Recoverable Quantum Computation: An Information-Centric Paradigm for Quantum Computing with Errors

Abstract

Quantum computing promises transformative advances in computation, communication, sensing, and machine learning. Yet the realization of large-scale fault-tolerant quantum computers remains hindered by the enormous overhead required for quantum error correction. This challenge raises a fundamental question: Must useful quantum computing wait until fully fault-tolerant quantum hardware becomes available? In this Perspective, we propose Recoverable Quantum Computation (RQC), an information-centric paradigm for quantum computing with errors. Rather than requiring faithful preservation of the complete quantum state, RQC focuses on preserving the computational information required to accomplish a given task. A quantum computation is considered recoverable if the desired computational information can be extracted from noisy quantum outputs with an overhead that preserves quantum advantage relative to the best known classical method. We introduce recoverability as an operational principle for evaluating noisy quantum computations and propose practical metrics based on recovery overhead and recoverability efficiency. We illustrate the framework using quantum Fourier transform period estimation on IBM quantum hardware and a conceptual example from quantum machine learning, demonstrating that useful computational information may remain recoverable despite significant physical errors. Building on these examples, we propose a preliminary classification of quantum applications according to their expected recoverability and outline a research roadmap toward a predictive theory of recoverability. RQC is intended not as an alternative to fault-tolerant quantum computing, but as a complementary paradigm for understanding and evaluating useful quantum computation in the broad intermediate regime between today's noisy quantum processors and tomorrow's fault-tolerant quantum computers.