The detection of rapid dynamics in diverse physical systems is traditionally very difficult and strongly dominated by several noise contributions. Laser mode-locking, electron bunches in accelerators, and optical-triggered phases in materials are events that carry important information about the system from which they emerge. By detecting single-shot spectra with high repetition rates over long-time scales, new possibilities and applications to diagnose, control and tailor the spectral dynamics of lasers and electron beams in synchrotron and free-electron laser (FEL) accelerators open up. This contribution focuses on the latest developments of real-time, single-shot, high-repetition-rate detectors and data acquisition systems, with a special focus on emerging technologies and new possibilities in the diagnostics of rogue optical signals.
KEYWORDS: Analog electronics, Clocks, System on a chip, Field programmable gate arrays, Picosecond phenomena, Calibration, Terahertz radiation, Data conversion, Photodetectors, Electro optics
The detection of rapid dynamics in diverse physical systems is traditionally very difficult and strongly dominated by several noise contributions. Laser mode-locking, electron bunches in accelerators and optical-triggered phases in materials are events that carry important information about the system from which they emerge. To understand the underlying dynamics of complex systems often large numbers of single-shot measurements must be acquired continuously over a long time with extremely high temporal resolution. Ultrafast real-time instruments allow the acquisition of large data sets, even for rare events, in a relatively short time period. The real-time measurement of fast single-shot events with large record lengths is one of the most challenging problems in the fields of instrumentation and measurement. In this contribution, the novel ultra-fast and continuous data sampling system THERESA using photonic time-stretch is presented and its performance is discussed. The proposed data acquisition system is based on the latest ZYNQ Radio Frequency System on Chip (ZYNQ-RFSoC) family from Xilinx, which combines an array of fast (GS/s) multi-channel Analog-to-Digital Converters (ADCs) with a Field Programmable Gate Array (FPGA) and a multi-core ARM processor in a single heterogeneous programmable device. The stretched pulse is sampled in parallel by 16 wideband sampling channels operating in time-interleaving mode. The sampled data is transferred by a 100 Gb Ethernet data link to the Data Acquisition (DAQ) compute node for further analysis. The combination of both, the photonic time-stretch and the fast sampling system, is capable of sampling short pulses with femtosecond time resolution. Applications of the new system, hardware implementation and the commissioning of the first system for the electron bunch diagnostics are presented.
KEYWORDS: Sensors, Field programmable gate arrays, Free electron lasers, Data processing, Electronics, Silicon, Synchrotrons, Analog electronics, Data acquisition, Diagnostics
KALYPSO is a novel detector operating at line rates above 10 Mfps. The detector board holds a silicon or InGaAs linear array sensor with spectral sensitivity ranging from 400 nm to 2600 nm. The sensor is connected to a cutting-edge, custom designed, ASIC readout chip, which is responsible for the remarkable frame rate. The FPGA readout architecture enables continuous data acquisition and processing in real time. This detector is currently employed in many synchrotron facilities for beam diagnostics and for the characterization of self-built Ytterbium-doped fiber laser emitting around 1050 nm with a bandwidth of 40 nm.
KALYPSO is a novel detector operating at line rates above 10 Mfps. It consists of a detector board connected to FPGA based readout card for real time data processing. The detector board holds a Si or InGaAs linear array sensor, with spectral sensitivity ranging from 400 nm to 2600 nm, which is connected to a custom made front-end ASIC. A FPGA readout framework performs the real time data processing. In this contribution, we present the detector system, the readout electronics and the heterogeneous infrastructure for machine learning processing. The detector is currently in use at several synchrotron facilities for beam diagnostics as well as for single-pulse laser characterizations. Thanks to the shot-to-shot capability over long time scale, new attractive applications are open up for imaging in biological and medical research.
Water transport from roots to shoots is a vital necessity in trees in order to sustain their photosynthetic activity and, hence, their physiological activity. The vascular tissue in charge is the woody body of root, stem and branches. In gymnosperm trees, like spruce trees (Picea abies (L.) Karst.), vascular tissue consists of tracheids: elongated, protoplast- free cells with a rigid cell wall that allow for axial water transport via their lumina. In order to analyze the over-all water transport capacity within one growth ring, time-consuming light microscopy analysis of the woody sample still is the conventional approach for calculating tracheid lumen area. In our investigations at the Imaging Beamline (IBL) operated by the Helmholtz-Zentrum Geesthacht (HZG) at PETRA III storage ring of the Deutsches Elektronen-Synchrotron DESY, Hamburg, we applied SRμCT on small wood samples of spruce trees in order to visualize and analyze size and formation of xylem elements and their respective lumina. The selected high-resolution phase-contrast technique makes full use of the novel 20 MPixel CMOS area detector developed within the cooperation of HZG and the Karlsruhe data by light microscopy analysis and, hence, prove, that μCT is a most appropriate method to gain valid information on xylem cell structure and tree water transport capacity.
Sebastian Schmelzle, Michael Heethoff, Vincent Heuveline, Philipp Lösel, Jürgen Becker, Felix Beckmann, Frank Schluenzen, Jörg Hammel, Andreas Kopmann, Wolfgang Mexner, Matthias Vogelgesang, Nicholas Tan Jerome, Oliver Betz, Rolf Beutel, Benjamin Wipfler, Alexander Blanke, Steffen Harzsch, Marie Hörnig, Tilo Baumbach, Thomas van de Kamp
Beamtime and resulting SRμCT data are a valuable resource for researchers of a broad scientific community in life sciences. Most research groups, however, are only interested in a specific organ and use only a fraction of their data. The rest of the data usually remains untapped. By using a new collaborative approach, the NOVA project (Network for Online Visualization and synergistic Analysis of tomographic data) aims to demonstrate, that more efficient use of the valuable beam time is possible by coordinated research on different organ systems. The biological partners in the project cover different scientific aspects and thus serve as model community for the collaborative approach. As proof of principle, different aspects of insect head morphology will be investigated (e.g., biomechanics of the mouthparts, and neurobiology with the topology of sensory areas). This effort is accomplished by development of advanced analysis tools for the ever-increasing quantity of tomographic datasets. In the preceding project ASTOR, we already successfully demonstrated considerable progress in semi-automatic segmentation and classification of internal structures. Further improvement of these methods is essential for an efficient use of beam time and will be refined in the current NOVAproject. Significant enhancements are also planned at PETRA III beamline p05 to provide all possible contrast modalities in x-ray imaging optimized to biological samples, on the reconstruction algorithms, and the tools for subsequent analyses and management of the data. All improvements made on key technologies within this project will in the long-term be equally beneficial for all users of tomography instrumentations.
KEYWORDS: X-ray imaging, Field programmable gate arrays, Imaging systems, Data acquisition, Image sensors, Sensors, Cameras, Data processing, Data storage, Data modeling
With ever-increasing data rates due to stronger light sources and better detectors, X-ray imaging experiments conducted at synchrotron beamlines face bandwidth and processing limitations that inhibit efficient workflows and prevent real-time operations. We propose an experiment platform comprised of programmable hardware and optimized software to lift these limitations and make beamline setups future-proof. The hardware consists of an FPGA-based data acquisition system with custom logic for data pre-processing and a PCIe data connection for transmission of currently up to 6.6 GB/s. Moreover, the accompanying firmware supports pushing data directly into GPU memory using AMD’s DirectGMA technology without crossing system memory first. The GPUs are used to pre-process projection data and reconstruct final volumetric data with OpenCL faster than possible with CPUs alone. Besides, more efficient use of resources this enables a real-time preview of a reconstruction for early quality assessment of both experiment setup and the investigated sample. The entire system is designed in a modular way and allows swapping all components, e.g. replacing our custom FPGA camera with a commercial system but keep reconstructing data with GPUs. Moreover, every component is accessible using a low-level C library or using a high-level Python interface in order to integrate these components in any legacy environment.
In this article we present the quantitative characterization of CCD and CMOS sensors which are used at the experiments
for microtomography operated by HZG at PETRA III at DESY in Hamburg, Germany. A standard commercial CCD
camera is compared to a camera based on a CMOS sensor. This CMOS camera is modified for grating-based differential
phase-contrast tomography.
The main goal of the project is to quantify and to optimize the statistical parameters of this camera system. These key
performance parameters such as readout noise, conversion gain and full-well capacity are used to define an optimized
measurement for grating-based phase-contrast. First results will be shown.
KEYWORDS: Control systems, Tomography, Data storage, Java, X-rays, C++, High dynamic range imaging, Data archive systems, Data processing, Image processing
A new control system for high-throughput experiments (X-Ray, Neutrons) is introduced in this article. The system
consists of several software components which are required to make optimized use of the beamtime and to fulfill the
demand to implement the new standardized data format established within the Helmholtz Association in Germany. The
main components are: PreExperiment Data Collector; Status server; Data Format Server. Especially for tomography a
concept for an online reconstruction based on GPU computing is presented. One of the main goals of the system is to
collect data that extends standard experimental data, e.g. instrument’s hardware state, preinvestigation data, experiment
description data etc. The collected data is stored together with the experiment data in the permanent storage of the user.
The stored data is then used for post processing and analysis of the experiment.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.