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We construct perfect t-embeddings for regular hexagons of the hexagonal lattice, providing the first example, and hence proving existence, for graphs with an outer face of degree greater than four. The construction is in terms of the inverse Kasteleyn matrix and relies only on symmetries of the graph. Using known formulas for the inverse Kasteleyn matrix, we derive exact contour integral formulas for these embeddings and their origami maps. Through steepest descent analysis, we establish scaling limits, proving convergence of origami maps to a maximal surface in the Minkowski space $\mathbb{R}^{2,1}$, and we verify structural rigidity conditions, leading to a new proof of convergence of height fluctuations to the Gaussian free field., Comment: 43 pages, 9 figures

Piezoelectricity, the generation of electric charge in response to mechanical stress, is a key property in both natural and synthetic materials. This study significantly boosts the piezoelectric response of chitosan, a biodegradable biopolymer, by integrating chitin/chitosan nanocrystals into natural chitosan-based thin film elastomers. The resulting materials achieve d$_{33}$ values of 15-19 pmV$^{-1}$, a marked improvement over the 5-9 pmV$^{-1}$ observed in pure chitosan films thanks to increased crystallinity from the nanocrystals. We utilize piezoresponse force microscopy (PFM) to accurately measure the d$_{33}$ coefficient, employing an engineered extraction method that eliminates the electrostatic contribution, which can overestimate the piezoelectric response. The resulting chitosan elastomers exhibit elastic deformation up to 40\% strain and a Young's modulus of approximately 100 MPa, similar to soft tissues. These properties, along with the fact that the employed materials can be entirely crafted from upcycled biowaste, make these elastomers ideal for prosthetics, wearable devices, energy harvesters, and sustainable transducers. Our findings underscore the potential of chitosan-based piezoelectric materials for advanced applications in biotechnology, soft robotics, and the green Internet of Things.

How to distribute a set of points uniformly on a spherical surface is a very old problem that still lacks a definite answer. In this work, we introduce a physical measure of uniformity based on the distribution of distances between points, as an alternative to commonly adopted measures based on interaction potentials. We then use this new measure of uniformity to characterize several algorithms available in the literature. We also study the effect of optimizing the position of the points through the minimization of different interaction potentials via a gradient descent procedure. In this way, we can classify different algorithms and interaction potentials to find the one that generates the most uniform distribution of points on the sphere., Comment: 17 pages, 15 figures

Developing new methods for predicting electromagnetic instabilities in cardiac activity is of primary importance. However, we still need a comprehensive view of the heart's magnetic activity at the tissue scale. To fill this gap, we present a model of soft active matter, including thermo-electric coupling, suitably modified to reproduce cardiac magnetic field. Our theoretical framework shows that periodic stimulations of cardiac cells create an external magnetic field evidencing restitution features of nonlinear cardiac dynamics and magnetic restitution curves better discriminate instabilities and bifurcations in cardiac activity. This new framework lays the foundation for innovative, non-invasive diagnostic tools for cardiac arrhythmias.

Results regarding spin glass models are, to this day, mainly confined to models with Ising spins. Spin glass models with continuous spins exhibit interesting new physical behaviors related to the additional degrees of freedom, but have been primarily studied on fully connected topologies. Only recently some advancements have been made in the study of continuous models on sparse graphs. In this work we partially fill this void by introducing a method to solve numerically the Belief Propagation equations for systems of Heisenberg spins on sparse random graphs via a discretization of the sphere. We introduce techniques to study the finite-temperature, finite-connectivity case as well as novel algorithms to deal with the zero-temperature and large connectivity limits. As an application, we locate the de Almeida-Thouless line for this class of models and the critical field at zero temperature, showing the full consistency of the methods presented. Beyond the specific results reported for Heisenberg models, the approaches presented in this paper have a much broader scope of application and pave the way to the solution of strongly disordered models with continuous variables., Comment: 24 pages, 15 figures; added references

Understanding how the complex connectivity structure of the brain shapes its information-processing capabilities is a long-standing question. Here, by focusing on a paradigmatic architecture, we study how the neural activity of excitatory and inhibitory populations encodes information on external signals. We show that information is maximized at the edge of stability, where excitation is balanced by inhibition. When the input switches among different stimuli, this maximum corresponds to the entropy of the external switching dynamics. By analyzing the case of a prolonged stimulus, we find that stronger inhibition is needed to maximize the instantaneous sensitivity, revealing an intrinsic trade-off between short-time responses and long-time accuracy. In agreement with recent experimental findings, our results open the avenue for a complete information-theoretic understanding of how and why inhibition strength should be tuned to optimize information-processing capabilities.

Complex systems with multiple processes evolving on different temporal scales are naturally described by multilayer networks, where each layer represents a different timescale. In this work, we show how the multilayer structure shapes the generation and propagation of information between layers. We derive a general decomposition of the multilayer probability for continuous stochastic processes described by Fokker-Planck operators. In particular, we focus on Gaussian processes, for which this solution can be obtained analytically. By explicitly computing the mutual information between the layers, we derive the fundamental principles that govern how information is propagated by the topology of the multilayer network. In particular, we unravel how edges between nodes in different layers affect their functional couplings. We find that interactions from fast to slow layers alone do not generate information, leaving the layers statistically independent even if they affect their dynamical evolution. On the other hand, interactions from slow to fast nodes lead to non-zero mutual information, which can then be propagated along specific paths of interactions between layers. We employ our results to study the interplay between information and instability, identifying the critical layers that drive information when pushed to the edge of stability. Our work generalizes previous results obtained in the context of discrete stochastic processes, allowing us to understand how the multilayer nature of complex systems affects their functional structure.

Metapopulation models have been instrumental in demonstrating the ecological impact of landscape structure on the survival of a focal species in complex environments. However, extensions to multiple species with arbitrary dispersal networks often rely on phenomenological assumptions limiting their scope. Here, we develop a multilayer network model of competitive dispersing metacommunities to investigate how spatially structured environments impact species coexistence and ecosystem stability. We show that homogeneous environments always lead to monodominance unless all species' fitness parameters are in an exact trade-off. However, this precise fine-tuning does not guarantee coexistence in generic heterogeneous environments. By introducing general spatial disorder in the model, we solve it exactly in the mean-field limit, finding that stable coexistence becomes possible in the presence of strong disorder. Crucially, coexistence is supported by the spontaneous localization of species through the emergence of ecological niches. Our results remain qualitatively valid in arbitrary dispersal networks, where topological features can improve species coexistence. Finally, we employ our model to study how correlated disorder promotes spatial ecological patterns in realistic terrestrial and riverine landscapes. Our work provides a novel framework to understand how landscape structure enables coexistence in metacommunities by acting as the substrate for ecological interactions., Comment: 11 pages, 4 figures

Biological and living organisms sense and process information from their surroundings, typically having access only to a subset of external observables for a limited amount of time. In this work, we uncover how biological systems can exploit these accessible degrees of freedom (DOFs) to transduce information from the inaccessible ones with a limited energy budget. We find that optimal transduction strategies may boost information harvesting over the ideal case in which all DOFs are known, even when only finite-time trajectories are observed, at the price of higher dissipation. We apply our results to red blood cells, inferring the implemented transduction strategy from membrane flickering data and shedding light on the connection between mechanical stress and transduction efficiency. Our framework offers novel insights into the adaptive strategies of biological systems under non-equilibrium conditions.

We provide an overview of three different query languages whose objective is to specify properties on the highly popular formalisms of fault trees (FTs) and attack trees (ATs). These are BFL, a Boolean Logic for FTs, PFL, a probabilistic extension of BFL and ATM, a logic for security metrics on ATs. We validate the framework composed by these three logics by applying them to the case study of a water distribution network. We extend the FT for this network - found in the literature - and we propose to model the system under analysis with the Fault Trees/Attack Trees (FT/ATs) formalism, combining both FTs and ATs in a unique model. Furthermore, we propose a novel combination of the showcased logics to account for queries that jointly consider both the FT and the AT of the model, integrating influences of attacks on failure probabilities of different components. Finally, we extend the domain specific language for PFL with novel constructs to capture the interplay between metrics of attacks - e.g., "cost", success probabilities - and failure probabilities in the system.

The pursue of what are properties that can be identified to permit an automated reasoning program to generate and find new and interesting theorems is an interesting research goal (pun intended). The automatic discovery of new theorems is a goal in itself, and it has been addressed in specific areas, with different methods. The separation of the "weeds", uninteresting, trivial facts, from the "wheat", new and interesting facts, is much harder, but is also being addressed by different authors using different approaches. In this paper we will focus on geometry. We present and discuss different approaches for the automatic discovery of geometric theorems (and properties), and different metrics to find the interesting theorems among all those that were generated. After this description we will introduce the first result of this article: an undecidability result proving that having an algorithmic procedure that decides for every possible Turing Machine that produces theorems, whether it is able to produce also interesting theorems, is an undecidable problem. Consequently, we will argue that judging whether a theorem prover is able to produce interesting theorems remains a non deterministic task, at best a task to be addressed by program based in an algorithm guided by heuristics criteria. Therefore, as a human, to satisfy this task two things are necessary: an expert survey that sheds light on what a theorem prover/finder of interesting geometric theorems is, and - to enable this analysis - other surveys that clarify metrics and approaches related to the interestingness of geometric theorems. In the conclusion of this article we will introduce the structure of two of these surveys - the second result of this article - and we will discuss some future work., Comment: In Proceedings ADG 2023, arXiv:2401.10725

Complex systems are characterized by multiple spatial and temporal scales. A natural framework to capture their multiscale nature is that of multilayer networks, where different layers represent distinct physical processes that often regulate each other indirectly. We model these regulatory mechanisms through triadic higher-order interactions between nodes and edges. In this work, we focus on how the different timescales associated with each layer impact their effective couplings in terms of their mutual information. We unravel the general principles governing how such information propagates across the multiscale structure, and apply them to study archetypal examples of biological signaling networks and effective environmental dependencies in stochastic processes. Our framework generalizes to any dynamics on multilayer networks, paving the way for a deeper understanding of how the multiscale nature of real-world systems shapes their information content and complexity.

Signatures of photo-induced superconductivity have been reported in cuprate materials subjected to a coherent phonon drive. A 'cold' superfluid was extracted from the transient Terahertz conductivity and was seen to coexist with 'hot' uncondensed quasi-particles, a hallmark of a driven-dissipative system of which the interplay between coherent and incoherent responses are not well understood. Here, time resolved spontaneous Raman scattering was used to probe the lattice temperature in the photo-induced superconducting state of YBa2Cu3O6.48. An increase in lattice temperature of approximately 80 K was observed by measuring the time dependent Raman scattering intensity of an undriven 'spectator' phonon mode. This is to be compared with an estimated increase in quasi-particle temperatures of nearly 200 K. These temperature changes provide quantitative information on the nature of the driven state and its decay, and may provide a strategy to optimize this effect., Comment: 14 pages, 4 figures

Recently, there has been much progress in understanding stationary measures for colored (also called multi-species or multi-type) interacting particle systems, motivated by asymptotic phenomena and rich underlying algebraic and combinatorial structures (such as nonsymmetric Macdonald polynomials). In this paper, we present a unified approach to constructing stationary measures for most of the known colored particle systems on the ring and the line, including (1) the Asymmetric Simple Exclusion Process (multispecies ASEP, or mASEP); (2) the q-deformed Totally Asymmetric Zero Range Process (TAZRP) also known as the q-Boson particle system; (3) the q-deformed Pushing Totally Asymmetric Simple Exclusion Process (q-PushTASEP). Our method is based on integrable stochastic vertex models and the Yang-Baxter equation. We express the stationary measures as partition functions of new "queue vertex models" on the cylinder. The stationarity property is a direct consequence of the Yang-Baxter equation. For the mASEP on the ring, a particular case of our vertex model is equivalent to the multiline queues of Martin (arXiv:1810.10650). For the colored q-Boson process and the q-PushTASEP on the ring, we recover and generalize known stationary measures constructed using multiline queues or other methods by Ayyer-Mandelshtam-Martin (arXiv:2011.06117, arXiv:2209.09859), and Bukh-Cox (arXiv:1912.03510). Our proofs of stationarity use the Yang-Baxter equation and bypass the Matrix Product Ansatz used for the mASEP by Prolhac-Evans-Mallick (arXiv:0812.3293). On the line and in a quadrant, we use the Yang-Baxter equation to establish a general colored Burke's theorem, which implies that suitable specializations of our queue vertex models produce stationary measures for particle systems on the line. We also compute the colored particle currents in stationarity., Comment: 69 pages, 35 figures

We survey the connections between the six-vertex (square ice) model of 2d statistical mechanics and random matrix theory. We highlight the same universal probability distributions appearing on both sides, and also indicate related open questions and conjectures. We present full proofs of two asymptotic theorems for the six-vertex model: in the first one the Gaussian Unitary Ensemble and GUE-corners process appear; the second one leads to the Tracy-Widom distribution $F_2$. While both results are not new, we found shorter transparent proofs for this text. On our way we introduce the key tools in the study of the six-vertex model, including the Yang-Baxter equation and the Izergin-Korepin formula., Comment: 53 pages, v3: fixed typos and made minor edits to improve clarity. To appear in Bulletin of the American Mathematical Society

Critical infrastructure systems - for which high reliability and availability are paramount - must operate securely. Attack trees (ATs) are hierarchical diagrams that offer a flexible modelling language used to assess how systems can be attacked. ATs are widely employed both in industry and academia but - in spite of their popularity - little work has been done to give practitioners instruments to formulate queries on ATs in an understandable yet powerful way. In this paper we fill this gap by presenting ATM, a logic to express quantitative security properties on ATs. ATM allows for the specification of properties involved with security metrics that include "cost", "probability" and "skill" and permits the formulation of insightful what-if scenarios. To showcase its potential, we apply ATM to the case study of a CubeSAT, presenting three different ways in which an attacker can compromise its availability. We showcase property specification on the corresponding attack tree and we present theory and algorithms - based on binary decision diagrams - to check properties and compute metrics of ATM-formulae.

In the manuscript arXiv:2306.07869v1, N. L. Wang and co-authors report the results of a near-infrared pump / terahertz probe study in the stripe-ordered cuprate La$_{1.875}$Ba$_{0.125}$CuO$_4$. They measured a change in optical conductivity, but did not find signatures of transient superconductivity. From this observation they extrapolate that in all cuprates in which striped states have been excited with light, there must be no light-induced superconductivity. They conclude that "transient superconductivity cannot be induced by melting of the competing stripe orders with pump pulses whose photon energy is much higher than the superconducting gap of cuprates." Here we show that this extrapolation is unwarranted. First, the absence of light-induced superconductivity in this particular compound was already reported in a previous paper, which instead showed positive evidence for La$_{1.885}$Ba$_{0.115}$CuO$_4$. In addition, the experiment discussed here used photo-excitation with too low fluence and at a suboptimal wavelength. More broadly, a negative result in one compound is rarely compelling indication of the absence of an effect in an entire class of materials., Comment: 3 pages, 2 figures, comment on arXiv:2306.07869v1

The work of this thesis concerns the problem of linear low energy excitations of vector spin glass models. An analytical and numerical study is carried out, considering a fully connected random-field Heisenberg model at zero temperature, a fully-connected vector p-spin glass model and a sparse random-field Heisenberg model. We test these models against the low temperature behavior of finite dimensional glassy systems, in particular we show that they posses phases where the density of states is gapless with quasi-localised modes. In the case of the sparse model, we show that the density of states follows a quartic law at low frequency, consistently with several recent measures of this quantity that can be found in the literature of computer glasses. In all the three models, the spin glass transition is characterised in terms of the behavior of the softest excitations. We found that in the fully connected models the zero temperature spin glass transition in a field is a delocalisation transition of the softest modes. In the sparse case, a weaker form of delocalisation appears at the transition. These results broaden our understanding of the zero temperature critical point, by showing how spin glass ordering affects the way the system responds to small magnetic perturbations., Comment: PhD thesis

Safety-critical infrastructures must operate in a safe and reliable way. Fault tree analysis is a widespread method used for risk assessment of these systems: fault trees (FTs) are required by, e.g., the Federal Aviation Administration and the Nuclear Regulatory Commission. In spite of their popularity, little work has been done on formulating structural queries about FT and analyzing these, e.g., when evaluating potential scenarios, and to give practitioners instruments to formulate queries on FTs in an understandable yet powerful way. In this paper, we aim to fill this gap by extending BFL [32], a logic that reasons about Boolean FTs. To do so, we introduce a Probabilistic Fault tree Logic (PFL). PFL is a simple, yet expressive logic that supports easier formulation of complex scenarios and specification of FT properties that comprise probabilities. Alongside PFL, we present LangPFL, a domain specific language to further ease property specification. We showcase PFL and LangPFL by applying them to a COVID-19 related FT and to a FT for an oil/gas pipeline. Finally, we present theory and model checking algorithms based on binary decision diagrams (BDDs)., Comment: arXiv admin note: text overlap with arXiv:2208.13424

In the manuscript arXiv:2210.01114, Dodge and co-authors discuss the influence of pump-probe profile deformations on the reconstructed non-equilibrium optical conductivity of K$_3$C$_{60}$. They state that when pump-induced saturation of the probe response is taken into account, the reconstructed optical properties are not superconducting-like, as was claimed in a number of experimental reports by our group. We show here that the conclusion reached by Dodge et al. is unjustified. In fact, independent of the specific model, including the problematic saturation profile proposed by the authors, the reconstructed optical properties are those of a finite temperature superconductor. The true fingerprint of superconductivity, which is the $1/\omega$ divergence of the imaginary conductivity, $\sigma_{2}(\omega)$, is retained and is virtually independent of the chosen model. The only model-dependent feature is the degree of gapping in $\sigma_{1}(\omega)$. In all cases the extracted optical properties reflect the presence of residual quasiparticles, which at finite temperatures are inevitably present alongside the superfluid., Comment: 3 pages, 1 figure, comment on arXiv:2210.01114

In this work we study a sequence of perfect t-embeddings of uniformly weighted Aztec diamonds. We show that these perfect t-embeddings can be used to prove convergence of gradients of height fluctuations to those of the Gaussian free field. In particular we provide a first proof of the existence of a model satisfying all conditions of the main theorem of arXiv:2109.06272. This confirms the prediction of arXiv:2002.07540. An important part of our proof is to exhibit exact integral formulas for perfect t-embeddings of uniformly weighted Aztec diamonds. In addition, we construct and analyze perfect t-embeddings of another sequence of uniformly weighted finite graphs called tower graphs. Although we do not check all technical assumptions of the mentioned theorem for these graphs, we use perfect t-embeddings to derive a simple transformation which identifies height fluctuations on the tower graph with those of the Aztec diamond., Comment: 45 pages, 18 figures. v2: minor edits to introduction, fixed typos

In this article we define a generalization of the domino shuffling algorithm for tilings of the Aztec diamond to the interacting $k$-tilings recently introduced by S. Corteel, A. Gitlin, and the first author. We describe the algorithm both in terms of dynamics on a system of colored particles and as operations on the dominos themselves., Comment: 43 pages, 18 figures

This Thesis explores how tools from Statistical Physics and Information Theory can help us describe and understand complex systems. In the first part, we study the interplay between internal interactions, environmental changes, and effective representations of complex stochastic systems. We model the environment as an unobserved stochastic process and investigate how the mutual information between internal degrees of freedom encodes internal and environmental processes, and how it can help us disentangle them. Then, we attempt to build effective representations via information-preserving projections that preserve the dependencies of a complex system. In the paradigmatic case of underdamped systems, we find that optimal effective representations may be unexpectedly singular, revealing fundamental limits of approximating complex models. In the second part of this Thesis, we apply these approaches and ideas from criticality to neural systems at different scales, showing that unobserved neural activity may lead to power-law neuronal avalanches in the absence of criticality. Remarkably, the properties of mutual information suggest that, whereas avalanches may emerge from stochastic modulation, interactions between neural populations are at the source of scale-free correlations. We further explore the role of the structure of interactions by showing how interaction networks change the nature of the phase transition of a well-known cellular automaton. Finally, we test a phenomenological coarse-graining procedure for neural timeseries in different settings, and in particular in the presence of stochastic environments. Our results shed light on the role of the interaction network, its topological features, and unobserved modulation in the emergence of collective patterns of brain activity and general complex systems., Comment: Doctoral Thesis in Physics, University of Padova

Biological and living systems process information across spatiotemporal scales, exhibiting the hallmark ability to constantly modulate their behavior to ever-changing and complex environments. In the presence of repeated stimuli, a distinctive response is the progressive reduction of the activity at both sensory and molecular levels, known as habituation. Here, we solve a minimal microscopic model devoid of biological details to show that habituation is driven by negative feedback provided by a slow storage mechanism. Crucially, an intermediate level of habituation is associated with a steep increase in the information that the system collects on the external input over time. We find that the region characterized both by maximal information gain and by the onset of habituation can be retrieved if the system tunes its parameters to minimize dissipation and maximize information at the same time. We test our dynamical predictions against experimentally recorded neural responses in a zebrafish larva subjected to repeated looming stimulation. Our work makes a fundamental step towards uncovering the core mechanisms that shape habituation in biological systems, elucidating its information-theoretic and functional role.

We study the dimer model on special subgraphs of the square hexagon lattice called "tower graphs" of size $N$. Using integrable probability techniques, we confirm that as $N \rightarrow \infty$, the local statistics are translation invariant Gibbs measures, as conjectured by Kenyon-Okounkov-Sheffield. We also present a 2+1-dimensional discrete time growth process, whose time $N$ distribution is exactly the dimer model on the size $N$ tower, and we compute the current of this growth process and confirm that the model belongs to the Anisotropic KPZ universality class., Comment: 30 pages, 17 figures

The Chapman-Enskog method, in combination with the quantum maximum entropy principle, is applied to the Wigner equation in order to obtain quantum Navier-Stokes equations for electrons in graphene in the isothermal case. The derivation is based on the quantum version of the maximum entropy principle and follows the lines of Ringhofer-Degond-M\'ehats' theory (J. Stat. Phys. 112, 2003 and Z. Angew. Math. Mech. 90, 2010). The model obtained in this way is then semiclassically expanded up to $\mathcal{O}(\hbar^2)$.

Coherent optical excitation of certain phonon modes in YBa$_2$Cu$_3$O$_{6+x}$ has been shown to induce superconducting-like interlayer coherence at temperatures higher than $T_c$. Recent work has associated these phenomena to a parametric excitation and amplification of Josephson plasma polaritons, which are overdamped above $T_c$ but are made coherent by the phonon drive. However, the dissipative response of uncondensed quasiparticles, which do not couple in the same way to the phonon drive, has not been addressed. Here, we investigate both the enhancement of the superfluid density, $\omega\sigma_2(\omega)$, and the dissipative response of quasiparticles, $\sigma_1(\omega)$, by systematically tuning the duration and energy of the mid-infrared pulse while keeping the peak field fixed. We find that the photo-induced superfluid density saturates to the zero-temperature equilibrium value for pulses made longer than the phonon dephasing time, whilst the dissipative component continues to grow with increasing pulse duration. We show that superfluid and dissipation remain uncoupled as long as the drive is on, and identify an optimal regime of pump pulse durations for which the superconducting response is maximum and dissipation is minimized., Comment: 14 pages, 8 figures

Safety-critical infrastructures must operate safely and reliably. Fault tree analysis is a widespread method used to assess risks in these systems: fault trees (FTs) are required - among others - by the Federal Aviation Authority, the Nuclear Regulatory Commission, in the ISO26262 standard for autonomous driving and for software development in aerospace systems. Although popular both in industry and academia, FTs lack a systematic way to formulate powerful and understandable analysis queries. In this paper, we aim to fill this gap and introduce Boolean Fault tree Logic (BFL), a logic to reason about FTs. BFL is a simple, yet expressive logic that supports easier formulation of complex scenarios and specification of FT properties. Alongside BFL, we present model checking algorithms based on binary decision diagrams (BDDs) to analyse specified properties in BFL, patterns and an algorithm to construct counterexamples. Finally, we propose a case-study application of BFL by analysing a COVID19-related FT.

While the Industry 4.0 is idolizing the potential of an artificial intelligence embedded into "things", it is neglecting the role of the human component, which is still indispensable in different manufacturing activities, such as a machine setup or maintenance operations. The present research study first proposes an Industrial Internet pyramid as emergent human-centric manufacturing paradigm within Industry 4.0 in which central is the role of a Ubiquitous Knowledge about the manufacturing system intuitively accessed and used by the manufacturing employees. Second, the prototype of a Service-oriented Digital Twin, which leverage on a flexible ontology-oriented knowledge structure and on augmented reality combined to a vocal interaction system for an intuitive knowledge retrieval and fruition, has been designed and developed to deliver this manufacturing knowledge. Two test-beds, complimentary for the problems in practice (the former on the maintenance-production interface in a large enterprise, the latter majorly focused in production and setups in a small and medium enterprise), show the significant benefits in terms of time, costs and process quality, thus validating the approach proposed. This research shows that a human-centric and knowledge-driven approach can drive the performance of Industry 4.0 initiatives and lead a Smart Factory towards its full potential., Comment: 16 pages, 12 figures, 5 tables

Despite Information and Communication Technologies (ICT) have reduced the information asymmetry and increased the degree of interorganizational collaboration, the companies participating a supply chain are less inclined to share data when information is sensible and partners cannot be fully trusted. In such a context, Blockchain is a decentralized certificate authority that may provide economic and operational benefits but companies operating in a supply chain claim to have little knowledge about Blockchain due to its novelty and to the lack of use cases and application studies. In this work, a software connector has been designed and developed to connect an Ethereum-like blockchain with the enterprises' information systems to allow companies to share information with their partners with different levels of visibility and to check data authenticity, integrity and invariability over time through the blockchain, thus building trust. In order to explore the potential of deploying the blockchain in a supply chain, a simulation model has been developed to recreate the supply chain operations and integrated with the blockchain through the same software connector to carry out a scenario statistical analysis. Application results shows how blockchain technology is a convenient instrument to overcome collaboration and trust issues in a supply chain, to increase the supply chain overall performance, to minimize the negative consequences of information asymmetry over the echelons of a supply chain but also to discourage companies from any misconduct (e.g. counterfeiting data or low data accuracy)., Comment: 13 pages, 15 figures, 10 tables

This article faces the problem of operative and procedural cooperative training in marine ports with particular attention to harbour pilots and port traffic controller. The design and development of an advanced system, equipped with dedicated hardware in the loop, for cooperative training of operators involved in the last mile of navigation is presented. Indeed, the article describes the software and hardware development of a distributed and interoperable system composed by two simulators (the bridge ship simulator and control tower simulator). Multiple problems are faced and solved including (i) the motion of the ship at sea that is based on a 6 Degree Of Freedom (DOF) model for surge, sway and yaw and closed form expressions for pitch, roll and heave and its validation; (ii) the development of the 3D geometric models and related virtual environments of a real marine port and vessel (to provide the trainees with the sensation to experience a real port and ship environment); (iii) the design of a bridge ship replica, the bridge hardware integration and the design of the visualization system; (iv) the design and development of the control tower simulator; (v) the integration of the bridge ship simulator and control tower simulator through the IEEE 1516 High Level Architecture standard for distributed simulation., Comment: 21 pages, 22 figures

As the Industry 4.0 takes shape, human operators experience an increased complexity of their daily tasks: they are required to be highly flexible and to demonstrate adaptive capabilities in a very dynamic working environment. It calls for tools and approaches that could be easily embedded into everyday practices and able to combine complex methodologies with high usability requirements. In this perspective, the proposed research work is focused on the design and development of a practical solution, called Sophos-MS, able to integrate augmented reality contents and intelligent tutoring systems with cutting-edge fruition technologies for operators' support in complex man-machine interactions. After establishing a reference methodological framework for the smart operator concept within the Industry 4.0 paradigm, the proposed solution is presented, along with its functional and non-function requirements. Such requirements are fulfilled through a structured design strategy whose main outcomes include a multi-layered modular solution, Sophos-MS, that relies on Augmented Reality contents and on an intelligent personal digital assistant with vocal interaction capabilities. The proposed approach has been deployed and its training potentials have been investigated with field experiments. The experimental campaign results have been firstly checked to ensure their statistical relevance and then analytically assessed in order to show that the proposed solution has a real impact on operators' learning curves and can make the difference between who uses it and who does not., Comment: 16 pages, 25 figures, 9 tables

Biochemistry, ecology, and neuroscience are examples of prominent fields aiming at describing interacting systems that exhibit non-trivial couplings to complex, ever-changing environments. We have recently shown that linear interactions and a switching environment are encoded separately in the mutual information of the overall system. Here, we first generalize these findings to a broad class of non-linear interacting models. We find that a new term in the mutual information appears, quantifying the interplay between non-linear interactions and environmental changes, and leading to either constructive or destructive information interference. Furthermore, we show that a higher mutual information emerges in out-of-equilibrium environments with respect to an equilibrium scenario. Finally, we generalize our framework to the case of continuously varying environments. We find that environmental changes can be mapped exactly into an effective spatially-varying diffusion coefficient, shedding light on modeling and information structure of biophysical systems in inhomogeneous media.

Disparity in spatial accessibility is strongly associated with growing inequalities among urban communities. Since improving levels of accessibility for certain communities can provide them with upward social mobility and address social exclusion and inequalities in cities, it is important to understand the nature and distribution of spatial accessibility among urban communities. To support decision-makers in achieving inclusion and fairness in policy interventions in cities, we present an open-source and data-driven framework to understand the spatial nature of accessibility to infrastructure among the different demographics. We find that accessibility to a wide range of infrastructure in any city (54 cities) converges to a Zipf's law, suggesting that inequalities also appear proportional to growth processes in these cities. Then, assessing spatial inequalities among the socioeconomically clustered urban profiles for 10 of those cities, we find urban communities are distinctly segregated along social and spatial lines. We find low accessibility scores for populations who have a larger share of minorities, earn less, and have a relatively lower number of individuals with a university degree. These findings suggest that the reproducible framework we propose may be instrumental in understanding processes leading to spatial inequalities and in supporting cities to devise targeted measures for addressing inequalities for certain underprivileged communities., Comment: 35 pages, 6 figures

Motivated by recent experiments that observed low-frequency second-order optical responses in doped striped superconductors, here we investigate the nonlinear electrodynamics of systems exhibiting a charge density wave (CDW) order parameter. Due to the Bragg scattering off the CDW order, an incoming spatially homogeneous electric field in addition to zero momentum current generates Umklapp currents that are modulated in space at momenta of the reciprocal CDW lattice. In particular, here we predict and microscopically evaluate the Umklapp shift current, a finite momentum analog of the regular shift current which represents the second-order optical process that downconverts homogeneous AC electric field into low-frequency, zero momentum current. Specifically, we evaluate real-time response functions within mean-field theory via the Keldysh technique and use the Peierls substitution to compute observables at finite momenta in lattice models. We find that systems with certain lattice symmetries (such as inversion symmetry), where the regular shift current is disallowed, may give rise to the Umklapp one. We apply our framework to investigate lattice symmetries in layered materials with helical-like stripes and show that both types of shift currents provide insight into the nature of intertwined phases of matter. Finally, we discuss the relation of our findings to recent experiments in striped superconductors.

Low-dimensional representations of underdamped systems often provide insightful grasps and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spatial trajectories. We show that, in paradigmatic systems, the minimization of the information loss drives the appearance of a discontinuous transition in the optimal model parameters. Our results raise serious warnings for general inference approaches and unravel fundamental properties of effective dynamical representations, impacting several fields, from biophysics to dimensionality reduction.

We introduce a family of Markov growth processes on discrete height functions defined on the 2-dimensional square lattice. Each height function corresponds to a configuration of the six vertex model on the infinite square lattice. We focus on the stochastic six vertex model corresponding to a particular two-parameter family of weights within the ferroelectric regime. It is believed (and partially proven, see Aggarwal, arXiv:2004.13272) that the stochastic six vertex model displays nontrivial pure (i.e., translation invariant and ergodic) Gibbs states of two types, KPZ and liquid. These phases have very different long-range correlation structure. The Markov processes we construct preserve the KPZ pure states in the full plane. We also show that the same processes put on the torus preserve arbitrary Gibbs measures for generic six vertex weights (not necessarily in the ferroelectric regime). Our dynamics arise naturally from the Yang-Baxter equation for the six vertex model via its bijectivisation, a technique first used in Bufetov-Petrov (arXiv:1712.04584). The dynamics we construct are irreversible; in particular, the height function has a nonzero average drift. In each KPZ pure state, we explicitly compute the average drift (also known as the current) as a function of the slope. We use this to analyze the hydrodynamics of a non-stationary version of our process acting on quarter plane stochastic six vertex configurations. The fixed-time limit shapes in the quarter plane model were obtained in Borodin-Corwin-Gorin (arXiv:1407.6729)., Comment: 59 pages, 21 figures

We study the linear excitations around typical energy minima of a mean-field disordered model with continuous degrees of freedom undergoing a Random First Order Transition (RFOT). Contrary to naive expectations, the spectra of linear excitations are ungapped and we find the presence of a pseudogap corresponding to localized excitations with arbitrary low excitation energy. Moving to deeper minima in the landscape, the excitations appear increasingly localized while their abundance decreases. Beside typical minima, there also exist rare ultra-stable minima, with an energy gap and no localised excitations.

Recent experiments in the doped cuprates La$_{2-x}$Ba$_x$CuO$_4$ have revealed the emission of anomalous terahertz radiation after impulsive optical excitation. Here, we theoretically investigate the nonlinear electrodynamics of such striped superconductors and explore the origin of the observed radiation. We argue that photoexcitation is converted into a photocurrent by a second-order optical nonlinearity, which is activated by the breaking of inversion symmetry in certain stripe configurations. We point out the importance of including Umklapp photocurrents modulated at the stripe periodicity itself, which impulsively drive surface Josephson plasmons and lead to a resonant structure of outgoing radiation, consistent with the experiments. We speculate on the utility of the proposed mechanism in the context of generating tunable terahertz radiation.

The interplay between charge order and superconductivity remains one of the central themes of research in quantum materials. In the case of cuprates, the coupling between striped charge fluctuations and local electromagnetic fields is especially important, as it affects transport properties, coherence and dimensionality of superconducting correlations. Here, we study the emission of coherent terahertz radiation in single-layer cuprates of the La$_{2-x}$Ba$_x$CuO$_4$ family, for which this effect is expected to be forbidden by symmetry. We find that emission vanishes for compounds in which the stripes are quasi-static, but is activated when $c$-axis inversion symmetry is broken by incommensurate or fluctuating charge stripes, such as in La$_{1.905}$Ba$_{0.095}$CuO$_4$ and in La$_{1.845}$Ba$_{0.155}$CuO$_4$. In this case, terahertz radiation is emitted by surface Josephson plasmons, which are generally dark modes, but couple to free space electromagnetic radiation because of the stripe modulation., Comment: 25 pages, 9 figures

Between 2019 and 2020, during the country's hottest and driest year on record, Australia experienced a dramatic bushfire season, with catastrophic ecological and environmental consequences. Several studies highlighted how such abrupt changes in fire regimes may have been in large part a consequence of climate change and other anthropogenic transformations. Here, we analyze the monthly evolution of the burned area in Australia from 2000 to 2020, obtained via satellite imaging through the MODIS platform. We find that the 2019-2020 peak is associated with signatures typically found near critical points. We introduce a modeling framework based on forest-fire models to study the properties of these emergent fire outbreaks, showing that the behavior observed during the 2019-2020 fire season matches the one of a percolation transition, where system-size outbreaks appear. Our model also highlights the existence of an absorbing phase transition that might be eventually crossed, after which the vegetation cannot recover.

Optical drives at terahertz and mid-infrared frequencies in quantum materials are increasingly used to reveal the nonlinear dynamics of collective modes in correlated many-body systems and their interplay with electromagnetic waves. Recent experiments demonstrated several surprising optical properties of transient states induced by driving, including the appearance of photo-induced edges in the reflectivity in cuprate superconductors, observed both below and above the equilibrium transition temperature. Furthermore, in other driven materials, reflection coefficients larger than unity have been observed. In this paper we demonstrate that unusual optical properties of photoexcited systems can be understood from the perspective of a Floquet system; a system with periodically modulated system parameters originating from pump-induced oscillations of a collective mode. We present a general phenomenological model of reflectivity from Floquet materials, which takes into account parametric generation of excitation pairs. We find a universal phase diagram of drive induced features in reflectivity which evidence a competition between driving and dissipation. To illustrate our general analysis we apply our formalism to two concrete examples motivated by recent experiments: a single plasmon band, which describes Josephson plasmons in layered superconductors, and a phonon-polariton system, which describes upper and lower polaritons in materials such as insulating SiC. Finally we demonstrate that our model can be used to provide an accurate fit to results of phonon-pump - terahertz-probe experiments in the high temperature superconductor $\rm{YBa_2Cu_3O_{6.5}}$. Our model explains the appearance of a pump-induced edge, which is higher in energy than the equilibrium Josephson plasmon edge, even if the interlayer Josephson coupling is suppressed by the pump pulse., Comment: 14 pages, 6 figures

Interlayer transport in high-$T_C$ cuprates is mediated by superconducting tunneling across the CuO$_2$ planes. For this reason, the terahertz frequency optical response is dominated by one or more Josephson plasma resonances and becomes highly nonlinear at fields for which the tunneling supercurrents approach their critical value, $I_C$. These large terahertz nonlinearities are in fact a hallmark of superconducting transport. Surprisingly, however, they have been documented in La$_{2-x}$Ba$_x$CuO$_4$ also above $T_C$ for doping values near $x=1/8$, and interpreted as an indication of superfluidity in the stripe phase. Here, Electric Field Induced Second Harmonic (EFISH) is used to study the dynamics of time-dependent interlayer voltages when La$_{2-x}$Ba$_x$CuO$_4$ is driven with large-amplitude terahertz pulses, in search of other characteristic signatures of Josephson tunnelling in the normal state. We show that this method is sensitive to the voltage anomalies associated with 2$\pi$ Josephson phase slips, which near $x=1/8$ are observed both below and above $T_C$. These results document a new regime of nonlinear transport that shares features of fluctuating stripes and superconducting phase dynamics., Comment: 26 pages, 7 figures

Microsoft Teams is a collaboration and communication platform developed by Microsoft that replaces and extends Microsoft Skype for Business. It differs from Skype for Business by the fact that it exists only as part of the Microsoft 365 products whereas Skype for Business can be deployed completely or partly on-premise. During the pandemic emergency in 2020 and 2021 Microsoft Teams has increased dramatically its base of users as most of the meetings and the communications had to be conducted in virtual environments by users working remotely. Microsoft Teams allows users to collaborate sending and sharing information virtually with anyone internal or external to the an organization with PCs and mobile devices, therefore it requires a careful review of all the security configurations and procedures within the organization. Microsoft Teams infrastructure can also be integrated with PSTN telephone services, natively within the Microsoft 365 services or by integrating other PSTN service providers. Therefore, its architecture extends the perimeter that could be exploited for an attack. Microsoft Teams features can also be extended by Apps. There are hundreds of Apps developed by Microsoft and by other companies to address the various needs of modern collaboration. "Walkie Talkie", one of those Apps, transforms the Teams client installed in a mobile phone into a Walkie Talkie communication device for registered users. The goal of this paper is to describe different Teams' usage scenarios and to analyse Teams' PSTN and Teams' Walkie Talkie communication scenarios describing forensics procedures to investigate inappropriate users' conduct.

We study the energy minima of the fully-connected $m$-components vector spin glass model at zero temperature in an external magnetic field for $m\ge 3$. The model has a zero temperature transition from a paramagnetic phase at high field to a spin glass phase at low field. We study the eigenvalues and eigenvectors of the Hessian in the minima of the Hamiltonian. The spectrum is gapless both in the paramagnetic and in the spin glass phase, with a pseudo-gap behaving as $\lambda^{m-1}$ in the paramagnetic phase and as $\sqrt{\lambda}$ in the spin glass phase. Despite the long-range nature of the model, the eigenstates close to the edge of the spectrum display quasi-localization properties. We show that the paramagnetic to spin glass transition corresponds to delocalization of the edge eigenvectors. We solve the model by the cavity method in the thermodynamic limit. We also perform numerical minimization of the Hamiltonian for $N\le 2048$ and compute the spectral properties, that show very strong corrections to the asymptotic scaling approaching the critical point.

Real-world systems are characterized by complex interactions of their internal degrees of freedom, while living in ever-changing environments whose net effect is to act as additional couplings. Here, we introduce a paradigmatic interacting model in a switching, but unobserved, environment. We show that the limiting properties of the mutual information of the system allow for a disentangling of these two sources of couplings. Further, our approach might stand as a general method to discriminate complex internal interactions from equally complex changing environments.

Resonant optical excitation of certain molecular vibrations in $\kappa$-(BEDT-TTF)$_2$Cu[N(CN)$_2$]Br has been shown to induce transient superconducting-like optical properties at temperatures far above equilibrium $T_c$. Here, we report experiments across the bandwidth-tuned phase diagram of this class of materials, and study the Mott insulator $\kappa$-(BEDT-TTF)$_2$Cu[N(CN)$_2$]Cl and the metallic compound $\kappa$-(BEDT-TTF)$_2$Cu(NCS)$_2$. We find non-equilibrium photoinduced superconductivity only in $\kappa$-(BEDT-TTF)$_2$Cu[N(CN)$_2$]Br, indicating that the proximity to the Mott insulating phase and possibly the presence of preexisting superconducting fluctuations are pre-requisites for this effect., Comment: 14 pages, 4 figures

We survey the state-of-the-art on model-based formalisms for safety and security joint analysis, where safety refers to the absence of unintended failures, and security to absence of malicious attacks. We conduct a thorough literature review and - as a result - we consider fourteen model-based formalisms and compare them with respect to several criteria: (1) Modelling capabilities and Expressiveness: which phenomena can be expressed in these formalisms? To which extent can they capture safety-security interactions? (2) Analytical capabilities: which analysis types are supported? (3) Practical applicability: to what extent have the formalisms been used to analyze small or larger case studies? Furthermore, (1) we present more precise definitions for safety-security dependencies in tree-like formalisms; (2) we showcase the potential of each formalism by modelling the same toy example from the literature and (3) we present our findings and reflect on possible ways to narrow highlighted gaps. In summary, our key findings are the following: (1) the majority of approaches combine tree-like formal models; (2) the exact nature of safety-security interaction is still ill-understood and (3) diverse formalisms can capture different interactions; (4) analyzed formalisms merge modelling constructs from existing safety- and security-specific formalisms, without introducing ad hoc constructs to model safety-security interactions, or (5) metrics to analyze trade offs. Moreover, (6) large case studies representing safety-security interactions are still missing.

The critical brain hypothesis has emerged as an attractive framework to understand neuronal activity, but it is still widely debated. In this work, we analyze data from a multi-electrodes array in the rat's cortex and we find that power-law neuronal avalanches satisfying the crackling-noise relation coexist with spatial correlations that display typical features of critical systems. In order to shed a light on the underlying mechanisms at the origin of these signatures of criticality, we introduce a paradigmatic framework with a common stochastic modulation and pairwise linear interactions inferred from our data. We show that in such models power-law avalanches that satisfy the crackling noise relation emerge as a consequence of the extrinsic modulation, whereas scale-free correlations are solely determined by internal interactions. Moreover, this disentangling is fully captured by the mutual information in the system. Finally, we show that analogous power-law avalanches are found in more realistic models of neural activity as well, suggesting that extrinsic modulation might be a broad mechanism for their generation.

Geochronology, or determination of absolute ages for geologic events, underpins many inquiries into the formation and evolution of planets and our Solar System. Absolute ages of ancient and recent magmatic products provide strong constraints on the dynamics of magma oceans and crustal formation, as well as the longevity and evolution of interior heat engines and distinct mantle/crustal source regions. Absolute dating also relates habitability markers to the timescale of evolution of life on Earth. However, the number of geochronologically-significant terrains across the inner Solar System far exceeds our ability to conduct sample return from all of them. In preparation for the upcoming Decadal Survey, our team formulated a set of medium-class (New Frontiers) mission concepts to three different locations (the Moon, Mars, and Vesta) where sites that record Solar System bombardment, magmatism, and/or habitability are uniquely preserved and accessible. We developed a notional payload to directly date planetary surfaces, consisting of two instruments capable of measuring radiometric ages in situ, an imaging spectrometer, optical cameras to provide site geologic context and sample characterization, a trace element analyzer to augment sample contextualization, and a sample acquisition and handling system. Landers carrying this payload to the Moon, Mars, and Vesta would likely fit into the New Frontiers cost cap in our study (~$1B). A mission of this type would provide crucial constraints on planetary history while also enabling a broad suite of investigations such as basic geologic characterization, geomorphologic analysis, ground truth for remote sensing analyses, analyses of major, minor, trace, and volatile elements, atmospheric and other long-lived monitoring, organic molecule analyses, and soil and geotechnical properties., Comment: Submitted to the Planetary Science Journal, October 2020