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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

On the resolution of dual readout calorimeters

Dual readout calorimeters allow state-of-the-art resolutions for hadronic energy measurements. Their various incarnations are leading candidates for the calorimeter systems for future colliders. In this paper, we present a simple formula for the resolution of a dual readout calorimeter, which we verify with a toy simulation and with full simulation results. This formula can help those new to dual readout calorimetry understand its strengths and limitations. The paper also highlights that the dual readout correction works not just to compensate for binding energy loss, but also for energies escaping the calorimeter or clustering algorithm. Formulae are also presented for approximate resolutions and energy scales in terms of different sources of response.

Calorimeters↗
DOE OSTI2020

Unfolding quantum computer readout noise

Abstract In the current era of noisy intermediate-scale quantum computers, noisy qubits can result in biased results for early quantum algorithm applications. This is a significant challenge for interpreting results from quantum computer simulations for quantum chemistry, nuclear physics, high energy physics (HEP), and other emerging scientific applications. An important class of qubit errors are readout errors. The most basic method to correct readout errors is matrix inversion, using a response matrix built from simple operations to probe the rate of transitions from known initial quantum states to readout outcomes. One challenge with inverting matrices with large off-diagonal components is that the results are sensitive to statistical fluctuations. This challenge is familiar to HEP, where prior-independent regularized matrix inversion techniques (“unfolding”) have been developed for years to correct for acceptance and detector effects, when performing differential cross section measurements. We study one such method, known as iterative Bayesian unfolding, as a potential tool for correcting readout errors from universal gate-based quantum computers. This method is shown to avoid pathologies from commonly used matrix inversion and least squares methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Leveraging the Run 3 experience for the evolution of the ATLAS software-based readout towards HL-LHC

The High-Luminosity Large Hadron Collider (HL-LHC), scheduled to start operating in 2030, aims to increase the instantaneous luminosity by a factor of 10 compared to the LHC. To match this increase, the ATLAS experiment has been implementing a major upgrade program divided into two phases. The first phase (Phase-I), completed in 2022, introduced new trigger and detector systems that have been used during the Run 3 data taking period which began in July 2022. These systems have been used in conjunction with the new Data Acquisition (DAQ) Readout system, based on a software application called Software Readout Driver (SW ROD). SW ROD receives and aggregates data from the front-end electronics via the Front-End Link eXchange (FELIX) system and passes aggregated data fragments to the High-Level Trigger (HLT) system. During Run 3, SW ROD operates in parallel with the legacy Readout System (ROS) at an input rate of 100 kHz. For the Phase-II, the legacy ROS will be completely replaced with a new system based on the next generation of FELIX and an evolution of the SW ROD application called Data Handler. Data Handler has the same functional requirements as SW ROD but must be able to operate at an input rate of 1 MHz. To facilitate this evolution the SW ROD has been implemented using plugin architecture. This contribution presents the design and implementation of the SW ROD application for Run 3, along with the strategy for its evolution to the Phase-II Readout system. It discusses the lessons learned during Run 3 and describes the challenges that have been addressed to accomplish the demanding performance requirements of HL-LHC.

Kolos, Serguei [Univ. of California, Irvine, CA (U↗
DOE OSTI2021

Silicon strip defects and their impact on electrical performance of readout electronics

Abstract In preparation for the High Luminosity LHC (HL-LHC) runs, the ATLAS inner detector will be completely replaced with an all silicon Inner Tracker (ITk). Hybrid silicon pixel modules will be used for the innermost tracking layers, and silicon micro-strip detectors will be used the outer layers of the tracker. During the production of the detector, the sensors, readout electronics, and other components will undergo a series of quality control (QC) and quality assurance tests. Defects in the fabrication of the sensors will be flagged early in the manufacturer's and ATLAS QC tests. A study of the influence of sensor defects was performed to assess the characteristics of these defects in completed modules, and whether any defect posed a risk to the operation of the front-end readout electronics. All defects were found to have no impact on the performance of the front-end readout electronics for healthy amplifier channels, and defects that short the coupling between the strip implant and the metal readout electrode were only noticeable for strip leakage currents in excess of 250 nA, beyond the end-of-life currents expected for most sensors at the HL-LHC.

Instruments & Instrumentation↗
DOE OSTI2022

Active readout-error mitigation

Mitigating errors is a significant challenge for near-term quantum computers. One of the most important sources of errors is related to the readout of the quantum state into a classical bit stream. A variety of techniques have been proposed to mitigate these errors with post-hoc corrections. Here, we propose a complementary scheme to actively reduce readout errors on a shot-by-shot basis by encoding single qubits, immediately prior to readout, into multiqubit states. The computational resources of our technique are independent of the circuit depth and are compatible with the error rates and connectivity of many current devices. We analyze the potential of our approach using two types of error-correcting codes, and, as a proof of principle, we demonstrate an 80% improvement in readout error on the IBMQ Mumbai quantum computer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enhancing Qubit Readout with Autoencoders

In addition to the need for stable and precisely controllable qubits, quantum computers take advantage of good readout schemes. Superconducting qubit states can be inferred from the readout signal transmitted through a dispersively coupled resonator. Here, this work proposes a readout classification method for superconducting qubits based on a neural network pretrained with an autoencoder approach. A neural network is pretrained with qubit readout signals as autoencoders in order to extract relevant features from the data set. Afterward, the pretrained-network inner-layer values are used to perform a classification of the inputs in a supervised manner. We demonstrate that this method can enhance classification performance, particularly for short- and long-time measurements where more traditional methods present inferior performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A Cryogenic readout integrated circuit with analog pile-up and in-Pixel ADC for high frame rate Skipper CCD-in-CMOS Sensors

The Skipper CCD-in-CMOS Parallel Read-Out Circuit V2 (SPROCKET2) is designed to enable high frame rate readout of Skipper CCD-in-CMOS image sensors. The SPROCKET2 pixel is fabricated in a 65 nm CMOS process and occupies a 60$\mu$m $\times$ 60$\mu$m footprint. SPROCKET2 is intended to be heterogeneously integrated with a pixelated Skipper CCD-in-CMOS sensor, such that one readout pixel is connected to a multiplexed array of 16 active image sensor pixels, to match their spatial geometry. Our design benefits from the Skipper CCD-in-CMOS sensor's non-destructive readout capability to achieve exceptionally low noise through multi-sampling and averaging while optimizing for total power consumption. The pixel readout utilizes correlated double sampling to minimize 1/f noise and includes "pile-up" of ten successive samples in the analog domain before digitizing at a rate of 66.7 ksps. Measurement results of in-pixel serial SAR ADC show DNL and INL of ~0. 44 LSB and 0.58 LBS respectively. A large area array of 20,000 SPROCKET2 ADC pixels (multiplexed 1:16 to 320,000 sensor pixels) is currently under test. By reading out data over a 10 Gbps optical link, this pixel design enables a frame rate of $\sim$ 4 kfps for large sensing areas with minimal sensing deadtime. In the highest gain mode, the pixelated ADC has an input-referred resolution of 10$\mu$V with a simulated power consumption of 50$\mu$W. The pixel operates with constant current draw to minimize power-rail crosstalk.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

Johnson, Hans↗
DOE OSTI2020

SAMPA Based Streaming Readout Data Acquisition Prototype

We have assembled a small-scale streaming data acquisition system based on the SAMPA front-end ASIC. The 32-channel SAMPA chip was designed for the high-luminosity upgrade of the ALICE Time Projection Chamber (TPC) detector at the CERN Large Hadron Collider. The goals of the prototype system are to determine if the SAMPA chip is appropriate for use in detector systems at Jefferson Lab, and to gain experience with the hardware and software required to deploy streaming data acquisition systems in nuclear physics experiments. The 800 channel system is composed of components used in the ALICE TPC data acquisition upgrade. Five front-end cards (FEC) support five SAMPA chips each. SAMPA data streams on an FEC are concentrated into two high-speed (4.48 Gb/s) serial data streams by a pair Gigabit Transceiver ASICs (GBTx). These ten streams (44.8 Gb/s) are transmitted from the FECs over fibers to a PCIe based readout unit. The FPGA engine on the readout unit compresses data for transmission to a server via 100 Gb ethernet. Components on the FECs are radiation tolerant. High data rates can be handled. The system is by design scalable and thus provides a functional prototype for high-rate streaming readout at Jefferson Lab and the future Electron Ion Collider. We have made fundamental measurements (noise, linearity, time resolution) on the SAMPA ASIC. We have also coupled the readout system to a small Gas Electron Multiplier (GEM) detector and have studied its response to cosmic rays. A beam test of the system is planned.

ABBOTT, David↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The beam test of the lead tungstate calorimeter prototype with SiPM readout at Jefferson Lab

The lead tungstate crystals (PWO4) are a well-known radiator material for precise homogeneous electromagnetic calorimetry. In nuclear physics experiments, the typical way to read out the crystals is using conventional photomultiplier tubes (PMTs). In the case of the presence of a magnetic field, such a method has some complications and requires a passive PMT shielding design. The recent development of Silicon Photomultipliers (SiPMs) with small pixel pitch sizes and relatively small noise levels opens an opportunity avenue to use such a device as an alternative to conventional PMTs. The SiPM readout method may be beneficial for future nuclear physics and collider experiments. We are presenting the beam test results of the calorimeter prototype instrumented with SiPM readout performed at Jefferson Lab. The SiPM readout performance was compared with PMT readout measured at the same experimental conditions. The prototype was successfully tested using beam of photons in the energy range between 3 GeV and 11 GeV in experimental Hall D. The detector performance was also studied using a secondary beam of positrons provided by Hall D pair spectrometer.

Berdnikov, Vladimir↗
DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗
DOE OSTI2025

Improved Charge Sensing on a SiMOS Double Quantum Dot using a Cryogenic Skipper Readout ASIC (Quandarum)

Major outstanding questions in high-energy physics such as the nature of dark matter and the existence of interactions beyond the standard model require new measurement techniques which are extremely sensitive to minute electromagnetic fields. An array of entangled spin qubits is a promising system for building novel detectors due to its combination of sensitivity and controllability. CMOS-based electron spin qubits, which have demonstrated the operational requirements for fault-tolerant quantum computing [1], offer a particular opportunity due to their compatibility with classical electronics, which allows the leveraging of decades of development of low-noise cryogenic detectors for physics. In this work, we combine a SiMOS double-quantum dot device architecture with a state-of-the-art cryoelectronic readout circuit [2-3] aimed to demonstrate improved charge readout using a single-electron transistor (SET). We identify the design characteristics for an SET that facilitate the use of on-chip classical electronics as a low-power, high-bandwidth first amplification stage and explore opportunities for sensor-readout co-design to minimize noise. This is the first of a series of steps to demonstrate high-fidelity readout of a large array of spin qubit with enough sensitivity to probe processes of interest for the investigation of beyond-standard-model physics.

Quinn, Adam [Fermilab]↗
DOE OSTI2020

Smart-readout of the Skipper-CCD: Achieving Sub-electron Noise Levels in Regions of Interest

The skipper CCD is a special type of charge coupled device in which the readout noise can be reduced to sub-electron levels by averaging independent measurements of the same charge. Thus the charge in the pixels can be determined by counting the exact number of electrons. The total readout time is proportional to the number of measurements of the charge in each pixel. For some applications this time may be too long; however, researchers usually are interested only on certain region within the matrix of pixels. In this paper we present the development of a smart skipper readout technique that allows the user to specify regions of interest of the CCD matrix where an arbitrary (high) number of measurements of the same charge can taken to obtain the desired noise level, and far less measurements are performed in those regions that are less interesting to the researcher, therefore reducing the total readout time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Multimodal photon and neutron imaging devices with fast event-by-event multisampling readout and optimized particle type discrimination

A particle imaging method for distinguishing between types of incident particles, such as neutrons, photons, and alphas, and improving the position resolution of particle imaging devices with matrix readout. The method includes high frequency multisampling readout electronics that provides the sequences of multiple measurements for each detected event, resulting in recorded detailed waveform information describing the signals. Such detailed information is used to approximate each signal waveform with a parameterized function in which the extracted parameter sets determine the type of the incident particle in an optimized fashion. The detailed event-by-event multisampling information for each signal readout channel in the matrix readout of the radiation imaging devices improves and optimizes the position resolution for variable shapes of the signals. Such devices can be used in mixed radiation fields, creating a new class of multimodal photon and neutron imagers.

Degtiarenko, Pavel V.↗
DOE OSTI2024

Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

Johnson, Hans↗
DOE OSTI2023

SLAC microresonator RF(SMuRF) electronics: A tone-tracking readout system for superconducting microwave resonator arrays

Here, we describe the newest generation of the SLAC Microresonator RF (SMuRF) electronics, a warm digital control and readout system for microwave-frequency resonator-based cryogenic detector and multiplexer systems, such as microwave superconducting quantum interference device multiplexers (μmux) or microwave kinetic inductance detectors. Ultra-sensitive measurements in particle physics and astronomy increasingly rely on large arrays of cryogenic sensors, which in turn necessitate highly multiplexed readout and accompanying room-temperature electronics. Microwave-frequency resonators are a popular tool for cryogenic multiplexing, with the potential to multiplex thousands of detector channels on one readout line. The SMuRF system provides the capability for reading out up to 3328 channels across a 4–8 GHz bandwidth. Notably, the SMuRF system is unique in its implementation of a closed-loop tone-tracking algorithm that minimizes RF power transmitted to the cold amplifier, substantially relaxing system linearity requirements and effective noise from intermodulation products. Here, we present a description of the hardware, firmware, and software systems of the SMuRF electronics, comparing achieved performance with science-driven design requirements. In particular, we focus on the case of large-channel-count, low-bandwidth applications, but the system has been easily reconfigured for high-bandwidth applications. The system described here has been successfully deployed in lab settings and field sites around the world and is baselined for use on upcoming large-scale observatories.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The upgrade of the ALICE TPC with GEMs and continuous readout

The upgrade of the ALICE TPC will allow the experiment to cope with the high interaction rates foreseen for the forthcoming Run 3 and Run 4 at the CERN LHC. In this article, we describe the design of new readout chambers and front-end electronics, which are driven by the goals of the experiment. Gas Electron Multiplier (GEM) detectors arranged in stacks containing four GEMs each, and continuous readout electronics based on the SAMPA chip, an ALICE development, are replacing the previous elements. The construction of these new elements, together with their associated quality control procedures, is explained in detail. Finally, the readout chamber and front-end electronics cards replacement, together with the commissioning of the detector prior to installation in the experimental cavern, are presented. After a nine-year period of R&D, construction, and assembly, the upgrade of the TPC was completed in 2020.

47 OTHER INSTRUMENTATION↗