Langevin Equation unusal form

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This equation is known as the Langevin equation and is used to describe the behavior of "forced thermal ratchets".
  • #1
jbunten
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I'm trying to understand a paper (Magnasco, 1993) which discusses "Forced thermal ratchets". It gives a Langevin equation as:

[tex]\stackrel{.}{x} = \epsilon(t) + f(x) + F(t)[/tex]

where x (a cyclic coordinate) describes the state of the ratchet, f(x) is a force field, F is a driving force and [tex]\epsilon[/tex] is gaussian noise.

I can't understand the [tex]\stackrel{.}{x}[/tex] term. If x is a coordinate then the term is velocity, however the RHS is all force, so logically x could only be momentum.

I would very much appreciate some help with this as I'm rather confused.

Thanks
 
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  • #2
in advance!The \stackrel{.}{x} term is the time derivative of x, meaning that it is the velocity of the ratchet. The equation states that the velocity of the ratchet is equal to the sum of a noise term, a force field, and a driving force. As such, x is the coordinate of the ratchet, not its momentum.
 
  • #3
for reaching out for clarification on the Langevin equation in the paper by Magnasco (1993). As you correctly pointed out, the \stackrel{.}{x} term represents the velocity of the ratchet, while the RHS includes both force and noise terms. This form of the Langevin equation is known as the "overdamped" Langevin equation, where the inertia of the system is neglected. In this case, the velocity is directly proportional to the driving force and the force field, and is also affected by the random fluctuations of the noise term.

To better understand this equation, it may be helpful to consider a simpler case where the force field f(x) is constant and there is no driving force F(t). In this case, the Langevin equation reduces to \stackrel{.}{x} = \epsilon(t) + f(x), which means that the velocity of the system is determined solely by the random noise and the constant force field. This type of equation is commonly used to model the Brownian motion of particles in a fluid, where the velocity is determined by the random collisions with the fluid molecules.

In the case of the paper by Magnasco, the addition of the driving force F(t) introduces a non-equilibrium situation, where the system is constantly driven in a particular direction. This leads to the concept of a "thermal ratchet", where the random fluctuations of the noise term, combined with the asymmetric force field, can result in a net motion in the direction of the driving force. The \stackrel{.}{x} term then represents the velocity of this motion.

I hope this explanation helps to clarify the Langevin equation in the paper. It is a useful tool for studying systems that are subject to both random forces and external driving forces, and has been applied in various fields such as statistical physics, biology, and finance. If you have any further questions or need more clarification, please don't hesitate to ask.
 

1. What is the Langevin equation in its unusual form?

The Langevin equation is a stochastic differential equation that describes the motion of a particle in a fluid under the influence of random forces. The unusual form refers to a modified version of the equation that takes into account non-Gaussian noise, which is often observed in real-world systems.

2. How is the Langevin equation used in scientific research?

The Langevin equation is widely used in many fields of science, including physics, chemistry, and biology. It is often used to study the dynamics of complex systems, such as the movement of particles in a fluid, the behavior of biomolecules, or the evolution of financial markets.

3. What makes the Langevin equation's unusual form different from the traditional form?

The traditional form of the Langevin equation assumes that the random forces acting on a particle follow a Gaussian distribution, while the unusual form takes into account non-Gaussian noise. This can lead to different predictions for the behavior of the system, especially in situations where the noise is significant.

4. Can the Langevin equation's unusual form be applied to all systems?

No, the unusual form of the Langevin equation is not applicable to all systems. It is most commonly used in systems that exhibit non-Gaussian noise, such as those with long-range interactions or complex structures. In systems with Gaussian noise, the traditional form of the Langevin equation is sufficient.

5. What are the practical applications of understanding the Langevin equation's unusual form?

Understanding the unusual form of the Langevin equation can have practical applications in various fields. For example, it can help in the design of more accurate models for predicting the behavior of complex systems, such as biological processes, financial markets, and chemical reactions. It can also aid in the development of new technologies and materials by providing insights into the underlying mechanisms of their dynamics.

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