Understanding Fourier Series and Heisenberg Uncertainty Principle

In summary, the conversation discusses the concept of Fourier series and its application in understanding the Heisenberg uncertainty principle. It is explained that any periodic waveform can be represented as the sum of an infinite number of sines and cosines with increasing frequencies. The conversation then delves into the question of how these frequencies are determined and how they relate to the concept of delta(f). It is clarified that while mathematically all frequencies up to infinity are considered, for practical purposes, only a few frequencies around the center of the waveform are relevant. This is because the contribution of extreme frequencies is negligible. The conversation concludes that physical wavepackets do not extend to infinity and only a few frequencies are relevant in determining the momentum and energy of a particle.
  • #1
OS Richert
35
0
Not sure if this should go into a math section, but I am trying to understand it in order to understand the Hesenberg uncertainy principle. I can't find a simple introduction to Fourier series to answer this question.

In my modern physics book, it does a quick introduction to Fourier series without proving any of it (fine with me), but I get a little confused. Any periodic waveform can be the sum of an infinite number of sines and cosines. Now, my understanding of infinite here needs to be defined, as off into infinity on the frequency axises. So we are summing sizes and cosines with larger and larger frequencies.

f = 0, 1/T, 2/T, 3/T, ..., presumably off into infinity. If we are apprioximating, the more terms we include the closer we get to the true answer.

It then says we can begin to let T grow to make are signal's period larger and larger (being influenced to model a single wave packet), and in this case, the fundlemental frequency gets smaller and all the harmonics move closer together. WE then determine we can move all the way to one single pulse by making T infinity large, and therefor using a continuous spread of frequencies.

The next section discusses that if we make our single pulse half as wide, it increases (perhaps doubles) the range of continues frequencies we need. Here is my confusion. Didn't we assume at the start the the frequencies needed to be exact went off into infinity. It seems now though, we have infinity many frequencies (since we are assuming a continious band), but the band itself is now finite. In other words, we may have a delta(f) centered around f at 100Mhz or so, with a delta of 10Mhz, (90-110Mhz), with infinitly many frequencies in between (to make the period T as large as we need). BUT(!), why don't we need to sum out the frequencies up to inifinity like we did at the start, 1000/T, 1000000/T, 50000343234/T, etc. What happen to all of these terms which would have frequencies greater then 110Mhz. My book makes no effort to explain this. I can't understand Heisenberg uncertainty principle until I understand why delta(f) is only a delta and does not have terms reaching out into infinite f.

I hope my question makes sense.
 
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  • #2
Excellent question. Look at a Gaussian waveform - that's a stereotypical waveform in frequency space. "Most" momenta are within one or two sigma of the packet center, those are the frequencies that matter. By "delta", you can freely substitute a "sigma" in a Gaussian waveform, that's what it means, a statistical standard deviation. In principle you worry about all those frequencies up to infinity - and to be rigorous, note that the integral does say to integrate [tex]\int_{-\infty}^{\infty} d \omega \quad[/tex] - but in terms of physical reasoning, those extreme terms don't really matter. Their contribution is truly neglible for all practical purposes.*

*But for the math to work out analytically, you really do need all of them in the integral. The difference between a physicist and a mathematician is just this - a physicist throws out tiny numbers that don't matter.
 
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  • #3
By the way - the Gaussian waveform is ubiquitous for many reasons - among which, it keeps the same shape under a Fourier transform (the parameters change).
 
  • #4
thank you for the reply. So if I can rephase just to see if I understand, in any given wave packet of a particle, we do actually have frequencies that increase all the way to infinity, but after a certain point they become so neglagibly small (the amplitute is neglagibly small) that they contribute nothing to any meaning measurment of momentum or energy of an actual particle.
 
  • #5
Exactly. In some treatments you will come across "wavepackets" that do extend to infinity, things like plane waves - but these are only a mathematical convenience, and do not represent anything physical. Physical wavepackets vanish at infinity. (that's so they can be properly normalized)
 

Related to Understanding Fourier Series and Heisenberg Uncertainty Principle

1. What is a Fourier series and how is it used in science?

A Fourier series is a mathematical representation of a periodic function using a combination of sine and cosine waves. It is commonly used in physics, engineering, and other scientific fields to analyze and model complex, repetitive phenomena such as sound waves and electromagnetic signals.

2. How does the Heisenberg Uncertainty Principle relate to Fourier series?

The Heisenberg Uncertainty Principle states that there is a fundamental limit to how accurately we can measure certain pairs of physical properties, such as position and momentum or time and frequency. Fourier series are used to analyze the frequency components of a signal, and the uncertainty principle puts a limit on how precisely we can know both the time and frequency components of a signal.

3. Can you explain the mathematical concept behind Fourier series?

Fourier series are based on the concept of representing a function as an infinite sum of sine and cosine waves with different frequencies, amplitudes, and phases. This is possible because any periodic function can be broken down into a series of harmonic components. The Fourier series allows us to analyze and manipulate a function by examining its frequency components.

4. What are some practical applications of Fourier series in science and technology?

Fourier series have a wide range of applications in science and technology. They are commonly used in signal processing, data compression, and image analysis. In physics, they are used to study the behavior of waves and oscillations in various systems. In engineering, they are used in designing and optimizing electronic circuits and systems.

5. How does understanding Fourier series and the Heisenberg Uncertainty Principle contribute to our understanding of the physical world?

By understanding Fourier series and the Heisenberg Uncertainty Principle, we gain a deeper understanding of the fundamental principles and limitations of the physical world. These concepts are essential for understanding complex phenomena such as waves and quantum mechanics. They also have practical applications in various fields of science and technology, allowing us to analyze and manipulate signals and systems in a more precise and efficient manner.

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