Collaborative Research: PIF: Scalable Quantum Computers in the Presence of Physical Noise: a Study of Surface Codes with Realistic Errors at the Algorithmic Level

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In principle, quantum computers can use the physics of atoms and molecules to perform calculations ranging from code-breaking to simulation of materials algorithmically faster than any conventional supercomputer. The main challenge for building a quantum computer is that quantum components are prone to error. Error correction can be used to overcome this challenge but it places stringent requirements on future quantum computer hardware. The primary goal of this research is to develop a path for bridging the gap between current physical hardware and large-scale quantum algorithms. Specifically how a state-of-the-art quantum error correction scheme, the surface code, behaves when mapped to realistic physical architectures will be examined. If successful, this research will help experimentalists build the first universal scalable quantum computer. The research will train graduate students and undergraduate students in the growing field of quantum information science and provide them with an opportunity to work with industrial collaborators at IBM. This proposal expands the frontiers of physics by exploring quantum computation at the intersection of experimental devices, computer architecture, and quantum information theory. Surface codes with a computational error threshold of 1% are a promising solution to the problem of decoherence and imperfections in quantum systems. Computation is performed by the creation, annihilation, and braiding of topological defects. Examining this process from the perspective of algorithms and architectures will help reveal common structures and provide a precise method for implementation of these ideas on real physical systems. Surface code implementations that account for realistic noise models and system-level constraints will be examined. This will leverage previous work in experimental device data, quantum circuit synthesis tools, computer architecture, and quantum programming languages and compilers. Additionally, there will be close collaboration with Sergey Bravyi at IBM (including summer internships at IBM for students) on the theoretical foundations of this work.