We propose and demonstrate a low-cost single-pixel terahertz imaging method based on near-field photomodulation and compressed sensing. By using monolayer graphene on a silicon substrate as the photomodulator, and a low-cost continuous-wave laser and digital micromirror device for effective patterned photomodulation, we achieve fast single-pixel terahertz imaging based on the compressed sensing algorithm. We further show that adopting a graphene on silicon substrate leads to deeper modulation depth and thus better image quality than a high-resistance silicon substrate. We expect this work will advance the development of low-cost single-pixel terahertz imaging and promote this technique into practical applications.
Here we report a tunable polarization-independent broadband absorber in the terahertz regime. The proposed structure consists of periodic all-dielectric array on a gold substrate, sandwiched by a monolayer graphene and an epsilon-near-zero layer. Simulation results show that the absorption that is independent from the incident polarization remains above 90% over a broadband spectral range from 1.6 THz to 4.1 THz, corresponding to a bandwidth of 2.5 THz and a relative bandwidth of 87.7%. By varying the graphenes Fermi energy from 0.2 eV to 0.5 eV, the absorption bandwidth can be turned from 1.5 THz to 2.5 THz. We expect this polarization- independent absorber with dynamically tunable bandwidth can be used a filters in applications such as terahertz detectors.
We propose a novel type of bowtie terahertz antenna based on hyperbolic metamaterials that are composed of multilayers of Indium Antimonide (InSb) and SiO2. The InSb-SiO2 multilayers have hyperbolic dispersion at terahertz frequency range. Compared with the conventional bowtie antenna composed of gold, fully-vectorial simulations show that, the localized field enhancement in the proposed structure is 16 times of that for the gold antenna. We further reveal that this great field enhancement attributes to the significantly enhanced out-of-plane electric field component in the hyperbolic metamaterial antenna. We expect this work will find applications in terahertz sensors, detectors, and nonlinear devices.
Here, we propose an effective classification strategy for THz pulsed signals of breast tissues based on wavelet packet energy (WPE) feature exaction and machine learning classifiers. The parafin-embedded breast tissue samples were adopted in this study and identified as tumor (226 samples), healthy fibrous tissue (233 samples) or adipose tissue (178 samples) based on the histological results. Firstly, the THz pulsed signals of tissue samples were acquired using a standard transmission THz time-domain spectrometer. Then, the signals were decomposed by the wavelet packet transform (WPT) and the features of the WPE were extracted. To reduce the dimensionality of extracted features, the principal components analysis (PCA) method was employed. Six different machine learning classifiers were then performed and compared for automatic classification of different tissue samples. The highest classification accuracy is up to 97% using the fine Gaussian support vector machine (SVM) approach. The results indicate that the WPE feature exaction combined with machine learning classifier can be used for automatic evaluation of biological tissue THz signals with good accuracy.
We propose and demonstrate an interferometric sensor based on visibility modulation. In the interferometric sensor, a section of
polarization maintain (PM) fiber is spliced into one arm as the sensing head. Due to the interference between the two beams in the two
arms, respectively, an interferometric fringe can be obtained. The birefringence of the PM fiber splits the beam in the sensing arm,
yielding a visibility envelop in the interferometric fringe. Strain applied on the PM fiber can be demodulated by measuring the
visibility change in a given wavelength. Experimental result shows that the sensor can achieve resolution of up to 28 nano-strain. This
demodulation scheme is immunity to the wavelength shift and power fluctuation of OSA, thus improving the accuracy of the sensor.
This type of sensor can be improved by using a wavelength-swept laser or a mode-locked fiber laser.
The humidity sensor made of polymer optical fiber Bragg grating (POFBG) responds to the water content change in fiber induced by the change of environmental condition. The response time strongly depends on fiber size as the water change is a diffusion process. The ultrashort laser pulses have been providing an effective microfabrication method to achieve spatial localized modification in materials. In this work we used the excimer laser to create different microstructures (slot, D-shape) in POFBG to improve its performance. A significant improvement in the response time has been achieved in a laser etched D-shaped POFBG humidity sensor.
This paper proposed a solution about low cost multi-channels Gallium Arsenide (GaAs) absorption-based fiber optic
temperature sensing system, which can get specific channel temperature information at pre-set time slots by combining
time division multiplexing technology and fiber optic multiplexing module. Established an seven channels fiber optic
temperature sensing system using only one spectrum analysis unit and achieved -/+ 1°C temperature resolution, 2Hz
measuring frequency at temperature range from 0°C to 150°C.
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