Generation and evolution of Vortex array with variable-ratio lateral-shearing interferometry

Different from the method by plane-wave interference, here an efficient approach is proposed to generate optical vortex array (VA) based on lateral-shearing interferometer (LSI), in which the evolution from light spot array to VA can be observed by continuously variable shear ratio in a certain range. VAs with topological charge 2 and 1 are simulated by software GLAD and proved to be effectiveness through optical experiment. Theoretical analysis and experimental results show that when the shear ratio approaches to zero, we can stably obtain a vortex array with high density and variable topological charge.

Theory of polarization-averaged core-level molecular-frame photoelectron angular distributions: III. new formula for p- and s-wave interference analogous to Young's double-slit experiment for core-level photoemission from hetero-diatomic molecules

We present a new variation of Young's double-slit formula for polarization-averaged molecular-frame photoelectron angular distributions (PA-MFPADs) of hetero-diatomic molecules, which may be used to extract the bond length. So far, empirical analysis of the PA-MFPADs has often been carried out employing Young's formula in which each of the two atomic centers emits a s-photoelectron wave. The PA-MFPADs, on the other hand, can consist of an interference between the p-wave from the X-ray absorbing atom emitted along the molecular axis and the s-wave scattered by neighboring atom, within the framework of Multiple Scattering theory. The difference of this p-s wave interference from the commonly used s-s wave interference causes a dramatic change in the interference pattern, especially near the angles perpendicular to the molecular axis. This change involves an additional fringe, urging us to caution when using the conventional Young's formula for retrieving the bond length. We have derived a new formula analogous to Young's formula but for the p-s wave interference. The bond lengths retrieved from the PA-MFPADs via the new formula reproduce the original C-O bond lengths used in the reference ab-initio PA-MFPADs within the relative error of 5 %. In the high energy regime, this new formula for p-s wave interference converges to the ordinary Young’s formula for the s-s wave interference. We expect it to be used to retrieve the bond length for time-resolved PA-MFPADs instead of the conventional Young's formula.

Spatially distributed computation in cortical circuits

The traditional view of neural computation in the cerebral cortex holds that sensory neurons are specialized, i.e., selective for certain dimensions of sensory stimuli. This view was challenged by evidence of contextual interactions between stimulus dimensions in which a neuron's response to one dimension strongly depends on other dimensions. Here we use methods of mathematical modeling, psychophysics, and electrophysiology to address shortcomings of the traditional view. Using a model of a generic cortical circuit, we begin with the simple demonstration that cortical responses are always distributed among neurons, forming characteristic waveforms, which we call neural waves. When stimulated by patterned stimuli, circuit responses arise by interference of neural waves. Resulting patterns of interference depend on interaction between stimulus dimensions. Comparison of these modeled responses with responses of biological vision makes it clear that the framework of neural wave interference provides a useful alternative to the standard concept of neural computation.

Getting the ducks in a row

Vessels – in the widest sense – travelling on a water surface continuously do work the water surrounding it, causing energy to be radiated in the form of surface waves. The concomitant resistance force, the wave resistance, can account for as much as half the total drag on the vessel, so reducing it to a minimum has been a major part of ship design research for many decades. Whether the ‘vessel’ is an ocean-going ship or a swimming duckling, the physics governing the V-shaped pattern of radiated waves behind it is in essence the same, and just as fuel economy is important for commercial vessels, it is reasonable to assume that also swimming waterfowl seek to minimise their energy expenditure. Using theory and methods from classic marine hydrodynamics, Yuan et al. (J. Fluid Mech., vol. 928, 2021, R2) consider whether, by organising themselves optimally, ducklings in a row behind a mother duck can reduce, eliminate or even reverse their individual wave resistance. They describe two mechanisms which they term ‘wave riding’ and ‘wave passing.’ The former is intuitive: the ducklings closest to the mother can receive a forward push by riding its mother's stern waves. The latter is perhaps a more striking phenomenon: when the interduckling distance is precisely right, every duckling in the row can, in principle, swim without wave resistance due to destructive wave interference. The phenomenon appears to be the same as motivates the recent US military research project Sea Train, a row of unmanned vehicles travelling in row formation.

Intersecting Linear Light Strands: A Particle Explanation for the Fresnel Central Spot

The Fresnel central spot in a shadow, theorized to be generated from wave interference, has given strong support for wave models of light. Using extended exposure macro imaging in various media, the shadow is shown to be more complex with multiple lines of light intersecting in the center. Using the particle concept of discrete light strands perpendicularly reflecting from a diffraction source, these observations can be more accurately explained. Another quantized aspect of light is shown where linear light strands become rings when an energy threshold is reached.

Fano interference in quantum resonances from angle-resolved elastic scattering

Asymmetric spectral line shapes are a hallmark of interference of a quasi-bound state with a continuum of states. Such line shapes are well known for multichannel systems, for example, in photoionization or Feshbach resonances in molecular scattering. On the other hand, in resonant single channel scattering, the signature of such interference may disappear due to the orthogonality of partial waves. Here, we show that probing the angular dependence of the cross section allows us to unveil asymmetric Fano profiles also in a single channel shape resonance. We observe a shift in the peak of the resonance profile in the elastic collisions between metastable helium and deuterium molecules with detection angle, in excellent agreement with theoretical predictions from full quantum scattering calculations. Using a model description for the partial wave interference, we can disentangle the resonant and background contributions and extract the relative phase responsible for the characteristic Fano-like profiles from our experimental measurements.

Narrowband Interference Cancellation using Set-membership Adaptive Predictor for GPS Receiver

The global positioning system (GPS) provides accurate positioning and timing information that is useful in various civil and military applications. The adaptive filtering predictor for GPS jamming suppression applications is proposed. This research uses the gLab-G software to substitute for the hardware receiver to record the GPS signal waveform. The normalized least-mean-square (NLMS) and set-membership NLMS (SM-NLMS) filtering methods are employed for continuous wave interference suppression. Simulation results reveal that our proposed methods can provide the better performances when the interference-to-noise ratios (INR) are varied from 20 to 50 dB. The anti-jamming performances are evaluated via extensive simulation by computing mean squared prediction error (MSPE) and signal-to-noise ratio (SNR) improvements.

Nanoscale neural network using non-linear spin-wave interference

We demonstrate the design of a neural network hardware, where all neuromorphic computing functions, including signal routing and nonlinear activation are performed by spin-wave propagation and interference. Weights and interconnections of the network are realized by a magnetic-field pattern that is applied on the spin-wave propagating substrate and scatters the spin waves. The interference of the scattered waves creates a mapping between the wave sources and detectors. Training the neural network is equivalent to finding the field pattern that realizes the desired input-output mapping. A custom-built micromagnetic solver, based on the Pytorch machine learning framework, is used to inverse-design the scatterer. We show that the behavior of spin waves transitions from linear to nonlinear interference at high intensities and that its computational power greatly increases in the nonlinear regime. We envision small-scale, compact and low-power neural networks that perform their entire function in the spin-wave domain.