In this paper, we study stealthy cyber-attacks on actuators of cyber-physical systems(CPS), namely zero dynamics and controllable attacks. In particular, under certain assumptions, we investigate and propose condition...
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In this paper, we study stealthy cyber-attacks on actuators of cyber-physical systems(CPS), namely zero dynamics and controllable attacks. In particular, under certain assumptions, we investigate and propose conditions under which one can execute zero dynamics and controllable attacks in the CPS. The above conditions are derived based on the Markov parameters of the CPS and elements of the system observability matrix. Consequently, in addition to outlining the number of required actuators to be attacked, these conditions provide one with the minimum system knowledge needed to perform zero dynamics and controllable cyber-attacks. As a countermeasure against the above stealthy cyber-attacks, we develop a dynamic coding scheme that increases the minimum number of the CPS required actuators to carry out zero dynamics and controllable cyber-attacks to its maximum possible value. It is shown that if at least one secure input channel exists, the proposed dynamic coding scheme can prevent adversaries from executing the zero dynamics and controllable attacks even if they have complete knowledge of the coding system. Finally, two illustrative numerical case studies are provided to demonstrate the effectiveness and capabilities of our derived conditions and proposed methodologies.
A silicon solar cell with a power conversion efficiency (PCE)of 4% was born in Bell Lab in 1954, seven decades ago. Today,silicon solar cells have reached an efficiency above 25%and achieved pervasive commercial succe...
A silicon solar cell with a power conversion efficiency (PCE)of 4% was born in Bell Lab in 1954, seven decades ago. Today,silicon solar cells have reached an efficiency above 25%and achieved pervasive commercial success [1]. In spite of the steady improvement in efficiency, the interest and enthusiasm in search for new materials and innovative device architectures for newgeneration solar cells have never diminished or subsided;
Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inher...
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Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion, low-rank representation, and robust matrix regression. We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the ?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers, backed by rigorous theoretical analysis for complexity and *** algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.
The authors consider the property of detectability of discrete event systems in the presence of sensor attacks in the context of *** authors model the system using an automaton and study the general notion of detectab...
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The authors consider the property of detectability of discrete event systems in the presence of sensor attacks in the context of *** authors model the system using an automaton and study the general notion of detectability where a given set of state pairs needs to be(eventually or periodically)distinguished in any estimate of the state of the *** authors adopt the ALTER sensor attack model from previous work and formulate four notions of CA-detectability in the context of this attack model based on the following attributes:strong or weak;eventual or *** authors present verification methods for strong CA-detectability and weak *** authors present definitions of strong and weak periodic CA-detectability that are based on the construction of a verifier automaton called the augmented *** development also resulted in relaxing assumptions in prior results on D-detectability,which is a special case of CA-detectability.
This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency *** guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a mo...
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This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency *** guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a modelbased reinforcement learning(MBRL)algorithm is combined with Lyapunov approach,which determines the safe region of states and *** obtain near optimal control policy,the control performance is safely improved by approximate dynamic programming(ADP)using data sampled from the region of attraction(ROA).Moreover,to enhance the control robustness against parameter uncertainty in the inverter,a Gaussian process(GP)model is adopted by the proposed algorithm to effectively learn system dynamics from *** simulations validate the effectiveness of the proposed algorithm.
Wide field of view and light weight optics are critical for advanced eyewear,with applications in augmented/virtual reality and night *** refractive lenses are often stacked to correct aberrations at a wide field of v...
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Wide field of view and light weight optics are critical for advanced eyewear,with applications in augmented/virtual reality and night *** refractive lenses are often stacked to correct aberrations at a wide field of view,leading to limited performance and increased size and *** particular,simultaneously achieving a wide field of view and large aperture for light collection is desirable but challenging to realize in a compact ***,we demonstrate a wide field of view(greater than 60°)meta-optic doublet eyepiece with an entrance aperture of 2.1 *** the design wavelength of 633 nm,the meta-optic doublet achieves comparable performance to a refractive lens-based eyepiece *** meta-doublet eyepiece illustrates the potential for meta-optics to play an important role in the development of high-quality monochrome near-eye displays and night vision systems.
The search for ferromagnetism in the Hubbard model has been a problem of outstanding interest since Nagaoka's original proposal in 1966. Recent advances in quantum simulation have today enabled the study of tunabl...
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The search for ferromagnetism in the Hubbard model has been a problem of outstanding interest since Nagaoka's original proposal in 1966. Recent advances in quantum simulation have today enabled the study of tunable doped Hubbard models in ultracold atomic systems. Employing large-scale density-matrix renormalization group calculations, we establish the existence of high-spin ground states of the Hubbard model on finite-sized triangular lattices, analyze the microscopic mechanisms behind their origin, and investigate the interplay between ferromagnetism and other competing orders, such as stripes. These results explain (and shed light on) the intriguing observations of ferromagnetic correlations in recent optical-lattice experiments. Additionally, we examine a generalized variant of the Hubbard model, wherein any second electron on a single lattice site is weakly bound compared to the first one, and demonstrate how this modification can lead to enhanced ferromagnetism, at intermediate lengthscales, on the nonfrustrated square lattice as well.
We utilize first-principles theory to investigate the role of electron-phonon interactions within a dataset of monolayer materials. Using density functional theory to describe excited-state transitions and the special...
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We utilize first-principles theory to investigate the role of electron-phonon interactions within a dataset of monolayer materials. Using density functional theory to describe excited-state transitions and the special displacement method to describe the role of phonons, we analyze the relationship between simple physical observables and electron-phonon coupling strength. For over 100 materials, we compute the band gap renormalization due to zero-point vibrational (ZPR) motion as a measure of electron-phonon interactions and train a machine learning model based on physical parameters. We demonstrate that the strength of electron-phonon interactions is highly dependent on the band gap, dielectric constant, and degree of ionicity, all of which can be physically justified. We then apply this model to 1302 2D materials, predicting the ZPR, which for five randomly selected materials tested agree well with the first-principles predictions. This work provides an approach for quantitatively predicting the ZPR as a measure of electron-phonon interactions in 2D materials.
The competition between scrambling and projective measurements can lead to measurement-induced entanglement phase transitions (MIPT). In this work, we show that the universality class of the MIPT can be drastically al...
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The competition between scrambling and projective measurements can lead to measurement-induced entanglement phase transitions (MIPT). In this work, we show that the universality class of the MIPT can be drastically altered when the system has a diffusing conserved density. As a numerical tractable model of this, we study a 1+1d random Clifford circuit locally monitored by classically diffusing particles (“measurers”). The resulting diffusive correlations in the measurement density are a relevant perturbation to the usual space-time random MIPT critical point, producing a new universality class for this phase transition. We find “Griffiths-like” effects due to rare space-time regions where, e.g., the diffusive measurers have a low or high density, but these are considerably weaker than the Griffiths effects that occur with quenched randomness that produce rare spatial regions with infinite lifetime.
The ground states of interacting one-dimensional metals are generically Luttinger liquids. Luttinger-liquid theory is usually considered for translation invariant systems. The Luttinger-liquid description remains vali...
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The ground states of interacting one-dimensional metals are generically Luttinger liquids. Luttinger-liquid theory is usually considered for translation invariant systems. The Luttinger-liquid description remains valid for weak quasiperiodic modulations; however, as the quasiperiodic modulation gets increasingly strong, it is increasingly renormalized and eventually fails, as the system becomes localized. We explore how quasiperiodic modulation renormalizes the Luttinger parameter characterizing this emergent Luttinger liquid, using the renormalization of transmission coefficients across a barrier as a proxy that remains valid for general quasiperiodic modulation. We find, unexpectedly, that quasiperiodic modulation weakens the effects of short-range interactions, but enhances those of long-range interactions. We support the former finding with matrix-product numerics. We also discuss how interactions affect the localization phase boundary.
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