Abstract:

Quantum computers are expected to overcome the curse of dimensionality and allow for more complex chemical simulations in disciplines ranging from quantum dynamics to electronic structure theory. Given the noise on present-day quantum computers, error mitigation methods are essential in order to use quantum computers to accurately simulate chemical systems. However, existing quantum error mitigation methods frequently require significant overhead, call for unrealistically accurate noise models, scale poorly in the face of high error, or are specific to certain error types or applications.
In order to circumvent these difficulties, we introduce the Random Inverse Depolarizing Approximation (RIDA) method, which models the global noise channel as a depolarizing channel and determines the depolarization probability of each circuit by running a randomly extracted half of the circuit followed by its inverse. RIDA then inverts the noise channel to estimate the error-free expectation via amplification of the noisy expectation value.
The resulting RIDA method requires minimal overhead, simultaneously mitigates both gate and measurement error, scales well to high errors, requires no prior noise model information, and applies to any quantum circuit of interest. In numerical experiments on simulated quantum computers, we show RIDA achieves lower error than both the benchmark zero-noise extrapolation method and a state-of-the-art method which uses only CNOT gates to estimate depolarization. This persists across the full range of expectation values, circuit sizes, error levels, and numbers of shots used, including 75% less error than the next best method in low-error, low-shot tests and 89% less error in high-error, high-shot tests.
These advantages bode well for the immediate practical use of RIDA to accelerate the potential of near-term quantum computing to simulate complicated molecular processes essential to fields ranging from pharmaceutical development to materials science.

Presenter:

Alexander Miller, Stanford University

Alexander Miller is an incoming freshman at Stanford University planning to major in physics and computer science. He has conducted research on quantum computing algorithms for two years under Dr. Micheline Soley, specifically with an eye towards chemistry applications.