Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers (2001.02826v1)

Abstract: Crosstalk is a major source of noise in Noisy Intermediate-Scale Quantum (NISQ) systems and is a fundamental challenge for hardware design. When multiple instructions are executed in parallel, crosstalk between the instructions can corrupt the quantum state and lead to incorrect program execution. Our goal is to mitigate the application impact of crosstalk noise through software techniques. This requires (i) accurate characterization of hardware crosstalk, and (ii) intelligent instruction scheduling to serialize the affected operations. Since crosstalk characterization is computationally expensive, we develop optimizations which reduce the characterization overhead. On three 20-qubit IBMQ systems, we demonstrate two orders of magnitude reduction in characterization time (compute time on the QC device) compared to all-pairs crosstalk measurements. Informed by these characterization, we develop a scheduler that judiciously serializes high crosstalk instructions balancing the need to mitigate crosstalk and exponential decoherence errors from serialization. On real-system runs on three IBMQ systems, our scheduler improves the error rate of application circuits by up to 5.6x, compared to the IBM instruction scheduler and offers near-optimal crosstalk mitigation in practice. In a broader picture, the difficulty of mitigating crosstalk has recently driven QC vendors to move towards sparser qubit connectivity or disabling nearby operations entirely in hardware, which can be detrimental to performance. Our work makes the case for software mitigation of crosstalk errors.

• The paper introduces an efficient crosstalk characterization method using targeted measurements based on qubit risk factors.
• The paper proposes an innovative SMT-based scheduling algorithm that minimizes cumulative errors in quantum circuits.
• The paper validates its approach with experiments on IBMQ devices, achieving up to a 5.6x reduction in error rates compared to baseline schedulers.

Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers

The paper "Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers" delves deeply into one of the critical issues affecting the fidelity of Noisy Intermediate-Scale Quantum (NISQ) systems—crosstalk noise. Crosstalk arises when multiple quantum gates execute simultaneously, leading to unwanted interactions that corrupt quantum states. This paper suggests that software solutions can effectively mitigate these errors, complementing or potentially substituting hardware-based solutions currently being pursued.

Key Contributions

1. Crosstalk Characterization: The authors provide an approach to efficiently characterize crosstalk in quantum systems. They reduce the computational overhead of this process by performing targeted measurements only on qubit pairs at risk of experiencing crosstalk, as determined by the device's physical layout and operating properties.
2. Instruction Scheduling for Crosstalk Mitigation: An innovative scheduling algorithm is introduced to balance between minimizing crosstalk and decoherence errors. By modeling scheduling as an optimization problem solved through Satisfiability Modulo Theory (SMT), the algorithm judiciously schedules quantum gates to minimize cumulative error in quantum circuits.
3. Practical Improvement in Error Rates: Real-system experiments demonstrate the effectiveness of the proposed scheduler. For instance, on the tested IBMQ devices, the error rates for circuits using the proposed scheduler improved by up to 5.6x in comparison to baseline schedulers.
4. Mitigation Insights for Future Architectures: The results argue against solely hardware-based solutions, such as more sparsely connected qubits, by showing that intelligent software can deliver substantial improvements in error rates. This is a significant consideration as the architectural complexity and qubit count increase.

Implications

On a theoretical level, this work highlights the potential of combining system-level characterization with compiler optimizations to tackle hardware imperfections. As quantum devices scale, such integrated approaches could become indispensable, challenging the current tendency to rely predominantly on hardware noise reduction.

Practically, the paper provides a roadmap for enhancing current quantum computing platforms' reliability, making them more viable for executing quantum algorithms. The integration within IBM's Qiskit framework indicates practicality and immediate applicability for users of IBMQ systems.

Future Directions

Several directions emerge from this foundational work:

• Extension to Different Quantum Architectures: While demonstrated on superconducting qubits, similar methods could be adapted for other architectures like trapped ions or photonic systems.
• Dynamic Scheduling: As classical computing has adopted dynamic scheduling to account for various run-time characteristics, extending these ideas to quantum computers could accommodate varying levels of noise and decoherence during operation.
• Joint Hardware-Software Co-Design: Encouraging collaborations between hardware developers and quantum compiler engineers could lead to more specialized solutions that further leverage both the strengths of hardware design and the flexibility of software.

In conclusion, by focusing on the software layer, this paper shifts some focus from hardware limitations, providing a complementary approach that could significantly elevate current quantum systems' operational capacity. With rapid advancements underway in quantum computing, tools such as the ones proposed here will be pivotal in bridging the gap between prototype quantum systems and practical quantum computing applications.