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A quantum key distribution (QKD) system must fulfill the requirement of universal composability to ensure that any cryptographic application (using the QKD system) is also secure. Furthermore, the theoretical proof responsible for security analysis and key generation should cater to the number N of the distributed quantum states being finite in practice. Continuous-variable (CV) QKD based on coherent states, despite being a suitable candidate for integration in the telecom infrastructure, has so far been unable to demonstrate composability as existing proofs require a rather large N for successful key generation. Here we report a Gaussian-modulated coherent state CVQKD system that is able to overcome these challenges and can generate composable keys secure against collective attacks with N ≈ 2 × 108 coherent states. With this advance, possible due to improvements to the security proof and a fast, yet low-noise and highly stable system operation, CVQKD implementations take a significant step towards their discrete-variable counterparts in practicality, performance, and security.

The rapid progress of computer technology has been accompanied by a corresponding evolution of software development, from hardwired components and binary machine code to high level programming languages, which allowed to master the increasing hardware complexity and fully exploit its potential. This paper investigates, how classical concepts like hardware abstraction, hierarchical programs, data types, memory management, flow of control and structured programming can be used in quantum computing. The experimental language QCL will be introduced as an example, how elements like irreversible functions, local variables and conditional branching, which have no direct quantum counterparts, can be implemented, and how non-classical features like the reversibility of unitary transformation or the non-observability of quantum states can be accounted for within the framework of a procedural programming language.1 Quantum Programming Quantum Programming LanguagesFrom a software engineering point of view, we can regard the formalism of Hilbert-space algebra as a specification language, as the mathematical description of a quantum algorithm is inherently declarative and provides no means to derive a unique decomposition into elementary operations for a given quantum hardware.Low level formalisms like quantum circuits [4], on the other hand, are usually restricted to specific tasks, such as the description of unitary transformations, and thus lack the generality to express all aspects of non-classical algorithms.The purpose of programming languages is therefore twofold, as they allow to express the semantics of the computation in an abstract manner, as well as the automated generation of a sequence of elementary operations to control the computing device.

Continuous-variable quantum key distribution (QKD) utilizes an ensemble of coherent states of light to distribute secret encryption keys between two parties. An essential ingredient of the QKD protocol is highly efficient information reconciliation. To achieve highly efficient reconciliation, error-correcting codes with a low channel coding rate are inevitable in the most common schemes of multilevel coding and multistage decoding (MLC-MSD) and multidimensional reconciliation. Multiedge-type (MET) low-density parity-check (LDPC) codes are well suited for highly efficient reconciliation at low rates. Here, we calculate the optimal channel coding rates in the MLC-MSD scheme for reverse reconciliation, introduce the concept of generalized extrinsic information transfer charts for MET-LDPC codes, which constitute a simple and fast asymptotic analysis tool, and present a set of MET-LDPC codes with asymptotic efficiency >97% for channel coding rates 0.1, 0.05, 0.02, and 0.01. We believe that our codes will find wide application in implementations of continuous-variable quantum key distribution based on Gaussian modulation.

Abstract. We report on work to parallelize QC-lib, a C++ library for the simulation of quantum computers at an abstract functional level. After a brief introduction to quantum computing, we give an outline of QClib, then describe its parallelization using MPI, and present performance measurements made on a Beowulf cluster. Using more processors allowed larger problems to be solved, and reasonable speedups were obtained for the Hadamard transform and Grover's quantum search algorithm.