Nonlinear Shift Research Articles

Characterization of Nonlinear Spectral Linewidth and Light Shift in Diffuse Laser Cooling Atoms

Abstract We demonstrate an integrating sphere to cool 87Rb atoms and measure the recoil-induced resonance and electromagnetically induced absorption spectrum. We measure the relationship between their linewidth and light shift with the variation of the detuning and power of the cooling laser and study the performance of the diffuse laser cooling mechanism by the absorption linewidth radio △ν E/△ν R and light shift |△R - △E| in the nonlinear spectroscopy. Specifically, when △ν E/△ν R reaches a value of 1.57, the temperature and number of cold atoms achieve the optimal cooling effect. This characterization of absorption linewidth and light shift will provide a method to estimate whether diffused light cooling achieves the best cooling effect, contributing to the future development of isotropic laser cooling for application in quantum sensing.

A lightweight dual-link accelerated authentication protocol based on NLFSR-XOR APUF

Physical Unclonable Function (PUF) circuits, as a lightweight hardware security primitive, can provide reliable authentication for resource-constrained Internet of Things (IoT) devices. However, in real-time environments and systems, authentication of embedded devices has strict requirements on resources and low latency. Therefore, this paper proposes a lightweight dual-link accelerated authentication protocol design based on NLFSR-XOR APUF, through the study of Non-Linear Feedback Shift Registers (NLFSR) and XOR APUF circuits. First, the scheme utilizes the symmetric path delay deviation characteristics of APUF and the complexity of NLFSR state transitions to form a nonlinear output function that changes with the challenge signal. Then, a lightweight and attack-resistant authentication protocol is established by combining the random probability of shuffling array bits with the XOR confusion mechanism. Finally, the advantages of GPU parallel computing and AES T-table reconfiguration scheme are used to achieve an accelerated and side-channel attack-resistant authentication protocol. Experimental results show that the PUF circuit can effectively resist various modeling attacks, including logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). The security of the protocol has been formally verified, and the prototype has been implemented on the Xilinx xc100T development board, effectively resisting deception attacks, physical attacks, and modeling attacks. The protocol's area overhead in terms of LUT and encryption time is reduced by 58.6 % and 67.8 %, respectively, compared to similar protocols.

Establishing a Robust Nonlinear Targeted Switch for C1 Electroproduction in Atomic Alloy Cox/Pd Bimetallenes

Establishing a targeted switch for CO2 conversion under electric drive is essential for achieving carbon‐balance by enabling selective chemicals. However, engineering the topological assembly of active sites to precisely regulate the competing pathways for various intermediates has been plagued by unclear structure‐function relationships. To tailor the CO/formate pathways, herein we established a robust nonlinear targeted switch with tunable active Cox sites integrated into Pd metallene, which involves Co1/Pd single‐atom alloy (favoring CO) and Co2/Pd diatomic alloy (favoring formate). Transitioning from Co1/Pd to Co2/Pd atomic alloy bimetallenes resulted in a nonlinear, high‐contrast flip in selectivity, surpassing 94% for CO and formate productions in both H‐cell and flow cell. Furthermore, the superior selectivity and current efficiency for CO (> 80 %) and formate (> 88%) were consistently maintained at ‐150 mA cm‐2 over continuous 200 h. Theoretical simulations and in‐situ spectroscopy analyses unveiled that appropriate adjacent metal site combinations (Pd‐Pd, Pd‐Co and Co‐Co) lead to tunable dz2 band center and a nonlinear shift in preferred adsorption configurations of intermediates, dictating the C1 pathways. Our finding reveals a desired switch in C1 selectivity and robust stability within Cox/Pd system, providing a new perspective for fine‐tuning energy conversion processes through specific topological assembly.

Establishing a Robust Nonlinear Targeted Switch for C1 Electroproduction in Atomic Alloy Cox/Pd Bimetallenes.

Establishing a targeted switch for CO2 conversion under electric drive is essential for achieving carbon-balance by enabling selective chemicals. However, engineering the topological assembly of active sites to precisely regulate the competing pathways for various intermediates has been plagued by unclear structure-function relationships. To tailor the CO/formate pathways, herein we established a robust nonlinear targeted switch with tunable active Cox sites integrated into Pd metallene, which involves Co1/Pd single-atom alloy (favoring CO) and Co2/Pd diatomic alloy (favoring formate). Transitioning from Co1/Pd to Co2/Pd atomic alloy bimetallenes resulted in a nonlinear, high-contrast flip in selectivity, surpassing 94 % for CO and formate productions in both H-cell and flow cell. Furthermore, the superior selectivity and current efficiency for CO (>80 %) and formate (>88 %) were consistently maintained at -150 mA cm-2 over continuous 200 h. Theoretical simulations and in situ spectroscopy analyses unveiled that appropriate adjacent metal site combinations (Pd-Pd, Pd-Co and Co-Co) lead to tunable dz 2 band center and a nonlinear shift in preferred adsorption configurations of intermediates, dictating the C1 pathways. Our finding reveals a desired switch in C1 selectivity and robust stability within Cox/Pd system, providing a new perspective for fine-tuning energy conversion processes through specific topological assembly.

Vertical Distribution of Rocky Intertidal Organisms Shifts With Sea-Level Variability on the Northeast Pacific Coast.

Disentangling the effects of cyclical variability in environmental forcing and long-term climate change on natural communities is a major challenge for ecologists, managers, and policy makers across ecosystems. Here we examined whether the vertical distribution of rocky intertidal taxa has shifted with sea-level variability occurring at multiple temporal scales and/or long-term anthropogenic sea-level rise (SLR). Because of the distinct zonation characteristic of intertidal communities, any shift in tidal dynamics or average sea level is expected to have large impacts on community structure and function. We found that across the Northeast Pacific Coast (NPC), sea level exhibits cyclical seasonal variability, tidal amplitude exhibits ecologically significant variability coherent with the 18.6-year periodicity of lunar declination, and long-term sea-level rise is occurring. Intertidal taxa largely do not exhibit significant vertical distribution shifts coherent with short-term (monthly to annual) sea-level variability but do exhibit taxa-specific vertical distribution shifts coherent with cyclical changes in lunar declination and long-term SLR at decadal timescales. Finally, our results show that responses to cyclical celestial mechanics and SLR vary among taxa, primarily according to their vertical distribution. Long-term SLR is occurring on ecologically relevant scales, but the confounding effects of cyclical celestial mechanics make interpreting shifts in zonation or community structure challenging. Such cyclical dynamics alternatingly amplify and dampen long-term SLR impacts and may modify the impacts of other global change related stressors, such as extreme heat waves and swell events, on intertidal organisms living at the edge of their physiological tolerances. As a result, intertidal communities will likely experience cyclical periods of environmental stress and concomitant nonlinear shifts in structure and function as long-term climate change continues. Our results demonstrate that consistent, large-scale monitoring of marine ecosystems is critical for understanding natural variability in communities and documenting long-term change.

Spin-polarized second-order nonlinear Hall effect in 8-Pmmn monolayer borophene

The second-order nonlinear Hall effect in 8-Pmmn monolayer borophene under the influence of an out-of-plane electric field and intrinsic spin–orbit interaction is reported. This unconventional response sensitive to the breaking of discrete and crystal symmetries can be tuned by the applied electric field, which can vary the bandgap induced by spin–orbit coupling. It is described by a Hall conductivity tensor that depends quadratically on the applied electric field. We find that the nonlinear Hall effect strongly depends on the spin polarization. In particular, it exhibits out of the phase character for spin-up and spin-down states. Remarkably, it undergoes a phase flip in the spin-up state at a large out-of-plane electric field that generates a staggered sublattice potential greater than the spin–orbit interaction strength. It is shown that the nonlinear Hall effect in the system originates from the broken inversion symmetry that plays an indispensable role in developing finite Berry curvature and its relevant dipole moment. It is found that at zero temperature, the nonlinear Hall response is maximal when the Fermi energy is twice the bandgap parameter and vanishes at large Fermi energies. Notably, the peak of nonlinear Hall response shifts to lower Fermi energies at finite temperature.

Bimodal substrate binding in the active site of the glycosidase BcX.

Bacillus circulans xylanase (BcX) from the glycoside hydrolase family 11 degrades xylan through a retaining, double-displacement mechanism. The enzyme is thought to hydrolyze glycosidic bonds in a processive manner and has a large, active site cleft, with six subsites allowing the binding of six xylose units. Such an active site architecture suggests that oligomeric xylose substrates can bind in multiple ways. In the crystal structure of the catalytically inactive variant BcX E78Q, the substrate xylotriose is observed in the active site, as well as bound to the known secondary binding site and a third site on the protein surface. Nuclear magnetic resonance (NMR) titrations with xylose oligomers of different lengths yield nonlinear chemical shift trajectories for active site nuclei resonances, indicative of multiple binding orientations for these substrates for which binding and dissociation are in fast exchange on the NMR timescale, exchanging on the micro- to millisecond timescale. Active site binding can be modeled with a 2 : 1 model with dissociation constants in the low and high millimolar range. Extensive mutagenesis of active site residues indicates that tight binding occurs in the glycon binding site and is stabilized by Trp9 and the thumb region. Mutations F125A and W71A lead to large structural rearrangements. Binding at the glycon site is sensed throughout the active site, whereas the weak binding mostly affects the aglycon site. The interactions with the two active site locations are largely independent of each other and of binding at the secondary binding site.

High-Efficiency 5G-Band Rectifier with Impedance Dispersion Compensation Network

This paper proposes a microwave rectifier designed for the popular 5G band, featuring impedance dispersion compensation and a cross-type impedance matching network. The rectifier has an ultra-high power conversion efficiency. The compensation network employs two parallel transmission lines to counteract the nonlinear shift of the diode input impedance caused by frequency variation. Additionally, the cross-over impedance matching network enhances matching and minimizes losses. After rigorous theoretical analysis and simulation, the rectifier is fabricated. Experimental results show significant conversion efficiency in the 5G band (across 4–6.5 GHz). At an input power of 12 dBm, the rectifier achieves more than 60% efficiency between 4.8 and 6.4 GHz and more than 70% between 5.2 and 6.2 GHz, with a peak efficiency of 78.1%. Moreover, the rectifier maintains more than 50% efficiency over a wide input power range of 5 to 14 dBm.

Nonlinear time-dependent behavior of rheodictic polymers: A theoretical and experimental investigation

The present study examined the nonlinear time-dependent behavior of rheodictic polymers, a class of noncrosslinked materials that exhibit flow. Such behavior was addressed with extended Schapery's nonlinear viscoelastic model by introducing new physical quantities, i.e., the flow term Φflow and corresponding nonlinear shift parameter g2,flow. While Φflow portrays irrecoverable deformation, g2,flow depicts a nonlinear contribution to flow acceleration. This theory was accompanied by analytical and experimental methodologies for identifying all the parameters in the linear and nonlinear viscoelastic domains. Predictions of long-term time-dependent behavior (in shear) at various stress states show excellent agreement with the experimental data, i.e., within 5% error, obtained for polycarbonate at 130°C. Surprisingly, the newly introduced g2,flow indicates that flow retardation occurs with increasing stress, implying that a highly deformed entangled system hinders molecular reptation/disentanglement. Nevertheless, the proposed extension of Schapery's nonlinear viscoelastic model not only allows accurate predictions of the nonlinear time-dependent behavior of rheodictic polymers but also enables a detailed outlook on the underlying molecular mechanisms under severe environmental and loading conditions.

Quantitative Stock Selection Model Using Graph Learning and a Spatial–Temporal Encoder

In the rapidly evolving domain of finance, quantitative stock selection strategies have gained prominence, driven by the pursuit of maximizing returns while mitigating risks through sophisticated data analysis and algorithmic models. Yet, prevailing models frequently neglect the fluid dynamics of asset relationships and market shifts, a gap that undermines their predictive and risk management efficacy. This oversight renders them vulnerable to market volatility, adversely affecting investment decision quality and return consistency. Addressing this critical gap, our study proposes the Graph Learning Spatial–Temporal Encoder Network (GL-STN), a pioneering model that seamlessly integrates graph theory and spatial–temporal encoding to navigate the intricacies and variabilities of financial markets. By harnessing the inherent structural knowledge of stock markets, the GL-STN model adeptly captures the nonlinear interactions and temporal shifts among assets. Our innovative approach amalgamates graph convolutional layers, attention mechanisms, and long short-term memory (LSTM) networks, offering a comprehensive analysis of spatial–temporal data features. This integration not only deciphers complex stock market interdependencies but also accentuates crucial market insights, enabling the model to forecast market trends with heightened precision. Rigorous evaluations across diverse market boards—Main Board, SME Board, STAR Market, and ChiNext—underscore the GL-STN model’s exceptional ability to withstand market turbulence and enhance profitability, affirming its substantial utility in quantitative stock selection.

Modulational instability and chirped modulated wave, chirped optical solitons for a generalized (3+1)-dimensional cubic-quintic medium with self-frequency shift and self-steepening nonlinear terms

We consider a generalized (3+1)-dimensional nonlinear Schrödinger with cubic-quintic nonlinear and self-frequency shift and self-steepening terms. We disrupt the plane wave to study the stability of the wave in this media. We examine how various factors—such as the amplitude of the plane wave, cubic and quintic nonlinear terms, self-steepening, and self-frequency shift—affect the modulational instability (MI). Our findings reveal that the amplitude of the plane wave and the quintic nonlinear term can expand the MI bands and increase the amplitude of the MI growth rate. Conversely, the self-steepening and self-frequency shift terms exert opposite effects, narrowing the MI bands and reducing the amplitude of the MI growth rate. We investigate the existence of modulated chirped rational and polynomial Jacobi elliptic function solutions and chirped optical solitons.

Nonlinear shifts and dislocations in financial market structure and composition.

This paper develops new mathematical techniques to identify temporal shifts among a collection of US equities partitioned into a new and more detailed set of market sectors. Although conceptually related, our three analyses reveal distinct insights about financial markets, with meaningful implications for investment managers. First, we explore a variety of methods to identify nonlinear shifts in a market sector structure and describe the mathematical connection between the measure used and the captured phenomena. Second, we study a network structure with respect to our new market sectors and identify meaningfully connected sector-to-sector mappings. Finally, we conduct a series of sampling experiments over different sample spaces and contrast the distribution of Sharpe ratios produced by long-only, long-short, and short-only investment portfolios. In addition, we examine the sector composition of the top-performing portfolios for each of these portfolio styles. In practice, the methods proposed in this paper could be used to identify regime shifts, optimally structured portfolios, and better communities of equities.

Aridity-dependent shifts in biodiversity-stability relationships but not in underlying mechanisms.

Climate change will affect the way biodiversity influences the stability of plant communities. Although biodiversity, associated species asynchrony, and species stability could enhance community stability, the understanding of potential nonlinear shifts in the biodiversity-stability relationship across a wide range of aridity (measured as the aridity index, the precipitation/potential evapotranspiration ratio) gradients and the underlying mechanisms remain limited. Using an 8-year dataset from 687 sites in Mongolia, which included 5496 records of vegetation and productivity, we found that the temporal stability of plant communities decreased more rapidly in more arid areas than in less arid areas. The result suggests that future aridification across terrestrial ecosystems may adversely affect community stability. Additionally, we identified nonlinear shifts in the effects of species richness and species synchrony on temporal community stability along the aridity gradient. Species synchrony was a primary driver of community stability, which was consistently negatively affected by species richness while being positively affected by the synchrony between C3 and C4 species across the aridity gradient. These results highlight the crucial role of C4 species in stabilizing communities through differential responses to interannual climate variations between C3 and C4 species. Notably, species richness and the synchrony between C3 and C4 species independently regulated species synchrony, ultimately affecting community stability. We propose that maintaining plant communities with a high diversity of C3 and C4 species will be key to enhancing community stability across Mongolian grasslands. Moreover, species synchrony, species stability, species richness and the synchrony between C3 and C4 species across the aridity gradient consistently mediated the impacts of aridity on community stability. Hence, strategies aimed at promoting the maintenance of biological diversity and composition will help ecosystems adapt to climate change or mitigate its adverse effects on ecosystem stability.

Design and Implementation of 32 Bit Linear Feedback Shift Register using FPGA

Abstract: Shift register is a common device for generating signals and sequences. Usually register is the combination of flipflops.The shift register is of two types which are: linear and nonlinear. Various sequences including pseudorandom codes are generated by linear and nonlinear feedback shift registers, respectively. Linear feedback shift register (LFSR) is composed of dynamic or static master-slave flip-flop. Its characteristics are usually characterized by a characteristic polynomial. The twoinput XOR gate is used to calculate the characteristic polynomial of the maximum or near maximum length of the feedback function without rectifying the register.

Characterization of solutions of certain class of linear and non-linear shift equations undershared values

In this paper we have considered the generalized form of Pielou Logistic Equation and Riccati Difference equation [6] and characterize the solution of that equation in terms of shared value problem. We have improved and extended the result of Li-Chen in [8].

The equivalence between Galois and Fibonacci NFSRs

Nonlinear feedback shift registers (NFSRs) are used in many stream ciphers as their main building blocks. In particular, Galois NFSRs with terminal bits are used in typical stream ciphers Grain and Trivium. Seven types of Galois NFSRs have been found equivalent to Fibonacci ones, among which three types are particular cases of another type of lower triangular Galois NFSRs. This paper continues the research of equivalence between Galois NFSRs and Fibonacci ones. It first enumerates the Galois NFSRs with terminal bits that are equivalent to a Fibonacci NFSR. It then discloses n-stage (n−2)-terminal-bit Galois NFSRs equivalent to Fibonacci ones, must be lower triangular Galois NFSRs. Finally, it presents two new types of Galois NFSRs that are equivalent to Fibonacci NFSRs. Some examples show that, compared to a Fibonacci NFSR, its equivalent Galois NFSR from our new types may decrease the area and increase the throughput of the circuits implementing feedback functions.

Enhancing Bitcoin Price Volatility Estimator Predictions: A Four-Step Methodological Approach Utilizing Elastic Net Regression

This paper provides a computationally efficient and novel four-step methodological approach for predicting volatility estimators derived from bitcoin prices. In the first step, open, high, low, and close bitcoin prices are transformed into volatility estimators using Brownian motion assumptions and logarithmic transformations. The second step determines the optimal number of time-series lags required for converting the series into an autoregressive model. This selection process utilizes random forest regression, evaluating the importance of each lag using the Mean Decrease in Impurity (MDI) criterion and optimizing the number of lags considering an 85% cumulative importance threshold. The third step of the developed methodological approach fits the Elastic Net Regression (ENR) to the volatility estimator’s dataset, while the final fourth step assesses the predictive accuracy of ENR, compared to decision tree (DTR), random forest (RFR), and support vector regression (SVR). The results reveal that the ENR prevails in its predictive accuracy for open and close prices, as these prices may be linear and less susceptible to sudden, non-linear shifts typically seen during trading hours. On the other hand, SVR prevails for high and low prices as these prices often experience spikes and drops driven by transient news and intra-day market sentiments, forming complex patterns that do not align well with linear modelling.

Bisimulations of nonlinear feedback shift registers

This work investigates how to reduce nonlinear feedback shift registers (NFSRs) in combination with bisimulation method via semi-tensor product (STP). By considering a large-scale NFSR as a smaller-scale Boolean system utilising bisimulation relations, the computing complexity of the system can be decreased. On the one hand, the properties of the bisimulation relation between two different NFSRs are examined, while on the other hand, a necessary and sufficient condition is discovered, as well as a reduction strategy utilising bisimulation. Besides, it is talked about how NFSR properties spread throughout the reduction process. The nonsingularity, driven stability and other aspects of the original NFSR are confirmed to be preserved by the reduced Boolean system.

An Analytical Model for Nonlinear-Elastic Compliant Mechanisms with Tension-Compression Asymmetry

Abstract While nonlinear-elastic materials demonstrate potential in enhancing the performance of compliant mechanisms, their behavior still needs to be captured in a generalized mechanical model. To inform new designs and functionality of compliant mechanisms, a better understanding of nonlinear-elastic materials is necessary and, in particular, their mechanical properties that often differ in tension and compression. In the current work, a beam-based analytical model incorporating nonlinear-elastic material behavior is defined for a folding compliant mechanism geometry. Exact equations are derived capturing the nonlinear curvature profile and shift in the neutral axis due to the material asymmetry. The deflection and curvature profile are compared with finite element analysis along with stress-distribution across the beam thickness. The analytical model is shown to be a good approximation of the behavior of nonlinear-elastic materials with tension-compression asymmetry under the assumptions of the von Kármán strain theory. Through a segmentation approach, the geometries of a semicircular arc and folding compliant mechanism design are defined. The deflection of the folding compliant mechanism due to an applied tip load is then evaluated against finite element analysis and experimental results. The generalized methods presented highlight the utility of the model for designing and predicting the behavior of other compliant mechanism geometries and different nonlinear-elastic materials.

One hundred and six years of change in a Sonoran Desert plant community: Impact of climate anomalies and trends in species sensitivities.

A major restriction in predicting plant community response to future climate change is a lack of long-term data needed to properly assess species and community response to climate and identify a baseline to detect climate anomalies. Here, we use a 106-year dataset on a Sonoran Desert plant community to test the role of extreme temperature and precipitation anomalies on community dynamics at the decadal scale and over time. Additionally, we tested the climate sensitivity of 39 desert plant species and whether sensitivity was associated with growth form, longevity, geographic range, or local dominance. We found that desert plant communities had shifted directionally over the 106 years, but the climate had little influence on this directional change primarily due to nonlinear shifts in precipitation anomalies. Decadal-scale climate had the largest impact on species richness, species relative density, and total plant cover, explaining up to 26%, 45%, and 55% of the variance in each, respectively. Drought and the interaction between the frequency of freeze events and above-average summer precipitation were among the most influential climate factors. Increased drought frequency and wetter periods with frequent freeze events led to larger reductions in total plant cover, species richness, and the relative densities of dominant subshrubs Ambrosia deltoidea and Encelia farinosa. More than 80% of the tested species were sensitive to climate, but sensitivity was not associated with a species' local dominance, longevity, geographic range, or growth form. Some species appear to exhibit demographic buffering, where when they have a higher sensitivity to drought, they also tend to have a higher sensitivity to favorable (i.e., wetter and hotter) conditions. Overall, our results suggest that, while decadal-scale climate variation substantially impacts these desert plant communities, directional change in temperature over the last century has had little impact due to the relative importance of precipitation and drought. With projections of increased drought in this region, we may see reductions in total vegetation cover and species richness due to the loss of species, possibly through a breakdown in their ability to demographically buffer climatic variation, potentially changing community dynamics through a change in facilitative and competitive processes.