A Time Optimization Framework for the Implementation of Robust and Low-latency Quantum Circuits (2412.18533v1)

Abstract: Quantum computing has garnered attention for its potential to solve complex computational problems with considerable speedup. Despite notable advancements in the field, achieving meaningful scalability and noise control in quantum hardware remains challenging. Incoherent errors caused by decoherence restrict the total computation time, making it very short. While hardware advancements continue to progress, quantum software specialists seek to minimize quantum circuit latency to mitigate dissipation. However, at the pulse level, fast quantum gates often lead to leakage, leaving minimal room for further optimization. Recent advancements have shown the effectiveness of quantum control techniques in generating quantum gates robust to coherent error sources. Nevertheless, these techniques come with a trade-off -- extended gate durations. In this paper, we introduce an alternative pulse scheduling approach that enables the use of both fast and robust quantum gates within the same quantum circuit. The time-optimization framework models the quantum circuit as a dependency graph, implements the fastest quantum gates on the critical path, and uses idle periods outside the critical path to optimally implement longer, more robust gates from the gate set, without increasing latency. Experiments conducted on IBMQ Brisbane show that this approach improves the absolute success probability of quantum circuit execution by more than 25%, with performance gains scaling as the number of qubits increases.

• The paper introduces a pulse scheduling framework that balances fast, critical-path gates with longer, robust gates to minimize overall latency.
• It models quantum circuits as dependency graphs and applies the Critical Path Method to dynamically optimize pulse scheduling.
• Experiments on IBMQ Brisbane show over 25% improvement in success probability, highlighting the framework's practical impact.

A Time Optimization Framework for the Implementation of Robust and Low-latency Quantum Circuits

The paper addresses a pressing challenge in quantum computing related to reducing quantum circuit latency while managing the trade-off between speed and robustness in quantum gate operations. The authors put forward a novel pulse scheduling framework that efficiently balances the deployment of fast and robust quantum gates, optimizing execution time without an increase in overall latency.

Context and Motivation

Quantum computing has made significant strides due to its potential to outperform classical computing in solving complex problems. However, scalability and noise management remain key obstacles to realizing this potential. Quantum errors, particularly incoherent errors arising from decoherence, constrict computation time and hinder the reliable execution of quantum circuits. As quantum circuits grow in complexity, managing latency becomes crucial to minimize dissipation and improve computational outcomes.

Time reduction techniques, leveraging faster quantum gates, face inherent challenges. While fast gates can reduce latency, they often lead to leakage errors, undermining reliability. Conversely, techniques that fortify against errors, typically via extended gate durations, face increased vulnerability to decoherence effects. This necessitates a framework that judiciously combines the strengths of both fast and robust gates, a gap this paper seeks to bridge.

Methodology and Framework

The proposed framework models quantum circuits as dependency graphs, integrating techniques from the Critical Path Method (CPM) used in project management. The framework employs the CPM to identify the critical path within a circuit, subsequently deploying fast gates along this path to curtail latency. Non-critical zones leverage extended-duration gates, capitalizing on available idle periods to enhance robustness without elongating execution time.

Key methodological contributions include the representation of the circuit as a quantum operation dependency graph, and the application of algorithms that leverage idle periods for dynamic pulse scheduling. Herein, the approach transcends static pulse scheduling methods traditionally emphasizing uniform gate sets, allowing for a dynamic, circuit-specific gate optimization.

Experimental Setup and Results

Experiments conducted on the IBMQ Brisbane quantum computer corroborate the efficacy of the framework. Static and dynamic pulse scheduling methods were assessed through Randomized Benchmarking (RB), a method for validating the fidelity of quantum operations. The implementations demonstrated notable performance gains, with a success probability improvement of more than 25% in some scenarios, particularly for circuits with increasing qubit counts. The improvements underline the potential of the algorithm in ameliorating latency without compromising on gate fidelity.

Implications and Future Directions

The framework presented holds significant theoretical and practical implications. Theoretically, it advances a comprehensive method for quantum gate scheduling, underpinning the integration of fast and robust gates in quantum circuits. Practically, it improves the success probability of quantum circuits, a critical factor for applications requiring high computational accuracy and reliability.

Future developments could explore more sophisticated pulse shape calibrations beyond Gaussian pulses, incorporating adaptive AI-driven learning techniques to further refine gate scheduling on-the-fly. Additionally, scaling up experiments to larger qubit circuits could further elucidate the capabilities and constraints of the framework, facilitating its deployment in broader real-world quantum computing scenarios.

This research enriches the growing discourse on quantum error management, providing a robust pathway to harness the full potential of quantum computing through innovative gate scheduling strategies.