Quantum computing offers the opportunity for revolutionizing scientific computing, and the DOE Office of Science Advanced Scientific Computing Research (ASCR) program has expressed considerable interest in this emerging area. In 2015 DOE sponsored a workshop to assess the viability of quantum computing technologies to meet computational requirements in support of the DOE’s science and energy mission; and in 2017 DOE sponsored a workshop on quantum computing testbeds and the technologies needed to advance quantum computing for scientific applications in the next five years.
What have we been doing?
In the Mathematics and Computer Science Division at Argonne, we are involved in many quantum computing projects, including the following:
- Numerical optimization - developing numerical optimization algorithms for common quantum computing problems
- Data compression - devising fast data compression techniques that reduce computational cost while maintaining precision
- Quantum entanglements - simulating and understanding experimental setups that maximize the intensity and duration of quantum entanglement
- Quantum simulation - applying quantum dynamics techniques to solve problems in chemistry and materials science
- Hybrid quantum computing - developing decomposition methods that use quantum computing with classical computing for solving large-scale mixed-integer nonlinear programming problems that arise in many applications, including energy infrastructure system planning and operations
We have recently received DOE funding to participate in the Quantum Algorithms, Mathematics and Compilation Tools for Chemical Sciences project. Our aim is to design novel technologies to advance machine learning on near-term quantum computing platforms. The Quantum Algorithms Team consists of researchers led by Lawrence Berkeley National Laboratory and including UC Berkeley and Harvard University.
Where have we been publishing?
Here are some recent papers we have published in peer-reviewed journals or presented at conferences.
- M. Otten, J. Larson, M. Min, S. M. Wild, M. Pelton, and S. K. Gray, “Origins and Optimization of Entanglement in Plasmonically Coupled Quantum Dots," Physical Review A, vol. 94, no. 2, p. 15, 2016.
- M. Otten, R. A. Shah, N. F. Scherer, M. S. Min, M. Pelton, and S. K. Gray, “Entanglement of Two, Three and Four Plasmonically Coupled Quantum Dots," Physical Review B, vol. 92, no. 12-15, 2015.
- A. Buluc, W. de Jong, J. Larson, L. Lin, S. Wild, "The Role of Applied Mathematics in Quantum Computing: Old Can Be New Again?" Whitepaper submitted to the 2017 DOE ASCR Applied Math Meeting, 2017.
- A. M. Gok, D. Tao, S. Di, V. Mironov, Y. Alexeev, F. Cappello, "PaSTRI: A Novel Data Compression Algorithm for Two-Electron Integrals in Quantum Chemistry," poster presented at SC17.
Also of note is a new solver, available on github, for general simulation of quantum systems:
- M. Otten, "QuaC: Open Quantum Systems in C," a time-dependent open quantum systems solver, 2017.
We've also been involved in several seminars and panels.
- S.Wild was session chair of Machine Learning and Quantum Computing at SC17.
- D. Maslov (NSF) gave an invited MCS seminar on "How to Program a Quantum Computer," Sept. 14, 2017.
- S. Caldwell (Rigetti Quantum Computing) gave an invited MCS Seminar on "Toward Full-Stack Quantum Computing Built on Superconducting Qubits," Sept. 12, 2017.
- A. M. Gok gave a seminar on "PaSTRI: A Novel Data Compression Algorithm for Two-Electron Integrals in Quantum Chemistry," August 21, 2017.