105,432 research outputs found
Adiabatic State Conversion and Pulse Transmission in Optomechanical Systems
Optomechanical systems with strong coupling can be a powerful medium for
quantum state engineering. Here, we show that quantum state conversion between
cavity modes with different wavelengths can be realized with high fidelity by
adiabatically varying the effective optomechanical couplings. The fidelity for
the conversion of gaussian states is derived by solving the Langevin equation
in the adiabatic limit. We also show that photon pulses can be transmitted
between input-output channels with different wavelengths via the effective
optomechanical couplings and the output pulse shape can also be manipulated.Comment: 5 pages, 2 figures. Supplementary Materials at
http://prl.aps.org/supplemental/PRL/v108/i15/e15360
Statistical Modelling of Information Sharing: Community, Membership and Content
File-sharing systems, like many online and traditional information sharing
communities (e.g. newsgroups, BBS, forums, interest clubs), are dynamical
systems in nature. As peers get in and out of the system, the information
content made available by the prevailing membership varies continually in
amount as well as composition, which in turn affects all peers' join/leave
decisions. As a result, the dynamics of membership and information content are
strongly coupled, suggesting interesting issues about growth, sustenance and
stability.
In this paper, we propose to study such communities with a simple statistical
model of an information sharing club. Carrying their private payloads of
information goods as potential supply to the club, peers join or leave on the
basis of whether the information they demand is currently available.
Information goods are chunked and typed, as in a file sharing system where
peers contribute different files, or a forum where messages are grouped by
topics or threads. Peers' demand and supply are then characterized by
statistical distributions over the type domain.
This model reveals interesting critical behaviour with multiple equilibria. A
sharp growth threshold is derived: the club may grow towards a sustainable
equilibrium only if the value of an order parameter is above the threshold, or
shrink to emptiness otherwise. The order parameter is composite and comprises
the peer population size, the level of their contributed supply, the club's
efficiency in information search, the spread of supply and demand over the type
domain, as well as the goodness of match between them.Comment: accepted in International Symposium on Computer Performance,
Modeling, Measurements and Evaluation, Juan-les-Pins, France, October-200
Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks
This work shows that it is possible to fool/attack recent state-of-the-art
face detectors which are based on the single-stage networks. Successfully
attacking face detectors could be a serious malware vulnerability when
deploying a smart surveillance system utilizing face detectors. We show that
existing adversarial perturbation methods are not effective to perform such an
attack, especially when there are multiple faces in the input image. This is
because the adversarial perturbation specifically generated for one face may
disrupt the adversarial perturbation for another face. In this paper, we call
this problem the Instance Perturbation Interference (IPI) problem. This IPI
problem is addressed by studying the relationship between the deep neural
network receptive field and the adversarial perturbation. As such, we propose
the Localized Instance Perturbation (LIP) that uses adversarial perturbation
constrained to the Effective Receptive Field (ERF) of a target to perform the
attack. Experiment results show the LIP method massively outperforms existing
adversarial perturbation generation methods -- often by a factor of 2 to 10.Comment: to appear ECCV 2018 (accepted version
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