Architectural Foundations for Checkpointing and Restoration in Quantum HPC Systems

2026-02-10

AI Summary

Current quantum high-performance computing systems lack effective fault-tolerance and recovery mechanisms, and conventional checkpointing approaches based on quantum state preservation are fundamentally hindered by the no-cloning theorem. This work proposes a novel algorithm-level fault-tolerance framework that reframes checkpointing and recovery as problems of control flow and algorithmic state management, thereby avoiding direct storage of quantum states. Instead, it leverages mid-circuit measurements, classical feedforward, and conditional operations in dynamic quantum circuits to efficiently capture and restore program execution states. The approach enables reliable interruption and resumption for representative iterative or staged quantum algorithms—including variational eigensolvers, the Quantum Approximate Optimization Algorithm (QAOA), and time-stepping simulations—significantly enhancing the reliability and restartability of quantum computational tasks.

Technology Category

• Machine Learning: Quantum Machine Learning
• Reasoning under Uncertainty: Stochastic Optimization
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Responsible Web: Algorithmic accountability and transparency on the web
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

In this work, we explore the design of the checkpointing and restoration for quantum HPC that leverages dynamic circuit technology to enable restartable and resilient quantum execution. Rather than attempting to checkpoint quantum states, our approach redefines checkpointing as a control flow and algorithmic state problem. By exploiting mid-circuit measurements, classical feed forward, and conditional execution supported by dynamic circuits, we capture sufficient program state to allow correct restoration of quantum workflows after interruption or failure. This design aligns naturally with iterative and staged quantum algorithms such as variational eigensolvers, quantum approximate optimization, and time-stepping methods commonly used in quantum simulation and scientific computing.

Problem

• checkpointing
• quantum HPC
• restoration
• fault tolerance
• quantum computing

Innovation

• quantum checkpointing
• dynamic circuits
• mid-circuit measurement
• fault tolerance
• quantum HPC