Structure Design
Design channel layouts and energy distribution through phase profiles, diffraction orders and detector positions.
COMPUTATIONAL SPECTROSCOPY
Encode with micro/nanostructures
Reconstruct spectra computationally
Two approaches—beam splitting and filtering—connect optical control, detection, system calibration and reconstruction algorithms.
01 / TWO ROUTES
Two approaches, one measurement workflow
Incident lightSpectrum S(λ)
DOE / Metasurface beam splitting
Channel 1 → DetectionChannel 2 → DetectionChannel 3 → Detection
Response calibration
Computational reconstruction
Computational reconstruction
Distribute light across spatial channels
Diffractive and phase structures control output direction or spot distribution. Spectral measurement additionally requires wavelength-dependent channel responses to be designed and calibrated so the detected signals contain distinguishable spectral information.
Channel Acquisition
Detector arrays read intensity at each output location, accounting for crosstalk, optical efficiency and spot stability.
Research infrastructure
Existing reports cover DOE prototypes for VCSEL-array beam splitting, imprint characterization and measured spots. Beam splitting alone does not establish spectral resolving performance.
Incident lightSpectrum S(λ)
Metasurface filter array
Channel 1 → DetectionChannel 2 → DetectionChannel 3 → Detection
Response calibration
Computational reconstruction
Computational reconstruction
Give each channel a distinct spectral response
Micro/nano resonators modify transmission, reflection or absorption. A set of response functions encodes the incident spectrum, which is reconstructed using detector readout and a calibration matrix.
Filter Elements
Adjust geometry, period, materials and layer structures to create differentiated spectral responses.
Array Design
Evaluate channel correlation, transmission, noise, incidence angle and polarization, rather than peak width alone.
Research infrastructure
Reports show localized surface plasmon resonance filters and multichannel control. Integration with the detector system and response-matrix calibration are subsequent steps.
02 / CALIBRATION & RECONSTRUCTION
From channel intensity to spectral estimation
y = A · s + n
y is measured channel intensity; A is the calibrated response of the optical structure, detector and optical path; s is the unknown spectrum; n is noise. Constrained or regularized reconstruction is evaluated against independent reference spectra.
STEP 01
Simulation & Samples
Control the optical field through materials, geometry and array design to establish channel encoding responses.
STEP 02
Reference Spectral Calibration
Establish calibration relationships using reference spectra, dark frames and system response measurements.
STEP 03
Multichannel Acquisition
Acquire corresponding spectra, images or sensor signals at the site and record acquisition conditions.
STEP 04
Reconstruction & Error Evaluation
Process signals using calibrated responses and assess error against independent reference data.
Channel count does not directly equal the number of independently resolvable spectral lines. Resolving ability depends on system response, signal-to-noise ratio, calibration and reconstruction conditions.
03 / RESEARCH EVIDENCE
Beam-Splitting & Filter Samples
Beam splitting: spots and energy distribution
Filtering: differences in channel response
Micro/Nanofabrication & Characterization ↗Multispectral Systems & Algorithms ↗Uncooled Infrared Computational Spectroscopy ↗
Technical references:Computational spectroscopy with microfilter arrays (Nature Communications)；Metasurface infrared spectral reconstruction (Optics Letters)。
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