Scalable Compression of Deep Neural Networks

Deep neural networks generally involve some layers with mil- lions of parameters, making them difficult to be deployed and updated on devices with limited resources such as mobile phones and other smart embedded systems. In this paper, we propose a scalable representation of the network parameters, so that different applications can select the most suitable bit rate of the network based on their own storage constraints. Moreover, when a device needs to upgrade to a high-rate network, the existing low-rate network can be reused, and only some incremental data are needed to be downloaded. We first hierarchically quantize the weights of a pre-trained deep neural network to enforce weight sharing. Next, we adaptively select the bits assigned to each layer given the total bit budget. After that, we retrain the network to fine-tune the quantized centroids. Experimental results show that our method can achieve scalable compression with graceful degradation in the performance.Comment: 5 pages, 4 figures, ACM Multimedia 201

Generating continuous variable quantum codewords in the near-field atomic lithography

Recently, D. Gottesman et al. [Phys. Rev. A 64, 012310 (2001)] showed how to encode a qubit into a continuous variable quantum system. This encoding was realized by using non-normalizable quantum codewords, which therefore can only be approximated in any real physical setup. Here we show how a neutral atom, falling through an optical cavity and interacting with a single mode of the intracavity electromagnetic field, can be used to safely encode a qubit into its external degrees of freedom. In fact, the localization induced by a homodyne detection of the cavity field is able to project the near-field atomic motional state into an approximate quantum codeword. The performance of this encoding process is then analyzed by evaluating the intrinsic errors induced in the recovery process by the approximated form of the generated codeword.Comment: 9 pages, 5 figure

Squashed States of Light: Theory and Applications to Quantum Spectroscopy

Using a feedback loop it is possible to reduce the fluctuations in one quadrature of an in-loop field without increasing the fluctuations in the other. This effect has been known for a long time, and has recently been called ``squashing'' [B.C. Buchler et al., Optics Letters {\bf 24}, 259 (1999)], as opposed to the ``squeezing'' of a free field in which the conjugate fluctuations are increased. In this paper I present a general theory of squashing, including simultaneous squashing of both quadratures and simultaneous squeezing and squashing. I show that a two-level atom coupled to the in-loop light feels the effect of the fluctuations as calculated by the theory. In the ideal limit of light squeezed in one quadrature and squashed in the other, the atomic decay can be completely suppressed.Comment: 8 pages plus one figure. Submitted to JEOS-B for Dan Walls Special Issu

A bio-inspired image coder with temporal scalability

We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalian retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, our decoded images do not show annoying artefacts such as ringing and block effects. As a whole, this article shows how to capture the main properties of a biological system, here the retina, in order to design a new efficient coder.Comment: 12 pages; Advanced Concepts for Intelligent Vision Systems (ACIVS 2011

Experimental test of modular noise propagation theory for quantum optics

We present and test against experiment a general technique that allows modular modeling of noise propagation in quantum optics experiments. Specifically, we consider a multielement frequency-doubling experiment that ultimately produces 1.7 dB/32% (3.0 dB/50% inferred) squeezing at 532 nm. Unlike previous theoretical treatments, we obtain completely analytical expressions for each element of the experiment. This allows intuitive analysis and straightforward experimental modeling. The exact role of driving noise is demonstrated: addition of a narrow linewidth mode cleaning cavity to reduce the driving noise improves the inferred squeezing from 0.75 to 3.0 dB. We find excellent agreement between the modular theory and experiment

Ponderomotive entangling of atomic motions

We propose the use of ponderomotive forces to entangle the motions of different atoms. Two situations are analyzed: one where the atoms belong to the same optical cavity and interact with the same radiation field mode; the other where each atom is placed in own optical cavity and the output field of one cavity enters the other.Comment: Revtex file, five pages, two eps figure

Broadly Tunable External Cavity Quantum Cascade Laser Development

FY07 final report for Laser Development task of ITAS project