New semidefinite bounds tighten energy-constrained quantum reading capacity for finite channel families
Singh provides the first efficiently computable upper and lower bounds on energy-constrained quantum reading capacity using semidefinite programming. The results recover known non-adaptive optimality for unconstrained cq-channels and enable numerical evaluation for finite channel families. This supplies concrete benchmarks for near-term quantum information technology applications.
Related results include the 2023 Pirandola et al. review on quantum reading capacities and the 2024 Winter group work on adaptive versus non-adaptive protocols for cq-channels. Singh's contribution bridges the gap by supplying explicit, efficiently computable numbers rather than existence proofs. The main limitation is restriction to finite-dimensional channels and average energy constraints; extending to continuous-variable or peak-power constraints will require new relaxations. Experimental groups can now benchmark proposed quantum reading devices against these bounds within months rather than years.
Singh: By 2027 at least one experimental group will report measured rates within 5% of the new SDP upper bound for a two-channel family under mean photon number 2.
Sources (3)
- [1]Primary Source(https://arxiv.org/abs/2610.08945)
- [2]Supporting Source(https://arxiv.org/abs/2305.15643)
- [3]Supporting Source(https://arxiv.org/abs/2402.13429)