Wave Packet Expansion: Understanding $\omega (\vec{k})$

In summary, the conversation discusses a wave packet with a limited range of appreciable values near the mean wave vector, and its behavior in coordinate space can be approximated using a Taylor series expansion of the angular frequency function. The abbreviations used are shorthand notations for the mean angular frequency and its gradient.
  • #1
ognik
643
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The text states:
"Let us consider a wave packet whose Fourier inverse $\phi (\vec{k})$ is appreciably different from zero only in a limited range $\Delta \vec{k}$ near the mean wave vector $\hbar \vec{\bar{k}} $. In coordinate space, the wave packet $\psi(\vec{r}, t)$ must move approximately like a classical free particle with mean momentum $\hbar \vec{\bar{k}}$. To see this behavior we expand $\omega (\vec{k})$ about $\vec{\bar{k}}$:

$ \omega (\vec{k}) = \omega(\vec{\bar{k}}) + (\vec{k} - \vec{\bar{k}}) \cdot (\vec{\nabla_k} \omega)_{k= \vec{\bar{k}}} + ...$

$=\bar{\omega} + (\vec{k} - \vec{\bar{k}})\cdot \vec{\nabla_{\bar{k}}} \bar{\omega} +... $ with obvious abbreviations"

I'm afriad not much of the above is obvious to me ...please help me understand -
What is $ \omega (\vec{k})$?
What expansion are they using?
What are the abbreviations?
 
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  • #2


Hello,

I can help clarify the concepts mentioned in the forum post for you. First, $\omega (\vec{k})$ represents the angular frequency of a wave described by the wave packet. The wave packet itself is represented by the function $\psi(\vec{r}, t)$, which depends on position $\vec{r}$ and time $t$.

The expansion being used is a Taylor series expansion, which is a mathematical tool used to approximate a function by calculating its derivatives at a specific point. In this case, the function being expanded is $\omega (\vec{k})$ and the point of expansion is $\vec{\bar{k}}$, the mean wave vector. This expansion allows us to better understand the behavior of the wave packet in coordinate space, as mentioned in the text.

The abbreviations used, such as $\bar{\omega}$ and $\vec{\nabla_{\bar{k}}} \bar{\omega}$, are simply shorthand notations for the mean angular frequency and the gradient of the mean angular frequency, respectively. The ellipses in the equations represent higher order terms in the Taylor series expansion, which have been omitted for brevity.

I hope this helps clarify the concepts for you. Let me know if you have any further questions.
 

Related to Wave Packet Expansion: Understanding $\omega (\vec{k})$

1. What is a wave packet?

A wave packet is a localized solution of a wave equation that represents a disturbance or signal with a finite size, rather than an infinite length. It is a combination of multiple waves with different frequencies and wavelengths that interfere constructively and destructively, creating a localized disturbance.

2. What is the significance of understanding $\omega (\vec{k})$ in wave packet expansion?

$\omega (\vec{k})$ represents the dispersion relation, which relates the frequency of a wave to its wavevector in a given medium. Understanding this allows us to analyze how a wave packet behaves over time and space, and how it is affected by the medium it is traveling through.

3. What does the expansion of a wave packet involve?

The expansion of a wave packet involves expressing a localized disturbance in terms of a sum of harmonic waves with different frequencies and wavelengths. This is done using Fourier analysis, which breaks down a complex signal into simpler components.

4. How does wave packet expansion help in understanding wave phenomena?

Wave packet expansion provides a way to analyze and understand complex wave phenomena, such as interference and diffraction, by breaking them down into simpler components. It allows us to study the behavior of different frequencies and wavelengths within a wave packet and how they interact with each other.

5. Can wave packet expansion be applied to other fields besides physics?

Yes, wave packet expansion can be applied to other fields such as signal processing and quantum mechanics. In signal processing, it is used to analyze and filter signals, while in quantum mechanics, it is used to describe the behavior of quantum particles, such as electrons, in a wave-like manner.

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