Representations of Inverse Functions by the Integral Transform with the Sign Kernel

Mathematics Subject Classification: Primary 30C40In this paper we give practical and numerical representations of inverse functions by using the integral transform with the sign kernel, and show corresponding numerical experiments by using computers. We derive a very simple formula from a general idea for the representation of the inverse functions, based on the theory of reproducing kernels

General treatment of Gaussian trusted noise in continuous variable quantum key distribution

Continuous Variable (CV) quantum key distribution (QKD) is a promising candidate for practical implementations due to its compatibility with the existing communication technology. A trusted device scenario assuming that an adversary has no access to imperfections such as electronic noises in the detector is expected to provide significant improvement in the key rate, but such an endeavor so far was made separately for specific protocols and for specific proof techniques. Here, we develop a simple and general treatment that can incorporate the effects of Gaussian trusted noises for any protocol that uses homodyne/heterodyne measurements. In our method, a rescaling of the outcome of a noisy homodyne/heterodyne detector renders it equivalent to the outcome of a noiseless detector with a tiny additional loss, thanks to a noise-loss equivalence well-known in quantum optics. Since this method is independent of protocols and security proofs, it is applicable to Gaussian-modulation and discrete-modulation protocols, to the finite-size regime, and to any proof techniques developed so far and yet to be discovered as well.Comment: 7 pages, 4 figure