arXiv subjects

Antonino Miceli

Publications and source records attributed to Antonino Miceli.

At least 37 records · Page 2Linked to original sources

arXiv2022

Pushing compute and AI onto detector silicon

In order to take full advantage of the U.S. Department of Energy's billion-dollar investments into the next-generation research infrastructure (e.g., exascale, light sources, colliders), advances are required not only in detector technology but also in computing and specifically AI. Let us consider an example from X-ray science. Nanoscale X-ray imaging is a crucial tool to enable a wide range of scientific explorations from materials science and biology to mechanical and civil engineering. The next-generation light sources will increase the X-ray beam brightness and coherent flux by 100 to 1,000 times. In order to image larger samples, the continuous frame rate of pixel array detectors must be increased, approaching 1 MHz, which requires several Tbps (aggregated) to transfer pixel data out to a data acquisition system. Using 65-nm CMOS technology, an optimistic raw data rate off such a chip is about 100-200 Gbps. However, a continuous 1 MHz detector with only $256 \times 256$ pixels at 16-bit resolution, for example, will require 1,000 Gbps (i.e., 1 Tbps) bandwidth off the chip! It is impractical to have multiple high-speed transceivers running in parallel to provide such bandwidth and represents the first data bottleneck. New approaches are necessary to reduce the data size by performing data compression or AI-based feature extraction directly inside a detector silicon chip in a streaming manner before sending it off-chip.

physics.ins-det↗

arXiv2022

Bridging Data Center AI Systems with Edge Computing for Actionable Information Retrieval

Extremely high data rates at modern synchrotron and X-ray free-electron laser light source beamlines motivate the use of machine learning methods for data reduction, feature detection, and other purposes. Regardless of the application, the basic concept is the same: data collected in early stages of an experiment, data from past similar experiments, and/or data simulated for the upcoming experiment are used to train machine learning models that, in effect, learn specific characteristics of those data; these models are then used to process subsequent data more efficiently than would general-purpose models that lack knowledge of the specific dataset or data class. Thus, a key challenge is to be able to train models with sufficient rapidity that they can be deployed and used within useful timescales. We describe here how specialized data center AI (DCAI) systems can be used for this purpose through a geographically distributed workflow. Experiments show that although there are data movement cost and service overhead to use remote DCAI systems for DNN training, the turnaround time is still less than 1/30 of using a locally deploy-able GPU.

cs.LG↗

arXiv2021

Devices for Thermal Conductivity Measurements of Electroplated Bi for X-ray TES Absorbers

Electroplated Bismuth (Bi) is commonly used in Transition-Edge Sensors (TESs) for X-rays because of its high stopping power and low heat capacity. Electroplated Bi is usually grown on top of another metal that acts as seed layer, typically gold (Au), making it challenging to extrapolate its thermoelectric properties. In this work, we present four-wire resistance measurement structures that allow us to measure resistance as a function of temperature of electroplated Bi independently of Au. The results show that the thermal conductivity of the Bi at 3 K is high enough to guarantee the correct thermalization of X-ray photons when used as an absorber for TESs.

physics.ins-det↗

arXiv2021

A Hardware Co-design Workflow for Scientific Instruments at the Edge

As spatial and temporal resolutions of scientific instruments improve, the explosion in the volume of data produced is becoming a key challenge. It can be a critical bottleneck for integration between scientific instruments at the edge and high-performance computers/emerging accelerators. Placing data compression or reduction logic close to the data source is a possible approach to solve the bottleneck. However, the realization of such a solution requires the development of custom ASIC designs, which is still challenging in practice and tends to produce one-off implementations unusable beyond the initial intended scope. Therefore, as a feasibility study, we have been investigating a design workflow that allows us to explore algorithmically complex hardware designs and develop reusable hardware libraries for the needs of scientific instruments at the edge. Our vision is to cultivate our hardware development capability for streaming/dataflow hardware components that can be placed close to the data source to enable extreme data-intensive scientific experiments or environmental sensing. Furthermore, reducing data movement is essential to improving computing performance in general. Therefore, our co-design efforts on streaming hardware components can benefit computing applications other than scientific instruments. This vision paper discusses hardware specialization needs in scientific instruments and briefly reviews our progress leveraging the Chisel hardware description language and emerging open-source hardware ecosystems, including a few design examples.

physics.ins-det↗

arXiv2021

Designing a Streaming Data Coalescing Architecture for Scientific Detector ASICs with Variable Data Velocity

Scientific detectors are a key technological enabler for many disciplines. Application-specific integrated circuits (ASICs) are used for many of these scientific detectors. Until recently, pixel detector ASICs have been used mainly for analog signal processing of the charge from the sensor layer and the transmission of raw pixel data off the detector ASIC. However, with the availability of more advanced ASIC technology nodes for scientific application, more digital functionality from the computing domains (e.g., compression) can be integrated directly into the detector ASIC to increase data velocity. However, these computing functionalities often have high and variable latency, whereas scientific detectors must operate in real-time (i.e., stall-free) to support continuous streaming of sampled data. This paper presents an example from the domain of pixel detectors with on-chip data compression for X-ray science applications. To address the challenges of variable-sized data from a parallel stream of compressors, we present an ASIC design architecture to coalesce variable-length data for transmission over a fixed bit-width network interface.

physics.ins-det↗

arXiv2021

BraggNN: Fast X-ray Bragg Peak Analysis Using Deep Learning

X-ray diffraction based microscopy techniques such as High Energy Diffraction Microscopy rely on knowledge of the position of diffraction peaks with high precision. These positions are typically computed by fitting the observed intensities in area detector data to a theoretical peak shape such as pseudo-Voigt. As experiments become more complex and detector technologies evolve, the computational cost of such peak detection and shape fitting becomes the biggest hurdle to the rapid analysis required for real-time feedback during in-situ experiments. To this end, we propose BraggNN, a deep learning-based method that can determine peak positions much more rapidly than conventional pseudo-Voigt peak fitting. When applied to a test dataset, BraggNN gives errors of less than 0.29 and 0.57 pixels, relative to the conventional method, for 75% and 95% of the peaks, respectively. When applied to a real experimental dataset, a 3D reconstruction that used peak positions computed by BraggNN yields 15% better results on average as compared to a reconstruction obtained using peak positions determined using conventional 2D pseudo-Voigt fitting. Recent advances in deep learning method implementations and special-purpose model inference accelerators allow BraggNN to deliver enormous performance improvements relative to the conventional method, running, for example, more than 200 times faster than a conventional method on a consumer-class GPU card with out-of-the-box software.

eess.IV↗

arXiv2020

Strategies for on-chip digital data compression for X-ray pixel detectors

The continued desire for X-ray pixel detectors with higher frame rates will stress the ability of application-specific integrated circuit (ASIC) designers to provide sufficient off-chip bandwidth to reach continuous frame rates in the 1 MHz regime. To move from the current 10 kHz to the 1 MHz frame rate regime, ASIC designers will continue to pack as many power-hungry high-speed transceivers at the periphery of the ASIC as possible. In this paper, however, we present new strategies to make the most efficient use of the off-chip bandwidth by utilizing data compression schemes for X-ray photon-counting and charge-integrating pixel detectors. In particular, we describe a novel in-pixel compression scheme that converts from analog to digital converter units to encoded photon counts near the photon Poisson noise level and achieves a compression ratio of $>\!1.5\times$ independent of the dataset. In addition, we describe a simple yet efficient zero-suppression compression scheme called ``zeromask'' (ZM) located at the ASIC's edge before streaming data off the ASIC chip. ZM achieves average compression ratios of $>\!4\times$, $>\!7\times$, and $>\!8\times$ for high-energy X-ray diffraction, ptychography, and X-ray photon correlation spectroscopy datasets, respectively. We present the conceptual designs, register-transfer level block diagrams, and the physical ASIC implementation of these compression schemes in 65-nm CMOS. When combined, these two digital compression schemes could increase the effective off-chip bandwidth by a factor of 6-12$\times$.

physics.ins-det↗

arXiv2019

Hard X-ray Fluorescence measurements with TESs at the Advanced Photon Source

Transition Edge Sensor (TES) spectrometers for hard X-ray beamline science will enable improved X-ray emission and absorption spectroscopy in the information-rich 2 to 20 keV energy range. We are building a TES-based instrument for the Advanced Photon Source (APS) synchrotron, to be made available to beamline users. 24-pixel prototype arrays have recently been fabricated and tested. The first spectroscopy measurements using these arrays are promising, with a best single-pixel energy resolution of 11.2 eV and saturation energy > 20 keV. We present a series of recent X-ray Fluorescence measurements involving transition metal elements and multi-element samples with closely spaced emission lines, in particular a Cu-Ni-Co thin film and a foil of Cu and Hf. The TES-measured spectra are directly compared to spectra measured with silicon drift detectors at an APS beamline, demonstrating the improved X-ray science made possible by TES spectrometers.

physics.ins-det↗

arXiv2019

Development of a High Rate Front-end ASIC for X-ray Spectroscopy and Diffraction Applications

We developed a new front-end application specific integrated circuit (ASIC) for the upgrade of the Maia x-ray microprobe. The ASIC instruments 32 configurable front-end channels that perform either positive or negative charge amplification, pulse shaping, peak amplitude and time extraction along with buffered analog storage. At a gain of 3.6 V/fC, 1 $μ$s peaking time and a temperature of 248 K, an electronic resolution of 13- and 10 electrons rms was measured with and without a SDD sensor respectively. A spectral resolution of 170 eV FWHM at 5.9 keV was obtained with an $^{55}$Fe source. The channel linearity was better than $\pm$ 1 % with rate capabilities up to 40 kcps. The ASIC was fabricated in a commercial 250 nm process with a footprint of 6.3 mm x 3.9 mm and dissipates 167 mW of static power.

physics.ins-det↗

arXiv2019

Modelling a Transition-Edge Sensor X-ray Microcalorimeter Linear Array for Compton Profile Measurements and Energy Dispersive Diffraction

Transition-edge sensors are a type of superconducting detector that offers high energy resolution based on their sharp resistance-temperature feature in the superconducting-to-normal transition. TES X-ray microcalorimeters have typically been designed and used for spectroscopic applications. In this work, we present a design optimization for a TES X-ray microcalorimeter array for high-energy scattering and diffraction measurements. In particular, Compton scattering provides information about the electron momentum distribution, while energy dispersive diffraction provides structural information about dense engineering materials. Compton scattering and energy dispersive diffraction experiments must be conducted in the very hard X-ray regime (~ 100 keV), demanding a high X-ray stopping power in the detector; therefore, an absorber with a large heat capacity is needed in conjunction with the TES. In addition, both applications would benefit from an array composed of parallel strips. We present a design for a TES X-ray microcalorimeter optimized for such applications. In particular, we model the longitudinal position dependence due to the finite thermal diffusion time in the absorber.

physics.ins-det↗

arXiv2019

A Two-Dimensional Resistor Network Model for Transition-Edge Sensors with Normal Metal Features

Transition-edge sensors (TESs) can be used in high-resolution photon detection, exploiting the steep slope of the resistance in the superconducting-to-normal transition edge. Normal metal bars on the TES film are commonly used to engineer its transition shape, namely the dependence of resistance on temperature and current. This problem has been studied in one dimension, however until now, there have been no predictive models of the influence of two-dimensional (2-D) normal metal features on the TES transition shape. In this work, we approach this problem by treating the TES as a 2-D network of resistors, the values of which are based on the two-fluid model. We present a study of the behavior of devices with different 2-D geometric features. Our 2-D network model is capable of predicting how typical TES geometry parameters, such as number of bars, bar spacing, and overall dimensions, influence device behavior and thus is a powerful tool to guide the engineering of new TES devices.

physics.ins-det↗

arXiv2018

Multi-element Germanium Detectors for Synchrotron Applications

We have developed a series of monolithic multi-element germanium detectors, based on sensor arrays produced by the Forschungzentrum Julich, and on Application-specific integrated circuits (ASICs) developed at Brookhaven. Devices have been made with element counts ranging from 64 to 384. These detectors are being used at NSLS-II and APS for a range of diffraction experiments, both monochromatic and energy-dispersive. Compact and powerful readout systems have been developed, based on the new generation of FPGA system-on-chip devices, which provide closely coupled multi-core processors embedded in large gate arrays. We will discuss the technical details of the systems, and present some of the results from them.

physics.ins-det↗

arXiv2018

Quantum Sensing for High Energy Physics

Report of the first workshop to identify approaches and techniques in the domain of quantum sensing that can be utilized by future High Energy Physics applications to further the scientific goals of High Energy Physics.

hep-ex↗

arXiv2017

Microstructure analysis of bismuth absorbers for transition-edge sensor X-ray microcalorimeters

Transition-edge sensors (TESs) as microcalorimeters offer high resolving power, owning to their sharp response and low operating temperature. In the hard X-ray regime and above, the demand for high quantum-efficiency requires the use of absorbers. Bismuth (Bi), owing to its low heat carrier density and high X-ray stopping power, has been widely used as an absorber material for TESs. However, distinct spectral responses have been observed for Bi absorbers deposited via evaporation versus electroplating. Evaporated Bi absorbers are widely observed to have a non-Gaussian tail on the low energy side of measured spectra. In this study, we fabricated Bi absorbers via these two methods, and performed microstructure analysis using scanning electron microscopy (SEM) and X-ray diffraction microscopy. The two types of material showed the same crystallographic structure, but the grain size of the evaporated Bi was about 40 times smaller than that of the electroplated Bi. This distinction in grain size is likely to be the cause of their different spectral responses.

physics.ins-det↗

arXiv2017

Eliminating the non-Gaussian spectral response of X-ray absorbers for transition-edge sensors

Transition-edge sensors (TES) as microcalorimeters for high-energy-resolution X-ray spectroscopy are often fabricated with an absorber made of materials with high Z (for X-ray stopping power) and low heat capacity (for high resolving power). Bismuth represents one of the most compelling options. TESs with evaporated bismuth absorbers have shown spectra with undesirable and unexplained low-energy tails. We have developed TESs with electroplated bismuth absorbers over a gold layer that are not afflicted by this problem and that retain the other positive aspects of this material. To better understand these phenomena, we have studied a series of TESs with gold, gold/evaporated bismuth, and gold/electroplated bismuth absorbers, fabricated on the same die with identical thermal coupling. We show that bismuth morphology is linked to the spectral response of X-ray TES microcalorimeters.

physics.ins-det↗

arXiv2016

Processing of X-ray Microcalorimeter Data with Pulse Shape Variation using Principal Component Analysis

We present a method using principal component analysis (PCA) to process x-ray pulses with severe shape variation where traditional optimal filter methods fail. We demonstrate that PCA is able to noise-filter and extract energy information from x-ray pulses despite their different shapes. We apply this method to a dataset from an x-ray thermal kinetic inductance detector which has severe pulse shape variation arising from position-dependent absorption.

physics.ins-det↗

arXiv2013

X-ray photon detection using superconducting resonators in thermal quasi-equilibrium

Superconducting resonators have to date been used for photon detection in a non-equilibrium manner. In this paper, we demonstrate that such devices can also be used in a thermal quasi-equilibrium manner to detect X-ray photons. We have used a resonator to measure the temperature rise induced by an X-ray photon absorbed in normal metal and superconducting absorbers on continuous and perforated silicon nitride membranes. We observed two distinct pulses with vastly different decay times. We attribute the shorter pulses to non-equilibrium quasiparticle relaxation and the longer pulses to a thermal relaxation process. In addition, we have measured the temperature dependence of the X-ray induced temperature rise and decay times. Finally, we have measured the resonator sensitivity and energy resolution. Superconducting resonators used in a thermal quasi-equilibrium manner have the potential to be used for X-ray microcalorimetry.

cond-mat.supr-con↗

arXiv2012

Tungsten silicide films for microwave kinetic inductance detectors

Microwave Kinetic Inductance Detectors (MKIDs) provide highly multiplexed arrays of detectors that can be configured to operate from the sub-millimeter to the X-ray regime. We have examined two tungsten silicide alloys (W5Si3 and WSi2), which are dense alloys that provide a critical temperature tunable with composition, large kinetic inductance fraction, and high normal-state resistivity. We have fabricated superconducting resonators and provide measurement data on critical temperature, surface resistance, quality factor, noise, and quasiparticles lifetime. Tungsten silicide appears to be promising for microwave kinetic inductance detectors.

cond-mat.supr-con↗