Commissioning of the MIGDAL detector with fast neutrons at NILE/ISIS
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Poster for the upcoming SPIE Conference, see https://spie.org/opo/conferencedetails/x-ray-gamma-ray-neutron-detector-physics, due August 17. A manuscript for this poster has also been published
Element6 has come out of a two year production pause (pre-COVID) with material that lacks their previous QC – some is excellent, but screening is needed. Applied Diamond can now make usable polycrystalline material, for applications not requiring absolute flux calibration. A large area possible (1cm 2 ). Great Lakes Crystal Technology has made great progress in two years, but still needs development to become a trusted supplier of single crystal material. LANL staff (Dongsung Kim) has developed proficient lithography and bonding expertise at CINT to make devices from vendor supplied material. LANL staff has continued and expanded capabilities for device testing at NSLS-II.
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Manuscript for a poster to be presented at SPIE Optics + Photonics 2020 Digital Forum, 24-28 August 2020, https://spie.org/opo/conferencedetails/x-ray-gamma-ray-neutron-detector-physics.
A newsletter article to appear in the FY 2022 Q1 issue of the LDRD Quarterly Highlights, https://www.lanl.gov/projects/ldrd-tri-lab/quarterly-highlights.php.
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A table left out of OSTI #1975655
Presentation on fast machine learning usage in high energy physics for detectors and control
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Recently, combinations of generative and Bayesian deep learning have been introduced in particle physics for both fast detector simulation and inference tasks. These neural networks aim to quantify the uncertainty on the generated distribution originating from limited training statistics. The interpretation of a distribution-wide uncertainty however remains ill-defined. We show a clear scheme for quantifying the calibration of Bayesian generative machine learning models. For a Continuous Normalizing Flow applied to a low-dimensional toy example, we evaluate the calibration of Bayesian uncertainties from either a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights, to gauge their behaviour on unsteady distribution edges. Well calibrated uncertainties can then be used to roughly estimate the number of uncorrelated truth samples that are equivalent to the generated sample and clearly indicate data amplification for smooth features of the distribution.
Here, a conceptual design of a scintillator-based fast-ion loss detector (FILD) has been developed for the Wendelstein 7-X stellarator (W7-X). Simulations using the Monte Carlo codes ASCOT5 and BEAMS3D have been performed to calculate the expected flux of neutral beam injection (NBI)-generated fast hydrogen ions onto the conceptual detector probe head. These fast-ion loss fluxes have been calculated for several magnetic field configurations as well as probe insertion positions. At the maximum insertion position, both co-and counter-going losses with high incident pitch angles are observed; however, at retracted positions, only co-going fast ions reach the probe head. The FILDSIM code has been used to optimize the geometry of the detector entrance and collimating elements to achieve a wide velocity space coverage as well as a high velocity–space resolution. A synthetic FILD signal is calculated for the expected loss distribution via forward modeling using the instrument response function. The synthetic signal is found to largely retain the velocity space features of the loss distribution.
BaF₂ is one of the fastest known scintillators, emitting at 220 nm with sub-nanosecond decay constant; Excellent for timing applications. 4.88 g/cm³ → High detection efficiency; At 15 cm thick, nearly 100% efficient for gammas up to 10 MeV. Problem: ~80% of the total light output consists of slower (600 ns decay constant) emission peaked at 310 nm; High count rate → pile up. Goal: develop a BaF₂-based detector that leverages the fast emission component for optimal timing characteristics; Suppression of slow component.
The first prototype of a fast scanning diamond beam profile detector (DBPD) suitable for invasive high power CW electron beam core profile measurements in transmittance mode was developed. It consists of a multi-strip solid state diamond detector to scan with high speed (up to 1 m/s) and precision (about 5 μm) through the core of an electron beam. The diamond sensor was made from a thin polycrystalline diamond (PCD) plate with highly B-doped diamond conductive strips both grown by CVD. Transient currents from the multi-strip detector were measured with fast digitizing electrometers. Successful operation of the DBPD was demonstrated for pulsed (5 Hz) and CW (78 kHz) CeC beams, including the detector’s ability to withstand a 20 sec insertion into the CW CeC beam core. The X-Y beam spatial profile was measured in one scan. Thermal modelling demonstrated a manageable thermal impact even from a relatively long insertion of the diamond sensor into the CW CeC core and very short (0.2 s) insertion into the CW LEReC beam core. Electrical impedance modelling of the detector and vacuum chamber assembly demonstrated minimal impact on beam line impedance with diamond sensor insertion.
There have been many applications of deep neural networks to detector calibrations and a growing number of studies that propose deep generative models as automated fast detector simulators. We show that these two tasks can be unified by using maximum likelihood estimation (MLE) from conditional generative models for energy regression. Unlike direct regression techniques, the MLE approach is prior independent and non-Gaussian resolutions can be determined from the shape of the likelihood near the maximum. Using an ATLAS-like calorimeter simulation, we demonstrate this concept in the context of calorimeter energy calibration. Published by the American Physical Society 2025
A new scintillator based fast-ion loss detector (FILD) system has been designed for the Wendelstein 7-X (W7-X) stellarator. The mechanical design of the system is presented here along with engineering analyses of the system. This includes an assessment of the structural loads which also considers electromagnetic forces calculated for possible disruption scenarios as well as a mode frequency analysis of the system. Furthermore, an analysis of the thermal characteristics of the actively cooled probe head under prescribed steady state and transient heat loads is presented. Finally, the optical relay system is described and its properties used to forward model synthetic camera signals using the FILDSIM code and based on theoretical fast-ion losses incident on the probe head calculated using the ASCOT5 code.