Fundamental thresholds of realistic quantum error correction circuits from classical spin models

Mapping the decoding of quantum error correcting (QEC) codes to classical disordered statistical mechanics models allows one to determine critical error thresholds of QEC codes under phenomenological noise models. Here, we extend this mapping to admit realistic, multi-parameter noise models of faulty QEC circuits, derive the associated strongly correlated classical spin models, and illustrate this approach for a quantum repetition code with faulty stabilizer readout circuits. We use Monte-Carlo simulations to study the resulting phase diagram and benchmark our results against a minimum-weight perfect matching decoder. The presented method provides an avenue to assess fundamental thresholds of QEC circuits, independent of specific decoding strategies, and can thereby help guiding the development of near-term QEC hardware.

Conditional Covariances for the Signal Lag Measurements in Fluoroscopic Imaging

In fluoroscopic imaging, we can acquire X-ray image sequences using a flat-panel dynamic detector. However, lag signals from previous frames are added to the subsequently acquired images and produce lag artifacts. The lag signals also inflate the measured noise power spectrum (NPS) of a detector. In order to correct the measured NPS, the lag correction factor (LCF) is generally used. However, the nonuniform temporal gain (NTG), which is from inconsistent X-ray sources and readout circuits, can significantly distort the LCF measurements. In this paper, we propose a simple scheme to alleviate the NTG problem in order to accurately and efficiently measure the detector LCF. We first theoretically analyze the effects of NTG, especially on the correlation-based LCF measurement methods, where calculating the correlation coefficients are required. In order to remove the biases due to NTG, a notion of conditional covariance is considered for unbiased estimates of the correlation coefficients. Experiments using practical X-ray images acquired from a dynamic detector were conducted. The proposed approach could yield accurate LCF values similarly to the current approaches of the direct and U-L corrections with a low computational complexity. By calculating the correlation coefficients based on conditional covariance, we could obtain accurate LCF values even under the NTG environment. This approach does not require any preprocessing scheme of the direct or U-L correction and can provide further accurate LCF values than the method of IEC62220-1-3 does.

Nanopore-based DNA sequencing sensors and CMOS readout approaches

Purpose Nanopore-based molecular sensing and measurement, specifically DNA sequencing, is advancing at a fast pace. Some embodiments have matured from coarse particle counters to enabling full human genome assembly. This evolution has been powered not only by improvements in the sensors themselves, but also in the assisting microelectronic CMOS readout circuitry closely interfaced to them. In this light, this paper aims to review established and emerging nanopore-based sensing modalities considered for DNA sequencing and CMOS microelectronic methods currently being used. Design/methodology/approach Readout and amplifier circuits, which are potentially appropriate for conditioning and conversion of nanopore signals for downstream processing, are studied. Furthermore, arrayed CMOS readout implementations are focused on and the relevant status of the nanopore sensor technology is reviewed as well. Findings Ion channel nanopore devices have unique properties compared with other electrochemical cells. Currently biological nanopores are the only variants reported which can be used for actual DNA sequencing. The translocation rate of DNA through such pores, the current range at which these cells operate on and the cell capacitance effect, all impose the necessity of using low-noise circuits in the process of signal detection. The requirement of using in-pixel low-noise circuits in turn tends to impose challenges in the implementation of large size arrays. Originality/value The study presents an overview on the readout circuits used for signal acquisition in electrochemical cell arrays and investigates the specific requirements necessary for implementation of nanopore-type electrochemical cell amplifiers and their associated readout electronics.

Design and Characterization of an Asynchronous Fixed Priority Tree Arbiter for SPAD Array Readout

The usage of single-photon avalanche diode arrays is becoming increasingly common in various domains such as medical imaging, automotive vision systems, and optical communications. Nowadays, thanks to the development of microelectronics technologies, the SPAD arrays designed for these applications has been drastically well-facilitated, allowing for the manufacturing of large matrices. However, there are growing challenges for the design of readout circuits with the needs of reducing their energy consumption (linked to the usage cost) and data rate. Indeed, the design of the readout circuit for the SPAD array is generally based on synchronous logic; the latter requires synchronization that may increase the dead time of the SPADs and clock trees management that are known to increase power consumption. With these limitations, the long-neglected asynchronous (clockless) logic proved to be a better alternative because of its ability to operate without a clock. In this paper, we presented the design of a 16-to-1 fixed-priority tree arbiter readout circuit for a SPAD array based on asynchronous logic principles. The design of this circuit was explained in detail and supported by simulation results. The manufactured chip was tested, and the experimental results showed that it is possible to record up to 333 million events per second; no reading errors were detected during the data extraction test.

Motion Artifact Removal Techniques for Wearable EEG and PPG Sensor Systems

Removal of motion artifacts is a critical challenge, especially in wearable electroencephalography (EEG) and photoplethysmography (PPG) devices that are exposed to daily movements. Recently, the significance of motion artifact removal techniques has increased since EEG-based brain–computer interfaces (BCI) and daily healthcare usage of wearable PPG devices were spotlighted. In this article, the development on EEG and PPG sensor systems is introduced. Then, understanding of motion artifact and its reduction methods implemented by hardware and/or software fashions are reviewed. Various electrode types, analog readout circuits, and signal processing techniques are studied for EEG motion artifact removal. In addition, recent in-ear EEG techniques with motion artifact reduction are also introduced. Furthermore, techniques compensating independent/dependent motion artifacts are presented for PPG.

A Pixel Design of a Branching Ultra-Highspeed Image Sensor

A burst image sensor named Hanabi, meaning fireworks in Japanese, includes a branching CCD and multiple CMOS readout circuits. The sensor is backside-illuminated with a light/charge guide pipe to minimize the temporal resolution by suppressing the horizontal motion of signal carriers. On the front side, the pixel has a guide gate at the center, branching to six first-branching gates, each bifurcating to second-branching gates, and finally connected to 12 (=6×2) floating diffusions. The signals are either read out after an image capture operation to replay 12 to 48 consecutive images, or continuously transferred to a memory chip stacked on the front side of the sensor chip and converted to digital signals. A CCD burst image sensor enables a noiseless signal transfer from a photodiode to the in-situ storage even at very high frame rates. However, the pixel count conflicts with the frame count due to the large pixel size for the relatively large in-pixel CCD memory elements. A CMOS burst image sensor can use small trench-type capacitors for memory elements, instead of CCD channels. However, the transfer noise from a floating diffusion to the memory element increases in proportion to the square root of the frame rate. The Hanabi chip overcomes the compromise between these pros and cons.

Surface Potential-Controlled Oscillation in FET-Based Biosensors

Field-effect transistor (FET)-based biosensors have garnered significant attention for their label-free electrical detection of charged biomolecules. Whereas conventional output parameters such as threshold voltage and channel current have been widely used for the detection and quantitation of analytes of interest, they require bulky instruments and specialized readout circuits, which often limit point-of-care testing applications. In this study, we demonstrate a simple conversion method that transforms the surface potential into an oscillating signal as an output of the FET-based biosensor. The oscillation frequency is proposed as a parameter for FET-based biosensors owing to its intrinsic advantages of simple and compact implementation of readout circuits as well as high compatibility with neuromorphic applications. An extended-gate biosensor comprising an Al2O3-deposited sensing electrode and a readout transistor is connected to a ring oscillator that generates surface potential-controlled oscillation for pH sensing. Electrical measurement of the oscillation frequency as a function of pH reveals that the oscillation frequency can be used as a sensitive and reliable output parameter in FET-based biosensors for the detection of chemical and biological species. We confirmed that the oscillation frequency is directly correlated with the threshold voltage. For signal amplification, the effects of circuit parameters on pH sensitivity are investigated using different methods, including electrical measurements, analytical calculations, and circuit simulations. An Arduino board to measure the oscillation frequency is integrated with the proposed sensor to enable portable and real-time pH measurement for point-of-care testing applications.