Single-shot electron bunch length measurements using a spatial electro-optical autocorrelation interferometer

A spatial, electro-optical autocorrelation (EOA) interferometer using the vertically polarized lobes of coherent transition radiation (CTR) has been developed as a single-shot electron bunch length monitor at an optical beam port downstream the 100 MeV preinjector LINAC of the Swiss Light Source. This EOA monitor combines the advantages of step-scan interferometers (high temporal resolution) [D. Mihalcea et al., Phys. Rev. ST Accel. Beams 9, 082801 (2006) and T. Takahashi and K. Takami, Infrared Phys. Technol. 51, 363 (2008)] and terahertz-gating technologies [U. Schmidhammer et al., Appl. Phys. B: Lasers Opt. 94, 95 (2009) and B. Steffen et al., Phys. Rev. ST Accel. Beams 12, 032802 (2009)] (fast response), providing the possibility to tune the accelerator with an online bunch length diagnostics. While a proof of principle of the spatial interferometer was achieved by step-scan measurements with far-infrared detectors, the single-shot capability of the monitor has been demonstrated by electro-optical correlation of the spatial CTR interference pattern with fairly long (500 ps) neodymium-doped yttrium aluminum garnet (Nd:YAG) laser pulses in a ZnTe crystal. In single-shot operation, variations of the bunch length between 1.5 and 4 ps due to different phase settings of the LINAC bunching cavities have been measured with subpicosecond time resolution.

Characterization of microfluidic systems with Doppler optical coherence tomography

Doppler Optical Coherence Tomography (DOCT) is a biomedical imaging technique that allows simultaneous structural imaging and flow monitoring inside biological tissues and materials with spatial resolution in the micrometer scale. It has recently been applied to the characterization of microfluidic systems. Structural and flow imaging of novel microfluidics platforms for cytotoxicologic applications were obtained with a real-time, Near Infrared Spectral Domain DOCT system. Characteristics such as flow homogeneity in the chamber, which is one of the most important parameters for cell culture, are investigated. OCT and DOCT images were used to monitor flow inside a specific platform that is based on microchannel division for a better flow homogeneity. In particular, the evolution of flow profile at the transition between the microchannel structure and the chamber is studied.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.