A programmable quantum system consisting of merely 50 to 100 qubits could revolutionize scientific research. While such a platform is naturally suited to address problems in quantum chemistry and materials science, applications range to fields as far as classical dynamics and computer science. A key milestone on the path towards realizing these applications will be the demonstration of an algorithm which exceeds the capabilities of any classical computer -achieving quantum supremacy. Sampling problems are an iconic example of algorithms designed specifically for this purpose. A successful demonstration of quantum supremacy would prove that engineered quantum systems, while still in their infancy, can outperform the most advanced classical computers.
Storing the state of a 46-qubit system takes nearly a petabyte of memory and is at the limit of the most powerful computers. Sampling from the output probabilities of such a system would therefore constitute a clear demonstration of quantum supremacy.
Google, UCSB and NASA have demonstrated an immediate path towards quantum supremacy. They show that the algorithm complexity scales exponentially with the number of qubits and can be implemented with high fidelity. If similar error rates are achievable in future devices with around 50 qubits, they will be able to explore quantum dynamics that are inaccessible otherwise.
Fundamental questions in chemistry and physics may never be answered due to the exponential complexity of the underlying quantum phenomena. A desire to overcome this challenge has sparked a new industry of quantum technologies with the promise that engineered quantum systems can address these hard problems. A key step towards demonstrating such a system will be performing a computation beyond the capabilities of any classical computer, achieving so-called quantum supremacy. Here, using 9 superconducting qubits, we demonstrate an immediate path towards quantum supremacy. By individually tuning the qubit parameters, we are able to generate thousands of unique Hamiltonian evolutions and probe the output probabilities. The measured probabilities obey a universal distribution, consistent with uniformly sampling the full Hilbert-space. As the number of qubits in the algorithm is varied, the system continues to explore the exponentially growing number of states. Combining these large datasets with techniques from machine learning allows us to construct a model which accurately predicts the measured probabilities. We demonstrate an application of these algorithms by systematically increasing the disorder and observing a transition from delocalized states to localized states. By extending these results to a system of 50 qubits, we hope to address scientific questions that are beyond the capabilities of any classical computer.
Arxiv – A blueprint for demonstrating quantum supremacy with superconducting qubits
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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