Non-Gaussian photonic state engineering with the quantum frequency processor

Andrew J. Pizzimenti, Joseph M. Lukens, Hsuan Hao Lu, Nicholas A. Peters, Saikat Guha, Christos N. Gagatsos

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Non-Gaussian quantum states of light are critical resources for optical quantum information processing, but methods to generate them efficiently remain challenging to implement. Here we introduce a generic approach for non-Gaussian state production from input states populating discrete frequency bins. Based on controllable unitary operations with a quantum frequency processor, followed by photon-number-resolved detection of ancilla modes, our method combines recent developments in both frequency-based quantum information and non-Gaussian state preparation. Leveraging and refining the K-function representation of quantum states in the coherent basis, we develop a theoretical model amenable to numerical optimization and, as specific examples, design quantum frequency processor circuits for the production of Schrödinger cat states, exploring the performance tradeoffs for several combinations of ancilla modes and circuit depth. Our scheme provides a valuable framework for producing complex quantum states in frequency bins, paving the way for single-spatial-mode, fiber-optic-compatible non-Gaussian resources.

Original languageEnglish
Article number062437
JournalPhysical Review A
Volume104
Issue number6
DOIs
StatePublished - Dec 2021

Funding

We thank R. C. Pooser and K. K. Sabapathy for useful discussions. This research was performed in part at Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Funding was provided by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, through the Transparent Optical Quantum Networks for Distributed Science Program and Early Career Research Program (Field Work Proposals ERKJ355 and ERKJ353). A.J.P. acknowledges support from the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists Science Undergraduate Laboratory Internship Program. C.N.G. and S.G. acknowledge an ORNL/DOE subaward under Grant No. 4000178321, and partial support from the Office of Naval Research (ONR) under Grant No. N00014-19-1-2189.

FundersFunder number
Office of Workforce Development for Teachers
Office of Naval ResearchN00014-19-1-2189
U.S. Department of EnergyDE-AC05-00OR22725, 4000178321
Office of Science
Advanced Scientific Computing ResearchERKJ355, ERKJ353
Oak Ridge National Laboratory

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