Write-Once-Memory Codes by Source Polarization

We propose a new Write-Once-Memory (WOM) coding scheme based on source polarization. By applying a source polarization transformation on the to-be-determined codeword, the proposed WOM coding scheme encodes information into the bits in the high-entropy set. We prove in this paper that the proposed WOM codes are capacity-achieving. WOM codes have found many applications in modern data storage systems, such as flash memories.Comment: 5 pages, Proceedings of the International Conference on Computing, Networking and Communications (ICNC 2015), Anaheim, California, USA, February 16-19, 201

The Cosmic Linear Anisotropy Solving System (CLASS) I: Overview

The Cosmic Linear Anisotropy Solving System (CLASS) is a new accurate Boltzmann code, designed to offer a more user-friendly and flexible coding environment to cosmologists. CLASS is very structured, easy to modify, and offers a rigorous way to control the accuracy of output quantities. It is also incidentally a bit faster than other codes. In this overview, we present the general principles of CLASS and its basic structure. We insist on the friendliness and flexibility aspects, while accuracy, physical approximations and performances are discussed in a series of companion papers.Comment: 19 pages, typos corrected. Code available at http://class-code.ne

Optical Quantum Computation

We review the field of Optical Quantum Computation, considering the various implementations that have been proposed and the experimental progress that has been made toward realizing them. We examine both linear and nonlinear approaches and both particle and field encodings. In particular we discuss the prospects for large scale optical quantum computing in terms of the most promising physical architectures and the technical requirements for realizing them

Universal Polarization

A method to polarize channels universally is introduced. The method is based on combining two distinct channels in each polarization step, as opposed to Arikan's original method of combining identical channels. This creates an equal number of only two types of channels, one of which becomes progressively better as the other becomes worse. The locations of the good polarized channels are independent of the underlying channel, guaranteeing universality. Polarizing the good channels further with Arikan's method results in universal polar codes of rate 1/2. The method is generalized to construct codes of arbitrary rates. It is also shown that the less noisy ordering of channels is preserved under polarization, and thus a good polar code for a given channel will perform well over a less noisy one.Comment: Submitted to the IEEE Transactions on Information Theor