Estimating the electrical energy cost of performing arbitrary state preparation using qubits and qudits in integrated photonic circuits

Abstract

As quantum photonic hardware scales toward computationally relevant sizes, energy consumption has emerged as a key constraint. Programmable photonic integrated circuits, composed of interferometer meshes with tunable phase modulators, provide a flexible platform for quantum information processing using both qubits and qudits. In this work, we analyze the energetic cost of such devices by focusing on arbitrary quantum state preparation, a resource-intensive task central to quantum simulation and information processing. Using a common hardware, we benchmark qudit-based implementations, gate-based quantum computation, and measurement-based quantum computation. We find that while qudit encodings are attractive at small scale, their footprint and reconfiguration costs grow rapidly with system size, whereas qubit-based approaches incur significant overhead from entangling operations, feedforward, and reprogramming. Across all paradigms, scaling beyond a few tens of qubits renders either the energy consumption or the total preparation time prohibitive on fully programmable PICs. Our results highlight the need for optimized, task-specific photonic architectures to enable energy-efficient scaling.

arXiv comment24 pages, 8 figures. Re-organization of the paper adding estimatives for MBQC and new protocol for GBQC