Machine-Learning-Assisted Quantum Photonics: From Algorithms to Applications

Interdisciplinary Areas: Data and Engineering Applications, Micro-, Nano-, and Quantum Engineering

Project Description

Emerging optical technologies such as planar metasurfaces and integrated quantum photonics promise to bring revolutionary advances to fundamental science of light and light matter interactions as well as to enable an entirely new generation of compact, efficient, and multifunctional devices for breakthrough applications in information processing and storage, computation, secure communication, nanometer-scale imaging, sensing and future quantum IT. Artificially engineered, ultra-thin photonic metasurfaces have already enabled unprecedented abilities to process and measure quantum information. Together with the emerging single photon sources, metasurfaces can enable quantum RAM concepts (qRAM) where multiple degrees of freedom of single photons are used in order to emulate the address, data and qRAM qudits. The single photons will interact with a sequence of metasurfaces performing the entangling operations between the different degrees of freedom. At the end of their trajectory the photons will be subjected to quantum tomography measurements to determine their full quantum state in all the degrees of freedom involved. This tomography will serve as a proof of a quantum evolution analogous to a real qRAM. This project will be a pioneering effort featuring an efficient interface between a classical and a quantum data world. 

Start Date

01/01/2021

Postdoc Qualifications

PhD holder or candidate in physical sciences or engineering with strong background in one or more of the following areas: nano/quantum photonics, electronics, machine learning, nanomaterials, quantum chemistry. Experience in IT and computer science would be beneficial. Strong abilities for independent, interdisciplinary research, and excellent oral and written communication skills. 

Co-Advisors

Alexandra Boltasseva, Professor, School of Electrical and Computer Engineering, Birck Nanotechnology Center Purdue University, Purdue Quantum Science and Engineering Institute, aeb@purdue.edu
https://engineering.purdue.edu/~aeb/

Sabre Kais, Professor, Department of Chemistry, Birck Nanotechnology Center, Purdue Quantum Science and Engineering Institute, kais@Purdue.edu http://www.chem.purdue.edu/kais

References

Kildishev, A. V.; Boltasseva, A.; Shalaev, V. M. Planar photonics with metasurfaces. Science 2013, 339 (6125), 1232009.

Bogdanov, S. I.; Shalaginov, M. Y.; Lagutchev, A. S.; Chiang, C.-C.; Shah, D.; Baburin, A. S.; Ryzhikov, I. A.; Rodionov, I. A.; Kildishev, A. V.; Boltasseva, A. Ultrabright room-temperature sub-nanosecond emission from single nitrogen-vacancy centers coupled to nanopatch antennas. Nano letters 2018, 18 (8), 4837-4844.

Bogdanov, S. I.; Boltasseva, A.; Shalaev, V. M. Overcoming quantum decoherence with plasmonics. Science 2019, 364 (6440), 532-533.

Xia, R.; Kais, S. Quantum machine learning for electronic structure calculations. Nature communications 2018, 9 (1), 4195

Shaltout, A. M.; Kim, J.; Boltasseva, A.; Shalaev, V. M.; Kildishev, A. V. Ultrathin and multicolour optical cavities with embedded metasurfaces. Nature communications 2018, 9 (1), 2673.