by the prompt emission. Here we report exceptional observations of GRB 260226A with the Fermi Large Area Telescope, which recorded the largest number of photons above 100 MeV from a gamma-ray burst. These data allow us to reconstruct the evolution of the bolometric flux of the afterglow from its emergence during the prompt emission phase with unprecedented detail. The afterglow component peaks near 50 MeV and fades rapidly, first as t$^{-1.5}$ and then transiting to an ultra-fast t$^{-2.8}$ decay after about one minute. This behavior cannot be explained by standard synchrotron emission from a blast wave propagating into a cold medium. We interpret it as external inverse Compton radiation from freshly heated electrons cooling on prompt photons in a dense, pair-loaded stellar wind. GRB 260226A therefore shows that MeV-GeV observations can directly reveal the formation of the external shock and the massive-star environment is significantly reshaped by the prompt emission. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Comments: Submitted

A Truckload of Satoshis: Detecting and Measuring One-Way Arbitrage in the Wild

Authors: Eugenio Nerio Nemmi, Tobias Lauinger, Paz Grimberg, Massimo La Morgia, Damon McCoy, Alessandro Mei

Abstract: Centralized cryptocurrency exchanges (CEXes) enable fast off-chain conversions between hundreds of coins. It is an open question which algorithmic trading patterns occur on these platforms. A major challenge to measuring CEXes is that their public trade data does not contain addresses or trader identifiers allowing linkage. We propose a novel methodology to infer one-way arbitrage (OWA) trading in… ▽ More Centralized cryptocurrency exchanges (CEXes) enable fast off-chain conversions between hundreds of coins. It is an open question which algorithmic trading patterns occur on these platforms. A major challenge to measuring CEXes is that their public trade data does not contain addresses or trader identifiers allowing linkage. We propose a novel methodology to infer one-way arbitrage (OWA) trading in anonymized spot trade data from CEXes. We identify 402 M likely OWA sequences in 5 years of trading on Binance (and almost 2 M during 9 years on Kraken), accounting for 0.94 % and 0.13 % of the total traded volume, respectively. While we estimate total profits of $31.2 M on Binance and $975 k on Kraken, profits from individual OWA sequences are less than $1 on average after accounting for trading fees. We also observe that OWA has become faster over time, while the profitability of individual sequences has decreased. Our findings highlight that pricing discrepancies regularly occur in CEXes, and raise questions for future work to identify the precise circumstances that enable profitable OWA. △ Less

Submitted 10 July, 2026; originally announced July 2026.

Multiwavelength properties of short gamma ray bursts with extended emission observed by Swift

Authors: M. M. Dinatolo, A. Mei, R. Brivio, M. Ferro, M. G. Bernardini, P. D'Avanzo, S. Belova, S. Campana, S. Covino, D. Frederiks, B. Haskell, R. Salvaterra, B. Sbarufatti, A. Tsvetkova

Abstract: Short gamma-ray bursts with extended emission (SGRBEEs) are a particular class of long GRBs (LGRBs) which, despite their duration, share several observational features with short GRBs (SGRBs). They are composed by a short, hard initial pulse (IP) followed by a longer and softer extended emission (EE). We investigate whether SGRBEEs originate from the same progenitor as SGRBs despite their duration… ▽ More Short gamma-ray bursts with extended emission (SGRBEEs) are a particular class of long GRBs (LGRBs) which, despite their duration, share several observational features with short GRBs (SGRBs). They are composed by a short, hard initial pulse (IP) followed by a longer and softer extended emission (EE). We investigate whether SGRBEEs originate from the same progenitor as SGRBs despite their duration, representing a peculiar subclass of LGRBs, or if they constitute a distinct population. Given their respective duration, we tested if the IP and the EE share properties with short and long GRBs, respectively. We analysed SGRBEEs from the flux-limited, redshift-complete SBAT4 sample using prompt-emission data from Swift/BAT, Fermi/GBM and Konus-WIND, and X-ray afterglow observations from Swift/XRT. The temporal and spectral properties of the IP and EE components were compared with those of SGRBs from the extended SBAT4 sample and LGRBs from the BAT6 sample. Despite observing a clear spectral evolution during the prompt phase of each SGRBEE, IPs and EEs as well as short and long GRBs can not be distinguished by their hardness ratio only. All bursts analysed have a spectral lag consistent with zero. SGRBEEs XRT light curves are consistently more complex than those of SGRBs, requiring the addition of multiple breaks and showing the presence of steep decays and plateaus. Our results indicate that SGRBEEs are not an intermediate class. During prompt emission, despite common spectral features, IPs and EEs temporally differ from short and long GRBs, respectively. EEs are on average too faint to appear in the Amati plane, but IPs occupy the same parameter space of SGRBs. In the afterglow, SGRBEEs are more luminous than standard GRBs at early-time, suggesting a direct contribution from the EE; at later times, these events behave as standard SGRBs, and both remain systematically less luminous than LGRBs. △ Less

Submitted 3 July, 2026; originally announced July 2026.

Comments: Submitted to A&A. Comments are welcome

Formalization of QFT

Authors: Michael R. Douglas, Sarah Hoback, Anna Mei, Ron Nissim

Abstract: A foundational result in constructive quantum field theory is the construction of the free bosonic quantum field theory in four-dimensional Euclidean spacetime and the proof that it satisfies the Glimm-Jaffe axioms, a variant of the Osterwalder-Schrader axioms. We present a formalization of this result in the Lean 4 interactive theorem prover. The project is intended as a proof of concept that ext… ▽ More A foundational result in constructive quantum field theory is the construction of the free bosonic quantum field theory in four-dimensional Euclidean spacetime and the proof that it satisfies the Glimm-Jaffe axioms, a variant of the Osterwalder-Schrader axioms. We present a formalization of this result in the Lean 4 interactive theorem prover. The project is intended as a proof of concept that extended arguments in mathematical physics can be translated into machine-checked proofs using existing AI tools. We begin by introducing interactive theorem proving and constructive quantum field theory, then describe our formalization and the design decisions that shaped it. We also explain the methods we used, including coding assistants, and conclude by considering how AI assisted formalization may influence the future of theoretical physics. Our original release assumed three results, Minlos' theorem, the nuclear property of Schwartz space, and Goursat's theorem. In subsequent releases from our group and from contributors from the Lean community, these assumptions have been proven (or avoided), so that the OS/GJ axioms are now proven using only Lean and its library Mathlib. △ Less

Submitted 16 March, 2026; originally announced March 2026.

Comments: 35 pages, 1 figure

MSC Class: 81T08; 68V20; 81-08; 46N50 ACM Class: F.4.1

Hyperactive Minority Alters the Stability of Community Notes

Authors: Jacopo Nudo, Eugenio Nerio Nemmi, Edoardo Loru, Alessandro Mei, Walter Quattrociocchi, Matteo Cinelli

Abstract: As platforms increasingly scale down professional fact-checking, community-based alternatives are promoted as more transparent and democratic. The main substitute being proposed is community-based contextualization, most notably Community Notes on X, where users write annotations and collectively rate their helpfulness under a consensus-oriented algorithm. This shift raises a basic empirical quest… ▽ More As platforms increasingly scale down professional fact-checking, community-based alternatives are promoted as more transparent and democratic. The main substitute being proposed is community-based contextualization, most notably Community Notes on X, where users write annotations and collectively rate their helpfulness under a consensus-oriented algorithm. This shift raises a basic empirical question: to what extent do users' social dynamics affect the emergence of Community Notes? We address this question by characterizing participation and political behavior, using the full public release of notes and ratings (between 2021 and 2025). We show that contribution activity is highly concentrated: a small minority of users accounts for a disproportionate share of ratings. Crucially, these high-activity contributors are not neutral volunteers: they are selective in the content they engage with and substantially more politically polarized than the overall contributor population. We replicate the notes' emergence process by integrating the open-source implementation of the Community Notes consensus algorithm used in production. This enables us to conduct counterfactual simulations that modify the display status of notes by varying the pool of raters. Our results reveal that the system is structurally unstable: the emergence and visibility of notes often depend on the behavior of a few dozen highly active users, and even minor perturbations in their participation can lead to markedly different outcomes. In sum, rather than decentralizing epistemic authority, community-based fact-checking on X reconfigures it, concentrating substantial power in the hands of a small, polarized group of highly active contributors. △ Less

Submitted 25 February, 2026; v1 submitted 9 February, 2026; originally announced February 2026.

MemeChain: A Multimodal Cross-Chain Dataset for Meme Coin Forensics and Risk Analysis

Authors: Alberto Maria Mongardini, Alessandro Mei

Abstract: The meme coin ecosystem has grown into one of the most active yet least observable segments of the cryptocurrency market, characterized by extreme churn, minimal project commitment, and widespread fraudulent behavior. While countless meme coins are deployed across multiple blockchains, they rely heavily on off-chain web and social infrastructure to signal legitimacy. These very signals are largely… ▽ More The meme coin ecosystem has grown into one of the most active yet least observable segments of the cryptocurrency market, characterized by extreme churn, minimal project commitment, and widespread fraudulent behavior. While countless meme coins are deployed across multiple blockchains, they rely heavily on off-chain web and social infrastructure to signal legitimacy. These very signals are largely absent from existing datasets, which are often limited to single-chain data or lack the multimodal artifacts required for comprehensive risk modeling. To address this gap, we introduce MemeChain, a large-scale, open-source, cross-chain dataset comprising 34,988 meme coins across Ethereum, BNB Smart Chain, Solana, and Base. MemeChain integrates on-chain data with off-chain artifacts, including website HTML source code, token logos, and linked social media accounts, enabling multimodal and forensic study of meme coin projects. Analysis of the dataset shows that visual branding is frequently omitted in low-effort deployments, and many projects lack a functional website. Moreover, we quantify the ecosystem's extreme volatility, identifying 1,801 tokens (5.15%) that cease all trading activity within just 24 hours of launch. By providing unified cross-chain coverage and rich off-chain context, MemeChain serves as a foundational resource for research in financial forensics, multimodal anomaly detection, and automated scam prevention in the meme coin ecosystem. △ Less

Submitted 28 January, 2026; originally announced January 2026.

MeV absorption in gamma-ray bursts as a probe of their progenitor environments

Authors: Gor Oganesyan, Om Sharan Salafia, Emanuele Sobacchi, Samanta Macera, Giancarlo Ghirlanda, Lara Nava, Annarita Ierardi, Biswajit Banerjee, Alessio Mei, Stefano Ascenzi, Marica Branchesi

Abstract: A small fraction of X-ray photons from $γ$-ray bursts (GRBs), after escaping the relativistic jet, are scattered by electrons in the circumburst medium. Subsequent photon-photon absorption between the incoming MeV $γ$-rays and the back-scattered X-rays generate electron-positron pairs, enriching the surrounding medium with leptons. We investigate how these back-scattered photons modify the prompt… ▽ More A small fraction of X-ray photons from $γ$-ray bursts (GRBs), after escaping the relativistic jet, are scattered by electrons in the circumburst medium. Subsequent photon-photon absorption between the incoming MeV $γ$-rays and the back-scattered X-rays generate electron-positron pairs, enriching the surrounding medium with leptons. We investigate how these back-scattered photons modify the prompt GRB spectrum through $γ-γ$ absorption. In a dense and pair-loaded environment, the emerging spectra exhibit a broad absorption feature, whose profile is sensitive to the low-energy spectral index $α$. In particular, spectra with $α> -1$ develop a pronounced, saddle-shaped absorption between 1 and 100 MeV (rest frame). Such external MeV absorption could account for the spectral curvature seen in some bright GRBs, and may point to a dense circum-stellar medium (CSM) around their progenitor stars - consistent with early observations of core-collapse supernovae. In this scenario, the blastwave caused by the GRB is expected to start off with a relatively low Lorentz factor, and undergo an acceleration phase when traversing the large density drop at the interface between the dense CSM and the surrounding medium. The impact of these non-trivial dynamics on the afterglow emission is yet to be explored. △ Less

Submitted 8 June, 2026; v1 submitted 20 January, 2026; originally announced January 2026.

Comments: Accepted for publication as a Letter to the Editor in A&A

DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

Authors: DeepSeek-AI, Aixin Liu, Aoxue Mei, Bangcai Lin, Bing Xue, Bingxuan Wang, Bingzheng Xu, Bochao Wu, Bowei Zhang, Chaofan Lin, Chen Dong, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenhao Xu, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Erhang Li, Fangqi Zhou, Fangyun Lin, Fucong Dai, Guangbo Hao , et al. (239 additional authors not shown)

Abstract: We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 are as follows: (1) DeepSeek Sparse Attention (DSA): We introduce DSA, an efficient attention mechanism that substantially reduces computational complexity while preserving model performance in long-context scenarios. (2)… ▽ More We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 are as follows: (1) DeepSeek Sparse Attention (DSA): We introduce DSA, an efficient attention mechanism that substantially reduces computational complexity while preserving model performance in long-context scenarios. (2) Scalable Reinforcement Learning Framework: By implementing a robust reinforcement learning protocol and scaling post-training compute, DeepSeek-V3.2 performs comparably to GPT-5. Notably, our high-compute variant, DeepSeek-V3.2-Speciale, surpasses GPT-5 and exhibits reasoning proficiency on par with Gemini-3.0-Pro, achieving gold-medal performance in both the 2025 International Mathematical Olympiad (IMO) and the International Olympiad in Informatics (IOI). (3) Large-Scale Agentic Task Synthesis Pipeline: To integrate reasoning into tool-use scenarios, we developed a novel synthesis pipeline that systematically generates training data at scale. This methodology facilitates scalable agentic post-training, yielding substantial improvements in generalization and instruction-following robustness within complex, interactive environments. △ Less

Submitted 2 December, 2025; originally announced December 2025.

Sparse Computations in Deep Learning Inference

Authors: Ioanna Tasou, Panagiotis Mpakos, Angelos Vlachos, Dionysios Adamopoulos, Georgios Giannakopoulos, Konstantinos Katsikopoulos, Ioannis Karaparisis, Maria Lazou, Spyridon Loukovitis, Areti Mei, Anastasia Poulopoulou, Angeliki Dimitriou, Giorgos Filandrianos, Dimitrios Galanopoulos, Vasileios Karampinis, Ilias Mitsouras, Nikolaos Spanos, Petros Anastasiadis, Ioannis Doudalis, Konstantinos Nikas, George Retsinas, Paraskevi Tzouveli, Christina Giannoula, Nectarios Koziris, Nikela Papadopoulou , et al. (3 additional authors not shown)

Abstract: The computational demands of modern Deep Neural Networks (DNNs) are immense and constantly growing. While training costs usually capture public attention, inference demands are also contributing in significant computational, energy and environmental footprints. Sparsity stands out as a critical mechanism for drastically reducing these resource demands. However, its potential remains largely untapp… ▽ More The computational demands of modern Deep Neural Networks (DNNs) are immense and constantly growing. While training costs usually capture public attention, inference demands are also contributing in significant computational, energy and environmental footprints. Sparsity stands out as a critical mechanism for drastically reducing these resource demands. However, its potential remains largely untapped and is not yet fully incorporated in production AI systems. To bridge this gap, this work provides the necessary knowledge and insights for performance engineers keen to get involved in deep learning inference optimization. In particular, in this work we: a) discuss the various forms of sparsity that can be utilized in DNN inference, b) explain how the original dense computations translate to sparse kernels, c) provide an extensive bibliographic review of the state-of-the-art in the implementation of these kernels for CPUs and GPUs, d) discuss the availability of sparse datasets in support of sparsity-related research and development, e) explore the current software tools and frameworks that provide robust sparsity support, and f) present evaluation results of different implementations of the key SpMM and SDDMM kernels on CPU and GPU platforms. Ultimately, this paper aims to serve as a resource for performance engineers seeking to develop and deploy highly efficient sparse deep learning models in productions. △ Less

Submitted 2 December, 2025; originally announced December 2025.

U-DiT Policy: U-shaped Diffusion Transformers for Robotic Manipulation

Authors: Linzhi Wu, Aoran Mei, Xiyue Wang, Guo-Niu Zhu, Zhongxue Gan

Abstract: Diffusion-based methods have been acknowledged as a powerful paradigm for end-to-end visuomotor control in robotics. Most existing approaches adopt a Diffusion Policy in U-Net architecture (DP-U), which, while effective, suffers from limited global context modeling and over-smoothing artifacts. To address these issues, we propose U-DiT Policy, a novel U-shaped Diffusion Transformer framework. U-Di… ▽ More Diffusion-based methods have been acknowledged as a powerful paradigm for end-to-end visuomotor control in robotics. Most existing approaches adopt a Diffusion Policy in U-Net architecture (DP-U), which, while effective, suffers from limited global context modeling and over-smoothing artifacts. To address these issues, we propose U-DiT Policy, a novel U-shaped Diffusion Transformer framework. U-DiT preserves the multi-scale feature fusion advantages of U-Net while integrating the global context modeling capability of Transformers, thereby enhancing representational power and policy expressiveness. We evaluate U-DiT extensively across both simulation and real-world robotic manipulation tasks. In simulation, U-DiT achieves an average performance gain of 10\% over baseline methods and surpasses Transformer-based diffusion policies (DP-T) that use AdaLN blocks by 6\% under comparable parameter budgets. On real-world robotic tasks, U-DiT demonstrates superior generalization and robustness, achieving an average improvement of 22.5\% over DP-U. In addition, robustness and generalization experiments under distractor and lighting variations further highlight the advantages of U-DiT. These results highlight the effectiveness and practical potential of U-DiT Policy as a new foundation for diffusion-based robotic manipulation. △ Less

Submitted 29 September, 2025; originally announced September 2025.

Quantum States in Twisted Tubes with Linear Cross-Section Variation

Authors: Guo-Hua Liang, Ai-Guo Mei, Men-Yun Lai, Shu-Sheng Xu

Abstract: We study the quantum dynamics of a particle confined in a twisted tube with a linearly varying cross section. By relating a general linear transformation matrix to the system's Hamiltonian, we use an extended thin-layer method to derive an effective Hamiltonian for tangential motion under mild and general linear transformations. Explicit forms are provided for three fundamental transformations: ro… ▽ More We study the quantum dynamics of a particle confined in a twisted tube with a linearly varying cross section. By relating a general linear transformation matrix to the system's Hamiltonian, we use an extended thin-layer method to derive an effective Hamiltonian for tangential motion under mild and general linear transformations. Explicit forms are provided for three fundamental transformations: rotation, scaling, and shearing. Rotation introduces a gauge field coupled to angular momentum, while scaling and shearing produce geometric potentials that lift degeneracies in non-circular cross sections. In square cross sections, these transformations cause energy splittings among formerly degenerate states, whereas circular cross sections retain degeneracy. Through an example combining rotation and squeezing, we analyze state evolution and compute the quantum geometric tensor to quantify geometric response. Our results demonstrate how geometric transformations can tailor quantum states and suggest that circular waveguides are more robust against mode mixing. △ Less

Submitted 30 August, 2025; originally announced September 2025.

Ultra-long MeV transient from a relativistic jet: a tidal disruption event candidate

Authors: Gor Oganesyan, Elias Kammoun, Annarita Ierardi, Alessio Ludovico De Santis, Biswajit Banerjee, Emanuele Sobacchi, Felix Aharonian, Samanta Macera, Pawan Tiwari, Alessio Mei, Shraddha Mohnani, Stefano Ascenzi, Samuele Ronchini, Marica Branchesi

Abstract: On July 2, 2025, the Gamma-ray Burst Monitor (GBM) onboard the Fermi Gamma-ray space telescope detected three short-duration MeV transients with overlapping sky locations. These events, named as GRB 250702D, B, and E (collectively referred to as DBE), triggered the detector with delays of approximately 1-2 hours between each burst. Follow-up observations of this unusually long MeV transient (lasti… ▽ More On July 2, 2025, the Gamma-ray Burst Monitor (GBM) onboard the Fermi Gamma-ray space telescope detected three short-duration MeV transients with overlapping sky locations. These events, named as GRB 250702D, B, and E (collectively referred to as DBE), triggered the detector with delays of approximately 1-2 hours between each burst. Follow-up observations of this unusually long MeV transient (lasting >3 hours) by the Neil Gehrels Swift Observatory and the Nuclear Spectroscopic Telescope Array over a period of 10 days revealed a steep temporal decline in soft X-rays ($\propto t^{-1.9 \pm 0.1}$). The time-averaged spectra during the outbursts are well described by a single power law $dN_γ/dE \propto E^{-1.5}$, while upper limits above 100 MeV imply a spectral cutoff between 10 MeV and 100 MeV. Using standard gamma-ray transparency arguments, we derive a lower limit on the bulk Lorentz factor. Combined with the steep decline in X-rays, these constraints point to a relativistic jet origin. The properties of DBE are inconsistent with established GRB spectral-energy correlations, disfavoring classical long GRB progenitors. Instead, the basic characteristics of DBE resemble those of previously reported jetted tidal disruption events (TDEs), though alternative progenitor channels cannot be excluded. In the relativistic TDE scenario, DBE is the first one with detected MeV gamma-ray emission. We argue that the observed emission is most likely produced by synchrotron radiation from sub-TeV electrons. △ Less

Submitted 14 October, 2025; v1 submitted 24 July, 2025; originally announced July 2025.

Comments: Accepted for publication in A&A (Letter)

Journal ref: A&A 703, L2 (2025)

A Midsummer Meme's Dream: Investigating Market Manipulations in the Meme Coin Ecosystem

Authors: Alberto Maria Mongardini, Alessandro Mei

Abstract: From viral jokes to a billion-dollar phenomenon, meme coins have become one of the most popular segments in cryptocurrency markets. Unlike utility-focused crypto assets like Bitcoin, meme coins derive value primarily from community sentiment, making them vulnerable to manipulation. This study presents an unprecedented cross-chain analysis of the meme coin ecosystem, examining 34,988 tokens across… ▽ More From viral jokes to a billion-dollar phenomenon, meme coins have become one of the most popular segments in cryptocurrency markets. Unlike utility-focused crypto assets like Bitcoin, meme coins derive value primarily from community sentiment, making them vulnerable to manipulation. This study presents an unprecedented cross-chain analysis of the meme coin ecosystem, examining 34,988 tokens across Ethereum, BNB Smart Chain, Solana, and Base. We characterize their tokenomics and track their growth in a three-month longitudinal analysis. We discover that among high-return tokens (>100%), an alarming 82.8% show evidence of artificial growth strategies designed to create a misleading appearance of market interest. These include wash trading and a new form of manipulation we define as Liquidity Pool-Based Price Inflation (LPI), where small strategic purchases trigger dramatic price increases. We find that profit extraction schemes, such as pump and dumps and rug pulls, typically follow initial manipulations like wash trading or LPI, indicating how early manipulations create the foundation for later exploitation. We quantify the economic impact of these schemes, identifying over 17,000 victimized addresses with realized losses exceeding $9.3 million. These findings reveal that combined manipulations are widespread among high-performing meme coins, suggesting that their dramatic gains are often driven by coordinated efforts rather than natural market dynamics. △ Less

Submitted 2 January, 2026; v1 submitted 16 April, 2025; originally announced July 2025.

Spin textures in curved paths on a curved surface

Authors: Guo-Hua Liang, Ai-Guo Mei, Zhi-Hui Yang, Ze-Lin Wei

Abstract: This study investigates the quantum dynamics of a spin-1/2 particle confined to a curved path from the dynamics of a two-dimensional curved thin-layer system incorporating spin connection contributions. We demonstrate that the geodesic curvature, normal curvature, and geodesic torsion govern the emergent non-Abelian gauge potential, while the geodesic and Gaussian curvatures govern the effective s… ▽ More This study investigates the quantum dynamics of a spin-1/2 particle confined to a curved path from the dynamics of a two-dimensional curved thin-layer system incorporating spin connection contributions. We demonstrate that the geodesic curvature, normal curvature, and geodesic torsion govern the emergent non-Abelian gauge potential, while the geodesic and Gaussian curvatures govern the effective scalar potential in the Hamiltonian. The resulting spin precession dynamics induced by the gauge potential are analyzed with and without the adiabatic approximation. Under this approximation, the surface topology is linked to the rotation angle of spin orientation along a surface boundary and to the pseudo-magnetic flux. Spin texture evolution along helices illustrates distinct behaviors under geodesic versus non-geodesic propagation. Furthermore, the spin evolution along Viviani's curve exemplifies surface dependence. The curve's topology ensures closure of the spin direction and independence of the spin from the path direction. Our theory establishes a framework for spin-state manipulation via engineered nanostructured channels, enabling novel topological quantum control strategies. △ Less

Submitted 9 August, 2025; v1 submitted 5 June, 2025; originally announced June 2025.

Comments: 10 pages, 3 figures

Tales of the 2025 Los Angeles Fire: Hotwash for Public Health Concerns in Reddit via LLM-Enhanced Topic Modeling

Authors: Sulong Zhou, Qunying Huang, Shaoheng Zhou, Yun Hang, Xinyue Ye, Aodong Mei, Kathryn Phung, Yuning Ye, Uma Govindswamy, Zehan Li

Abstract: Wildfires have become increasingly frequent, irregular, and severe in recent years. Understanding how affected populations perceive and respond during wildfire crises is critical for timely and empathetic disaster response. Social media platforms offer a crowd-sourced channel to capture evolving public discourse, providing hyperlocal information and insight into public sentiment. This study analyz… ▽ More Wildfires have become increasingly frequent, irregular, and severe in recent years. Understanding how affected populations perceive and respond during wildfire crises is critical for timely and empathetic disaster response. Social media platforms offer a crowd-sourced channel to capture evolving public discourse, providing hyperlocal information and insight into public sentiment. This study analyzes Reddit discourse during the 2025 Los Angeles wildfires, spanning from the onset of the disaster to full containment. We collect 385 posts and 114,879 comments related to the Palisades and Eaton fires. We adopt topic modeling methods to identify the latent topics, enhanced by large language models (LLMs) and human-in-the-loop (HITL) refinement. Furthermore, we develop a hierarchical framework to categorize latent topics, consisting of two main categories, Situational Awareness (SA) and Crisis Narratives (CN). The volume of SA category closely aligns with real-world fire progressions, peaking within the first 2-5 days as the fires reach the maximum extent. The most frequent co-occurring category set of public health and safety, loss and damage, and emergency resources expands on a wide range of health-related latent topics, including environmental health, occupational health, and one health. Grief signals and mental health risks consistently accounted for 60 percentage and 40 percentage of CN instances, respectively, with the highest total volume occurring at night. This study contributes the first annotated social media dataset on the 2025 LA fires, and introduces a scalable multi-layer framework that leverages topic modeling for crisis discourse analysis. By identifying persistent public health concerns, our results can inform more empathetic and adaptive strategies for disaster response, public health communication, and future research in comparable climate-related disaster events. △ Less

Submitted 5 January, 2026; v1 submitted 14 May, 2025; originally announced May 2025.

Comments: Fix typos in Method Section. Add data/code availability

SO-DETR: Leveraging Dual-Domain Features and Knowledge Distillation for Small Object Detection

Authors: Huaxiang Zhang, Hao Zhang, Aoran Mei, Zhongxue Gan, Guo-Niu Zhu

Abstract: Detection Transformer-based methods have achieved significant advancements in general object detection. However, challenges remain in effectively detecting small objects. One key difficulty is that existing encoders struggle to efficiently fuse low-level features. Additionally, the query selection strategies are not effectively tailored for small objects. To address these challenges, this paper pr… ▽ More Detection Transformer-based methods have achieved significant advancements in general object detection. However, challenges remain in effectively detecting small objects. One key difficulty is that existing encoders struggle to efficiently fuse low-level features. Additionally, the query selection strategies are not effectively tailored for small objects. To address these challenges, this paper proposes an efficient model, Small Object Detection Transformer (SO-DETR). The model comprises three key components: a dual-domain hybrid encoder, an enhanced query selection mechanism, and a knowledge distillation strategy. The dual-domain hybrid encoder integrates spatial and frequency domains to fuse multi-scale features effectively. This approach enhances the representation of high-resolution features while maintaining relatively low computational overhead. The enhanced query selection mechanism optimizes query initialization by dynamically selecting high-scoring anchor boxes using expanded IoU, thereby improving the allocation of query resources. Furthermore, by incorporating a lightweight backbone network and implementing a knowledge distillation strategy, we develop an efficient detector for small objects. Experimental results on the VisDrone-2019-DET and UAVVaste datasets demonstrate that SO-DETR outperforms existing methods with similar computational demands. The project page is available at https://github.com/ValiantDiligent/SO_DETR. △ Less

Submitted 11 April, 2025; originally announced April 2025.

Roadmap to fault tolerant quantum computation using topological qubit arrays

Authors: David Aasen, Morteza Aghaee, Zulfi Alam, Mariusz Andrzejczuk, Andrey Antipov, Mikhail Astafev, Lukas Avilovas, Amin Barzegar, Bela Bauer, Jonathan Becker, Juan M. Bello-Rivas, Umesh Bhaskar, Alex Bocharov, Srini Boddapati, David Bohn, Jouri Bommer, Parsa Bonderson, Jan Borovsky, Leo Bourdet, Samuel Boutin, Tom Brown, Gary Campbell, Lucas Casparis, Srivatsa Chakravarthi, Rui Chao , et al. (157 additional authors not shown)

Abstract: We describe a concrete device roadmap towards a fault-tolerant quantum computing architecture based on noise-resilient, topologically protected Majorana-based qubits. Our roadmap encompasses four generations of devices: a single-qubit device that enables a measurement-based qubit benchmarking protocol; a two-qubit device that uses measurement-based braiding to perform single-qubit Clifford operati… ▽ More We describe a concrete device roadmap towards a fault-tolerant quantum computing architecture based on noise-resilient, topologically protected Majorana-based qubits. Our roadmap encompasses four generations of devices: a single-qubit device that enables a measurement-based qubit benchmarking protocol; a two-qubit device that uses measurement-based braiding to perform single-qubit Clifford operations; an eight-qubit device that can be used to show an improvement of a two-qubit operation when performed on logical qubits rather than directly on physical qubits; and a topological qubit array supporting lattice surgery demonstrations on two logical qubits. Devices that enable this path require a superconductor-semiconductor heterostructure that supports a topological phase, quantum dots and coupling between those quantum dots that can create the appropriate loops for interferometric measurements, and a microwave readout system that can perform fast, low-error single-shot measurements. We describe the key design components of these qubit devices, along with the associated protocols for demonstrations of single-qubit benchmarking, Clifford gate execution, quantum error detection, and quantum error correction, which differ greatly from those in more conventional qubits. Finally, we comment on implications and advantages of this architecture for utility-scale quantum computation. △ Less

Submitted 18 July, 2025; v1 submitted 17 February, 2025; originally announced February 2025.

Comments: v2: 12+8 pages, 9+5 figures, significant main text and appendix revisions

Gamma-ray burst prompt emission spectra at high energies

Authors: Samanta Macera, Biswajit Banerjee, Alessio Mei, Pawan Tiwari, Gor Oganesyan, Marica Branchesi

Abstract: Despite more than fifty years of gamma-ray burst (GRB) observations, several questions regarding the origin of the prompt emission, particularly at high energies, remain unresolved. We present a comprehensive analysis of 35 GRBs observed by \textit{Fermi}/GBM and \textit{Fermi}/LAT over the past 15 years, focusing on the nature of high-energy (HE, E$>$100 MeV) emission during the prompt emission p… ▽ More Despite more than fifty years of gamma-ray burst (GRB) observations, several questions regarding the origin of the prompt emission, particularly at high energies, remain unresolved. We present a comprehensive analysis of 35 GRBs observed by \textit{Fermi}/GBM and \textit{Fermi}/LAT over the past 15 years, focusing on the nature of high-energy (HE, E$>$100 MeV) emission during the prompt emission phase. Our study combines temporal and spectral analyses to investigate the synchrotron origin of the observed emission spanning the energy range from 10 keV to 100 GeV and explore the possible contribution of additional spectral components. Temporal modeling of \textit{Fermi}/LAT light curves for 12 GRBs in our sample reveals deviations from standard afterglow scenarios during the early phases, suggesting a significant contamination from prompt emission. We find that most GRB spectra align with synchrotron emission extending to GeV energies, with the slope $p$ of the non-thermal electron distribution clustering around $p\sim2.7$, consistently with theoretical predictions. For three GRBs, an additional power law component is required to explain the high-energy emission, but the nature and temporal evolution of this component remain unclear due to the limited quality of \textit{Fermi}/LAT data. When the power law component is needed, the synchrotron spectrum shows a sharp MeV suppression. It could be explained by the pair loading effects in the early afterglow. These findings emphasize the importance of multi-wavelength observations in unveiling the mechanisms driving early HE prompt emission in GRBs. We briefly discuss the implications of our findings for future very-high-energy (VHE, E$>$100 GeV) gamma-ray observatories, such as the Cherenkov Telescope Array, and address the detection prospects of additional non-thermal components in GRB spectra. △ Less

Submitted 17 January, 2025; originally announced January 2025.

Comments: Comments and suggestions are welcome

Gamma-ray burst spectral-luminosity correlations in the synchrotron scenario

Authors: Alessio Mei, Gor Oganesyan, Samanta Macera

Abstract: For over two decades, gamma-ray burst (GRB) prompt emission spectra were modelled with smoothly-broken power laws (Band function), and a positive and tight correlation between the spectral rest-frame peak energy $E_p$ and the total isotropic-equivalent luminosity $L_{iso}$ was found, constituting the so-called Yonetoku relation. However, more recent studies show that many prompt emission spectra a… ▽ More For over two decades, gamma-ray burst (GRB) prompt emission spectra were modelled with smoothly-broken power laws (Band function), and a positive and tight correlation between the spectral rest-frame peak energy $E_p$ and the total isotropic-equivalent luminosity $L_{iso}$ was found, constituting the so-called Yonetoku relation. However, more recent studies show that many prompt emission spectra are well described by the synchrotron radiation model, hence significantly deviating from the Band function. In this work, we test the impact of a more suited spectral model such as an idealized synchrotron spectrum from non-thermal electrons on the Yonetoku relation and its connection with physical parameters. We select GRBs with measured redshift observed by Fermi/GBM together with high energy observations (>30 MeV), and perform spectral analysis dividing them in two samples: the single-bin sample, using the light curve peak spectrum of each GRB, and the multiple-bins sample, where we explore the whole duration of 13 bright bursts with time-resolved spectral analysis. We observed that the $E_p$ of synchrotron spectra in fast-cooling regime ($ν_m/ν_c\gg1$) is generally larger than the one provided by the Band function. For this reason, we do not find any $E_p-L_{iso}$ correlation in our samples except for the GRBs in an intermediate-cooling regime ($1<ν_m/ν_c<3$), namely where peak and break energies are very close. We instead find in both our samples a new tight correlation between the rest-frame cooling frequency $ν_{c,z}$ and $L_{iso}$: $ν_{c,z} \propto L_{iso}^{(0.53 \pm 0.06)}$. These results suggest that, assuming that prompt emission spectra are produced by synchrotron radiation, the physical relation is between $ν_{c,z}$ and $L_{iso}$. The fit of the Band function to an intrinsic synchrotron spectrum returns peak energy values $E_{p,z}^{Band} \sim ν_{c,z}$. △ Less

Submitted 12 September, 2024; originally announced September 2024.

Comments: Submitted to A&A

ReplanVLM: Replanning Robotic Tasks with Visual Language Models

Authors: Aoran Mei, Guo-Niu Zhu, Huaxiang Zhang, Zhongxue Gan

Abstract: Large language models (LLMs) have gained increasing popularity in robotic task planning due to their exceptional abilities in text analytics and generation, as well as their broad knowledge of the world. However, they fall short in decoding visual cues. LLMs have limited direct perception of the world, which leads to a deficient grasp of the current state of the world. By contrast, the emergence o… ▽ More Large language models (LLMs) have gained increasing popularity in robotic task planning due to their exceptional abilities in text analytics and generation, as well as their broad knowledge of the world. However, they fall short in decoding visual cues. LLMs have limited direct perception of the world, which leads to a deficient grasp of the current state of the world. By contrast, the emergence of visual language models (VLMs) fills this gap by integrating visual perception modules, which can enhance the autonomy of robotic task planning. Despite these advancements, VLMs still face challenges, such as the potential for task execution errors, even when provided with accurate instructions. To address such issues, this paper proposes a ReplanVLM framework for robotic task planning. In this study, we focus on error correction interventions. An internal error correction mechanism and an external error correction mechanism are presented to correct errors under corresponding phases. A replan strategy is developed to replan tasks or correct error codes when task execution fails. Experimental results on real robots and in simulation environments have demonstrated the superiority of the proposed framework, with higher success rates and robust error correction capabilities in open-world tasks. Videos of our experiments are available at https://youtu.be/NPk2pWKazJc. △ Less

Submitted 31 July, 2024; originally announced July 2024.

Coherent control of a triangular exchange-only spin qubit

Authors: Edwin Acuna, Joseph D. Broz, Kaushal Shyamsundar, Antonio B. Mei, Colin P. Feeney, Valerie Smetanka, Tiffany Davis, Kangmu Lee, Maxwell D. Choi, Brydon Boyd, June Suh, Wonill D. Ha, Cameron Jennings, Andrew S. Pan, Daniel S. Sanchez, Matthew D. Reed, Jason R. Petta

Abstract: We demonstrate coherent control of a three-electron exchange-only spin qubit with the quantum dots arranged in a close-packed triangular geometry. The device is tuned to confine one electron in each quantum dot, as evidenced by pairwise charge stability diagrams. Time-domain control of the exchange coupling is demonstrated and qubit performance is characterized using blind randomized benchmarking,… ▽ More We demonstrate coherent control of a three-electron exchange-only spin qubit with the quantum dots arranged in a close-packed triangular geometry. The device is tuned to confine one electron in each quantum dot, as evidenced by pairwise charge stability diagrams. Time-domain control of the exchange coupling is demonstrated and qubit performance is characterized using blind randomized benchmarking, with an average single-qubit gate fidelity F = 99.84%. The compact triangular device geometry can be readily scaled to larger two-dimensional quantum dot arrays with high connectivity. △ Less

Submitted 5 June, 2024; originally announced June 2024.

Camelidae on BOAT: observation of a second spectral component in GRB 221009A

Authors: Biswajit Banerjee, Samanta Macera, Alessio Ludovico De Santis, Alessio Mei, Jacopo Tissino, Gor Oganesyan, Dmitry D. Frederiks, Alexandra L. Lysenko, Dmitry S. Svinkin, Anastasia E. Tsvetkova, Marica Branchesi

Abstract: Observing and understanding the origin of the very-high-energy (VHE) spectral component in gamma-ray bursts (GRBs) has been challenging because of the lack of sensitivity in MeV-GeV observations, so far. The majestic GRB 221009A, known as the brightest of all times (BOAT), offers a unique opportunity to identify spectral components during the prompt and early afterglow phases and probe their origi… ▽ More Observing and understanding the origin of the very-high-energy (VHE) spectral component in gamma-ray bursts (GRBs) has been challenging because of the lack of sensitivity in MeV-GeV observations, so far. The majestic GRB 221009A, known as the brightest of all times (BOAT), offers a unique opportunity to identify spectral components during the prompt and early afterglow phases and probe their origin. Analyzing simultaneous observations spanning from keV to TeV energies, we identified two distinct spectral components during the initial 20 minutes of the burst. The second spectral component peaks between $10-300$ GeV, and the bolometric fluence (10 MeV-10 TeV) is estimated to be greater than 2$\times10^{-3}$ erg/ cm$^{2}$. Performing broad-band spectral modeling, we provide constraints on the magnetic field and the energies of electrons accelerated in the external relativistic shock. We interpret the VHE component as an afterglow emission that is affected by luminous prompt MeV radiation at early times. △ Less

Submitted 24 May, 2024; originally announced May 2024.

Comments: Comments and suggestions are welcome

Journal ref: A&A 701, A68 (2025)

GameVLM: A Decision-making Framework for Robotic Task Planning Based on Visual Language Models and Zero-sum Games

Authors: Aoran Mei, Jianhua Wang, Guo-Niu Zhu, Zhongxue Gan

Abstract: With their prominent scene understanding and reasoning capabilities, pre-trained visual-language models (VLMs) such as GPT-4V have attracted increasing attention in robotic task planning. Compared with traditional task planning strategies, VLMs are strong in multimodal information parsing and code generation and show remarkable efficiency. Although VLMs demonstrate great potential in robotic task… ▽ More With their prominent scene understanding and reasoning capabilities, pre-trained visual-language models (VLMs) such as GPT-4V have attracted increasing attention in robotic task planning. Compared with traditional task planning strategies, VLMs are strong in multimodal information parsing and code generation and show remarkable efficiency. Although VLMs demonstrate great potential in robotic task planning, they suffer from challenges like hallucination, semantic complexity, and limited context. To handle such issues, this paper proposes a multi-agent framework, i.e., GameVLM, to enhance the decision-making process in robotic task planning. In this study, VLM-based decision and expert agents are presented to conduct the task planning. Specifically, decision agents are used to plan the task, and the expert agent is employed to evaluate these task plans. Zero-sum game theory is introduced to resolve inconsistencies among different agents and determine the optimal solution. Experimental results on real robots demonstrate the efficacy of the proposed framework, with an average success rate of 83.3%. △ Less

Submitted 22 May, 2024; originally announced May 2024.

Interferometric Single-Shot Parity Measurement in an InAs-Al Hybrid Device

Authors: Morteza Aghaee, Alejandro Alcaraz Ramirez, Zulfi Alam, Rizwan Ali, Mariusz Andrzejczuk, Andrey Antipov, Mikhail Astafev, Amin Barzegar, Bela Bauer, Jonathan Becker, Umesh Kumar Bhaskar, Alex Bocharov, Srini Boddapati, David Bohn, Jouri Bommer, Leo Bourdet, Arnaud Bousquet, Samuel Boutin, Lucas Casparis, Benjamin James Chapman, Sohail Chatoor, Anna Wulff Christensen, Cassandra Chua, Patrick Codd, William Cole , et al. (137 additional authors not shown)

Abstract: The fusion of non-Abelian anyons or topological defects is a fundamental operation in measurement-only topological quantum computation. In topological superconductors, this operation amounts to a determination of the shared fermion parity of Majorana zero modes. As a step towards this, we implement a single-shot interferometric measurement of fermion parity in indium arsenide-aluminum heterostruct… ▽ More The fusion of non-Abelian anyons or topological defects is a fundamental operation in measurement-only topological quantum computation. In topological superconductors, this operation amounts to a determination of the shared fermion parity of Majorana zero modes. As a step towards this, we implement a single-shot interferometric measurement of fermion parity in indium arsenide-aluminum heterostructures with a gate-defined nanowire. The interferometer is formed by tunnel-coupling the proximitized nanowire to quantum dots. The nanowire causes a state-dependent shift of these quantum dots' quantum capacitance of up to 1 fF. Our quantum capacitance measurements show flux h/2e-periodic bimodality with a signal-to-noise ratio of 1 in 3.7 $μ$s at optimal flux values. From the time traces of the quantum capacitance measurements, we extract a dwell time in the two associated states that is longer than 1 ms at in-plane magnetic fields of approximately 2 T. These results are consistent with a measurement of the fermion parity encoded in a pair of Majorana zero modes that are separated by approximately 3 $μ$m and subjected to a low rate of poisoning by non-equilibrium quasiparticles. The large capacitance shift and long poisoning time enable a parity measurement error probability of 1%. △ Less

Submitted 2 April, 2024; v1 submitted 17 January, 2024; originally announced January 2024.

Comments: Added data on a second measurement of device A and a measurement of device B, expanded discussion of a trivial scenario. Refs added, author list updated

Journal ref: Nature 638, 651 (2025)

The Conspiracy Money Machine: Uncovering Telegram's Conspiracy Channels and their Profit Model

Authors: Vincenzo Imperati, Massimo La Morgia, Alessandro Mei, Alberto Maria Mongardini, Francesco Sassi

Abstract: In recent years, major social media platforms have implemented increasingly strict moderation policies, resulting in bans and restrictions on conspiracy theory-related content. To circumvent these restrictions, conspiracy theorists are turning to alternatives, such as Telegram, where they can express and spread their views with fewer limitations. Telegram offers channels, virtual rooms where only… ▽ More In recent years, major social media platforms have implemented increasingly strict moderation policies, resulting in bans and restrictions on conspiracy theory-related content. To circumvent these restrictions, conspiracy theorists are turning to alternatives, such as Telegram, where they can express and spread their views with fewer limitations. Telegram offers channels, virtual rooms where only administrators can broadcast messages, and a more permissive content policy. These features have created the perfect breeding ground for a complex ecosystem of conspiracy channels. In this paper, we illuminate this ecosystem. First, we propose an approach to detect conspiracy channels. Then, we discover that conspiracy channels can be clustered into four distinct communities comprising over 17,000 channels. Finally, we uncover the "Conspiracy Money Machine," revealing how most conspiracy channels actively seek to profit from their subscribers. We find conspiracy theorists leverage e-commerce platforms to sell questionable products or lucratively promote them through affiliate links. Moreover, we observe that conspiracy channels use donation and crowdfunding platforms to raise funds for their campaigns. We determine that this business involves hundreds of thousands of donors and generates a turnover of almost $71 million. △ Less

Submitted 15 September, 2025; v1 submitted 24 October, 2023; originally announced October 2023.

Comments: This paper is included in the Proceedings of the 34th USENIX Security Symposium 2025 (USENIX Security 25), Seattle, WA, USA: https://www.usenix.org/system/files/usenixsecurity25-imperati.pdf

ASSERT: Automated Safety Scenario Red Teaming for Evaluating the Robustness of Large Language Models

Authors: Alex Mei, Sharon Levy, William Yang Wang

Abstract: As large language models are integrated into society, robustness toward a suite of prompts is increasingly important to maintain reliability in a high-variance environment.Robustness evaluations must comprehensively encapsulate the various settings in which a user may invoke an intelligent system. This paper proposes ASSERT, Automated Safety Scenario Red Teaming, consisting of three methods -- sem… ▽ More As large language models are integrated into society, robustness toward a suite of prompts is increasingly important to maintain reliability in a high-variance environment.Robustness evaluations must comprehensively encapsulate the various settings in which a user may invoke an intelligent system. This paper proposes ASSERT, Automated Safety Scenario Red Teaming, consisting of three methods -- semantically aligned augmentation, target bootstrapping, and adversarial knowledge injection. For robust safety evaluation, we apply these methods in the critical domain of AI safety to algorithmically generate a test suite of prompts covering diverse robustness settings -- semantic equivalence, related scenarios, and adversarial. We partition our prompts into four safety domains for a fine-grained analysis of how the domain affects model performance. Despite dedicated safeguards in existing state-of-the-art models, we find statistically significant performance differences of up to 11% in absolute classification accuracy among semantically related scenarios and error rates of up to 19% absolute error in zero-shot adversarial settings, raising concerns for users' physical safety. △ Less

Submitted 11 November, 2023; v1 submitted 14 October, 2023; originally announced October 2023.

Comments: In Findings of the 2023 Conference on Empirical Methods in Natural Language Processing

Let's Think Frame by Frame with VIP: A Video Infilling and Prediction Dataset for Evaluating Video Chain-of-Thought

Authors: Vaishnavi Himakunthala, Andy Ouyang, Daniel Rose, Ryan He, Alex Mei, Yujie Lu, Chinmay Sonar, Michael Saxon, William Yang Wang

Abstract: Despite exciting recent results showing vision-language systems' capacity to reason about images using natural language, their capacity for video reasoning remains under-explored. We motivate framing video reasoning as the sequential understanding of a small number of keyframes, thereby leveraging the power and robustness of vision-language while alleviating the computational complexities of proce… ▽ More Despite exciting recent results showing vision-language systems' capacity to reason about images using natural language, their capacity for video reasoning remains under-explored. We motivate framing video reasoning as the sequential understanding of a small number of keyframes, thereby leveraging the power and robustness of vision-language while alleviating the computational complexities of processing videos. To evaluate this novel application, we introduce VIP, an inference-time challenge dataset designed to explore models' reasoning capabilities through video chain-of-thought. Inspired by visually descriptive scene plays, we propose two formats for keyframe description: unstructured dense captions and structured scene descriptions that identify the focus, action, mood, objects, and setting (FAMOuS) of the keyframe. To evaluate video reasoning, we propose two tasks: Video Infilling and Video Prediction, which test abilities to generate multiple intermediate keyframes and predict future keyframes, respectively. We benchmark GPT-4, GPT-3, and VICUNA on VIP, demonstrate the performance gap in these complex video reasoning tasks, and encourage future work to prioritize language models for efficient and generalized video reasoning. △ Less

Submitted 9 November, 2023; v1 submitted 23 May, 2023; originally announced May 2023.

Comments: Accepted to the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)

Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings

Authors: Daniel Rose, Vaishnavi Himakunthala, Andy Ouyang, Ryan He, Alex Mei, Yujie Lu, Michael Saxon, Chinmay Sonar, Diba Mirza, William Yang Wang

Abstract: Recent advances in large language models elicit reasoning in a chain-of-thought that allows models to decompose problems in a human-like fashion. Though this paradigm improves multi-step reasoning ability in language models, it is limited by being unimodal and applied mainly to question-answering tasks. We claim that incorporating visual augmentation into reasoning is essential, especially for com… ▽ More Recent advances in large language models elicit reasoning in a chain-of-thought that allows models to decompose problems in a human-like fashion. Though this paradigm improves multi-step reasoning ability in language models, it is limited by being unimodal and applied mainly to question-answering tasks. We claim that incorporating visual augmentation into reasoning is essential, especially for complex, imaginative tasks. Consequently, we introduce VCoT, a novel method that leverages chain-of-thought prompting with vision-language grounding to recursively bridge the logical gaps within sequential data. Our method uses visual guidance to generate synthetic multimodal infillings that add consistent and novel information to reduce the logical gaps for downstream tasks that can benefit from temporal reasoning, as well as provide interpretability into models' multi-step reasoning. We apply VCoT to the Visual Storytelling and WikiHow summarization datasets and demonstrate through human evaluation that VCoT offers novel and consistent synthetic data augmentation beating chain-of-thought baselines, which can be used to enhance downstream performance. △ Less

Submitted 22 January, 2024; v1 submitted 3 May, 2023; originally announced May 2023.

A bright megaelectronvolt emission line in $γ$-ray burst GRB 221009A

Authors: Maria Edvige Ravasio, Om Sharan Salafia, Gor Oganesyan, Alessio Mei, Giancarlo Ghirlanda, Stefano Ascenzi, Biswajit Banerjee, Samanta Macera, Marica Branchesi, Peter G. Jonker, Andrew J. Levan, Daniele B. Malesani, Katharine B. Mulrey, Andrea Giuliani, Annalisa Celotti, Gabriele Ghisellini

Abstract: The highly variable and energetic pulsed emission of a long gamma-ray burst (GRB) is thought to originate from local, rapid dissipation of kinetic or magnetic energy within an ultra-relativistic jet launched by a newborn compact object, formed during the collapse of a massive star. The spectra of GRB pulses are best modelled by power-law segments, indicating the dominance of non-thermal radiation… ▽ More The highly variable and energetic pulsed emission of a long gamma-ray burst (GRB) is thought to originate from local, rapid dissipation of kinetic or magnetic energy within an ultra-relativistic jet launched by a newborn compact object, formed during the collapse of a massive star. The spectra of GRB pulses are best modelled by power-law segments, indicating the dominance of non-thermal radiation processes. Spectral lines in the X-ray and soft $γ$-ray regime for the afterglow have been searched for intensively, but never confirmed. No line features ever been identified in the high energy prompt emission. Here we report the discovery of a highly significant ($> 6 σ$) narrow emission feature at around $10$ MeV in the brightest ever GRB 221009A. By modelling its profile with a Gaussian, we find a roughly constant width $σ\sim 1$ MeV and temporal evolution both in energy ($\sim 12$ MeV to $\sim 6$ MeV) and luminosity ($\sim 10^{50}$ erg/s to $\sim 2 \times 10^{49}$ erg/s) over 80 seconds. We interpret this feature as a blue-shifted annihilation line of relatively cold ($k_\mathrm{B}T\ll m_\mathrm{e}c^2$) electron-positron pairs, which could have formed within the jet region where the brightest pulses of the GRB were produced. A detailed understanding of the conditions that can give rise to such a feature could shed light on the so far poorly understood GRB jet properties and energy dissipation mechanism. △ Less

Submitted 28 March, 2023; originally announced March 2023.

Comments: Submitted

Users are the North Star for AI Transparency

Authors: Alex Mei, Michael Saxon, Shiyu Chang, Zachary C. Lipton, William Yang Wang

Abstract: Despite widespread calls for transparent artificial intelligence systems, the term is too overburdened with disparate meanings to express precise policy aims or to orient concrete lines of research. Consequently, stakeholders often talk past each other, with policymakers expressing vague demands and practitioners devising solutions that may not address the underlying concerns. Part of why this hap… ▽ More Despite widespread calls for transparent artificial intelligence systems, the term is too overburdened with disparate meanings to express precise policy aims or to orient concrete lines of research. Consequently, stakeholders often talk past each other, with policymakers expressing vague demands and practitioners devising solutions that may not address the underlying concerns. Part of why this happens is that a clear ideal of AI transparency goes unsaid in this body of work. We explicitly name such a north star -- transparency that is user-centered, user-appropriate, and honest. We conduct a broad literature survey, identifying many clusters of similar conceptions of transparency, tying each back to our north star with analysis of how it furthers or hinders our ideal AI transparency goals. We conclude with a discussion on common threads across all the clusters, to provide clearer common language whereby policymakers, stakeholders, and practitioners can communicate concrete demands and deliver appropriate solutions. We hope for future work on AI transparency that further advances confident, user-beneficial goals and provides clarity to regulators and developers alike. △ Less

Submitted 9 March, 2023; originally announced March 2023.

Comments: 9 pages, 3 tables

TGDataset: Collecting and Exploring the Largest Telegram Channels Dataset

Authors: Massimo La Morgia, Alessandro Mei, Alberto Maria Mongardini

Abstract: Telegram is one of the most popular instant messaging apps in today's digital age. In addition to providing a private messaging service, Telegram, with its channels, represents a valid medium for rapidly broadcasting content to a large audience (COVID-19 announcements), but, unfortunately, also for disseminating radical ideologies and coordinating attacks (Capitol Hill riot). This paper presents t… ▽ More Telegram is one of the most popular instant messaging apps in today's digital age. In addition to providing a private messaging service, Telegram, with its channels, represents a valid medium for rapidly broadcasting content to a large audience (COVID-19 announcements), but, unfortunately, also for disseminating radical ideologies and coordinating attacks (Capitol Hill riot). This paper presents the TGDataset, a new dataset that includes 120,979 Telegram channels and over 400 million messages, making it the largest collection of Telegram channels to the best of our knowledge. After a brief introduction to the data collection process, we analyze the languages spoken within our dataset and the topic covered by English channels. Finally, we discuss some use cases in which our dataset can be extremely useful to understand better the Telegram ecosystem, as well as to study the diffusion of questionable news. In addition to the raw dataset, we released the scripts we used to analyze the dataset and the list of channels belonging to the network of a new conspiracy theory called Sabmyk. △ Less

Submitted 3 March, 2025; v1 submitted 9 March, 2023; originally announced March 2023.

Foveate, Attribute, and Rationalize: Towards Physically Safe and Trustworthy AI

Authors: Alex Mei, Sharon Levy, William Yang Wang

Abstract: Users' physical safety is an increasing concern as the market for intelligent systems continues to grow, where unconstrained systems may recommend users dangerous actions that can lead to serious injury. Covertly unsafe text is an area of particular interest, as such text may arise from everyday scenarios and are challenging to detect as harmful. We propose FARM, a novel framework leveraging exter… ▽ More Users' physical safety is an increasing concern as the market for intelligent systems continues to grow, where unconstrained systems may recommend users dangerous actions that can lead to serious injury. Covertly unsafe text is an area of particular interest, as such text may arise from everyday scenarios and are challenging to detect as harmful. We propose FARM, a novel framework leveraging external knowledge for trustworthy rationale generation in the context of safety. In particular, FARM foveates on missing knowledge to qualify the information required to reason in specific scenarios and retrieves this information with attribution to trustworthy sources. This knowledge is used to both classify the safety of the original text and generate human-interpretable rationales, shedding light on the risk of systems to specific user groups and helping both stakeholders manage the risks of their systems and policymakers to provide concrete safeguards for consumer safety. Our experiments show that FARM obtains state-of-the-art results on the SafeText dataset, showing absolute improvement in safety classification accuracy by 5.9%. △ Less

Submitted 19 May, 2023; v1 submitted 19 December, 2022; originally announced December 2022.

Comments: In Findings of the 2023 Conference of the Association for Computational Linguistics

A Game of NFTs: Characterizing NFT Wash Trading in the Ethereum Blockchain

Authors: Massimo La Morgia, Alessandro Mei, Alberto Maria Mongardini, Eugenio Nerio Nemmi

Abstract: The Non-Fungible Token (NFT) market in the Ethereum blockchain experienced explosive growth in 2021, with a monthly trade volume reaching \… ▽ More The Non-Fungible Token (NFT) market in the Ethereum blockchain experienced explosive growth in 2021, with a monthly trade volume reaching \$6 billion in January 2022. However, concerns have emerged about possible wash trading, a form of market manipulation in which one party repeatedly trades an NFT to inflate its volume artificially. Our research examines the effects of wash trading on the NFT market in Ethereum from the beginning until January 2022, using multiple approaches. We find that wash trading affects 5.66% of all NFT collections, with a total artificial volume of \$3,406,110,774. We look at two ways to profit from wash trading: Artificially increasing the price of the NFT and taking advantage of the token reward systems provided by some marketplaces. Our findings show that exploiting the token reward systems of NFTMs is much more profitable (mean gain of successful operations is \$1.055M on LooksRare), more likely to succeed (more than 80% of operations), and less risky than reselling an NFT at a higher price using wash trading (50% of activities result in a loss). Our research highlights that wash trading is frequent in Ethereum and that NFTMs should implement protective mechanisms to stop such illicit behavior. △ Less

Submitted 2 September, 2024; v1 submitted 2 December, 2022; originally announced December 2022.

Comments: 12 pages, 7 figures, 3 tables

Mitigating Covertly Unsafe Text within Natural Language Systems

Authors: Alex Mei, Anisha Kabir, Sharon Levy, Melanie Subbiah, Emily Allaway, John Judge, Desmond Patton, Bruce Bimber, Kathleen McKeown, William Yang Wang

Abstract: An increasingly prevalent problem for intelligent technologies is text safety, as uncontrolled systems may generate recommendations to their users that lead to injury or life-threatening consequences. However, the degree of explicitness of a generated statement that can cause physical harm varies. In this paper, we distinguish types of text that can lead to physical harm and establish one particul… ▽ More An increasingly prevalent problem for intelligent technologies is text safety, as uncontrolled systems may generate recommendations to their users that lead to injury or life-threatening consequences. However, the degree of explicitness of a generated statement that can cause physical harm varies. In this paper, we distinguish types of text that can lead to physical harm and establish one particularly underexplored category: covertly unsafe text. Then, we further break down this category with respect to the system's information and discuss solutions to mitigate the generation of text in each of these subcategories. Ultimately, our work defines the problem of covertly unsafe language that causes physical harm and argues that this subtle yet dangerous issue needs to be prioritized by stakeholders and regulators. We highlight mitigation strategies to inspire future researchers to tackle this challenging problem and help improve safety within smart systems. △ Less

Submitted 20 March, 2023; v1 submitted 17 October, 2022; originally announced October 2022.

Comments: In Findings of the 2022 Conference on Empirical Methods in Natural Language Processing

Neutrino search from γ-ray bursts during the prompt and X-ray afterglow phases using 10 years of IceCube public data

Authors: Francesco Lucarelli, Gor Oganesyan, Teresa Montaruli, Marica Branchesi, Alessio Mei, Samuele Ronchini, Francesco Brighenti, Biswajit Banerjee

Abstract: Neutrino emission from gamma-ray bursts (GRBs) has been sought for a long time, and stringent limits on the most accredited GRB emission models have been obtained from IceCube. Multi-wavelength GRB observations of the last decades improved our knowledge of the GRB emission parameters, such as the Lorentz factor and the luminosity, which can vary from one GRB to another by several orders of magnitu… ▽ More Neutrino emission from gamma-ray bursts (GRBs) has been sought for a long time, and stringent limits on the most accredited GRB emission models have been obtained from IceCube. Multi-wavelength GRB observations of the last decades improved our knowledge of the GRB emission parameters, such as the Lorentz factor and the luminosity, which can vary from one GRB to another by several orders of magnitude. Empirical correlations among such parameters have been identified during the prompt phase, with direct implications on GRB models. In this work, we use the PSLab open-access code, developed for IceCube data analyses, to search for individual neutrino emission from the prompt and afterglow phases of selected GRBs, and for stacking emission from the ensemble of such GRBs. For the afterglow phase, we focus in particular on GRBs with X-ray flares and plateaus. While past stacking searches assumed the same GRB fluence at Earth, we present a stacking scheme based on physically motivated GRB weights. Moreover, we conceive a new methodology for the prompt phase that uses the empirical correlations to infer the GRB luminosity and Lorentz factor, when redshift measurements are not available. We do not observe any significant neutrino excess. Hence, we set constraints on the GRB neutrino fluxes and on relevant GRB parameters, including the magnetic field in the jet. Notably, the baryon loading is found to be <10 for typical GRB prompts, thus disfavoring a baryonic-dominated origin of the GRB ejecta. △ Less

Submitted 29 August, 2022; originally announced August 2022.

Comments: Submitted for publication to A&A. Comments are welcome

Journal ref: A&A 672, A102 (2023)

Token Spammers, Rug Pulls, and SniperBots: An Analysis of the Ecosystem of Tokens in Ethereum and in the Binance Smart Chain (BNB)

Authors: Federico Cernera, Massimo La Morgia, Alessandro Mei, Francesco Sassi

Abstract: In this work, we perform a longitudinal analysis of the BNB Smart Chain and Ethereum blockchain from their inception to March 2022. We study the ecosystem of the tokens and liquidity pools, highlighting analogies and differences between the two blockchains. We discover that about 60% of tokens are active for less than one day. Moreover, we find that 1% of addresses create an anomalous number of to… ▽ More In this work, we perform a longitudinal analysis of the BNB Smart Chain and Ethereum blockchain from their inception to March 2022. We study the ecosystem of the tokens and liquidity pools, highlighting analogies and differences between the two blockchains. We discover that about 60% of tokens are active for less than one day. Moreover, we find that 1% of addresses create an anomalous number of tokens (between 20% and 25%). We discover that these tokens are used as disposable tokens to perform a particular type of rug pull, which we call 1-day rug pull. We quantify the presence of this operation on both blockchains discovering its prevalence on the BNB Smart Chain. We estimate that 1-day rug pulls generated $240 million in profits. Finally, we present sniper bots, a new kind of trader bot involved in these activities, and we detect their presence and quantify their activity in the rug pull operations. △ Less

Submitted 2 September, 2024; v1 submitted 16 June, 2022; originally announced June 2022.

Comments: This paper is included in the Proceedings of the 32nd USENIX Security Symposium

Report number: 32nd USENIX Security Symposium (USENIX Security 23)

Journal ref: https://www.usenix.org/conference/usenixsecurity23/presentation/cernera ISBN: 978-1-939133-37-3 Year:2023

GeV emission from a compact binary merger

Authors: Alessio Mei, Biswajit Banerjee, Gor Oganesyan, Om Sharan Salafia, Stefano Giarratana, Marica Branchesi, Paolo D'Avanzo, Sergio Campana, Giancarlo Ghirlanda, Samuele Ronchini, Amit Shukla, Pawan Tiwari

Abstract: An energetic $\rm γ$-ray burst (GRB), GRB 211211A, was observed on 2021 December 11 by the Neil Gehrels Swift Observatory. Despite its long duration, typically associated with bursts produced by the collapse of massive stars, the discovery of an optical-infrared kilonova and a quasi-periodic oscillation during a gamma-ray precursor points to a compact object binary merger origin. The complete unde… ▽ More An energetic $\rm γ$-ray burst (GRB), GRB 211211A, was observed on 2021 December 11 by the Neil Gehrels Swift Observatory. Despite its long duration, typically associated with bursts produced by the collapse of massive stars, the discovery of an optical-infrared kilonova and a quasi-periodic oscillation during a gamma-ray precursor points to a compact object binary merger origin. The complete understanding of this nearby ($\sim$ 1 billion light-years) burst will significantly impact our knowledge of GRB progenitors and the physical processes that lead to electromagnetic emission in compact binary mergers. Here, we report the discovery of a significant ($\rm >5 σ$) transient-like emission in the high-energy $\rm γ$-rays (HE; E$>0.1$ GeV) observed by Fermi/LAT starting at $10^3$ s after the burst. After an initial phase with a roughly constant flux ($\rm \sim 5\times 10^{-10}\ erg\ s^{-1}\ cm^{-2}$) lasting $\sim 2\times 10^4$ s, the flux started decreasing and soon went undetected. The multi-wavelength afterglow emission observed at such late times is usually in good agreement with synchrotron emission from a relativistic shock wave that arises as the GRB jet decelerates in the interstellar medium. However, our detailed modelling of a rich dataset comprising public and dedicated multi-wavelength observations demonstrates that GeV emission from GRB 211211A is in excess with respect to the expectation of this scenario. We explore the possibility that the GeV excess is inverse Compton emission due to the interaction of a long-lived, low-power jet with an external source of photons. We discover that the kilonova emission can provide the necessary seed photons for GeV emission in binary neutron star mergers. △ Less

Submitted 17 February, 2025; v1 submitted 17 May, 2022; originally announced May 2022.

Constrains on the physics of the prompt emission from a distant and energetic gamma-ray burst GRB 220101A

Authors: Alessio Mei, Gor Oganesyan, Anastasia Tsvetkova, Maria Edvige Ravasio, Biswajit Banerjee, Francesco Brighenti, Samuele Ronchini, Marica Branchesi, Dmitry Frederiks

Abstract: The emission region of $\rm γ$-ray bursts (GRBs) is poorly constrained. The uncertainty on the size of the dissipation site spans over 4 orders of magnitude ($\rm 10^{12}-10^{17}$ cm) depending on the unknown energy composition of the GRB jets. The joint multi-band analysis from soft X-rays to high energies (up to $\rm \sim$ 1 GeV) of one of the most energetic and distant GRB 220101A (z = 4.618) a… ▽ More The emission region of $\rm γ$-ray bursts (GRBs) is poorly constrained. The uncertainty on the size of the dissipation site spans over 4 orders of magnitude ($\rm 10^{12}-10^{17}$ cm) depending on the unknown energy composition of the GRB jets. The joint multi-band analysis from soft X-rays to high energies (up to $\rm \sim$ 1 GeV) of one of the most energetic and distant GRB 220101A (z = 4.618) allows us for an accurate distinction between prompt and early afterglow emissions. The enormous amount of energy released by GRB 220101A ($\rm E_{iso} \approx 3 \times10^{54}$ erg) and the spectral cutoff at $\rm E_{cutoff} = 85_{-26}^{+16}$ MeV observed in the prompt emission spectrum constrains the parameter space of GRB dissipation site. We put stringent constraints on the prompt emission site, requiring $\rm 700<Γ_0<1160 $ and $\rm R_γ\sim 4.5 \times 10^{13}$ cm. Our findings further highlights the difficulty of finding a simple self consistent picture in the electron-synchrotron scenario, favoring instead a proton-synchrotron model, which is also consistent with the observed spectral shape. Deeper measurements of the time variability of GRBs together with accurate high-energy observations (MeV-GeV) would unveil the nature of the prompt emission. △ Less

Submitted 22 November, 2022; v1 submitted 9 March, 2022; originally announced March 2022.

Comments: 16 pages, 7 figures. Accepted for ApJ publication

Nonvolatile Electric-Field Control of Inversion Symmetry

Authors: Lucas Caretta, Yu-Tsun Shao, Jia Yu, Antonio B. Mei, Bastien F. Grosso, Cheng Dai, Piush Behera, Daehun Lee, Margaret McCarter, Eric Parsonnet, Harikrishnan K. P., Fei Xue, Ed Barnard, Steffen Ganschow, Archana Raja, Lane W. Martin, Long-Qing Chen, Manfred Fiebig, Keji Lai, Nicola A. Spaldin, David A. Muller, Darrell G. Schlom, Ramamoorthy Ramesh

Abstract: In condensed-matter systems, competition between ground states at phase boundaries can lead to significant changes in material properties under external stimuli, particularly when these ground states have different crystal symmetries. A key scientific and technological challenge is to stabilize and control coexistence of symmetry-distinct phases with external stimuli. Using BiFeO3 (BFO) layers con… ▽ More In condensed-matter systems, competition between ground states at phase boundaries can lead to significant changes in material properties under external stimuli, particularly when these ground states have different crystal symmetries. A key scientific and technological challenge is to stabilize and control coexistence of symmetry-distinct phases with external stimuli. Using BiFeO3 (BFO) layers confined between layers of the dielectric TbScO3 as a model system, we stabilize the mixed-phase coexistence of centrosymmetric and non-centrosymmetric BFO phases with antipolar, insulating and polar, semiconducting behavior, respectively at room temperature. Application of in-plane electric (polar) fields can both remove and introduce centrosymmetry from the system resulting in reversible, nonvolatile interconversion between the two phases. This interconversion between the centrosymmetric insulating and non-centrosymmetric semiconducting phases coincides with simultaneous changes in the non-linear optical response of over three orders of magnitude, a change in resistivity of over five orders of magnitude, and a change in the polar order. Our work establishes a materials platform allowing for novel cross-functional devices which take advantage of changes in optical, electrical, and ferroic responses. △ Less

Submitted 2 January, 2022; originally announced January 2022.

Comments: L Caretta and Y-T Shao contributed equally. 64 pages, 4 figures, 25 supplemental figures, 1 supplemental table

Uncovering the Dark Side of Telegram: Fakes, Clones, Scams, and Conspiracy Movements

Authors: Massimo La Morgia, Alessandro Mei, Alberto Maria Mongardini, Jie Wu

Abstract: Telegram is one of the most used instant messaging apps worldwide. Some of its success lies in providing high privacy protection and social network features like the channels -- virtual rooms in which only the admins can post and broadcast messages to all its subscribers. However, these same features contributed to the emergence of borderline activities and, as is common with Online Social Network… ▽ More Telegram is one of the most used instant messaging apps worldwide. Some of its success lies in providing high privacy protection and social network features like the channels -- virtual rooms in which only the admins can post and broadcast messages to all its subscribers. However, these same features contributed to the emergence of borderline activities and, as is common with Online Social Networks, the heavy presence of fake accounts. Telegram started to address these issues by introducing the verified and scam marks for the channels. Unfortunately, the problem is far from being solved. In this work, we perform a large-scale analysis of Telegram by collecting 35,382 different channels and over 130,000,000 messages. We study the channels that Telegram marks as verified or scam, highlighting analogies and differences. Then, we move to the unmarked channels. Here, we find some of the infamous activities also present on privacy-preserving services of the Dark Web, such as carding, sharing of illegal adult and copyright protected content. In addition, we identify and analyze two other types of channels: the clones and the fakes. Clones are channels that publish the exact content of another channel to gain subscribers and promote services. Instead, fakes are channels that attempt to impersonate celebrities or well-known services. Fakes are hard to identify even by the most advanced users. To detect the fake channels automatically, we propose a machine learning model that is able to identify them with an accuracy of 86%. Lastly, we study Sabmyk, a conspiracy theory that exploited fakes and clones to spread quickly on the platform reaching over 1,000,000 users. △ Less

Submitted 3 March, 2025; v1 submitted 26 November, 2021; originally announced November 2021.

Comments: 12 pages, 6 figures, and 3 tables

MSC Class: K.4.2

XMM-Newton spectrum of the radio-loud quasar 3C 215: slim accretion disk or SMBH binary?

Authors: Alessio Mei, Francesco Tombesi

Abstract: We want to explore the geometrical structure and mutual interactions of the innermost components of the broad line radio galaxy (BLRG) 3C 215, with particular interest in the accretion and ejection mechanisms involving the central supermassive black hole (SMBH). We compare these observational features with the ones of the RQ Seyfert 1 galaxies. Investigating their differences it is possible to und… ▽ More We want to explore the geometrical structure and mutual interactions of the innermost components of the broad line radio galaxy (BLRG) 3C 215, with particular interest in the accretion and ejection mechanisms involving the central supermassive black hole (SMBH). We compare these observational features with the ones of the RQ Seyfert 1 galaxies. Investigating their differences it is possible to understand more about the jet launching mechanisms, and why this phenomenon is efficient only in a small fraction of all the AGNs. Using high quality data from a $\sim60$ ks observation with XMM-Newton, we carried out a detailed X-ray spectral analysis of 3C 215 in the broad energy range $0.5-10$ keV. We modeled the spectrum with an absorbed double power-law model for the primary continuum, reprocessed by reflection from ionized and cold neutral material and modified by relativistic blurring. We also compared our results with the ones obtained with previous multi-wavelength observations. We obtain a primary continuum photon index from the corona $Γ_1=1.97\pm0.06$ and evidence of a jet contribution, modeled as a power law with photon index $Γ_2\simeq1.29$. The reflector, possibly the accretion disk and portions of the broad-line region (BLR), is ionized ($\logξ=2.31_{-0.27}^{+0.37}\ \mathrm{erg\ s^{-1}\ cm}$) and relatively distant from the SMBH ($R_{in}>38\ R_g$), where $R_g=GM_{BH}/c^2$ is the gravitational radius. The obscuring torus seems patchy, dust-poor and inefficient, while the jet emission shows a twisted and knotted geometry. We propose three scenarios in order to describe these characteristics: 1.) ADAF state in the inner disk; 2.) Slim accretion disk; 3.) sub-pc SMBH binary system (SMBHB). △ Less

Submitted 30 July, 2021; originally announced July 2021.

Comments: 11 pages, 4 figures. Accepted for publication in A&A

Journal ref: A&A 653, A100 (2021)

The Doge of Wall Street: Analysis and Detection of Pump and Dump Cryptocurrency Manipulations

Authors: Massimo La Morgia, Alessandro Mei, Francesco Sassi, Julinda Stefa

Abstract: Cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these assets, and nowadays, cryptocurrency exchanges process transactions for over 100 billion US dollars per month. Despite this, many cryptocurrencies have low liquidity and are highly prone to market manipulation. This paper performs an in-depth analysis of two market manipulations organized by… ▽ More Cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these assets, and nowadays, cryptocurrency exchanges process transactions for over 100 billion US dollars per month. Despite this, many cryptocurrencies have low liquidity and are highly prone to market manipulation. This paper performs an in-depth analysis of two market manipulations organized by communities over the Internet: The pump and dump and the crowd pump. The pump and dump scheme is a fraud as old as the stock market. Now, it got new vitality in the loosely regulated market of cryptocurrencies. Groups of highly coordinated people systematically arrange this scam, usually on Telegram and Discord. We monitored these groups for more than 3 years detecting around 900 individual events. We report on three case studies related to pump and dump groups. We leverage our unique dataset of the verified pump and dumps to build a machine learning model able to detect a pump and dump in 25 seconds from the moment it starts, achieving the results of 94.5% of F1-score. Then, we move on to the crowd pump, a new phenomenon that hit the news in the first months of 2021, when a Reddit community inflates the price of the GameStop stocks (GME) by over 1,900% on Wall Street, the world's largest stock exchange. Later, other Reddit communities replicate the operation on the cryptocurrency markets. The targets were DogeCoin (DOGE) and Ripple (XRP). We reconstruct how these operations developed and discuss differences and analogies with the standard pump and dump. We believe this study helps understand a widespread phenomenon affecting cryptocurrency markets. The detection algorithms we develop effectively detect these events in real-time and help investors stay out of the market when these frauds are in action. △ Less

Submitted 2 September, 2024; v1 submitted 3 May, 2021; originally announced May 2021.

Comments: Extended journal extension of arXiv:2005.06610

Journal ref: ACM Transactions on Internet Technology 23, 1, Article 11 (February 2023), 28 pages

Optimization of Quantum-dot Qubit Fabrication via Machine Learning

Authors: Antonio B. Mei, Ivan Milosavljevic, Amanda L. Simpson, Valerie A. Smetanka, Colin P. Feeney, Shay M. Seguin, Sieu D. Ha, Wonill Ha, Matthew D. Reed

Abstract: Precise nanofabrication represents a critical challenge to developing semiconductor quantum-dot qubits for practical quantum computation. Here, we design and train a convolutional neural network to interpret in-line scanning electron micrographs and quantify qualitative features affecting device functionality. The high-throughput strategy is exemplified by optimizing a model lithographic process w… ▽ More Precise nanofabrication represents a critical challenge to developing semiconductor quantum-dot qubits for practical quantum computation. Here, we design and train a convolutional neural network to interpret in-line scanning electron micrographs and quantify qualitative features affecting device functionality. The high-throughput strategy is exemplified by optimizing a model lithographic process within a five-dimensional design space and by demonstrating a new approach to address lithographic proximity effects. The present results emphasize the benefits of machine learning for developing robust processes, shortening development cycles, and enforcing quality control during qubit fabrication. △ Less

Submitted 15 December, 2020; originally announced December 2020.

Journal ref: Appl. Phys. Lett. 118, 204001 (2021)

Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations

Authors: Massimo La Morgia, Alessandro Mei, Francesco Sassi, Julinda Stefa

Abstract: In the last years, cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these securities and nowadays cryptocurrency exchanges process transactions for over 100 billion US dollars per month. However, many cryptocurrencies have low liquidity and therefore they are highly prone to market manipulation schemes. In this paper, we perform an in-depth analy… ▽ More In the last years, cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these securities and nowadays cryptocurrency exchanges process transactions for over 100 billion US dollars per month. However, many cryptocurrencies have low liquidity and therefore they are highly prone to market manipulation schemes. In this paper, we perform an in-depth analysis of pump and dump schemes organized by communities over the Internet. We observe how these communities are organized and how they carry out the fraud. Then, we report on two case studies related to pump and dump groups. Lastly, we introduce an approach to detect the fraud in real time that outperforms the current state of the art, so to help investors stay out of the market when a pump and dump scheme is in action. △ Less

Submitted 2 September, 2024; v1 submitted 4 May, 2020; originally announced May 2020.

Comments: Accepted for publication at The 29th International Conference on Computer Communications and Networks (ICCCN 2020)

GDPR: When the Right to Access Personal Data Becomes a Threat

Authors: Luca Bufalieri, Massimo La Morgia, Alessandro Mei, Julinda Stefa

Abstract: After one year since the entry into force of the GDPR, all web sites and data controllers have updated their procedures to store users' data. The GDPR does not only cover how and what data should be saved by the service providers, but it also guarantees an easy way to know what data are collected and the freedom to export them. In this paper, we carry out a comprehensive study on the right to ac… ▽ More After one year since the entry into force of the GDPR, all web sites and data controllers have updated their procedures to store users' data. The GDPR does not only cover how and what data should be saved by the service providers, but it also guarantees an easy way to know what data are collected and the freedom to export them. In this paper, we carry out a comprehensive study on the right to access data provided by Article 15 of the GDPR. We examined more than 300 data controllers, performing for each of them a request to access personal data. We found that almost each data controller has a slightly different procedure to fulfill the request and several ways to provide data back to the user, from a structured file like CSV to a screenshot of the monitor. We measure the time needed to complete the access data request and the completeness of the information provided. After this phase of data gathering, we analyze the authentication process followed by the data controllers to establish the identity of the requester. We find that 50.4\% of the data controllers that handled the request, even if they store the data in compliance with the GDPR, have flaws in the procedure of identifying the users or in the phase of sending the data, exposing the users to new threats. With the undesired and surprising result that the GDPR, in its present deployment, has actually decreased the privacy of the users of web services. △ Less

Submitted 4 May, 2020; originally announced May 2020.

Comments: Accepted for publication at IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS) 2020

Adaptive hard and tough mechanical response in single-crystal B1 VNx ceramics via control of anion vacancies

Authors: A. B. Mei, H. Kindlund, E. Broitman, L. Hultman, I. Petrov, J. E. Greene, D. G. Sangiovanni

Abstract: High hardness and toughness are generally considered mutually exclusive properties for single-crystal ceramics. Combining experiments and ab initio molecular dynamics (AIMD) atomistic simulations at room temperature, we demonstrate that both the hardness and toughness of single-crystal NaCl-structure VNx/MgO(001) thin films are simultaneously enhanced through the incorporation of anion vacancies.… ▽ More High hardness and toughness are generally considered mutually exclusive properties for single-crystal ceramics. Combining experiments and ab initio molecular dynamics (AIMD) atomistic simulations at room temperature, we demonstrate that both the hardness and toughness of single-crystal NaCl-structure VNx/MgO(001) thin films are simultaneously enhanced through the incorporation of anion vacancies. Nanoindentation results show that VN0.8, here considered as representative understoichiometric VNx system, is ~20% harder, as well as more resistant to fracture than stoichiometric VN samples. AIMD modeling of VN and VN0.8 supercells subjected to [001] and [110] elongation reveal that the tensile strengths of the two materials are similar. Nevertheless, while the stoichiometric VN phase systematically cleaves in a brittle manner at tensile yield points, the understoichiometric compound activates transformation-toughening mechanisms that dissipate accumulated stresses. AIMD simulations also show that VN0.8 exhibits an initially greater resistance to both {110}<1-10> and {111}<1-10> shear deformation than VN. However, for progressively increasing shear strains, the VN0.8 mechanical behavior gradually evolves from harder to more ductile than VN. The transition is mediated by anion vacancies, which facilitate {110}<1-10> and {111}<1-10> lattice slip by reducing activation shear stresses by as much as 35%. Electronic-structure analyses show that the two-regime hard/tough mechanical response of VN0.8 primarily stems from its intrinsic ability to transfer d electrons between 2nd-neighbor and 4th-neighbor (i.e., across vacancy sites) V-V metallic states. Our work offers a route for electronic-structure design of hard materials in which a plastic mechanical response is triggered with loading. △ Less

Submitted 21 March, 2020; v1 submitted 24 January, 2020; originally announced January 2020.

Spin-Orbit-Torque Field-Effect Transistor (SOTFET): Proposal for a New Magnetoelectric Memory

Authors: Xiang Li, Phillip Dang, Joseph Casamento, Zexuan Zhang, Olalekan Afuye, Antonio B. Mei, Alyssa B. Apsel, Darrell G. Schlom, Debdeep Jena, Daniel C. Ralph, Huili Grace Xing

Abstract: Spin-based memories are attractive for their non-volatility and high durability but provide modest resistance changes, whereas semiconductor logic transistors are capable of large resistance changes, but lack memory function with high durability. The recent availability of multiferroic materials provides an opportunity to directly couple the change in spin states of a magnetic memory to a charge c… ▽ More Spin-based memories are attractive for their non-volatility and high durability but provide modest resistance changes, whereas semiconductor logic transistors are capable of large resistance changes, but lack memory function with high durability. The recent availability of multiferroic materials provides an opportunity to directly couple the change in spin states of a magnetic memory to a charge change in a semiconductor transistor. In this work, we propose and analyze the spin-orbit torque field-effect transistor (SOTFET), a device with the potential to significantly boost the energy efficiency of spin-based memories, and to simultaneously offer a palette of new functionalities. △ Less

Submitted 31 March, 2020; v1 submitted 17 September, 2019; originally announced September 2019.

Imaging uncompensated moments and exchange-biased emergent ferromagnetism in FeRh thin films

Authors: Isaiah Gray, Gregory M. Stiehl, John T. Heron, Antonio B. Mei, Darrell G. Schlom, Ramamoorthy Ramesh, Daniel C. Ralph, Gregory D. Fuchs

Abstract: Uncompensated moments in antiferromagnets are responsible for exchange bias in antiferromagnet/ferromagnet heterostructures; however, they are difficult to directly detect because any signal they contribute is typically overwhelmed by the ferromagnetic layer. We use magneto-thermal microscopy to image uncompensated moments in thin films of FeRh, a room-temperature antiferromagnet that exhibits a 1… ▽ More Uncompensated moments in antiferromagnets are responsible for exchange bias in antiferromagnet/ferromagnet heterostructures; however, they are difficult to directly detect because any signal they contribute is typically overwhelmed by the ferromagnetic layer. We use magneto-thermal microscopy to image uncompensated moments in thin films of FeRh, a room-temperature antiferromagnet that exhibits a 1st-order phase transition to a ferromagnetic state near 100~$^\circ$C. FeRh provides the unique opportunity to study both uncompensated moments in the antiferromagnetic phase and the interaction of uncompensated moments with emergent ferromagnetism within a relatively broad (10-15~$^\circ$C) temperature range near $T_C$. In the AF phase below $T_C$, we image both pinned UMs, which cause local vertical exchange bias, and unpinned UMs, which exhibit an enhanced coercive field that reflects exchange-coupling to the AF bulk. Near $T_C$, where AF and FM order coexist, we find that the emergent FM order is exchange-coupled to the bulk Néel order. This exchange coupling leads to the nucleation of unusual configurations in which different FM domains are pinned parallel, antiparallel, and perpendicular to the applied magnetic field before suddenly collapsing into a state uniformly parallel to the field. △ Less

Submitted 17 June, 2019; originally announced June 2019.

Comments: 29 pages and 16 figures with appendix

Journal ref: Phys. Rev. Materials 3, 124407 (2019)

Local Photothermal Control of Phase Transitions for On-demand Room-temperature Rewritable Magnetic Patterning

Authors: Antonio B. Mei, Isaiah Gray, Yongjian Tang, Jurgen Schubert, Don Werder, Jason Bartell, Daniel C. Ralph, Gregory D. Fuchs, Darrell G. Schlom

Abstract: The ability to make controlled patterns of magnetic structures within a nonmagnetic background is essential for several types of existing and proposed technologies. Such patterns provide the foundation of magnetic memory and logic devices, allow the creation of artificial spin-ice lattices and enable the study of magnon propagation. Here, we report a novel approach for magnetic patterning that all… ▽ More The ability to make controlled patterns of magnetic structures within a nonmagnetic background is essential for several types of existing and proposed technologies. Such patterns provide the foundation of magnetic memory and logic devices, allow the creation of artificial spin-ice lattices and enable the study of magnon propagation. Here, we report a novel approach for magnetic patterning that allows repeated creation and erasure of arbitrary shapes of thin-film ferromagnetic structures. This strategy is enabled by epitaxial Fe$_{0.52}$Rh$_{0.48}$ thin films designed so that both ferromagnetic and antiferromagnetic phases are bistable at room temperature. Starting with the film in a uniform antiferromagnetic state, we demonstrate the ability to write arbitrary patterns of the ferromagnetic phase by local heating with a focused laser. If desired, the results can then be erased by cooling with a thermoelectric cooler and the material repeatedly re-patterned. △ Less

Submitted 17 June, 2019; originally announced June 2019.

Comments: 3 figures, 5 pages

Scan-and-Pay on Android is Dangerous

Authors: Enis Ulqinaku, Julinda Stefa, Alessandro Mei

Abstract: Mobile payments have increased significantly in the recent years and one-to-one money transfers are offered by a wide variety of smartphone applications. These applications usually support scan-and-pay -- a technique that allows a payer to easily scan the destination address of the payment directly from the payee's smartphone screen. This technique is pervasive because it does not require any part… ▽ More Mobile payments have increased significantly in the recent years and one-to-one money transfers are offered by a wide variety of smartphone applications. These applications usually support scan-and-pay -- a technique that allows a payer to easily scan the destination address of the payment directly from the payee's smartphone screen. This technique is pervasive because it does not require any particular hardware, only the camera, which is present on all modern smartphones. However, in this work we show that a malicious application can exploit the overlay feature on Android to compromise the integrity of transactions that make use of the scan-and-pay technique. We implement Malview, a proof-of-concept malicious application that runs in the background on the payee's smartphone and show that it succeeds in redirecting payments to a malicious wallet. We analyze the weaknesses of the current defense mechanisms and discuss possible countermeasures against the attack. △ Less

Submitted 24 May, 2019; originally announced May 2019.

Comments: Published in Infocom MobiSec Workshop 2019, Paris, France