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Published on: August 12, 2013
Experimental Implementation of the Optical Fractional Fourier Transform in the Time-Frequency Domain
Bartosz Niewelt1,2, Marcin Jastrzębski1,2, Stanisław Kurzyna1,2
1Centre for Quantum Optical Technologies, Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097 Warsaw, Poland.
We experimentally realized the fractional Fourier transform (FrFT) in the time-frequency domain using an atomic quantum-optical memory. This method enables advanced optical signal processing for enhanced communication and computing applications.
Area of Science:
- Quantum optics
- Digital signal processing
- Optical signal processing
Background:
- The fractional Fourier transform (FrFT) is crucial in physics and signal processing for tasks like noise reduction.
- Processing optical signals in the time-frequency domain offers advantages over traditional digitization.
- Quantum-optical memory systems provide a platform for advanced signal manipulation.
Purpose of the Study:
- To experimentally demonstrate the fractional Fourier transform (FrFT) in the time-frequency domain.
- To utilize an atomic quantum-optical memory system for implementing the FrFT.
- To explore the potential of this technique for enhancing quantum and classical communication protocols.
Main Methods:
- Implementation of the FrFT by imposing programmable, interleaved spectral and temporal phases.
- Utilizing an atomic quantum-optical memory system with integrated processing capabilities.
- Verification of the FrFT through chronocyclic Wigner function analysis.
Main Results:
- Successful experimental realization of the fractional Fourier transform in the time-frequency domain.
- Demonstration of programmable phase control for FrFT implementation.
- Validation of results using precise measurements with a shot-noise limited homodyne detector.
Conclusions:
- The developed scheme provides a novel method for optical signal processing in the time-frequency domain.
- This experimental realization of FrFT holds significant promise for applications in temporal-mode sorting and superresolved parameter estimation.
- The findings pave the way for advancements in quantum and classical communication, sensing, and computing.
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