Beyond-classical computation in quantum simulation

Area of Science:

• Quantum Computing
• Computational Physics
• Quantum Simulation

Background:

• Classical computers face limitations in solving complex quantum mechanical problems.
• Quantum annealers offer a potential pathway to overcome these computational barriers.

Purpose of the Study:

• To demonstrate the capability of superconducting quantum annealing processors for solving the Schrödinger equation.
• To compare the performance of quantum annealers against leading classical approximation methods.

Main Methods:

• Utilizing superconducting quantum annealing processors to generate samples.
• Analyzing the quench dynamics of spin glasses in various dimensions.
• Comparing results with matrix-product-state, tensor network, and neural network approaches.

Main Results:

• Quantum annealers rapidly produced samples in close agreement with Schrödinger equation solutions.
• Area-law scaling of entanglement was observed in spin glass dynamics.
• Classical methods (tensor networks, neural networks) could not match quantum annealer accuracy in a timely manner.

Conclusions:

• Superconducting quantum annealers can efficiently solve problems intractable for classical computation.
• Quantum annealers provide a practical tool for addressing significant scientific questions.
• The findings support the potential of quantum computing for advancing scientific discovery.