Stochastic Pulse Research Articles

Extreme bandwidths via stochastic self-phase-modulation

We examine the spectral broadening of stochastic laser pulses experiencing self-phase modulation (SPM) in a medium with Kerr nonlinearity. The statistics of extreme bandwidths emerging from such a process is shown to converge, in the large-sample-size limit, to a generalized Poisson distribution whose mean is given by the exponent of the respective extreme-event statistics. In striking contrast to the SPM spectral broadening of deterministic laser pulses, the properties of spectral broadening in stochastic SPM depend not only on the field intensity and the propagation path, but also on the signal-to-noise ratio a of laser pulses and the sample size N. For N >> 1 laser pulses with a high signal-to-noise ratio, the upper bound of SPM-broadened spectra shifts as (lnN/a2)δs, δs being the deterministic SPM bandwidth. The parameter Na=exp(a2/2) is shown to provide an important benchmark, setting a borderline between deterministic and stochastic SPM. These findings offer useful insights into the extreme-event properties of supercontinuum generation.

Long gamma-ray burst light curves as the result of a common stochastic pulse--avalanche process

The complexity and variety exhibited by the light curves of long gamma-ray bursts (GRBs) enclose a wealth of information that has not yet been fully deciphered. Despite the tremendous advance in the knowledge of the energetics, structure, and composition of the relativistic jet that results from the core collapse of the progenitor star, the nature of the inner engine, how it powers the relativistic outflow, and the dissipation mechanisms remain open issues. A promising way to gain insights is describing GRB light curves as the result of a common stochastic process. In the Burst And Transient Source Experiment (BATSE) era, a stochastic pulse avalanche model was proposed and tested through the comparison of ensemble-average properties of simulated and real light curves. Here our aim was to revive and further test this model. We applied it to two independent datasets, BATSE and Swift /BAT, through a machine learning approach: the model parameters are optimised using a genetic algorithm. The average properties were successfully reproduced. Notwithstanding the different populations and passbands of both datasets, the corresponding optimal parameters are interestingly similar. In particular, for both sets the dynamics appear to be close to a critical state, which is key to reproducing the observed variety of time profiles. Our results propel the avalanche character in a critical regime as a key trait of the energy release in GRB engines, which underpins some kind of instability.

The impact of Brownian motion on the optical solutions of the stochastic ultra-short pulses mathematical model

The stochastic generalized nonlinear Schrödinger equation (SGNLSE) of third order in the Stratonovich sense is examined here. New elliptic, hyperbolic, trigonometric, and rational stochastic solutions are obtained using a modified mapping method. Because the GNLSE is extensively used in nonlinear optical phenomena, optical fiber communication systems, communication and heat pulse propagation in materials, the obtained solutions may be used to study a broad range of relevant physical phenomena. In order to interpret the effects of multiplicative noise, the dynamic performances of the various obtained solutions are displayed utilizing 3-D and 2-D graphs. We infer that multiplicative noise impacts and stabilizes the behavior of SGNLSE solutions.

Wait time to stochastic self-focusing

The first passage time extended to stochastic nonlinear beam dynamics emerges as a natural time scale and a meaningful estimator for the expected wait time to the first self-focusing event within a large sample of stochastic laser pulses. We show that the ratio P/Pcr of the laser peak power P to the critical power of self-focusing Pcr, which plays a central role in deterministic self-focusing, keeps its status as a key governing parameter in stochastic self-focusing. However, in contrast to its deterministic counterpart, the Pcr/P ratio of a stochastic laser beam is no longer an indicator of whether self-focusing will occur, but is, rather, a predictor of when the self-focusing is expected, in the sense of the first passage time, given the statistics of the laser field.

Helicopter radio system for low altitudes and flight speed measuring with pulsed ultra-wideband stochastic sounding signals and artificial intelligence elements

The subject matter of this study is algorithms for measuring the components of an aircraft speed vector and altitude. The goal of this study is to improve algorithms for processing wideband stochastic pulse signals in helicopter low-altitude and flight-speed radio systems by introducing secondary signal processing based on artificial intelligence elements. The tasks to be solved are as follows: to develop an optimal algorithm for determining the speed and altitude of flight for a helicopter radio complex; to supplement the signal processing algorithm with an artificial intelligence-based processor to determine the "safety" of the current trajectory; provide the pilot with relevant information about possible options for further actions based on an analysis of the current position of the helicopter and flight parameters; and to analyse the efficiency of the proposed complex when using various artificial intelligence-based algorithms. The methods used are as follows: methods of mathematical statistics and optimal solutions for solving problems of statistical synthesis of active radio complex structure; methods of machine learning; and methods of computer simulation. The following results were obtained. The algorithms for signal processing in a helicopter radio complex are obtained by the method of maximum likelihood, and the use of three radio channels to calculate the full vector of speed and altitude is argued. The structure of a secondary information processing system, using algorithms based on artificial intelligence is proposed. The effectiveness of determining the safety of the current landing trajectory using various algorithms based on artificial intelligence (LinearSVC, GaussianNB, DecisionTreeClassifier, RandomForestClassifier, KNeighborsClassifier, MLPClassifier and RidgeClassifier) was analysed. Conclusions. The simulation results show that in the presence of accurate (noise-free) information on the current location of the helicopter, its axial velocities, and a map of the terrain with defined areas dangerous for landing, the DecisionTreeClassifier and RandomForestClassifier algorithms can provide a high probability of correctly determining the safety of the current landing trajectory. At the same time, in the presence of instability in the measurements of helicopter movement parameters, only the RandomForestClassifier algorithm maintains high accuracy.

Non-ideal program-time conservation in charge trap flash for deep learning

Training deep neural networks (DNNs) is computationally intensive, but arrays of non-volatile memories such as charge trap flash (CTF) can accelerate DNN operations using in-memory computing. Specifically, the resistive processing unit (RPU) architecture uses a voltage-threshold program with stochastic encoded pulse trains and analog memory features to accelerate vector-vector outer product and weight update for gradient descent algorithms. Although CTF, offering high precision, has been regarded as an excellent choice for implementing RPU, the accumulation of charge due to the applied stochastic pulse trains is ultimately of critical significance in determining the final weight update. In this paper, we report on the non-ideal program-time conservation in CTF through pulsing input measurements. We experimentally measure the effect of pulse width and pulse gap, keeping the total ON-time of the input pulse train constant, and report three non-idealities: (1) the cumulative shift reduces when total ON-time is fragmented into a larger number of shorter pulses, (2) the cumulative shift drops abruptly for pulse widths <2 s, (3) the cumulative shift depends on the gap between consecutive pulses and the shift reduction recovers for smaller gaps. We present an explanation based on a transient tunneling field enhancement due to blocking oxide trap-charge dynamics to explain these non-idealities. Identifying and modeling the responsible mechanisms and predicting their system-level effects during learning is critical. This non-ideal accumulation is expected to affect algorithms and architectures relying on devices for implementing mathematically equivalent functions for in-memory computing-based acceleration.

The σB alternative sigma factor circuit modulates noise to generate different types of pulsing dynamics.

Single-cell approaches are revealing a high degree of heterogeneity, or noise, in gene expression in isogenic bacteria. How gene circuits modulate this noise in gene expression to generate robust output dynamics is unclear. Here we use the Bacillus subtilis alternative sigma factor σB as a model system for understanding the role of noise in generating circuit output dynamics. σB controls the general stress response in B. subtilis and is activated by a range of energy and environmental stresses. Recent single-cell studies have revealed that the circuit can generate two distinct outputs, stochastic pulsing and a single pulse response, but the conditions under which each response is generated are under debate. We implement a stochastic mathematical model of the σB circuit to investigate this and find that the system's core circuit can generate both response types. This is despite one response (stochastic pulsing) being stochastic in nature, and the other (single response pulse) being deterministic. We demonstrate that the main determinant for whichever response is generated is the degree with which the input pathway activates the core circuit, although the noise properties of the input pathway also biases the system towards one or the other type of output. Thus, our work shows how stochastic modelling can reveal the mechanisms behind non-intuitive gene circuit output dynamics.

Fabrication and characterization of tapered photonic crystal fiber for broadband 2 µm: four-wave mixing-based fibered OPCPA

We present the simulation, fabrication, and characterization of large area microstructured fiber tapers which enables broadband phasematching conditions of the four wave-mixing process. These silica-based tapers are intended to serve as a nonlinear gain medium for intense and high average power Fiber Optical Parametric Chirped Pulse Amplifier emitting at 2 upmu hbox {m} and strongly pumped at Yb wavelength. Different geometries (tapered/untapered, aspect ratio, etc.) are fabricated, analyzed and their broadening properties—key for supporting ultrashort pulses amplification—are compared and discussed. The characterization of nonlinear gain bandwidth of the tapers relies on a tunable source of stochastic pulses based on tunable amplified spontaneous emission in Yb-doped amplifiers. The strong overshoots of this source allows degenerate four-wave mixing process to occur thus generating broadband incoherent visible signal and mid-infrared idler waves at much lower average power than usually needed with coherent pumping. The idler centered around 1.85 mum is broadened due to zero-dispersion wavelength shift along the taper.

Realization of homogeneous dielectric barrier discharge in atmospheric pressure argon and the effect of beads on its characteristics

This paper describes the realization of a homogeneous dielectric barrier discharge (DBD) in argon at atmospheric pressure. The effect of the morphology of the dielectric surface (especially the dielectric surface covered by hollow ceramic beads (99% Al2O3) with different diameters) on discharge is investigated. With different dielectrics, the argon DBD presents two discharge modes: a filamentary mode and a homogeneous mode. Fast photography shows that the filamentary mode operates in a streamer discharge, and the homogeneous mode operates in a Townsend discharge regime. It is found that a homogeneous discharge can be generated within a certain voltage range. The voltage amplitude range decreases, and the breakdown voltage increases with the increase in the mean diameter of the ceramic beads. Waveforms of the total current and optical emission signal present stochastic pulses per half voltage cycle for the filamentary mode, whereas there is one single hump per half voltage cycle for the homogeneous mode. In the homogeneous mode, the intensity of the optical emission decreases with the mean diameter of the ceramic beads. The optical emission spectrum is mainly composed of atomic lines of argon and the second positive system of molecular nitrogen. It reveals that the electron density decreases with the increasing mean diameter of the ceramic beads. The vibrational temperature increases with the increasing mean diameter of the ceramic beads. It is believed that a large number of microdischarges are formed, and smaller ceramic beads have a larger activation surface area and more point discharge. Electrons liberated in the shallow well and electrons generated from microdischarges can increase the secondary electron emission coefficient of the cathode and provide initial electrons for discharge continuously. Therefore, the breakdown electric field is reduced, which contributes to easier generation of homogeneous discharge. This is confirmed by the simulation results.

Ghost-imaging-enhanced noninvasive spectral characterization of stochastic x-ray free-electron-laser pulses

High-intensity ultrashort X-ray free-electron laser (XFEL) pulses are revolutionizing the study of fundamental nonlinear x-ray matter interactions and coupled electronic and nuclear dynamics. To fully exploit the potential of this powerful tool for advanced x-ray spectroscopies, a noninvasive spectral characterization of incident stochastic XFEL pulses with high resolution is a key requirement. Here we present a methodology that combines high-acceptance angle-resolved photoelectron time-of-flight spectroscopy and ghost imaging to enhance the quality of spectral characterization of x-ray free-electron laser pulses. Implementation of this noninvasive high-resolution x-ray diagnostic can greatly benefit the ultrafast x-ray spectroscopy community by functioning as a transparent beamsplitter for applications such as transient absorption spectroscopy in averaging mode as well as covariance-based x-ray nonlinear spectroscopies in single-shot mode where the shot-to-shot fluctuations inherent to a self-amplified spontaneous emission (SASE) XFEL pulse are a powerful asset.

Frequency modulation of a bacterial quorum sensing response

In quorum sensing, bacteria secrete or release small molecules into the environment that, once they reach a certain threshold, trigger a behavioural change in the population. As the concentration of these so-called autoinducers is supposed to reflect population density, they were originally assumed to be continuously produced by all cells in a population. However, here we show that in the α-proteobacterium Sinorhizobium meliloti expression of the autoinducer synthase gene is realized in asynchronous stochastic pulses that result from scarcity and, presumably, low binding affinity of the key activator. Physiological cues modulate pulse frequency, and pulse frequency in turn modulates the velocity with which autoinducer levels in the environment reach the threshold to trigger the quorum sensing response. We therefore propose that frequency-modulated pulsing in S. meliloti represents the molecular mechanism for a collective decision-making process in which each cell’s physiological state and need for behavioural adaptation is encoded in the pulse frequency with which it expresses the autoinducer synthase gene; the pulse frequencies of all members of the population are then integrated in the common pool of autoinducers, and only once this vote crosses the threshold, the response behaviour is initiated.

Stochastic modeling of plasma fluctuations with bursts and correlated noise in TCABR

Blob-like filamentary structures are omnipresent in magnetized plasmas. Their transport deteriorates the particle confinement and may damage plasma-facing components of future fusion devices. In local measurements of density, these turbulent structures are seen as high-amplitude bursts, and, since the last decade, a stochastic pulse train model (SPTM) has been developed to describe these locally measured signals. The SPTM, which is also known as a filtered Poisson process, models plasma fluctuations as a superposition of pulses plus a background with Gaussian noise. In the present article, a fitting method for this model is introduced, considering a mixture of dynamical and observational noise. The proposed method exploits the fact the model parameters can be fitted in steps, using first the signal characteristic function, then the conditionally averaged burst, and finally the frequency spectrum. By employing this fit, we compare predictions of the model for ion saturation current measurements made with a Langmuir probe mounted in the outboard mid-plane region of the TCABR tokamak. The model is able to highlight a series of differences between the plasma edge and scrape-off layer. Furthermore, radial profiles of the SPTM parameters reveal a relation between the signal kurtosis, the intermittency of the pulses, and background parameters. Also, a linear increase in the pulse duration was found with the position. Finally, by using recurrence quantification analysis, we show evidence that the mixture of dynamical and measurement noise may be more accurate than just one of the two to describe the dynamic behavior of density fluctuations in TCABR.

Asynchronous Architecture of Stochastic Computing Spiking Neuron Network

Stochastic computing encodes binary numbers into stochastic pulse sequences in operating, which takes advantages of low power consumption and low resource usage. The application of stochastic computing in the design of spiking neural network (SNN) accelerator is beneficial to realize brain-like operation. In order to realize the low-power edge calculation of neural network, an asynchronous architecture using stochastic computing is designed, which can be used to realize the operation of full connected SNN. Cross array controlled by asynchronous micro-pipeline is implemented to achieve the leaky integrate and fire (LIF) neuron model. In the input layer of SNN, input values are encoded into stochastic pulses, and the synaptic weights and input pulses are calculated through accumulation, and the attenuation of neuron membrane potential value is realized based on logic calculation. The event-driven coding and the transmission of stochastic pulse are controlled by the asynchronous architecture, which can reduce the power consumption of SNN operation; The proposed architecture achieves an operation of SNN with 784 input and 10 output, which is verified on Xilinx KCU116 platform and achieves a peak throughput of 78.4 GSOPS and an energy efficiency of 137.47 GSOPS/W.

Transient measurement of phononic states with covariance-based stochastic spectroscopy

We present a novel approach to transient Raman spectroscopy, which combines stochastic probe pulses and a covariance-based detection to measure stimulated Raman signals in alpha-quartz. A coherent broadband pump is used to simultaneously impulsively excite a range of different phonon modes, and the phase, amplitude, and energy of each mode are independently recovered as a function of the pump–probe delay by a noisy-probe and covariance-based analysis. Our experimental results and the associated theoretical description demonstrate the feasibility of 2D-Raman experiments based on the stochastic-probe schemes, with new capabilities not available in equivalent mean-value-based 2D-Raman techniques. This work unlocks the gate for nonlinear spectroscopies to capitalize on the information hidden within the noise and overlooked by a mean-value analysis.

Phytoplankton responses to repeated pulse perturbations imposed on a trend of increasing eutrophication.

While eutrophication remains one of the main pressures acting on freshwater ecosystems, the prevalence of anthropogenic and nature‐induced stochastic pulse perturbations is predicted to increase due to climate change. Despite all our knowledge on the effects of eutrophication and stochastic events operating in isolation, we know little about how eutrophication may affect the response and recovery of aquatic ecosystems to pulse perturbations. There are multiple ways in which eutrophication and pulse perturbations may interact to induce potentially synergic changes in the system, for instance, by increasing the amount of nutrients released after a pulse perturbation. Here, we performed a controlled press and pulse perturbation experiment using mesocosms filled with natural lake water to address how eutrophication modulates the phytoplankton response to sequential mortality pulse perturbations; and what is the combined effect of press and pulse perturbations on the resistance and resilience of the phytoplankton community. Our experiment showed that eutrophication increased the absolute scale of the chlorophyll‐a response to pulse perturbations but did not change the proportion of the response relative to its pre‐event condition (resistance). Moreover, the capacity of the community to recover from pulse perturbations was significantly affected by the cumulative effect of sequential pulse perturbations but not by eutrophication itself. By the end of the experiment, some mesocosms could not recover from pulse perturbations, irrespective of the trophic state induced by the press perturbation. While not resisting or recovering any less from pulse perturbations, phytoplankton communities from eutrophying systems showed chlorophyll‐a levels much higher than non‐eutrophying ones. This implies that the higher absolute response to stochastic pulse perturbations in a eutrophying system may increase the already significant risks for water quality (e.g., algal blooms in drinking water supplies), even if the relative scale of the response to pulse perturbations between eutrophying and non‐eutrophying systems remains the same.

A Survey of Intelligent Chip Design Research Based on Spiking Neural Networks

The traditional neural network Intelligent chip has the problem of high power consumption due to classical computing architecture, limiting the development of neural network Intelligent chips. Stochastic computing (SC) encodes binary numbers into stochastic pulse sequences in operation, taking advantage of low power consumption and high performance. The application of SC in spiking neural networks (SNNs) Intelligent chips is beneficial to solving the high power consumption of traditional neural network chips. This article first summarizes the basic elements of SNNs and the basic principles of SC. Then, we review the development trends of the stochastic computation-based neural network chips and existing SNN chips under research at home and abroad, respectively, and analyze the current problems. Finally, a review of SNN chips based on SC is highlighted. This paper aims to provide new research directions and to learn ideas for the field of SNN chips through systematic summaries.

Temporal optical rogue waves in high power short-cavity Yb-doped random fiber laser

A high power short-cavity random fiber laser employing the gain mechanism of the Yb-doped fiber and the half-open cavity structure and the temporal optical rogue waves (RWs) behavior are observed and investigated in the paper. The record output power without the stimulated Raman scattering (SRS) is promoted to 26.6 W in the Yb-doped random fiber lasers (YDRFL) with the Ge-doped fiber (GDF) length of 120 m. The stochastic pulses and temporal optical RWs are observed and demonstrated in the short cavity YDRFL for the first time. It is found that the proportion of RWs depends on the GDF length and can also affect the stability of output lasing and the M2 factor distribution. The M2 factor distribution demonstrated a special longitudinal mode instability phenomenon. The experimental phenomenons display that the multiple high order SRS stokes lights and the visible light radiations are generated by the soliton self-frequency shift and Cherenkov radiation in the YDRFL with shorter GDF length. The research results reveal that achieving the relative stable output power requires the greater pump power for the shorter GDF length, although decreasing the GDF length will promote the maximum output power of the YDRFL without the SRS.

Denoising of Heavily Contaminated Partial Discharge Signals in High-Voltage Cables Using Maximal Overlap Discrete Wavelet Transform

Online detection of partial discharges (PD) is imperative for condition monitoring of high voltage equipment as well as power cables. However, heavily contaminated sites often burden the signals with various types of noise that can be challenging to remove (denoise). This paper proposes an algorithm based on the maximal overlap discrete wavelet transform (MODWT) to denoise PD signals originating from defects in power cables contaminated with various levels of noises. The three most common noise types, namely, Gaussian white noise (GWN), discrete spectral interference (DSI), and stochastic pulse shaped interference (SPI) are considered. The algorithm is applied to an experimentally acquired void-produced partial discharge in a power cable. The MODWT-based algorithm achieved a good improvement in the signal-to-noise ratio (SNR) and in the normalized correlation coefficient (NCC) for the three types of noises. The MODWT-based algorithm performance was also compared to that of the empirical Bayesian wavelet transform (EBWT) algorithm, in which the former showed superior results in denoising SPI and DSI, as well as comparable results in denoising GWN. Finally, the algorithm performance was tested on a PD signal contaminated with the three type of noises simultaneously in which the results were also superior.

Resonant X-ray emission spectroscopy from broadband stochastic pulses at an X-ray free electron laser

Hard X-ray spectroscopy is an element specific probe of electronic state, but signals are weak and require intense light to study low concentration samples. Free electron laser facilities offer the highest intensity X-rays of any available light source. The light produced at such facilities is stochastic, with spikey, broadband spectra that change drastically from shot to shot. Here, using aqueous ferrocyanide, we show that the resonant X-ray emission (RXES) spectrum can be inferred by correlating for each shot the fluorescence intensity from the sample with spectra of the fluctuating, self-amplified spontaneous emission (SASE) source. We obtain resolved narrow and chemically rich information in core-to-valence transitions of the pre-edge region at the Fe K-edge. Our approach avoids monochromatization, provides higher photon flux to the sample, and allows non-resonant signals like elastic scattering to be simultaneously recorded. The spectra obtained match well with spectra measured using a monochromator. We also show that inaccurate measurements of the stochastic light spectra reduce the measurement efficiency of our approach.

Unveiling the spatial distribution of molecular coherences at conical intersections by covariance X-ray diffraction signals

The outcomes and timescales of molecular nonadiabatic dynamics are decisively impacted by the quantum coherences generated at localized molecular regions. In time-resolved X-ray diffraction imaging, these coherences create distinct signatures via inelastic photon scattering, but they are buried under much stronger background elastic features. Here, we exploit the rich dynamical information encoded in the inelastic patterns, which we reveal by frequency-dispersed covariance ultrafast powder X-ray diffraction of stochastic X-ray free-electron laser pulses. This is demonstrated for the photoisomerization of azobenzene involving the passage through a conical intersection, where the nuclear wave packet branches and explores different quantum pathways. Snapshots of the coherence dynamics are obtained at high frequency shifts, not accessible with conventional diffraction measurements. These provide access to the timing and to the confined spatial distribution of the valence electrons directly involved in the conical intersection passage. This study can be extended to full three-dimensional imaging of conical intersections with ultrafast X-ray and electron diffraction.