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Arbitrary linear transformations for photons in the frequency synthetic dimension
Siddharth Buddhiraju1, Avik Dutt1, Momchil Minkov1
1Ginzton Laboratory, Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
Nature Communications
|April 24, 2021
Summary
Researchers developed a photonic architecture using synthetic frequency dimensions to perform arbitrary linear transformations. This reconfigurable integrated system offers high fidelity for classical and quantum applications.
Area of Science:
- Photonics
- Quantum Information Processing
- Integrated Optics
Background:
- Arbitrary linear transformations are fundamental in photonic applications like signal processing, communications, quantum computing, and machine learning.
- Existing photonic architectures often face limitations in scalability, reconfigurability, and fidelity for complex transformations.
Purpose of the Study:
- To present a novel photonic architecture capable of implementing arbitrary linear transformations.
- To leverage the synthetic frequency dimension for enhanced photonic manipulation.
- To demonstrate a reconfigurable and scalable solution for integrated photonic systems.
Main Methods:
- Utilizing dynamically modulated micro-ring resonators to create tunable couplings between frequency modes.
- Employing inverse design with automatic differentiation to optimize short- and long-range couplings.
- Harnessing the synthetic frequency dimension of photons for computation.
Main Results:
- Achieved arbitrary scattering matrices in synthetic space with near-unity fidelity.
- Demonstrated the reconfigurability of the same physical structure for diverse manipulations.
- Showcased favorable scaling properties for the proposed architecture.
Conclusions:
- The presented photonic architecture enables compact, scalable, and reconfigurable integrated systems for arbitrary linear transformations.
- This approach is applicable to both classical and quantum photonic domains using current technology.
- Offers a versatile platform for advanced photonic signal processing and quantum information tasks.
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