Pulse-efficient circuit transpilation for quantum applications on cross-resonance-based hardware
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
We show a pulse-efficient circuit transpilation framework for noisy quantum hardware. This is achieved by scaling cross-resonance pulses and exposing each pulse as a gate to remove redundant single-qubit operations with the transpiler.Crucially, no additional calibration is needed to yield better results than a CNOT-based transpilation. This pulse-efficient circuit transpilation therefore enables a better usage of the finite coherence time without requiring knowledge of pulse-level details from the user. As demonstration, we realize a continuous family of cross-resonance-based gates for SU(4) by leveraging Cartan's decomposition. We measure the benefits of a pulse-efficient circuit transpilation with process tomography and observe up to a 50% error reduction in the fidelity of RZZ({\theta}) and arbitrary SU(4) gates on IBM Quantum devices.We apply this framework for quantum applications by running circuits of the Quantum Approximate Optimization Algorithm applied to MAXCUT. For an 11 qubit non-hardware native graph, our methodology reduces the overall schedule duration by up to 52% and errors by up to 38%