Self-accelerating wave packets in free space

Turker, Z.

doi:10.1007/s12043-022-02380-5

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…In this paper, our aim is predicting the max density points of self-accelerating waves. We will use waves which we found in our previous research [15]. We found the most general formula for selfaccelerating waves in free space by performing numerical computations.…”

Section: Self-accelerating Wavesmentioning

confidence: 99%

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Density prediction of self-accelerating waves

2023

IJANSER

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Self-accelerating waves have attracted a lot of attention not merely in terms of principles and practical demonstrations, but also in terms of a diverse variety of applications. Some of these applications are filamentation, biomedical imaging, particle manipulation, material processing and plasmons. In this paper, we study the prediction of maximum points of self-accelerating waves. We predict maximum points of the self-accelerating waves. We apply machine learning algorithm to predict the maximum point. We use two machine learning algorithm Decision Tree Classifying and Logistic Regression. The data is processed in python programming using two main Machine Learning Algorithm namely Decision Tree Algorithm and Logistic Regression which shows the best algorithm among these two in terms of accuracy level of maximum point of a self-accelerating wave.

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Section: Self-accelerating Wavesmentioning

confidence: 99%

“…A brief outline of current advances as well as many sorts of applications that make advantage of the features of accelerating waves are given in [14]. The most generic formula for selfaccelerating waves in free space has recently been constructed [15]. In higher dimensions, researchers discovered a family of non-diffracting, selfaccelerating waves.…”

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confidence: 99%