Compression of Deep Neural Networks on the Fly

Thanks to their state-of-the-art performance, deep neural networks are increasingly used for object recognition. To achieve these results, they use millions of parameters to be trained. However, when targeting embedded applications the size of these models becomes problematic. As a consequence, their usage on smartphones or other resource limited devices is prohibited. In this paper we introduce a novel compression method for deep neural networks that is performed during the learning phase. It consists in adding an extra regularization term to the cost function of fully-connected layers. We combine this method with Product Quantization (PQ) of the trained weights for higher savings in storage consumption. We evaluate our method on two data sets (MNIST and CIFAR10), on which we achieve significantly larger compression rates than state-of-the-art methods

Efficient Scheme for Perfect Collective Einstein-Podolsky-Rosen Steering

A practical scheme for the demonstration of perfect one-sided device-independent quantum secret sharing is proposed. The scheme involves a three-mode optomechanical system in which a pair of independent cavity modes is driven by short laser pulses and interact with a movable mirror. We demonstrate that by tuning the laser frequency to the blue (anti-Stokes) sideband of the average frequency of the cavity modes, the modes become mutually coherent and then may collectively steer the mirror mode to a perfect Einstein-Podolsky-Rosen state. The scheme is shown to be experimentally feasible, it is robust against the frequency difference between the modes, mechanical thermal noise and damping, and coupling strengths of the cavity modes to the mirror.Comment: 9 pages, 4 figure

Aspects of Floquet Bands and Topological Phase Transitions in a Continuously Driven Superlattice

Recently the creation of novel topological states of matter by a periodic driving field has attracted great attention. To motivate further experimental and theoretical studies, we investigate interesting aspects of Floquet bands and topological phase transitions in a continuously driven Harper model. In such a continuously driven system with an odd number of Floquet bands, the bands are found to have nonzero Chern numbers in general and topological phase transitions take place as we tune various system parameters, such as the amplitude or the period of the driving field. The nontrivial Floquet band topology results in a quantized transport of Wannier states in the lattice space. For certain parameter choices, very flat yet topologically nontrivial Floquet bands may also emerge, a feature that is potentially useful for the simulation of physics of strongly correlated systems. Some cases with an even number of Floquet bands may also have intriguing Dirac cones in the spectrum. Under open boundary conditions, anomalous counter-propagating chiral edge modes and degenerate zero modes are also found as the system parameters are tuned. These results should be of experimental interest because a continuously driven system is easier to realize than a periodically kicked system.Comment: 29 pages, 9 figures. Comments are welcom