Understanding Brownian Motion with Weiner Integral and Delta Functions

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SUMMARY

This discussion focuses on solving Brownian motion using the Wiener Integral, specifically for the potential function V(x) defined as V(x) = δ(x) + δ(x-1) + δ(x-2). The integral presented is expressed as ∫ ℳ [x_t] exp(-∫ dt (m/2(ẋ)² - V(x))). Participants seek clarification on the notation used, including x_t, ẋ, and ℳ, which are essential for understanding the mathematical framework of the problem.

PREREQUISITES
  • Understanding of Wiener Integrals in stochastic calculus
  • Familiarity with delta functions in mathematical physics
  • Knowledge of Brownian motion and its mathematical representation
  • Basic concepts of variational calculus
NEXT STEPS
  • Study the properties of Wiener Integrals in stochastic processes
  • Research delta functions and their applications in quantum mechanics
  • Explore advanced topics in Brownian motion modeling
  • Learn about variational methods in path integrals
USEFUL FOR

Mathematicians, physicists, and students specializing in stochastic processes, quantum mechanics, or mathematical physics will benefit from this discussion.

tpm
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HI, i would need some help to solve the Brownian motion given by the Weiner Integral(over paths):

[tex]\int \mathcal D [x_{t}]exp(-\int dt (m/2(\dot x)^{2}-V(x))[/tex]

for the case [tex]V(x)=\delta (x) +\delta (x-1)+\delta (x-2)[/tex]

any help would be appreciated, thanks
 
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What do you mean by that: "solve the Brownian motion" ?
 
tpm said:
HI, i would need some help to solve the Brownian motion given by the Weiner Integral(over paths):

[tex]\int \mathcal D [x_{t}]exp(-\int dt (m/2(\dot x)^{2}-V(x))[/tex]

for the case [tex]V(x)=\delta (x) +\delta (x-1)+\delta (x-2)[/tex]

any help would be appreciated, thanks
Can you please explain your notation? In particular, what is [tex]x_t[/tex], what is [tex]\dot x[/tex], and what is [tex]\mathcal D[/tex]?
 

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