Readout Performance Research Articles

A high‐performance asynchronous readout circuit with cascade function for a neural recording micro‐electrode array

AbstractThe data‐driven machine learning technology used for neural decoding emphasizes the requirements of in vivo and in vitro neural signal acquisition with high spatial and temporal resolution. However, micro‐electrode arrays (MEAs) that simultaneously achieve high spatial and temporal resolution neural signal acquisition are not yet available. Meanwhile, the high data bandwidth of large‐scale MEA brings challenges in power consumption, data transmission, storage, and neural signal processing. This research aims to improve the spatial and temporal resolution of MEA, reduce the cost and time of large‐scale MEA customization through cascading, and reduce the bandwidth of large‐scale MEA through spike compression. Firstly, based on in‐pixel spike detection, a row‐based neural spike readout mechanism and related array circuit to improve the neural spike readout performance and temporal resolution of neural signal acquisition is proposed. To further enhance the spatial resolution and reduce the risk of large‐scale MEA fabrication, the cascading capability of the readout circuit is explored. Lastly, spatial correlation‐based neural spike encoding is proposed to reduce the data bandwidth, achieving a 5.2× compression rate. This is a study on implementing large‐scale MEA through cascaded readout circuits and novel study to utilize the spatial correlation between detected neural spikes for further compression.

Pure kinetic inductance coupling for cQED with flux qubits

We demonstrate a qubit-readout architecture where the dispersive coupling is entirely mediated by a kinetic inductance. This allows us to engineer the dispersive shift of the readout resonator independent of the qubit and resonator capacitances. We validate the pure kinetic coupling concept and demonstrate various generalized flux qubit regimes from plasmon to fluxon, with dispersive shifts ranging from 60 kHz to 2 MHz at the half-flux quantum sweet spot. We achieve readout performances comparable to conventional architectures with quantum state preparation fidelities of 99.7% and 92.7% for the ground and excited states, respectively, and below 0.1% leakage to non-computational states.

Iodide based electrochemical gold quantification method for lateral flow assays

The lateral flow assay (LFA) is an ideal technology for at-home medical diagnostic tests due to its ease of use, cost-effectiveness, and rapid results. Despite these advantages, only few LFAs, such as the pregnancy and COVID-19 tests, have been translated from the laboratory to the homes of patients. To date, the medical applicability of LFAs is limited by the fact that they only provide yes/no answers unless combined with optical readers that are too expensive for at-home applications. Furthermore, LFAs are unable to compete with the state-of-the-art technologies in centralized laboratories in terms of detection limits. To address those shortcomings, we have developed an electrochemical readout procedure to enable quantitative and sensitive LFAs. This technique is based on a voltage-triggered in-situ dissolution of gold nanoparticles, the conventional label used to visualize target-specific signals on the test line in LFAs. Following the dissolution, the amount of gold is measured by electroplating onto an electrode and subsequent electrochemical quantification of the deposited gold. The measured current has a low noise, which achieves superior detection limits compared to optical techniques where background light scattering is limiting the readout performance. In addition, the hardware for the readout was developed to demonstrate translatability towards low-cost electronics.

Multimodule microwave assembly for fast readout and charge-noise characterization of silicon quantum dots

Fast measurements of quantum devices is useful in areas such as quantum sensing, quantum computing, and nanodevice quality analysis. Here, we develop a superconductor-semiconductor multimodule microwave assembly to demonstrate charge-state readout at the state of the art. The assembly consist of a superconducting readout resonator interfaced to a silicon-on-insulator (SOI) chiplet containing quantum dots (QDs) in a high-κ nanowire transistor. The superconducting chiplet contains resonant and coupling elements as well as LC filters that, when interfaced with the silicon chip, result in a resonant frequency f=2.12 GHz, a loaded quality factor Q=850, and a resonator impedance Z=470Ω. Combined with the large gate lever arms of SOI technology, we achieve a minimum integration time for single and double QD transitions of 2.77 and 13.5 ns, respectively. We utilize the assembly to measure charge noise over 9 decades of frequency up to 500 kHz and find a 1/f dependence across the whole frequency spectrum as well as a charge-noise level of 4μeV/Hz at 1 Hz. The modular microwave circuitry presented here can be directly utilized in conjunction with other quantum devices to improve the readout performance as well as enable large bandwidth noise spectroscopy, all without the complexity of superconductor-semiconductor monolithic fabrication. Published by the American Physical Society 2024

Model and analysis of the data readout architecture for the ITS3 ALICE Inner Tracker System

The ALICE collaboration is developing the Inner Tracker System 3 (ITS3), a novel detector that exploits the stitching technique to construct single-die monolithic pixel sensors of up-to 266 mm × 93 mm. ITS3 requires all hits from a particle flux of 5.75 MHz/cm2 to be transmitted on-chip to one of the sensor edges. This on-chip readout must balance the resources of power consumption, dead area, and readout performance by tuning different design parameters such as on-chip memories or on-chip links bandwidth. For doing so, a model of the ITS3 on-chip readout architecture will be presented. This model combines an accurate simulation of the particle flux fluctuations expected in ALICE with a clock-accurate digital readout simulator, combining high accuracy with fast code in terms of simulation speed.

Photon-Noise-Tolerant Dispersive Readout of a Superconducting Qubit Using a Nonlinear Purcell Filter

Residual noise photons in a readout resonator become a major source of dephasing for a superconducting qubit when the resonator is optimized for a fast, high-fidelity dispersive readout. Here, we propose and demonstrate a nonlinear Purcell filter that suppresses such an undesirable dephasing process without sacrificing the readout performance. When a readout pulse is applied, the filter automatically reduces the effective linewidth of the readout resonator, increasing the sensitivity of the qubit to the input field. The noise tolerance of the device we have fabricated is shown to be enhanced by a factor of 3 relative to a device with a linear filter. The measurement rate is enhanced by another factor of 3 by utilizing the bifurcation of the nonlinear filter. A readout fidelity of 99.4% and a quantum nondemolition fidelity of 99.2% are achieved using a 40-ns readout pulse. The nonlinear Purcell filter will be an effective tool for realizing a fast, high-fidelity readout without compromising the coherence time of the qubit. Published by the American Physical Society 2024

Design of Ultra-High Density Archival Storage Memory with Nanoprobe and Patterned Oxygenated Amorphous Carbon with Metal Nanoclusters

Recent prosperity of artificial intelligence is undoubtedly making global data increase at a phenomenal rate. This obviously poses more stringent requirements on current storage devices. Unfortunately, considerable effort is only devoted to the development of on-chip storage device, while off-chip storage technology, particularly for archival storage device, remains slowly progressed. To further innovate the archival storage device, and thus revive its market, we here proposed a novel concept of an archival storage device based on scanning nanoprobe and oxygenated amorphous carbon having metal nanoclusters. A comprehensive numerical model was developed to mimic the write and readout performances of such archival storage device. It was found that the introduction of metal nanoclusters induced much stronger electric field inside the amorphous carbon layer than the case without metal nanoclusters. This beneficially facilitated the growth of conductive filament along metal nanoclusters, and the feasibility of using the proposed device to achieve an areal density of terabit per-square-inch area density, a write energy of picojoule energy per bit, and a switching speed of tens of nanoseconds, was demonstrated.

Smart Chemical Sensor and Biosensor Networks for Healthcare 4.0.

Driven by technological advances from Industry 4.0, Healthcare 4.0 synthesizes medical sensors, artificial intelligence (AI), big data, the Internet of things (IoT), machine learning, and augmented reality (AR) to transform the healthcare sector. Healthcare 4.0 creates a smart health network by connecting patients, medical devices, hospitals, clinics, medical suppliers, and other healthcare-related components. Body chemical sensor and biosensor networks (BSNs) provide the necessary platform for Healthcare 4.0 to collect various medical data from patients. BSN is the foundation of Healthcare 4.0 in raw data detection and information collecting. This paper proposes a BSN architecture with chemical sensors and biosensors to detect and communicate physiological measurements of human bodies. These measurement data help healthcare professionals to monitor patient vital signs and other medical conditions. The collected data facilitates disease diagnosis and injury detection at an early stage. Our work further formulates the problem of sensor deployment in BSNs as a mathematical model. This model includes parameter and constraint sets to describe patient body characteristics, BSN sensor features, as well as biomedical readout requirements. The proposed model's performance is evaluated by multiple sets of simulations on different parts of the human body. Simulations are designed to represent typical BSN applications in Healthcare 4.0. Simulation results demonstrate the impact of various biofactors and measurement time on sensor selections and readout performance.

Accurate Sneak-Path-Controlled Readout for a Cross-Point Resistive Sensor Array

A readout method of measuring resistances from a sensor array is proposed. As opposed to the conventional method of feedback readout, in which the crosstalk is suppressed by an op-amp, the sneak paths are controlled by switches, and a matrix equation of the circuit is derived from measured voltage. Thus, the scanning speed and power consumption of an interface circuit are not inherently deteriorated by the op-amp. The main factors affecting readout accuracy are parasitic resistance of the analog switch and quantized error of the analog-to-digital converters (ADCs). Therefore, calibration of switch resistance is also proposed to maintain readout accuracy by additional ADCs. To evaluate the proposed readout system, “sneak-path-controlled readout” (SPCR) and “accurate sneak-path-controlled readout” (ASPCR) are implemented. To verify the accuracy of the proposed readout method, the interface circuit and the calibration of switch resistance were simulated by MATLAB. The target array size was 32×32, and the sensor resistances were distributed in the same manner as real sensors. Since readout performance is also affected by the pattern of resistances, several patterns of resistance were prepared, and their results were compared. The results of the simulations show that SPCR using a 16-bit ADC can read normally distributed sensors with readout error of 0.05%. Moreover, ASPCR can handle a wider resistance distribution, and its readout error was less than 0.3% with a resistance pattern in which resistance ranges from 1.71 kΩ to 217 kΩ.

Noise-resistant quantum state compression readout

Qubit measurement is generally the most error-prone operation that degrades the performance of near-term quantum devices, and the exponential decay of readout fidelity severely impedes the development of large-scale quantum information processing. Given these disadvantages, we present a quantum state readout method, named compression readout, that naturally avoids large multi-qubit measurement errors by compressing the quantum state into a single qubit for measurement. Our method generally outperforms direct measurements in terms of accuracy, and the advantage grows with the system size. Moreover, because only one-qubit measurements are performed, our method requires solely a fine readout calibration on one qubit and is free of correlated measurement error, which drastically diminishes the demand for device calibration. These advantages suggest that our method can immediately boost the readout performance of near-term quantum devices and will greatly benefit the development of large-scale quantum computing.

Online optimization for optical readout of a single electron spin in diamond

The nitrogen-vacancy (NV) center in diamond has been developed as a promising platform for quantum sensing, especially for magnetic field measurements in the nano-tesla range with a nano-meter resolution. Optical spin readout performance has a direct effect on the signal-to-noise ratio (SNR) of experiments. In this work, we introduce an online optimization method to customize the laser waveform for readout. Both simulations and experiments reveal that our new scheme optimizes the optically detected magnetic resonance in NV center. The SNR of optical spin readout has been witnessed a 44.1% increase in experiments. In addition, we applied the scheme to the Rabi oscillation experiment, which shows an improvement of 46.0% in contrast and a reduction of 12.1% in mean deviation compared to traditional constant laser power SNR optimization. This scheme is promising to improve sensitivities for a wide range of NV-based applications in the future.

Phase-Change Nanophotonic Circuits With Crossbar Electrodes and Integrated Microheaters

Phase-change photonics integrated circuits (PICs) have most recently attained considerable attention due to their broad bandwidth, superfast processing speed, and multiplexing function. However, their poor scalability adversely limited current PICs into single cell or simple architectures. To overcome this issue, for the first time we modelled the write and readout performances of Ge2Sb2Te5-based nanophotonic architecture with integrated indium-Tin-oxide (ITO) heater and crossbar platinum (Pt) electrodes. The updated architecture, when compared with other reported prototypes, exhibited better scalability and smaller energy consumptions. Its ability to achieve random access and multilevel functions at system level was also demonstrated by simulations, implying its bright prospect for in-memory computing and neuromorphic computing applications.

Study of Readout Channel Signals from Electrical Probe Memory

Electrical probe memory using phase-change materials (PCM) has been considered as one of the most promising candidates for the future archival storage market. This can be attributed to the use of nanoscale probe that allows for ultra-high density and PCMs that lead to ultra-fast write/read speed and ultra-small energy consumption. For above reasons, considerable research is devoted to researching the write performances of the electrical probe memory, while ignoring the detailed study on its readout performances. To address this issue, we investigated the impulse response and step response of the electrical probe memory with crystalline bit embedded inside the amorphous matrix, which are the key factors to the readout channel design. Additionally, the appropriate readout excitations and the resulting DC offset are also well-established in order to ensure the reliability of the readout performances. We also assess the tip offset interference that may have an adverse effect on resulting signals. The calculated channel impulse response signal is eventually mathematically modelled so as to understand the behavior of the readback channel in linear and non-linear sense based on Gaussian and Lorentzian approximations.

Generalized figure of merit for qubit readout

Many promising approaches to fault-tolerant quantum computation require repeated quantum nondemolition (QND) readout of binary observables such as quantum bits (qubits). A commonly used figure of merit for readout performance is the error rate for binary assignment in a single repetition. However, it is known that this figure of merit is insufficient. Indeed, real-world readout outcomes are typically analog instead of binary. Binary assignment therefore discards important information on the level of confidence in the analog outcomes. Here, a generalized figure of merit that fully captures the information contained in the analog readout outcomes is suggested. This figure of merit is the Chernoff information associated with the statistics of the analog readout outcomes in one repetition. Unlike the single-repetition error rate, the Chernoff information uniquely determines the asymptotic cumulative error rate for arbitrary readout noise. As a result, non-Gaussian readout noise common in experiments can be described by effective Gaussian noise with the same Chernoff information. Importantly, it is shown that such a universal description persists for the small number of repetitions and non-QND imperfections relevant to real experiments. Finally, the Chernoff information is used to rigorously quantify the amount of information discarded by analog-to-binary conversion. These results provide a unified framework for qubit readout and should facilitate optimization and engineering of near-term quantum devices across all platforms.

Carbon resistive probe memory designed for ultra-high storage density

Probe-based storage memories are considered one of the most promising solutions to address the mass storage issues in the near future. However, data size arising from conventional probe memories is usually larger than probe size due to the thermal diffusion effect. To eliminate such thermal interference and make data dimension fully dominated by probe dimension, we proposed a concept of carbon-based resistive probe memory and developed a comprehensive computational model to predict its write, rewrite and readout performances governed by electro-thermal and mass concentration processes. The physical reality of such a theoretical model was demonstrated through the good agreement between the calculated and experimental measured threshold voltages for different layered thickness. The data bit of carbon-based resistive probe memory, considered as the sp2 filament inside sp3 background, is formed completely underneath the tip edge due to the localized electric field induced here. This makes the bit size fully determined by the probe tip dimension and allows for the achievement of ultra-high density using an ultra-small probe tip with low energy consumption. Such a conductive filament can be also rewritten back to its pristine sp3 state at relatively high temperature (~250 °C) and detected by sensing the device reading contrast (~1). The designed carbon-based resistive probe memory can retain its bit completeness even if we reduce the bit pitch to 28 nm for a probe size of 25 nm, exhibiting a superior immunity to thermal cross-talk effect. It, however, induces strong readout cross-talk, which is revealed from the resistance image of the multiple bit pattern. This adversely reduces the achievable recording density due to the required large bit pitch, which can be alleviated using either a very sharp tip apex or the optical readout scheme.

Design of a Nonvacuum-Cooling Compact CCD Camera for Scientific Detection

In this article, a nonvacuum-cooling compact (NVCC) scientific charge-coupled device (CCD) camera is presented that includes low noise clocks, a bias driver circuit, a data acquisition circuit, and a temperature control circuit. Experiments are conducted to test the readout performance of the proposed imaging system. The scheme for generating the CCD clocks and the bias driver circuit through ultralow noise low-dropout regulators is designed. The entire design can operate from −40 °C to 40 °C. The test results of the camera show that the system can run at a maximum readout rate of 5 Mpixels/s. The readout noise of the camera is as low as $9.29\,\, {e}^{-}$ when the readout speed is 500 Kpixels/s. The designed camera is currently used in a 1.2-m telescope system at Delingha Observatory.

Behavioral modeling of integrated phase-change photonic devices for neuromorphic computing applications

The combination of phase-change materials and integrated photonics has led to the development of new forms of all-optical devices, including photonic memories, arithmetic and logic processors, and synaptic and neuronal mimics. Such devices can be readily fabricated into photonic integrated circuits, so potentially delivering large-scale all-optical arithmetic-logic units and neuromorphic processing chips. To facilitate in the design and optimization of such large-scale systems, and to aid in the understanding of device and system performance, fast yet accurate computer models are needed. Here, we describe the development of a behavioral modeling tool that meets such requirements, being capable of essentially instantaneous modeling of the write, erase, and readout performance of various integrated phase-change photonic devices, including those for synaptic and neuronal mimics.

Scanning probe memory with patterned amorphous carbon layer

The write and readout performances of a novel patterned probe memory using amorphous carbon film is investigated by a newly developed electrical switching model based on the modified Poole–Frenkel mechanism. According to this model, the optimized media stack consists of a 40 nm titanium nitride underlayer and amorphous carbon cells with the dimension of 5 × 5 × 5 nm3, isolated by a silicon dioxide region with a width of 3 nm. The capability of the designed device to provide ultra-high density, utmost reading contrast, ultra-low energy consumption and superb anti-thermal/readout interference was demonstrated, thus making it superior to any reported probe memories to date.

Theoretical Study of a Surface Collinear Holographic Memory

Holographic memory is currently attracting attention as a data storage system capable of achieving a data transfer rate of about 105~106105~106 times that of an optical disc such as Blu-ray disc. In conventional holographic memory, data is generally recorded by optical writing using volume holograms. However, a volume hologram has the problem not only that it is required to have high mechanical accuracy of a system and low coefficient of thermal expansion of a recording medium, because reconstruction tolerance is extremely low, but also that duplicating time efficiency is poor because whole data cannot be recorded at once. In this paper we proposed surface holographic memory that achieved a high data transfer rate, stable readout performance, and collective duplication by expressing holograms with fine surface asperity. Furthermore, the theoretical formulas of recording and reconstruction processes in the proposed system were derived and the reconstruction characteristics of the hologram were evaluated by numerical simulation. As a result, the proposed method generated reconstructed image readout with sufficient signal for a single page recording. However, the reconstructed image had noise, which was particular to a surface holographic memory.

Fabrication of a flexible wireless pressure sensor for intravascular blood pressure monitoring

This work presents the development of a wireless passive pressure sensor for cardiovascular pressure monitoring. The device is designed to be inserted into a stent that can be deployed within a blood vessel using a catheter-based delivery system. By utilizing micromachining techniques, a variable capacitor and an inductor were implemented in the sensor as an L-C resonator for wireless pressure sensing and signal retrieving. The sensor employs biocompatible polymeric material, parylene-C, as the substrate material. The pressure responses of the sensor, such as the sensitivity, linearity, and hysteresis, were measured and discussed. The sensitivity was approximately 6.19 × 10−2/kPa (8.25 × 10−3/mmHg), and the linearity over the ranges of 0–6 kPa (0–50 mmHg) and 6–33 kPa (50–250 mmHg) were approximately 91.5% and 87.6%, respectively. The wireless pressure sensing performance of the sensor was evaluated using the phase-dip technique. Additionally, the measured results indicate that the resonant frequency of the resonator shifted from 211 MHz to 182 MHz, as the pressure varied from 0 to 33 kPa (250 mmHg). The maximum standard error of the mean is 0.86 MHz. Finally, the influence of coil thickness on the wireless readout performance was investigated.