Strong converse for the classical capacity of the pure-loss bosonic channel

TL;DR

This paper establishes a strong converse for the classical capacity of the pure-loss bosonic channel, showing that under a maximum photon number constraint, the capacity cannot be exceeded, and demonstrates a coding scheme that meets this constraint.

Contribution

It proves a strong converse theorem for the channel's capacity under maximum photon number constraints and proposes a compatible coding scheme.

Findings

Strong converse holds under maximum photon number constraint.

Trade-off exists between rate and error probability under mean-photon constraint.

A modified coherent-state coding scheme meets the maximum photon number constraint.

Abstract

This paper strengthens the interpretation and understanding of the classical capacity of the pure-loss bosonic channel, first established in [Giovannetti et al., Physical Review Letters 92, 027902 (2004), arXiv:quant-ph/0308012]. In particular, we first prove that there exists a trade-off between communication rate and error probability if one imposes only a mean-photon number constraint on the channel inputs. That is, if we demand that the mean number of photons at the channel input cannot be any larger than some positive number N_S, then it is possible to respect this constraint with a code that operates at a rate g(\eta N_S / (1-p)) where p is the code's error probability, \eta\ is the channel transmissivity, and g(x) is the entropy of a bosonic thermal state with mean photon number x. We then prove that a strong converse theorem holds for the classical capacity of this channel (that such a rate-error trade-off cannot occur) if one instead demands for a maximum photon number constraint, in such a way that mostly all of the "shadow" of the average density operator for a given code is required to be on a subspace with photon number no larger than n N_S, so that the shadow outside this subspace vanishes as the number n of channel uses becomes large. Finally, we prove that a small modification of the well-known coherent-state coding scheme meets this more demanding constraint.