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