Investigation of random telegraph noise characteristics of Hf-based MONOS nonvolatile memory devices with HfO2 and HfON tunneling layer

This paper investigated the low frequency noise (LFN) utilizing 1/f noise and random telegraph noise (RTN) characteristics of Hf-based metal/oxide/nitride/oxide/silicon (MONOS) nonvolatile memory (NVM) device with HfO2 and HfON tunneling layer (TL). The low frequency noise spectral density (SID ) was investigated to evaluate the interface characteristics with fresh and after programming/erasing (P/E) cycles of 104. Both devices show similar slope of ~1/f in all of the frequency regions. Although HfON TL shows high SID compared to HfO2 TL, increased ratio is 15.4 which is low compared to HfO2 TL of 21.3. As decreasing the channel length from 10 to 2 μm, HfON TL shows small increased ratio of SID . Due to the nitrided characteristics, HfON TL suppress the degradation of interface. Finally, it is found that trap site of HfO2 TL is located near the interface by RTN measurement with capture (τC) and emission time constant (τE).

Multilevel RTN Removal Tools for Dynamic FBG Strain Measurements Corrupted by Peak-Splitting Artefacts

Strain measurements using fibre Bragg grating (FBG) optical sensors are becoming ever more commonplace. However, in some cases, these measurements can become corrupted by sudden jumps in the signal, which manifest as spikes or step-like offsets in the data. These jumps are caused by a defect in the FBG itself, which is referred to as peak-splitting. The effects of peak splitting artefacts on FBG strain measurements show similarities with an additive multi-level telegraph noise process, in which the amplitudes and occurrences of the jumps are related to fibre deformation states. Whenever it is not possible to re-assess the raw spectral data with advanced peak tracking software, other means for removing the jumps from the data have to be found. The two methods presented in this article are aimed at removing additive multi-level random telegraph noise (RTN) from the raw data. Both methods are based on denoising the sample wise difference signal using a combination of an outlier detection scheme followed by an outlier replacement step. Once the difference signal has been denoised, the cumulative sum is used to arrive back at a strain time series. Two methods will be demonstrated for reconstructing severely corrupted strain time series; the data for this verification has been collected from sub-soil strain measurements obtained from an operational offshore wind-turbine. The results show that the proposed methods can be used effectively to reconstruct the dynamic content of the corrupted strain time series. It has been illustrated that errors in the outlier replacements accumulate and can cause a quasi-static drift. A representative mean value and drift correction are proposed in terms of an optimization problem, which maximizes the overlap between the reconstruction and a subset of the raw data; whereas a high-pass filter is suggested to remove the quasi static drift if only the dynamic band of the signal is of interest.

Fluctuations and Pinning for Individually Manipulated Skyrmions

We numerically examine the dynamics of individually dragged skyrmions interacting simultaneously with an array of other skyrmions and quenched disorder. For drives just above depinning, we observe a broadband noise signal with a 1/f characteristic, while at higher drives, narrowband or white noise appears. Even in the absence of quenched disorder, the threshold force that must be applied to translate the driven skyrmion is finite due to elastic interactions with other skyrmions. The depinning threshold increases as the strength of the quenched disorder is raised. Above the depinning force, the skyrmion moves faster in the presence of quenched disorder than in a disorder-free system since the pinning sites prevent other skyrmions from being dragged along with the driven skyrmion. For strong pinning, we find a stick-slip motion of the driven skyrmion which produces a telegraph noise signature. The depinning threshold increases monotonically with skyrmion density in the absence of quenched disorder, but when pinning is present, the depinning threshold changes nonmonotonically with skyrmion density, and there are reentrant pinned phases due to a competition between pinning induced by the quenched disorder and that produced by the elastic interactions of the skyrmion lattice.

Dynamics of quantum correlations in a qubit-qutrit spin system under random telegraph noise

We study the dimensionless time evolution of the logarithmic negativity and geometric quantum discord of a qubit-qutrit XXX spin model under the both Markovian and non-Markovian noise channels. We find that at a special temperature interval the quantum entanglement based on the logarithmic negativity reveals entanglement sudden deaths together with revivals. The revival phenomenon is due to the non-Markovianity resulting from the feedback effect of the environment. At high temperatures, the scenario of death and revival disappears. The geometric quantum discord evolves alternatively versus time elapsing with damped amplitudes until the system reaches steady state. It is demonstrated that the dynamics of entanglement negativity undergoes substantial changes by varying temperature, and it is much more fragile against the temperature rather than the geometric quantum discord. The real complex heterodinuclear [Ni(dpt (H2O)Cu(pba)]·2H2O [with pba =1,3-propylenebis(oxamato) and dpt = bis-(3-aminopropyl)amine] is an experimental representative of our considered bipartite qubit-qutrit system that may show remarkable entanglement deaths and revivals at relatively high temperatures and high magnetic field that is comparable with the strength of the exchange interaction J between Cu+2 and Ni+2 ions, i.e., kBT ≈ J and μBB ≈ J.

A Noise-Resilient Neuromorphic Digit Classifier Based on NOR Flash Memories with Pulse-Width Modulation Scheme

In this work, we investigate the implementation of a neuromorphic digit classifier based on NOR Flash memory arrays as artificial synaptic arrays and exploiting a pulse-width modulation (PWM) scheme. Its performance is compared in presence of various noise sources against what achieved when a classical pulse-amplitude modulation (PAM) scheme is employed. First, by modeling the cell threshold voltage (VT) placement affected by program noise during a program-and-verify scheme based on incremental step pulse programming (ISPP), we show that the classifier truthfulness degradation due to the limited program accuracy achieved in the PWM case is considerably lower than that obtained with the PAM approach. Then, a similar analysis is carried out to investigate the classifier behavior after program in presence of cell VT instabilities due to random telegraph noise (RTN) and to temperature variations, leading again to results in favor of the PWM approach. In light of these results, the present work suggests a viable solution to overcome some of the more serious reliability issues of NOR Flash-based artificial neural networks, paving the way to the implementation of highly-reliable, noise-resilient neuromorphic systems.

Evaluation of Low-Frequency Noise in MOSFETs Used as a Key Component in Semiconductor Memory Devices

Methods for evaluating low-frequency noise, such as 1/f noise and random telegraph noise, and evaluation results are described. Variability and fluctuation are critical in miniaturized semiconductor devices because signal voltage must be reduced in such devices. Especially, the signal voltage in multi-bit memories must be small. One of the most serious issues in metal-oxide-semiconductor field-effect-transistors (MOSFETs) is low-frequency noise, which occurs when the signal current flows at the interface of different materials, such as SiO2/Si. Variability of low-frequency noise increases with MOSFET shrinkage. To assess the effect of this noise on MOSFETs, we must first understand their characteristics statistically, and then, sufficient samples must be accurately evaluated in a short period. This study compares statistical evaluation methods of low-frequency noise to the trend of conventional evaluation methods, and this study’s findings are presented.

Design of True Random Number Circuit with Controllable Frequency

True random number generators (TRNGs) have been a research hotspot due to secure encryption algorithm requirements. Therefore, such circuits are necessary building blocks in state-of-the-art security controllers. In this paper, a TRNG based on random telegraph noise (RTN) with a controllable rate is proposed. A novel method of noise array circuits is presented, which consists of digital decoder circuits and RTN noise circuits. The frequency of generating random numbers is controlled by the speed of selecting different gating signals. The results of simulation show that the array circuits consist of 64 noise source circuits that can generate random numbers by a frequency from 1 kHz to 16 kHz.