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Register a new userOvercoming the speckle correlation limit to achieve a fiber wavemeter with attometer resolution
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The measurement of the wavelength of light using speckle is a promising tool for the realization of compact and precise wavemeters and spectrometers. However, the resolution of these devices is limited by strong correlations between the speckle patterns produced by closely-spaced wavelengths. Here, we show how principal component analysis of speckle images provides a route to overcome this limit. Using this, we demonstrate a compact wavemeter which measures wavelength changes of a stabilized diode laser of 5.3 am, eight orders of magnitude below the speckle correlation limit.
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Many areas of optical science require an accurate measurement of optical spectra. Devices based on laser speckle promise compact wavelength measurement, with attometer-level sensitivity demonstrated for single wavelength laser fields. The measurement of multimode spectra using this approach would be attractive, yet this is currently limited to picometer resolution. Here, we present a method to improve the resolution and precision of speckle-based multi-wavelength measurements. We measure multiple wavelengths simultaneously, in a device comprising a single 1 m-long step-index multimode fiber and a fast camera. Independent wavelengths separated by as little as 1 fm are retrieved with 0.2 fm precision using Principal Component Analysis. The method offers a viable way to measure sparse spectra containing multiple individual lines and is likely to find application in the tracking of multiple lasers in fields such as portable quantum technologies and optical telecommunications.
Recovering the wavelength from disordered speckle patterns has become an exciting prospect as a wavelength measurement method due to its high resolution and simple design. In previous studies, panel cameras have been used to detect the subtle differences between speckle patterns. However, the volume, bandwidth, sensitivity, and cost (in non-visible bands) associated with panel cameras have hindered their utility in broader applications, especially in high speed and low-cost measurements. In this work, we broke the limitations imposed by panel cameras by using a quadrant detector (QD) to capture the speckle images. In the scheme of QD detection, speckle images are directly filtered by convolution, where the kernel is equal to one quarter of a speckle pattern. First, we proposed an up-sampling algorithm to pre-process the QD data. Then a new convolution neural network (CNN) based algorithm, shallow residual network (SRN), was proposed to train the up-sampled images. The experimental results show that a resolution of 4 fm (~ 0.5 MHz) was achieved at 1550nm with an updating speed of ~ 1 kHz. More importantly, the SRN shows excellent robustness. The wavelength can be precisely reconstructed from raw QD data without any averaging, even where there exists apparent noise. The low-cost, simple structure, high speed and robustness of this design promote the speckle-based wavemeter to the industrial grade. In addition, without the restriction of panel cameras, it is believed that this wavemeter opens new routes in many other fields, such as distributed optical fiber sensors, optical communications, and laser frequency stabilization.
Speckle patterns have been widely confirmed that can be utilized to reconstruct the wavelength information. In order to achieve higher resolution, a varies of optical diffusing waveguides have been investigated with a focus on their wavelength sensitivity. However, it has been a challenge to reach the balance among cost, volumes, resolution, and stability. In this work, we designed a compact cylindrical random scattering waveguide (CRSW) as the light diffuser only by mixing TiO2 particles and ultra-violate adhesive. The speckle patterns are generated by the light multiple scattering in the CRSW. Importantly, the thin layer of upconversion nanoparticles (UCNPs) were sprayed on the end face of the CRSW. This allows the near infrared (NIR) light to be converted to the visible light, breaking the imaging limitation of visible cameras in the NIR range. We further designed a convolution neural network (CNN) to recognize the wavelength of the speckle patterns with good robustness and excellent ability of transfer learning, resulting in the achievement of a high resolution of 20 kHz ( 0.16 fm) at around 1550 nm with temperature resistance of 2 celsius. Our results provide a low-cost, compact, and simple NIR wavemeter in particular with the ultra high resolution and good temperature stability.
We report an experimental demonstration of sub-wavelength interference without correlation. Typically, people can achieve sub-wavelength effect with correlation measurement no matter by using bi-photon or thermal light sources. Here we adopt a thermal light source. And we count the realizations in which the intensities of the definite symmetric points are above or below a certain threshold. The distribution of numbers of these realizations who satisfy the restriction will show a sub-wavelength effect. With proper constrictions, positive and negative interference patterns are demonstrated.
A nanoparticle detection scheme with single particle resolution is presented. The sensor contains only a taper fiber thus offering the advantages of compactness and installation flexibility. Sensing method is based on monitoring the transmitted light power which shows abrupt jumps with each particle binding to the taper surface. The experimental validation of the sensor is demonstrated with polystyrene nanoparticles of radii 120 nm and 175 nm in the 1550 nm wavelength band.
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