Implementing two-qubit gates at the quantum speed limit

TL;DR

This paper demonstrates two-qubit gates at the quantum speed limit using machine learning-based optimal control, significantly enhancing the speed of quantum operations in superconducting qubits.

Contribution

It introduces a method to implement two-qubit gates at the quantum speed limit with high fidelity, applicable across various quantum platforms.

Findings

Achieved two-qubit gates near the quantum speed limit

Method requires only moderate increase in single-qubit drive strength

Potential for speeding up non-native two-qubit gates

Abstract

The speed of elementary quantum gates, particularly two-qubit gates, ultimately sets the limit on the speed at which quantum circuits can operate. In this work, we experimentally demonstrate commonly used two-qubit gates at nearly the fastest possible speed allowed by the physical interaction strength between two superconducting transmon qubits. We achieve this quantum speed limit by implementing experimental gates designed using a machine learning inspired optimal control method. Importantly, our method only requires the single-qubit drive strength to be moderately larger than the interaction strength to achieve an arbitrary two-qubit gate close to its analytical speed limit with high fidelity. Thus, the method is applicable to a variety of platforms including those with comparable single-qubit and two-qubit gate speeds, or those with always-on interactions. We expect our method to offer significant speedups for non-native two-qubit gates that are typically achieved with a long sequence of single-qubit and native two-qubit gates.