What is Brownian Motion (Weiner process)?

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Discussion Overview

The discussion revolves around the concept of Brownian motion and its relationship to the Wiener process, exploring definitions, properties, and mathematical implications. Participants examine the characteristics of these processes, including continuity and differentiability, and how they relate to random walks.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant questions whether the concept of a random walk with steps taken at random times is equivalent to Brownian motion, seeking clarification on the notation "W_t" and its meaning.
  • Another participant explains that "t → W_t" indicates that the Wiener process is a continuous function of time, suggesting that Brownian motion and the Wiener process are essentially the same, though noting potential differences regarding physical Brownian motion.
  • A participant raises a concern about the differentiability of Brownian motion, referencing a property that states it is continuous everywhere but differentiable nowhere, and questions the implications of this in light of continuity theorems.
  • Another participant responds by stating that while differentiability implies continuity, the reverse is not true, and notes that there are continuous functions that are nowhere differentiable, providing a reference to the Weierstrass function.
  • A later reply suggests that a Wiener process might be viewed as the limit of Brownian motion with infinitely small particles, introducing a potential distinction between the two concepts.

Areas of Agreement / Disagreement

Participants generally agree on the equivalence of Brownian motion and the Wiener process, but there are differing views on the implications of continuity and differentiability, as well as the relationship to random walks. The discussion remains unresolved regarding the nuances of these properties.

Contextual Notes

Participants express uncertainty about the definitions and properties of Brownian motion and the Wiener process, particularly concerning the implications of continuity and differentiability. There are references to external resources that may contain additional assumptions or definitions not fully explored in the discussion.

Who May Find This Useful

This discussion may be of interest to students and professionals in mathematics, physics, and engineering who are exploring stochastic processes, particularly those related to Brownian motion and its mathematical treatment.

woundedtiger4
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Hi all,

When random walk takes the steps at random times, and in that case the position X_t is defined as the continuum of times t≥0, isn't this concept/phenomenon/rule is Brownian motion (Weiner process)? At http://en.wikipedia.org/wiki/Wiener_process in section "Characterizations of the Wiener process" denote it as "W_t", does it tell the position at time "t" just like we find the position in random walks? In the same section, I don't understand the second property, particularly "t→W_t" , what is this?

Thanks in advance

Note: The text says that the mathematical treatment of Brownian motion is called Weiner process, therefore I am thinking that both Brownian motion & Weiner are same, am I correct?
 
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t -> W_t is part of a sentence which says the Weiner process is a continuous (almost everywhere) function of time (t).

Essentially Brownian motion and Weiner process refer to the same things. There may be some quibble, since physical Brownian motion also refers to processes with jumps.
 
mathman said:
t -> W_t is part of a sentence which says the Weiner process is a continuous (almost everywhere) function of time (t).

Essentially Brownian motion and Weiner process refer to the same things. There may be some quibble, since physical Brownian motion also refers to processes with jumps.
thanks for the reply, you are always very helpful.


At http://www.math.uchicago.edu/~may/VIGRE/VIGRE2009/REUPapers/McKnight.pdf the 3rd property says that Brownian motion is continuous everywhere and differentiable nowhere, if I am not wrong then BM (Brownian motion) is not differentiable nowhere because there are no jumps or discontinuity anywhere in BM or roughly speaking the graph of BM is too rough or it has too much spikes but at http://tutorial.math.lamar.edu/Classes/CalcI/DefnOfDerivative.aspx the last theorem (at the bottom of the page) says that if f(x) is differentiable at x=a then f(x) is continuous at x=a, why does it contradict? Is it because BM is random variable whereas the continuity theorem is about normal variables?

thanks in advance
 
differentiability => continuity, but not the reverse. In fact it is possible to construct continuous functions which are nowhere differentiable - this is a general fact, not particularly for Brownian motion. See the following:

http://en.wikipedia.org/wiki/Weierstrass_function
 
mathman said:
differentiability => continuity, but not the reverse. In fact it is possible to construct continuous functions which are nowhere differentiable - this is a general fact, not particularly for Brownian motion. See the following:

http://en.wikipedia.org/wiki/Weierstrass_function

GOT IT :)
Thank you Sir.
 
woundedtiger4 said:
Hi all,

When random walk takes the steps at random times, and in that case the position X_t is defined as the continuum of times t≥0, isn't this concept/phenomenon/rule is Brownian motion (Weiner process)? At http://en.wikipedia.org/wiki/Wiener_process in section "Characterizations of the Wiener process" denote it as "W_t", does it tell the position at time "t" just like we find the position in random walks? In the same section, I don't understand the second property, particularly "t→W_t" , what is this?

Thanks in advance

Note: The text says that the mathematical treatment of Brownian motion is called Weiner process, therefore I am thinking that both Brownian motion & Weiner are same, am I correct?
I don't really recall, but my impression is that a Weiner process is the limit of Brownian motion with infinitely small particles.
 

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