1,975 research outputs found
Compressive Privacy for a Linear Dynamical System
We consider a linear dynamical system in which the state vector consists of
both public and private states. One or more sensors make measurements of the
state vector and sends information to a fusion center, which performs the final
state estimation. To achieve an optimal tradeoff between the utility of
estimating the public states and protection of the private states, the
measurements at each time step are linearly compressed into a lower dimensional
space. Under the centralized setting where all measurements are collected by a
single sensor, we propose an optimization problem and an algorithm to find the
best compression matrix. Under the decentralized setting where measurements are
made separately at multiple sensors, each sensor optimizes its own local
compression matrix. We propose methods to separate the overall optimization
problem into multiple sub-problems that can be solved locally at each sensor.
We consider the cases where there is no message exchange between the sensors;
and where each sensor takes turns to transmit messages to the other sensors.
Simulations and empirical experiments demonstrate the efficiency of our
proposed approach in allowing the fusion center to estimate the public states
with good accuracy while preventing it from estimating the private states
accurately
On the Relationship Between Information-Theoretic Privacy Metrics And Probabilistic Information Privacy
Information-theoretic (IT) measures based on -divergences have recently
gained interest as a measure of privacy leakage as they allow for trading off
privacy against utility using only a single-value characterization. However,
their operational interpretations in the privacy context are unclear. In this
paper, we relate the notion of probabilistic information privacy (IP) to
several IT privacy metrics based on -divergences. We interpret probabilistic
IP under both the detection and estimation frameworks and link it to
differential privacy, thus allowing a precise operational interpretation of
these IT privacy metrics. We show that the -divergence privacy metric
is stronger than those based on total variation distance and Kullback-Leibler
divergence. Therefore, we further develop a data-driven empirical risk
framework based on the -divergence privacy metric and realized using
deep neural networks. This framework is agnostic to the adversarial attack
model. Empirical experiments demonstrate the efficacy of our approach
Gate-tunable antiferromagnetic Chern insulator in twisted bilayer transition metal dichalcogenides
A series of recent experimental works on twisted MoTe homobilayers have
unveiled an abundance of exotic states in this system. Valley-polarized quantum
anomalous Hall states have been identified at hole doping of , and
the fractional quantum anomalous Hall effect is observed at and
. In this work, we investigate the electronic properties of
AA-stacked twisted bilayer MoTe at by -space Hartree-Fock
calculations. We find that the phase diagram is qualitatively similar to the
phase diagram of a Kane-Mele-Hubbard with staggered onsite potential. A
noteworthy phase within the diagram is the antiferromagnetic Chern insulator,
stabilized by the external electric field. We attribute the existence of this
Chern insulator to an antiferromagnetic instability at a topological phase
transition between the quantum spin hall phase and a band insulator phase. We
highlight that the antiferromagnetic Chern insulator phase is most evident at a
twist angle of approximately . Our research proposes the potential of
realizing a Chern insulator beyond , and contributes fresh perspectives
on the interplay between band topology and electron-electron correlations in
moir\'e superlattices
Gate-tunable phonon magnetic moment in bilayer graphene
We develop a first-principles quantum scheme to calculate the phonon magnetic
moment in solids. As a showcase example, we apply our method to study gated
bilayer graphene, a material with strong covalent bonds. According to the
classical theory based on the Born effective charge, the phonon magnetic moment
in this system should vanish, yet our quantum mechanical calculations find
significant phonon magnetic moments. Furthermore, the magnetic moment is highly
tunable by changing the gate voltage. Our results firmly establish the
necessity of the quantum mechanical treatment, and identify small-gap covalent
materials as a promising platform for studying tunable phonon magnetic moment.Comment: 6 pages, 3 figure
Arbitrarily Strong Utility-Privacy Tradeoff in Multi-Agent Systems
Each agent in a network makes a local observation that is linearly related to
a set of public and private parameters. The agents send their observations to a
fusion center to allow it to estimate the public parameters. To prevent leakage
of the private parameters, each agent first sanitizes its local observation
using a local privacy mechanism before transmitting it to the fusion center. We
investigate the utility-privacy tradeoff in terms of the Cram\'er-Rao lower
bounds for estimating the public and private parameters. We study the class of
privacy mechanisms given by linear compression and noise perturbation, and
derive necessary and sufficient conditions for achieving arbitrarily strong
utility-privacy tradeoff in a multi-agent system for both the cases where prior
information is available and unavailable, respectively. We also provide a
method to find the maximum estimation privacy achievable without compromising
the utility and propose an alternating algorithm to optimize the
utility-privacy tradeoff in the case where arbitrarily strong utility-privacy
tradeoff is not achievable
Optimization of the longitudinal-torsional ultrasonic step-like horn design for milling tool applications via the tool load account
Ultrasonic horns are used in the ultrasonic-assisted milling and cutting tools. However, the interaction with tool end vibrations deteriorates the horn performance. In this study, the amplification coefficients and vibration node locations of an ultrasonic horn were determined via the 1D wave theory and optimized by the tool load effect account. By arranging spiral grooves at the straight part of the ultrasonic horn, a longitudinal-torsional modal converter was introduced. This made it possible to convert longitudinal vibrations into longitudinal-torsional coupled ones by the superposition of incident and reflected longitudinal waves with reflected transverse ones at grooves. Orthogonal L9 (33) tests with parameters of spiral grooves as variables were designed and conducted, and longitudinal-torsional ratios (LTR) of the milling tool end under different conditions were assessed using the commercial ANSYS software package. The in-depth analysis of simulation results implies that the LTR values are controlled by the following influence factors in the decreasing order: helical angle, number of grooves, and groove width. Single-factor tests indicate that LTR exhibits an initial drop and a further rise with the helical angle, attaining its minimal value at 30°; it drops with the number of grooves n, and remains practically unchanged with the groove width variation. Finally, the vibration tests of the proposed horn with the optimized parameters corroborated its feasibility and demonstrated its excellent performance in the ultrasonic-assisted milling tool application
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