Keck-PAD Fast-Framing Hybrid X-ray Pixel Array Detector
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Direct X-ray detection in silicon has been transformative for scattering experiments in biology and materials science. While bump-bonded hybrid pixels have been attractive for hard X-ray detection, the challenge for single photon soft X-ray detection is sufficiently low noise. CCD structures on thick, high-resistivity silicon have been successfully used as sensors over the range of soft to hard X-rays at storage rings and FELs. The VeryFastCCD is a high frame rate, column-parallel CCD sensor with 48 μm pixels. Combined with 256-channel custom readout ASICs, frame rates of 5–10 kHz have been achieved with readout noise as low as 20 e and full-well capacity >4 × 10 5 e/pixel. Thin (10 nm and 100 nm) entrance window contact processes have also been developed which provide >85% quantum efficiency for 285 eV X-rays. Systems are currently being developed for several beamlines at the upgraded Advanced Light Source.
Coordinate transformation between focal plane and detector pixel systems must be handled carefully at the X-ray Calibration Facility (XRCF) as it will be during flight. The High Resolution Mirror Assembly (HRMA) X-ray Detection System (HXDS) stage dithers, and the five-axis mount (FAM) attachment points underwent various types of motion during testing. At the XRCF when the FAM moved, the Science Instrument Module (SIM) travel direction was not necessarily aligned with the mirror axis motion, and, in addition, an arbitrary position offset had to be calibrated. Misalignment from the mirror axis was assessed by measuring its displacement from the boresight configuration of the default FAM frame, and the HXDS stage was monitored for motion from the default FAM reference point. Mirror position, prescribed in a mirror modal coordinate system, was measured in HRMA pitch and yaw axes. Prior to corrections for dithering and FAM movement, the coordinate data at XRCF also had to be corrected for possible misalignments of the mirror mount relative to XRCF and the default FAM axes due to the movement of the FAM feet. Those misalignments were processed in terms of yaw-pitch-roll Euler angles in the mirror nodal coordinate, and in the default FAM frame, respectively. An AXAF Science Center (ASC) coordinate library, pixlib, has been built to support these coordinate transformations and was used during x-ray calibration at the George C. Marshall Space Flight Center, Huntsville, AL. The design and implementation of this library will be discussed.
I describe a method for accurately refining the geometrical parameters of segmented X-ray area detectors on the basis of serial crystallography data, using 'Millepede' – an algorithm created for a very similar problem in high-energy physics. The Millepede method for serial crystallography builds on the approach of Brewster et al. [Acta Cryst. (2018), D74, 877–894], in which the detector parameters are refined simultaneously with the parameters for each individual crystal. This accounts for the mutual dependency between the parameters and thereby avoids the bias and slow convergence problems that have afflicted older approaches in which the deviations between observed and calculated Bragg peak positions were taken directly as the updates for the detector panel positions. The Millepede method uses the special structure of the least-squares normal equations to reduce them to a much smaller form that can be solved very quickly, even compared with the sparse matrix methods used previously. This makes it practical to refine the detector geometry frequently and thereby maintain accurate calibration without specialized alignment campaigns. Tilts of detector panels out of the plane can be reliably refined, as can the overall distance of the detector in the beam direction. With a simulated test case, the new method produced panel shifts within 7% of the correct values with only one iteration, and produced almost exactly correct shifts after a second iteration. A simulated out-of-plane panel rotation was correctly determined to within 0.001°. Applied to experimental data from an X-ray free-electron laser, the method increased the indexable fraction of frames from 30% to 91% in a single iteration, and to 96% after two further iterations. Computing the geometry updates on the basis of 2060 crystals took only 0.819 s on desktop computing hardware, including the time taken to read the required data from disk. The scaling was found to be very close to linear for up to 100 980 sets of crystal parameters, which took only 78.2 s to process under the same conditions. The method has been applied as part of a real-time feedback system at a synchrotron radiation beamline, in which an out-of-plane detector tilt of 0.04° was detected and corrected. Possible further applications are also described here.
The current primary method of deepspace navigation is the NASA Deep Space Network (DSN). High-performance navigation is achieved using Delta Differential One-Way Range techniques that utilize simultaneous observations from multiple DSN sites, and incorporate observations of quasars near the line-of-sight to a spacecraft in order to improve the range and angle measurement accuracies. Over the past four decades, x-ray astronomers have identified a number of xray pulsars with pulsed emissions having stabilities comparable to atomic clocks. The x-ray pulsar-based navigation and time determination (XNAV) system uses phase measurements from these sources to establish autonomously the position of the detector, and thus the spacecraft, relative to a known reference frame, much as the Global Positioning System (GPS) uses phase measurements from radio signals from several satellites to establish the position of the user relative to an Earth-centered fixed frame of reference. While a GPS receiver uses an antenna to detect the radio signals, XNAV uses a detector array to capture the individual xray photons from the x-ray pulsars. The navigation solution relies on detailed xray source models, signal processing, navigation and timing algorithms, and analytical tools that form the basis of an autonomous XNAV system. Through previous XNAV development efforts, some techniques have been established to utilize a pulsar pulse time-of-arrival (TOA) measurement to correct a position estimate. One well-studied approach, based upon Kalman filter methods, optimally adjusts a dynamic orbit propagation solution based upon the offset in measured and predicted pulse TOA. In this delta position estimator scheme, previously estimated values of spacecraft position and velocity are utilized from an onboard orbit propagator. Using these estimated values, the detected arrival times at the spacecraft of pulses from a pulsar are compared to the predicted arrival times defined by the pulsar s pulse timing model. A discrepancy provides an estimate of the spacecraft position offset, since an error in position will relate to the measured time offset of a pulse along the line of sight to the pulsar. XNAV researchers have been developing additional enhanced approaches to process the photon TOAs to arrive at an estimate of spacecraft position, including those using maximum-likelihood estimation, digital phase locked loops, and "single photon processing" schemes that utilize all available time data associated with each photon. Using pulsars from separate, non-coplanar locations provides range and range-rate measurements in each pulsar s direction. Combining these different pulsar measurements solves for offsets in position and velocity in three dimensions, and provides accurate overall navigation for deep space vehicles.