[Submitted on 29 May 2026 (v1), last revised 28 Jul 2026 (this version, v2)]

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Abstract:This paper introduces a new framework for quantum simultaneous information and power transfer (QSIPT), enabling the joint use of quantum states for classical information and energy transfer in quantum communication systems. We propose a model in which quantum states simultaneously transmit classical information through a quantum channel and transfer energy to an energy harvesting (EH) receiver. The trade-off between communication rate and harvested energy is characterized by the capacity-power function, defined for both discrete-variable (DV) and continuous-variable (CV) quantum channels. For DV channels, we derive properties of the capacity-power function, providing analytical upper and lower bounds for the amplitude damping channel and an exact closed-form characterization for the quantum erasure channel. For CV channels, we extend the framework by introducing a generalized beam-splitter (BS) receiver with adjustable transmissivity, jointly optimized with a transmitter mean-photon-number budget, splitting the channel output between the information decoder and the EH receiver. We analyze the capacity-power and achievable-rate-power trade-off under various Gaussian encoding schemes, including coherent, squeezed, and thermal states, for both lossy bosonic and additive Gaussian noise channels. Closed-form expressions are derived for coherent-state encoding under the joint photon-number-budget and adjustable-transmissivity formulation; squeezed-state inputs are evaluated numerically. Our results show that, within the considered displaced Gaussian encoding class, coherent states achieve the best capacity-power trade-off, squeezed states do not outperform coherent-state encoding under the phase-insensitive channel and passive receiver architecture, and thermal states enable energy transfer without supporting reliable communication.

Submission history

From: Nizar Khalfet [view email]
[v1] Fri, 29 May 2026 22:48:55 UTC (298 KB)
[v2] Tue, 28 Jul 2026 13:20:34 UTC (298 KB)