Quantum technologies need photonics for scaling. This is true even for “non-photonic” quantum systems based on superconductors, or trapped atoms and ions in vacuum. For example, new types of spatial light modulators and switches are needed to trap and control atoms and ions, microwave to optical quantum transducers are needed for networking superconducting processors, chip-scale laser systems are required for controlling atoms or spin qubits in solids, and very high efficiency integrated photonics is needed for quantum networks, sensors, and chip- based semiconductor quantum systems. Unfortunately, these photonics functionalities and performances are not available even in today’s best integrated photonic systems. We show how inverse design (which combines AI hardware with new types of physics solvers) can lead to much better photonics designs, and how new photonic materials combined with new nanofabrication and heterogenous integration can lead to desired performances. Specific examples include development of miniaturized titanium:sapphire lasers on chip, strontium titanate transducers, quantum network nodes in diamond, and a quantum simulator and computer with silicon carbide color centers.
Jelena Vuckovic (PhD Caltech 2002) is the Jensen Huang Professor of Global Leadership, Professor of Electrical Engineering and, by courtesy, of Applied Physics at Stanford. She is a member of the National Academy of Sciences and an External Scientific Member of the Max Planck Institute for Quantum Optics. Her awards include the Zeiss Award, Vannevar Bush Faculty Fellowship, Geoffrey Frew Fellowship from the Australian Academy of Sciences, the IET A. F. Harvey Engineering Research Prize, Mildred Dresselhaus Lectureship from MIT, and the Humboldt Prize. She is a Fellow of the APS, Optica, and IEEE, a lead editor of Physical Review Applied, and a co-founder and a lead scientific advisor of SPINS Photonics.