Understanding the Role of Degrees of Freedom in 1-Dimensional Random Walks

In summary, the conversation discusses a physics question about random walks and the concept of delta as the distance a particle moves. The question is about the appearance of n-1 and its relation to degrees of freedom. The conversation then delves into equations and the use of delta in calculating positions, with a discussion about the encircled expression in equation 2 and its impact on the final outcome. Ultimately, there is a question about the correctness of the thought process and whether the resulting position is in the opposite direction of the negative delta average.
  • #1
SansaStark
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Hello!
I'm struggling with a probably easy physics question concerning random walks. Here I have the slide regarding this:
Delta is the distance that a particle moves.
upload_2016-1-2_16-32-9.png


Can someone explain where the n-1 initially comes from? Does it have to do wtih the concept of the degrees of freedom?
Than you already! Regards, Vera
 
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  • #2
Not sure if I understand the question. So your first equation states that after ##n## steps the particle is at the position it was after the previous step (which is the ##(n-1)##th step) plus some ##\delta##. If you put in ##n=1## you get that the position after the first step is the initial position plus some ##\delta##: ##x_1(1) - x_i(0) \pm \delta##. Every next step a new ##\delta## is added, so of course the position after ##n## steps depends on the position after ##(n-1)## steps. Why do you think this has to do anything with degrees of freedom?
 
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  • #3
After ##n-1## steps, particle i is at position ##x_i(n-1)##.
One step after that, at step ##n##, particle i has moved by ##\pm \delta##: therefore ##x_i(n)=x_i(n-1)\pm \delta##.
 
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  • #4
The notations ##x_n^{(i)}## and ##<x_n^{(i)} | 1≤i≤N >## might have been less confusing. Or more.
 
  • #5
Oh okay, thank you. After some thinking ad not giving that much emphasis of on this n-1 (which so muchly looks like the n-1 from the df concept) I finally realized what both of you mean ;) I was really confused about why suddenly this n-1 would appear. But its probably quite reasonable. oO Thanks a lot!
 
  • #6
@fresh42: More (for I have no clue what the vertical bar means AND SO ON) ;)
 
  • #7
Another question:
Equation 1.) is followed by equation 2.). In equation 2.) the delta is treated separately as encircled in red colour. Is this just a process of pulling the expression after the sigma sign in equ. 1 apart?
But then, why is the second expression (in the circle) SUBTRACTED from the first part of equ. 2.)? I know it doesn't really matter as delta is 0... but just assume that the encircled expression without the minus in the beginning would equal a positive number. Then the outcome would be different compared to when the expression was negative. I know there's a mistake in thinking but I I just can figure out what's behind this. ^^

1.)
upload_2016-1-2_18-17-55.png
2.)
upload_2016-1-2_18-10-26.png
Just how I'd approach this: The first part of equ. 2.) is the average of all preceding steps (n-1) and the second part is the average of all distances after one step. Then, if I subtract all deltas and assume their average was negative (which just means this whole particle is moving in the opposite direction compared to a positive delta) this would result in a position (x) actually in the opposite direction of the negative delta average for it is subtracted from the first average...

Is that right or complete bullsh**? ;) Thanks!
 

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1. What is a 1-dimensional random walk?

A 1-dimensional random walk is a mathematical model used to describe the movement of a particle in a straight line, where each step is taken in a random direction. It is often used to study the behavior of molecules, particles, or other systems that exhibit random motion.

2. How does a 1-dimensional random walk work?

In a 1-dimensional random walk, the particle starts at a certain position on a number line and takes a step either to the left or right with equal probability. This process is repeated for a certain number of steps, and the final position of the particle is recorded. This can be repeated many times to observe the overall behavior of the particle.

3. What is the significance of a 1-dimensional random walk in science?

1-dimensional random walks are important in various scientific fields, such as physics, chemistry, biology, and economics. They can be used to model diffusion and other random processes, as well as to analyze the behavior of complex systems.

4. How is a 1-dimensional random walk different from a 2-dimensional or 3-dimensional random walk?

A 1-dimensional random walk only allows the particle to move in one direction (left or right), while a 2-dimensional random walk allows movement in two directions (up/down or left/right) and a 3-dimensional random walk allows movement in three directions (up/down, left/right, and forward/backward).

5. Can a 1-dimensional random walk be used to predict the exact path of a particle?

No, a 1-dimensional random walk is a stochastic process and the exact path of the particle cannot be predicted. However, it can provide insights into the overall behavior and patterns of the particle's movement.

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