Jacob Daniel Biamonte FInstP is an American physicist and theoretical computer scientist active in the fields of quantum information theory and quantum computing. He left a tenured professorship at the Skolkovo Institute of Science and Technology in Russia[1] after the start of the Russo-Ukrainian War.
Jacob Daniel Biamonte | |
|---|---|
| Born | January 22, 1979 |
| Education | B.S. (2004), Ph.D. (2010), D.Sc. (2022) |
| Alma mater | Portland State University University of Oxford Moscow Institute of Physics and Technology |
| Known for | Adiabatic Quantum Computing, Quantum Machine Learning |
| Awards | USERN Medal, Fellow IMA |
| Scientific career | |
| Fields | Quantum Computing Tensor Networks Mathematical Physics |
| Institutions | Skolkovo Institute of Science and Technology Harvard University University of Oxford |
Biamonte contributed several universality proofs which established the first experimentally relevant universal models of adiabatic quantum computation. He also proved universality of the NISQ era variational model of quantum computation[2] and published several results in the development of quantum machine learning[3] and the mathematics of tensor networks. His interests include developing tools in tensor networks and Hamiltonian engineering. [4]
Education
editBiamonte completed a Ph.D. at the University of Oxford in 2010.[5] In 2022 he defended a thesis for Russia's Doctor of Physical and Mathematical Sciences at Moscow Institute of Physics and Technology.[6][7]
Honors and awards
editIn 2023 Biamonte was elected Fellow of the Institute of Physics and in 2021 he became a Fellow of the Institute of Mathematics and its Applications. In 2018 Biamonte was awarded the USERN Medal in Formal Sciences for his work on quantum algorithms.[8] In 2014 Biamonte became an invited member of the Foundational Questions Institute.[9][10]
References
edit- ^ "Faculty Profile at the Skolkovo Institute of Science and Technology". skoltech.ru. Retrieved May 9, 2022.
- ^ Biamonte, Jacob (2021). "Universal variational quantum computation". Physical Review A. 103 (3): L030401. arXiv:1903.04500. doi:10.1103/PhysRevA.103.L030401.
- ^ Biamonte, Jacob; Wittek, Peter; Nicola, Pancotti; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth (2017). "Quantum machine learning". Nature. 549 (7671): 195–202. arXiv:1611.09347. doi:10.1038/nature23474. PMID 28905917. S2CID 64536201.
- ^ "Jacob Biamonte". Simons Institute for the Theory of Computing. Retrieved 2024-08-08.
- ^ "Mathematics Genealogy Project". genealogy.math.ndsu.nodak.edu. Retrieved May 9, 2022.
- ^ "Moscow Institute of Physics and Technology Dissertation Council". mipt.ru. Retrieved May 9, 2022.
- ^ Biamonte, Jacob (2022). On the mathematical structure of quantum models of computation based on Hamiltonian minimisation (DSc). Moscow Institute of Physics and Technology. p. 242. arXiv:2009.10088.
- ^ "The 2018 USERN Prize Ceremony in Reggio Calabria". usern.tums.ac.ir. Retrieved May 12, 2022.
- ^ "Awarded Projects Announcements". fqxi.org. Retrieved May 12, 2022.
- ^ "Six Degrees to the Emergence of Reality, FQXi interview, by Carinne Piekema". fqxi.org. Retrieved May 12, 2022.
External links
edit- Laboratory for Quantum Information Processing at the Skolkovo Institute of Science and Technology
- Jacob Biamonte publications indexed by Google Scholar