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Synopsis
Excerpt from Sunspot Cycle Simulation Using a Narrowband Gaussian Process
Since the discovery of the cyclic behavior of sunspots by Schwabe in 1843, many authors have referred to the sunspot record as an example of naturally occurring periodic behavior not easily explained by the dynamics of rotating systems. Yule [1] characterized the sunspot numbers as a disturbed harmonic function, which he likened to the motion of a pendulum that boys are pelting with peas. Time series analysis texts [2] and statistical works [3] commonly cite the sunspot number series as a function that is more or less periodic. The noisy, but nearly periodic, character of the sunspot record suggests a very simple model of solar activity that simulates the observed Sunspot numbers to a surprising degree. The observed annual mean sunspot numbers [4] and simulated annual mean sunspot numbers (produced using methods described in this paper) are shown in figure 1.
Our model, in its simplest form, is the squared output of a narrowband filter driven by white Gaussian noise. If elaborate filtering schemes are used, it is possible to mimic the stochastic properties of agy existing signal. In other words, given sufficient resources, it is possible to mimic almost any existing signal. Suppose, on the other hand, a white noise signal (perhaps the simplest of signals) is filtered by a simple narrowband filter and the squared output signal resembles a com plicated existing signal in all its gross characteristics does this not compel one to give serious consideration to the physical implications of the stochastic process?
We see no reason to be uncomfortable with the suggestion that some Gaussian-noise process may be at work in the interior of the Sun. White Gaussian-noise is common in the Universe at all levels from the microscopic to the macroscopic; whether we consider the noise produced in thermionic emission in an electron tube or the noise received from some distant radio galaxy. By the same token, it is not discomforting to consider that the Sun might have resonant modes which act as filters. Many of the physical objects in our everyday lives exhibit the properties of filters. That is, they respond to certain modes of excitation and they are to a greater or lesser extent resonators. Is it not natural then to expect that the massive solar body with great mechanical, thermal and gravitational forces at work has its own natural modes of response that cause it to behave as a filter? Indeed, calculations of the solar thermal diffusion constant [5] indicate that where solar luminosity is concerned, the Sun does act like a low pass filter.
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- PublisherForgotten Books
- Publication date2018
- ISBN 10 0260940658
- ISBN 13 9780260940650
- BindingPaperback
- LanguageEnglish
- Number of pages29
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Sunspot Cycle Simulation Using a Narrowband Gaussian Process (Classic Reprint)
Print on DemandSeller: Forgotten Books, London, United Kingdom
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Paperback. Condition: New. Print on Demand. This book introduces a novel, accessible model that simulates sunspot cycles at remarkable computer speeds. The author uses a simple square root of a narrowband Gaussian process to demonstrate its effectiveness. Traditionally, the study of sunspot cycles has been complex and time-consuming, but this book presents an efficient and easy-to-understand approach. The book also delves into the physical basis of the model, emphasizing the resonance involved. By examining the secular cycles and extensive minima characteristic of narrowband Gaussian processes, the author explores the stochastic nature of sunspot cycles. Furthermore, the book discusses the implications of the model's findings on solar activity, highlighting the potential for limited sunspot cycle predictionâ"insights that could prove invaluable in fields heavily influenced by solar activity. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9780260940650_0
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