Related Experiment Video
Updated: Apr 25, 2026

08:19
Patterning via Optical Saturable Transitions - Fabrication and Characterization
Published on: December 11, 2014
6.0K
Tunable, nondispersive optical filter using photonic Hilbert transformation
Optics Letters
|August 29, 2014
Summary
We introduce a novel optical filter design using photonic Hilbert transformers within a Michelson interferometer. This tunable filter offers adjustable bandwidths for band-pass or band-reject applications, demonstrating wide tunability from MHz to GHz.
Area of Science:
- Photonics
- Optical Engineering
- Signal Processing
Background:
- Nondispersive optical filters are crucial for various signal processing applications.
- Existing tunable filters often face limitations in bandwidth range or complexity.
- Complementary filters (band-pass/band-reject) offer versatile spectral shaping capabilities.
Purpose of the Study:
- To propose and numerically demonstrate a new design for tunable nondispersive complementary optical filters.
- To achieve a wide range of bandwidth tunability in optical filtering.
- To integrate photonic Hilbert transformers (PHTs) into a Michelson interferometer (MI) for filter implementation.
Main Methods:
- Numerical demonstration of a novel optical filter design.
- Utilizing two photonic Hilbert transformers (PHTs) integrated into a Michelson interferometer (MI).
- Controlling the central frequencies of the PHTs to tune filter characteristics.
- Employing fiber Bragg grating-based PHTs for feasibility.
Main Results:
- Successful numerical demonstration of a tunable nondispersive complementary optical filter.
- Achieved bandwidth tunability from 260 MHz to 60 GHz.
- Demonstrated a high extinction ratio (>20 dB) and sharp transition slope (170 dB/GHz).
- Central frequency and spectral width of pass/reject bands are tunable by adjusting PHT central frequencies.
Conclusions:
- The proposed design offers a versatile and tunable solution for optical filtering.
- The integration of PHTs within an MI enables wide bandwidth tunability and high performance.
- This approach provides a promising platform for advanced optical signal processing applications.
Related Concept Videos
Properties of Fourier Transform II
1.0K
The Fourier Transform (FT) is an essential mathematical tool in signal processing, transforming a time-domain signal into its frequency-domain representation. This transformation elucidates the relationship between time and frequency domains through several properties, each revealing unique aspects of signal behavior.
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
1.0K
Reconstruction of Signal using Interpolation
915
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
915
IR Spectrometers
3.1K
There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
3.1K

