arXiv subjects
Publications and source records attributed to Francesco Romeo.
We compute the diagonal $F$-threshold of binomial edge ideals associated to graphs in the case of cycles, cycles with whiskers, bipartite graphs, and block graphs. Moreover, we provide general bounds for any graph.
The Fast Beam Condition Monitor (BCM1F) has been used at the CMS Experiment since the first LHC circulating beams in 2008. Originally meant as a beam-induced background monitor for fast beam losses detection, it showed a potential also for luminosity measurements in 2012 running, and has been used for luminosity measurements since the beginning of Run 2 data taking in 2015 as a part of the Beam Radiation, Instrumentation and Luminosity (BRIL) system. Over the years, the system has undergone various upgrades to the sensors, the front-end and back-end electronics, providing improvements in the precision of the measurements, that remain valid in the higher pileup conditions of LHC Run 3 (2022-2026). Based on the experience of all BCM1F Run 2 upgrades, the detector was completely rebuilt prior to LHC Run 3 using AC-coupled silicon-pad diodes and active cooling. This latest detector version exhibits excellent linearity with instantaneous luminosity and achieves nanosecond-level timing precision, enabling improved systematic corrections for luminosity and background measurements. This paper presents a detailed overview of the detector system for LHC Run 3, including the selection and qualification of sensors as well as a summary of the readout system. It also outlines the processing and calibration strategy for luminosity data, discussing operational hurdles and comparing BCM1F measurements to other CMS luminosity measurements to assess the system's performance as a luminometer. Lastly, the implications for the design of a future luminosity detector to be used in the envisioned HL-LHC upgrade are discussed.
We introduce Extreme Quantum Cognition Machines, a class of quantum learning architectures for deliberative decision making that is tolerant to noisy and contradictory training data. Inspired by the quantum cognition paradigm, Extreme Quantum Cognition Machines are closely related to quantum extreme learning and quantum reservoir computing, where fixed quantum dynamics generates a nonlinear feature map and learning is confined to a linear readout. A dynamical attention mechanism, implemented through an input-dependent interaction term in the Hamiltonian, modulates the quantum evolution and biases the resulting feature embedding toward task-relevant correlations. The approach is validated on linguistic classification tasks, which serve as paradigmatic examples of deliberative inference. Hardware-compatible quantum implementations of the proposed framework are discussed, together with potential applications in symbolic inference, sequence analysis, anomaly detection, and automatic diagnosis, with direct relevance to domains such as biology, forensics, and cybersecurity.
We compute the diagonal F-thresholds of determinantal hypersurfaces arising from a generic matrix and from a generic symmetric matrix, as well as of the Pfaffian hypersurface arising from a generic skew-symmetric matrix of even size. The main ingredient is a cohomology vanishing theorem for certain line bundles on flag varieties in characteristic $p$. In the cases of the generic matrix and the generic skew-symmetric matrix, we show that the diagonal F-threshold attains its minimal possible value, namely the negative of the a-invariant. The symmetric case is more subtle and relies in addition on a polynomiality result for representations afforded by cohomology, building on work of the second author with VandeBogert.
We study spin-resolved transport in a ballistic quantum dot with Rashba spin-orbit coupling, focusing on charge-to-spin conversion and spin Hall effect. In the regime where the dot size is comparable to the Fermi wavelength, we identify a clear crossover from weak localization to weak antilocalization as the Rashba coupling increases. This transition is accompanied by gate-tunable spin currents of Edelstein and spin Hall type, whose behavior reflects the underlying electron wavefunction interference. Notably, the Edelstein current shows an inflection point at the critical Rashba strength, signaling the crossover from weak localization to weak antilocalization. In the presence of an in-plane magnetic field we also report a transition in angular periodicity of the magnetoresistance -- from $\pi$ to $2\pi$ -- arising from the interplay between spin-orbit interaction and Zeeman coupling. These results establish a direct link between quantum coherence, charge-to-spin conversion, and geometric confinement in mesoscopic systems.
In altermagnets, time-reversal symmetry breaking spin-polarizes electronic states, while total magnetization remains zero. In addition, at altermagnetic surfaces Rashba-spin orbit coupling is activated due to broken inversion symmetry, introducing a competing spin-momentum locking interaction. Here we show that their interplay leads to the formation of complex, chiral spin textures that offer novel, non-linear spin-to-charge conversion properties. Whereas altermagnetic order suppresses the canonical linear in-plane Rashba-Edelstein response, we establish the presence of an \textit{anomalous} transversal Edelstein effect for planar applied electric and magnetic field, or alternatively, an in-plane magnetization. Additionally, we predict a purely electric-field-driven non-linear out-of-plane magnetization. We compute the anomalous response within a general altermagnet $d$-wave model, with parameters extracted from the ab-initio electronic structure of an altermagnetic bilayer. Our results suggest altermagnetic surfaces as a promising platform for unconventional spintronic functionalities.
We propose a new strategy to probe heavy neutrinos with non-universal fermion couplings at the Large Hadron Collider (LHC) using a novel production mechanism and machine-learning algorithms. Focusing on proton--proton collisions at $\sqrt{s} = 13.6~\mathrm{TeV}$, we investigate final states containing a charged lepton, missing transverse energy, and two jets. For heavy neutrino masses below $\mathcal{O}(1~\mathrm{TeV})$, production is dominated by the $s$ channel process. At higher masses, vector boson fusion becomes the dominant production mechanism, with cross sections that decrease slowly as the heavy neutrino mass increases. We simulate both signal and Standard Model background events and employ gradient-boosted decision trees to optimize event classification. Assuming an integrated luminosity of $3000~\mathrm{fb^{-1}}$, expected for the high-luminosity, and considering realistic statistical and systematic uncertainties, we find that heavy neutrinos in the mass range $50~\mathrm{GeV}$--$10~\mathrm{TeV}$ can be probed with sensitivity to the mixing parameter $|V_{\ell N}|^2$ spanning from $\mathcal{O}(10^{-5})$ to 1. This approach enhances the discovery potential for heavy neutrinos and provides a complementary pathway to existing search strategies.
We investigate the inverse Edelstein effect in a non-homogeneous system consisting of a ferromagnetic layer coupled to a Rashba two-dimensional electron gas. Within a semiclassical Boltzmann framework, we derive analytical expressions for the charge and spin currents and analyze their dependence on key parameters such as the chemical potential and the Rashba coupling strength. We show how interfacial exchange and spin-orbit interactions jointly control the efficiency of spin-to-charge conversion, leading to distinct regimes characterized by qualitatively different transport responses. A central outcome of our work is the availability of closed-form analytical results, which provide direct physical insight and enable a transparent and quantitative benchmarking with experiments on complex oxide interfaces, such as LaAlO$_3$/SrTiO$_3$.
In a recent work [B. J. P. Jones and J. A. Formaggio, Phys. Rev. Lett. 135, 111801 (2025)], the possibility of superradiant neutrino emission from atomic condensates has been theoretically proposed. Subsequent analysis by Y. K. Lu, H. Lin, and W. Ketterle [arXiv:2510.21705] questioned this scenario, emphasizing the limiting role of the fermionic nature of the decayed atoms. In this study, we revisit the problem and discuss under which conditions collective emission phenomena might still emerge in cold-atom systems.
Policy as Code (PaC) is a paradigm that encodes security and compliance policies into machine-readable formats, enabling automated enforcement in Infrastructure as Code (IaC) environments. However, its adoption is hindered by the complexity of policy languages and the risk of misconfigurations. In this work, we present ARPaCCino, an agentic system that combines Large Language Models (LLMs), Retrieval-Augmented-Generation (RAG), and tool-based validation to automate the generation and verification of PaC rules. Given natural language descriptions of the desired policies, ARPaCCino generates formal Rego rules, assesses IaC compliance, and iteratively refines the IaC configurations to ensure conformance. Thanks to its modular agentic architecture and integration with external tools and knowledge bases, ARPaCCino supports policy validation across a wide range of technologies, including niche or emerging IaC frameworks. Experimental evaluation involving a Terraform-based case study demonstrates ARPaCCino's effectiveness in generating syntactically and semantically correct policies, identifying non-compliant infrastructures, and applying corrective modifications, even when using smaller, open-weight LLMs. Our results highlight the potential of agentic RAG architectures to enhance the automation, reliability, and accessibility of PaC workflows.
The interplay between spin and charge degrees of freedom in low-dimensional systems is a cornerstone of modern spintronics, where achieving all-electrical control of spin currents is a major goal. Spin-orbit interactions provide a promising mechanism for such control, yet understanding how spin and charge transport emerge from microscopic principles remains a fundamental challenge. Here we develop a spin-dependent scattering matrix approach to describe spin and charge transport in a multiterminal system in the presence of Rashba spin-orbit interaction. Our framework generalizes the Büttiker formalism by offering explicit real-space expressions for spin and charge current densities, along with the corresponding linear response function. It simultaneously captures the effects of quantum confinement, the orbital response to external magnetic fields, and the intrinsic (geometric) properties of the electronic bands, offering a comprehensive description of the spin-charge interconversion mechanisms at play in a Hall bar, in agreement with experiments.
The characterization and the experimental measurement of the Berry curvature in solids have become an increasingly relevant task in condensed matter physics. We present the theoretical prediction of a gate tunable anomalous Hall effect (AHE) in a non magnetic oxide interface as a hallmark of a non-trivial Berry curvature. The observed AHE at low-temperatures in the presence of a planar magnetic field comes from a multiband low-energy model with a generalized Rashba interaction that supports characteristic out-of-plane spin and orbital textures. We also discuss strategies for reconstructing the Berry curvature from the AHE non-linearities in (111) SrTiO$_3$ heterostructure interfaces.
The security of Industrial Control Systems (ICSs) is critical to ensuring the safety of industrial processes and personnel. The rapid adoption of Industrial Internet of Things (IIoT) technologies has expanded system functionality but also increased the attack surface, exposing ICSs to a growing range of cyber threats. Honeypots provide a means to detect and analyze such threats by emulating target systems and capturing attacker behavior. However, traditional ICS honeypots, often limited to software-based simulations of a single Programmable Logic Controller (PLC), lack the realism required to engage sophisticated adversaries. In this work, we introduce a modular honeynet framework named ICSLure. The framework has been designed to emulate realistic ICS environments. Our approach integrates physical PLCs interacting with live data sources via industrial protocols such as Modbus and Profinet RTU, along with virtualized network components including routers, switches, and Remote Terminal Units (RTUs). The system incorporates comprehensive monitoring capabilities to collect detailed logs of attacker interactions. We demonstrate that our framework enables coherent and high-fidelity emulation of real-world industrial plants. This high-interaction environment significantly enhances the quality of threat data collected and supports advanced analysis of ICS-specific attack strategies, contributing to more effective detection and mitigation techniques.
The rapid adoption of Large Language Model (LLM) agents and multi-agent systems enables remarkable capabilities in natural language processing and generation. However, these systems introduce security vulnerabilities that extend beyond traditional content generation to system-level compromises. This paper presents a comprehensive evaluation of the LLMs security used as reasoning engines within autonomous agents, highlighting how they can be exploited as attack vectors capable of achieving computer takeovers. We focus on how different attack surfaces and trust boundaries can be leveraged to orchestrate such takeovers. We demonstrate that adversaries can effectively coerce popular LLMs into autonomously installing and executing malware on victim machines. Our evaluation of 18 state-of-the-art LLMs reveals that 94.4% of models succumb to Direct Prompt Injection, and 83.3% are vulnerable to the more stealthy and evasive RAG Backdoor Attack. Notably, we tested trust boundaries within multi-agent systems, where LLM agents interact and influence each other, and we revealed that LLMs which successfully resist direct injection or RAG backdoor attacks will execute identical payloads when requested by peer agents. We found that 100.0% of tested LLMs can be compromised through Inter-Agent Trust Exploitation attacks, and that every model exhibits context-dependent security behaviors that create exploitable blind spots.
We prove that wheels and block graphs have sequentially Cohen-Macaulay binomial edge ideals. Moreover, we provide a construction of new families of sequentially Cohen-Macaulay graphs by cones.
The growing and evolving landscape of cybersecurity threats necessitates the development of supporting tools and platforms that allow for the creation of realistic IT environments operating within virtual, controlled settings as Cyber Ranges (CRs). CRs can be exploited for analyzing vulnerabilities and experimenting with the effectiveness of devised countermeasures, as well as serving as training environments for building cyber security skills and abilities for IT operators. This paper proposes ARCeR as an innovative solution for the automatic generation and deployment of CRs, starting from user-provided descriptions in a natural language. ARCeR relies on the Agentic RAG paradigm, which allows it to fully exploit state-of-art AI technologies. Experimental results show that ARCeR is able to successfully process prompts even in cases that LLMs or basic RAG systems are not able to cope with. Furthermore, ARCeR is able to target any CR framework provided that specific knowledge is made available to it.
We investigate spin-to-charge conversion via the Edelstein effect in a 2D Rashba electron gas using the semiclassical Boltzmann approach. We analyze the magnetization arising from the direct Edelstein effect, taking into account an anisotropic Rashba model. We study how this effect depends on the effective masses and Rashba spin--orbit coupling parameters, extracting analytical expressions for the high electronic density regime. {Indeed, it is possible to manipulate the anisotropy introduced into the system through these parameters to achieve a boost in the Edelstein response compared to the isotropic Rashba model.} We also discuss the theoretical framework to study the inverse Edelstein effect and calculate self-consistently the electric current induced by the proximity of the system to a ferromagnet. These results provide insights into the role of Rashba spin--orbit coupling and anisotropic effects in spin--charge conversion phenomena.
We report a novel neutron interferometry scheme aimed at probing the potential existence of mirror neutrons, which have been proposed as viable dark matter candidates. Our theoretical analysis demonstrates that if mirror neutrons exist, ordinary neutrons would acquire a measurable geometric phase as a result of their mixing with these mirror counterparts.