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Ethan Smith

ethan smith
Ethan Smith
Computer Science Department

Ethan is a researcher focused on the optimization of classical and quantum software. His background is in classical compilers and programming languages, with an emphasis on type systems. His main research focus is optimizing quantum software to target near term and future quantum hardware. He currently work on the following projects:

  • BQSKit : Berkeley Quantum Synthesis Toolkit. A quantum software system centered around synthesis
  • Qsearch: A compiler for quantum computers based on A* and numerical optimization.

Journal Articles

Akel Hashim, Ravi K. Naik, Alexis Morvan, Jean-Loup Ville, Bradley Mitchell, John Mark Kreikebaum, Marc Davis, Ethan Smith, Costin Iancu, Kevin P. O Brien, Ian Hincks, Joel J. Wallman, Joseph Emerson, Irfan Siddiqi, "Randomized Compiling for Scalable Quantum Computing on a Noisy Superconducting Quantum Processor", Physical Review X, 2021, 11:041039, doi: 10.1103/PhysRevX.11.041039

Conference Papers

Ethan H. Smith, Marc G. Davis, Jeffery M. Larson, Costin Iancu, "LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach", International Workshop of Quantum Computing Software at Supercomputing, November 2020,

Marc G. Davis, Ethan Smith, Ana Tudor, Koushik Sen, Irfan Siddiqi, Costin Iancu, "Towards Optimal Topology Aware Quantum Circuit Synthesis", 2020 IEEE International Conference on Quantum Computing and Engineering (QCE), Denver, CO, USA, IEEE, October 12, 2020, doi: 10.1109/QCE49297.2020.00036

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseeable Noisy-Intermediate-Scale Quantum devices era, our A* inspired algorithm minimizes their count while accounting for connectivity. We discuss the formulation of synthesis as a search problem as well as an algorithm to find solutions. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4× average (up to 5.3×) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set while obtaining similar quality results. We believe that tools like ours can facilitate algorithmic exploration and guide gate set discovery for quantum processor designers, as well as being useful for optimization in the quantum compilation tool-chain.

Marc Grau Davis, Ethan Smith, Ana Tudor, Koushik Sen, Irfan Siddiqi, Costin Iancu, "Heuristics for Quantum Compiling with a Continuous Gate Set", 3rd International Workshop on Quantum Compilation as part of the International Conference On Computer Aided Design 2019, December 5, 2019,

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As accurate CNOT gates are hard for the foreseeable Noisy- Intermediate-Scale Quantum devices era, our A* inspired algorithm attempts to minimize their count, while accounting for connectivity. We discuss the search strategy together with metrics to expand the solution frontier. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4x average (up to 5.3x) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set, while obtaining similar quality results. We believe that empirical tools like ours can facilitate algorithmic exploration, gate set discovery for quantum processor designers, as well as providing useful optimization blocks within the quantum compilation tool-chain.

Others

Akel Hashim, Ravi Naik, Alexis Morvan, Jean-Loup Ville, Brad Mitchell, John Mark Kreikebaum, Marc Davis, Ethan Smith, Costin Iancu, Kevin O Brien, Ian Hincks, Joel Wallman, Joseph V Emerson, David Ivan Santiago, Irfan Siddiqi, Scalable Quantum Computing on a Noisy Superconducting Quantum Processor via Randomized Compiling, Bulletin of the American Physical Society, 2021,

Coherent errors in quantum hardware severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable, large-scale quantum computations. Randomized compiling achieves this goal by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of aggregate performance via cycle benchmarking estimates. In this work, we demonstrate significant performance gains under randomized compiling for both the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. We also validate solution accuracy using experimentally-measured error rates. Our results demonstrate that randomized compiling can be utilized to maximally-leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing.