Optimized Entanglement Purification

We investigate novel protocols for entanglement purification of qubit Bell pairs. Employing genetic algorithms for the design of the purification circuit, we obtain shorter circuits achieving higher success rates and better final fidelities than what is currently available in the literature. We provide a software tool for analytical and numerical study of the generated purification circuits, under customizable error models. These new purification protocols pave the way to practical implementations of modular quantum computers and quantum repeaters. Our approach is particularly attentive to the effects of finite resources and imperfect local operations - phenomena neglected in the usual asymptotic approach to the problem. The choice of the building blocks permitted in the construction of the circuits is based on a thorough enumeration of the local Clifford operations that act as permutations on the basis of Bell states

Optimized Cartesian KK-Means

Product quantization-based approaches are effective to encode high-dimensional data points for approximate nearest neighbor search. The space is decomposed into a Cartesian product of low-dimensional subspaces, each of which generates a sub codebook. Data points are encoded as compact binary codes using these sub codebooks, and the distance between two data points can be approximated efficiently from their codes by the precomputed lookup tables. Traditionally, to encode a subvector of a data point in a subspace, only one sub codeword in the corresponding sub codebook is selected, which may impose strict restrictions on the search accuracy. In this paper, we propose a novel approach, named Optimized Cartesian $K$-Means (OCKM), to better encode the data points for more accurate approximate nearest neighbor search. In OCKM, multiple sub codewords are used to encode the subvector of a data point in a subspace. Each sub codeword stems from different sub codebooks in each subspace, which are optimally generated with regards to the minimization of the distortion errors. The high-dimensional data point is then encoded as the concatenation of the indices of multiple sub codewords from all the subspaces. This can provide more flexibility and lower distortion errors than traditional methods. Experimental results on the standard real-life datasets demonstrate the superiority over state-of-the-art approaches for approximate nearest neighbor search.Comment: to appear in IEEE TKDE, accepted in Apr. 201

Optimized Pre-Compensating Compression

In imaging systems, following acquisition, an image/video is transmitted or stored and eventually presented to human observers using different and often imperfect display devices. While the resulting quality of the output image may severely be affected by the display, this degradation is usually ignored in the preceding compression. In this paper we model the sub-optimality of the display device as a known degradation operator applied on the decompressed image/video. We assume the use of a standard compression path, and augment it with a suitable pre-processing procedure, providing a compressed signal intended to compensate the degradation without any post-filtering. Our approach originates from an intricate rate-distortion problem, optimizing the modifications to the input image/video for reaching best end-to-end performance. We address this seemingly computationally intractable problem using the alternating direction method of multipliers (ADMM) approach, leading to a procedure in which a standard compression technique is iteratively applied. We demonstrate the proposed method for adjusting HEVC image/video compression to compensate post-decompression visual effects due to a common type of displays. Particularly, we use our method to reduce motion-blur perceived while viewing video on LCD devices. The experiments establish our method as a leading approach for preprocessing high bit-rate compression to counterbalance a post-decompression degradation

Optimized Constant Pressure Stochastic Dynamics

A recently proposed method for computer simulations in the isothermal-isobaric (NPT) ensemble, based on Langevin-type equations of motion for the particle coordinates and the ``piston'' degree of freedom, is re-derived by straightforward application of the standard Kramers-Moyal formalism. An integration scheme is developed which reduces to a time-reversible symplectic integrator in the limit of vanishing friction. This algorithm is hence expected to be quite stable for small friction, allowing for a large time step. We discuss the optimal choice of parameters, and present some numerical test results.Comment: 16 pages, 2 figures, submitted to J. Chem. Phy

High-speed pulse train amplification in semiconductor optical amplifiers with optimized bias current

In this paper, we have experimentally investigated the optimized bias current of semiconductor optical amplifiers (SOAs) to achieve high-speed input pulse train amplification with high gain and low distortion. Variations of the amplified output pulse duration with the amplifier bias currents have been analyzed and, compared to the input pulse duration, the amplified output pulse duration is broadened. As the SOA bias current decreases from the high level (larger than the saturated bias current) to the low level, the broadened pulse duration of the amplified output pulse initially decreases slowly and then rapidly. Based on the analysis, an optimized bias current of SOA for high-speed pulse train amplification is introduced. The relation between the SOA optimized bias current and the parameters of the input pulse train (pulse duration, power, and repetition rate) are experimentally studied. It is found that the larger the input pulse duration, the lower the input pulse power or a higher repetition rate can lead to a larger SOA optimized bias current, which corresponds to a larger optimized SOA gain. The effects of assist light injection and different amplifier temperatures on the SOA optimized bias current are studied and it is found that assist light injection can effectively increase the SOA optimized bias current while SOA has a lower optimized bias current at the temperature 20°C than that at other temperatures