Integrating Hybrid Area Detectors for Storage Ring and Free-Electron Laser Applications

Graafsma, H.; Becker, Julian; Grüner, Sol M.

doi:10.1007/978-3-319-04507-8_37-1

Cited by 13 publications

(5 citation statements)

References 56 publications

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“…In particular, scientific applications relying on very low photon detection noise and/or spectro-imaging capability benefit from the continuous improvements of the charge coupled device (CCD) technology during the last decade. The FastCCD (Doering et al, 2012), MPCCD (Kameshima et al, 2014) and pnCCD (Strü der et al, 2010) are a few exemplary monolithic detectors playing an important role at storage rings and FELs [see Graafsma et al (2020) and Hatsui & Graafsma (2015) for an in-depth review].…”

Section: Introductionmentioning

confidence: 99%

The 1-Megapixel pnCCD detector for the Small Quantum Systems Instrument at the European XFEL: system and operation aspects

Kuster

Ahmed

Ballak

et al. 2021

J Synchrotron Radiat

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The X-ray free-electron lasers that became available during the last decade, like the European XFEL (EuXFEL), place high demands on their instrumentation. Especially at low photon energies below 1 keV, detectors with high sensitivity, and consequently low noise and high quantum efficiency, are required to enable facility users to fully exploit the scientific potential of the photon source. A 1-Megapixel pnCCD detector with a 1024 × 1024 pixel format has been installed and commissioned for imaging applications at the Nano-Sized Quantum System (NQS) station of the Small Quantum System (SQS) instrument at EuXFEL. The instrument is currently operating in the energy range between 0.5 and 3 keV and the NQS station is designed for investigations of the interaction of intense FEL pulses with clusters, nano-particles and small bio-molecules, by combining photo-ion and photo-electron spectroscopy with coherent diffraction imaging techniques. The core of the imaging detector is a pn-type charge coupled device (pnCCD) with a pixel pitch of 75 µm × 75 µm. Depending on the experimental scenario, the pnCCD enables imaging of single photons thanks to its very low electronic noise of 3 e− and high quantum efficiency. Here an overview on the EuXFEL pnCCD detector and the results from the commissioning and first user operation at the SQS experiment in June 2019 are presented. The detailed descriptions of the detector design and capabilities, its implementation at EuXFEL both mechanically and from the controls side as well as important data correction steps aim to provide useful background for users planning and analyzing experiments at EuXFEL and may serve as a benchmark for comparing and planning future endstations at other FELs.

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Section: Introductionmentioning

confidence: 99%

The 1-Megapixel pnCCD detector for the Small Quantum Systems Instrument at the European XFEL: system and operation aspects

Kuster

Ahmed

Ballak

et al. 2021

J Synchrotron Radiat

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“…A number of fast X-ray 2D area detectors have been developed recently for XPCS experiments where the intensity of the incoming X-ray specular reflection pattern is measured with sub-millisecond timing resolution (Denes et al, 2009;Johnson et al, 2012;Becker et al, 2013;Pennicard et al, 2013;Hatsuia & Graafsma, 2015;Zhang et al, 2016Zhang et al, , 2018Rumaiz et al, 2016;Kleczek et al, 2018;Graafsma et al, 2020). Most of these devices are built for moderate-to-high X-ray energies, exceeding $10 keV.…”

Section: Introductionmentioning

confidence: 99%

“…Denes et al, 2009). For fast hybrid detectors, where incoming photons are converted to a charge in Si or other solid-state sensors and subsequently registered by a readout-specific integrated circuit (ROIC), such as event-counting Medipix/Timepix, integrating AGIPD devices (Graafsma et al, 2020) have a minimum charge threshold value corresponding to a photon energy of several keV. Detection of soft X-ray photons ($100 eV to $1.2 keV) therefore requires charge amplification.…”

Section: Introductionmentioning

confidence: 99%

Photon-counting MCP/Timepix detectors for soft X-ray imaging and spectroscopic applications

Tremsin¹,

Vallerga²,

Siegmund³

et al. 2021

J Synchrotron Radiat

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Detectors with microchannel plates (MCPs) provide unique capabilities to detect single photons with high spatial (<10 µm) and timing (<25 ps) resolution. Although this detection technology was originally developed for applications with low event rates, recent progress in readout electronics has enabled their operation at substantially higher rates by simultaneous detection of multiple particles. In this study, the potential use of MCP detectors with Timepix readout for soft X-ray imaging and spectroscopic applications where the position and time of each photon needs to be recorded is investigated. The proof-of-principle experiments conducted at the Advanced Light Source demonstrate the capabilities of MCP/Timepix detectors to operate at relatively high input counting rates, paving the way for the application of these detectors in resonance inelastic X-ray scattering and X-ray photon correlation spectroscopy (XPCS) applications. Local count rate saturation was investigated for the MCP/Timepix detector, which requires optimization of acquisition parameters for a specific scattering pattern. A single photon cluster analysis algorithm was developed to eliminate the charge spreading effects in the detector and increase the spatial resolution to subpixel values. Results of these experiments will guide the ongoing development of future MCP devices optimized for soft X-ray photon-counting applications, which should enable XPCS dynamics measurements down to sub-microsecond timescales.

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“…We present Tensorflow versions of usual, state-of-the-art algorithms used at LCLS for all steps of processing images from X-ray integrating pixel detectors and reducing it to photons. Due to the short pulse duration at FELs (in the order of femtoseconds), photon counting detectors can't be used; instead, integrating detectors must be used [10]. Raw data from integrating pixel detectors requires (or at least benefits from) the following processing steps ( Fig.…”

Section: Introductionmentioning

confidence: 99%

Ultrafast processing of pixel detector data with machine learning frameworks

Blaj

Chang

Kenney

2019

AIP Conference Proceedings

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Modern photon science performed at high repetition rate free-electron laser (FEL) facilities and beyond relies on 2D pixel detectors operating at increasing frequencies (towards 100 kHz at LCLS-II) and producing rapidly increasing amounts of data (towards TB/s). This data must be rapidly stored for offline analysis and summarized in real time for online feedback to the scientists. While at LCLS all raw data has been stored, at LCLS-II this would lead to a prohibitive cost; instead, enabling real time processing of pixel detector data (dark, gain, common mode, background, charge summing, subpixel position, photon counting, data summarization) allows reducing the size and cost of online processing, offline processing and storage by orders of magnitude while preserving full photon information. This could be achieved by taking advantage of the compressibility of sparse data typical for LCLS-II applications. Faced with a similar big data challenge a decade ago, computer vision stimulated revolutionary advances in machine learning hardware and software. We investigated if these developments are useful in the field of data processing for high speed pixel detectors and found that typical deep learning models and autoencoder architectures failed to yield useful noise reduction while preserving full photon information, presumably because of the very different statistics and feature sets in computer vision and radiation imaging. However, the raw performance of modern frameworks like Tensorflow inspired us to redesign in Tensorflow mathematically equivalent versions of the state-of-the-art, "classical" algorithms used at LCLS. The novel Tensorflow models resulted in elegant, compact and hardware agnostic code, gaining 1 to 2 orders of magnitude faster processing on an inexpensive consumer GPU, reducing by 3 orders of magnitude the projected cost of online analysis and compression without photon loss at LCLS-II. The novel Tensorflow models also enabled ongoing development of a pipelined hardware system expected to yield an additional 3 to 4 orders of magnitude speedup, necessary for meeting the data acquisition and storage requirements at LCLS-II, potentially enabling acquiring every single FEL pulse at full speed. Computer vision a decade ago was dominated by hand-crafted filters; their structure inspired the deep learning revolution resulting in modern deep convolutional networks; similarly, our novel Tensorflow filters provide inspiration for designing future deep learning models for ultrafast and efficient processing and classification of pixel detector images at FEL facilities.

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Integrating Hybrid Area Detectors for Storage Ring and Free-Electron Laser Applications

Cited by 13 publications

References 56 publications

The 1-Megapixel pnCCD detector for the Small Quantum Systems Instrument at the European XFEL: system and operation aspects

The 1-Megapixel pnCCD detector for the Small Quantum Systems Instrument at the European XFEL: system and operation aspects

Photon-counting MCP/Timepix detectors for soft X-ray imaging and spectroscopic applications

Ultrafast processing of pixel detector data with machine learning frameworks

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