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Tensorization of the strong data processing inequality for quantum chi-square divergences

Quantum Physics 2019-10-30 v2 Information Theory Mathematical Physics math.IT math.MP

Abstract

It is well-known that any quantum channel E\mathcal{E} satisfies the data processing inequality (DPI), with respect to various divergences, e.g., quantum χκ2\chi^2_{\kappa}divergences and quantum relative entropy. More specifically, the data processing inequality states that the divergence between two arbitrary quantum states ρ\rho and σ\sigma does not increase under the action of any quantum channel E\mathcal{E}. For a fixed channel E\mathcal{E} and a state σ\sigma, the divergence between output states E(ρ)\mathcal{E}(\rho) and E(σ)\mathcal{E}(\sigma) might be strictly smaller than the divergence between input states ρ\rho and σ\sigma, which is characterized by the strong data processing inequality (SDPI). Among various input states ρ\rho, the largest value of the rate of contraction is known as the SDPI constant. An important and widely studied property for classical channels is that SDPI constants tensorize. In this paper, we extend the tensorization property to the quantum regime: we establish the tensorization of SDPIs for the quantum χκ1/22\chi^2_{\kappa_{1/2}} divergence for arbitrary quantum channels and also for a family of χκ2\chi^2_{\kappa} divergences (with κκ1/2\kappa \ge \kappa_{1/2}) for arbitrary quantum-classical channels.

Keywords

Cite

@article{arxiv.1904.06562,
  title  = {Tensorization of the strong data processing inequality for quantum chi-square divergences},
  author = {Yu Cao and Jianfeng Lu},
  journal= {arXiv preprint arXiv:1904.06562},
  year   = {2019}
}

Comments

Accepted by Quantum

R2 v1 2026-06-23T08:38:42.988Z