Chain Rule in Lagrangian Transformation

In summary, the conversation discusses using the Goldstein textbook to show the invariance of the Lagrangian under coordinate transformations. The confusion arises from the use of the chain rule and the lack of the term ##(\partial q/\partial \dot s) \ddot s##. It is suggested to use the Hamiltonian formalism for more general transformations.
  • #1
SEGFAULT1119
4
0
Hello,
I'm trying to follow Goldstein textbook to show that the Lagrangian is invariant under coordinate transformation. I got confused by the step below
So
## L = L(q_{i}(s_{j},\dot s_{j},t),\dot q_{i}(s_{j},\dot s_{j},t),t)##

The book shows that ##\dot q_{i} = \frac {\partial q_{i}}{\partial s_{j}} \dot s_{j} + \frac{\partial q_{i}}{\partial t} ##,and I'm not sure where the ##\frac{\partial q_{i}}{\partial t} ## term come from? I've tried to look up chain rules for coordinate transformation but I can't find anything.

Please help!

Thank you :D
 
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  • #2
It is just the standard chain rule. Consider a function ##f(h,g)## where ##h## and ##g## are functions of some parameter ##t## and differentiate ##f## with respect to ##t##. The chain rule now states
$$
\frac{df}{dt} = \frac{\partial f}{\partial h} \frac{dh}{dt} + \frac{\partial f}{\partial g} \frac{dg}{dt}.
$$
Now, if ##g = t## you would obtain ##dg/dt = dt/dt = 1## and ##\partial f/\partial g = \partial f/\partial t## and therefore
$$
\frac{df}{dt} = \frac{\partial f}{\partial h} \frac{dh}{dt} + \frac{\partial f}{\partial t}.
$$

What is unclear is why a term ##(\partial q/\partial \dot s) \ddot s## is not included. You can only ignore this term if ##q## is a function only of ##s## and not of ##\dot s##.
 
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  • #3
@Oroduin,

You are correct. q is independent of ##\dot s##. I mistyped the question. And thank you for your answer.
 
  • #4
If you want more general transformations, it's better to use the generalized Hamilton principle in terms of the Hamiltonian rather the Lagrangian formulation. This leads to the more general canonical transformations in phase space rather than the less general diffeomorphism invariance of the Lagrangian formalism in configuration space.

The Hamiltonian phase-space formalism turns out to be the most valuable form of classical mechanics from a fundamental-physics point of view since it reveals the symplectic structure of phase space and allows for a quasi algebraic formulation of the dynamics in terms of Poisson brackets, which brings the classical theory very close to its extension to quantum theory.
 

1. What is the Chain Rule in Lagrangian Transformation?

The Chain Rule in Lagrangian Transformation is a mathematical concept used in classical mechanics to find equations of motion for a system. It allows us to find the derivative of a function with respect to a variable that is not directly involved in the function.

2. How does the Chain Rule work in Lagrangian Transformation?

The Chain Rule in Lagrangian Transformation works by breaking down a complex function into smaller, simpler functions. The derivative of the complex function is then found by multiplying the derivatives of the smaller functions together.

3. What is the significance of the Chain Rule in Lagrangian Transformation?

The Chain Rule in Lagrangian Transformation is significant because it allows us to simplify the equations of motion for a system by reducing the number of variables involved. This makes it easier to solve complex problems in classical mechanics.

4. Can the Chain Rule be applied to any function in Lagrangian Transformation?

Yes, the Chain Rule can be applied to any function in Lagrangian Transformation as long as the function is differentiable and has multiple variables involved. It is a fundamental concept in classical mechanics and is used extensively in solving problems.

5. How is the Chain Rule used in practical applications?

The Chain Rule in Lagrangian Transformation is used in practical applications such as celestial mechanics, fluid dynamics, and electromagnetism. It allows scientists to model and understand the behavior of complex systems, making it a valuable tool in many fields of science and engineering.

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