Jacob D. Biamonte, Head of Skoltech’s Laboratory for Quantum Information Processing
Center for Photonics and Quantum Materials (CPQM)
Skolkovo Institute of Science and Technology
Moscow, Russian Federation
Quantum machine learning, Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe & Seth Lloyd, Nature, volume 549, pages 195–202 (2017).
After his undergraduate studies (Bachelor of Science from Portland State University), Biamonte was employed as one of the world’s first quantum software programmers at D-Wave Systems Inc. in Vancouver B.C., Canada (2004-2007). His subsequent Doctorate from Oxford (2010) earned a Chancellors award. Biamonte worked as a research fellow at Harvard and as part of a joint Oxford/Singapore postdoctoral program before joining the Institute for Scientific Interchange (ISI Foundation) in Torino Italy to direct the institute’s Quantum Science Division (2012-2017). Biamonte joined Skoltech in 2017, while Skoltech’s Laboratory for Quantum Information Processing was officially founded in 2019 with Biamonte appointed Head of Laboratory.
Biamonte’s research focuses broadly on the theory and implementation of modern quantum algorithms and employs various mathematical techniques, particularly group-algebraic techniques, tensor networks and the formal theory of computation and information.
Biamonte is best known for several results:
- A 2019 proof that variational quantum computation can be used as a computationally universal model of quantum computation [arXiv:1903.04500].
- A definition given in 2016 of a spectral graph function which provably satisfies both (i) the definition of an entropy and (ii) subadditivity [with Domenico in PRX 6, 041062 (2016)].
- A 2015 proof that #P-hard counting problems (and hence 2, 3-SAT decision problems) can be solved efficiently when their tensor network expression has at most O(log c) COPY-tensors and polynomial bounded fan-out [with Turner and Morton in J. Stat. Phys. 160, 1389 (2015)].
- A 2008 proof that the two-body model Hamiltonian with tunable XX, ZZ terms is (i) computationally universal for adiabatic quantum computation and (ii) admits a QMA-complete ground state energy decision problem [with Love in PRA 78, 012352 (2008)]
Biamonte is also credited for pioneering work developing quantum algorithms for electronic structure calculations and more recently for work uniting quantum information processing with machine learning.
Biamonte has further provided theoretical support to enable milestone quantum information processing experimental demonstrations. The list includes the first quantum algorithmic demonstration of quantum chemistry [Nature Chemistry 2, 106 (2009)] (linear optics), the first experimental implementation of optimal control [Nature Communications 5, 3371 (2014)] (creating a quantum random access memory using NV-centers in diamond) as well as the first demonstration of neural network quantum state tomography on actual experimental data [npj Quantum Information 6:20 (2020)] (linear optics).
- Usern Medal Laureate in Formal Sciences (2018)
- Shapiro Lecture in Mathematical Physics, Pennsylvania State University (2014)
- Invited lifelong member (from 2013) of the Foundational Questions Institute (FQXi)
- Longuet-Higgins Paper Prize [jointly with JD Whitfield and AA Guzik for Molecular Physics 109, 735 (2011)]
Skoltech’s Laboratory for Quantum Information Processing (affectionately called, Deep Quantum Lab) contributes primarily to the theory, development and implementation of quantum enhanced algorithms, a topic underrepresented inside the Russian Federation and globally. The research capacity of the laboratory responds critically to inquiries from the public and private sectors and the research output has established Skoltech’s role internationally in quantum science and technology. The Laboratory was officially created as an autonomous laboratory structure by order number 44 enacted on 19 February 2019.
The laboratory currently participates in several national initiatives and industrial projects, including
- The large-scale national Digital Economy project, Leading Research Center on Quantum Computing (agreement No. 014/20)
- Ongoing multi-year collaboration agreements sponsored by Huawei Technologies Co., Ltd.
- Quantum algorithms research and consulting projects sponsored by Gaspromneft PJSC