Scalar product and generalised coordinates

Click For Summary
SUMMARY

The discussion centers on the equivalence of the scalar product in Hamiltonian mechanics, specifically the relationship between the expressions \( p \cdot v \) and \( p_i v_i \). Participants clarify that the inner product in \( \mathbb{R}^n \) is defined independently of any basis, and that generalized coordinates can be treated as vectors without requiring an orthonormal basis. The confusion arises from the application of these concepts in Hamiltonian mechanics, where generalized coordinates and momenta are utilized. Ultimately, the inner product remains valid regardless of the basis used, as long as the vectors are properly defined.

PREREQUISITES
  • Understanding of Hamiltonian mechanics and Lagrangian mechanics
  • Familiarity with vector spaces and inner products in \( \mathbb{R}^n \)
  • Knowledge of generalized coordinates and their properties
  • Basic grasp of linear algebra concepts, including basis vectors and transformations
NEXT STEPS
  • Study the definition and properties of inner products in \( \mathbb{R}^n \)
  • Explore the concept of generalized coordinates in Hamiltonian mechanics
  • Learn about the role of basis vectors in vector spaces and their impact on inner products
  • Investigate the differences between Lagrangian and Hamiltonian formulations in classical mechanics
USEFUL FOR

Physicists, mathematicians, and students of mechanics who seek to deepen their understanding of vector operations in Hamiltonian mechanics and the implications of generalized coordinates.

  • #31
I don't know, what you mean by "standard basis". We have an Euclidean vector space ##V## with a scalar product. A Cartesian basis ##\vec{e}_i## fulfills by definition the propery ##\vec{e}_i \cdot \vec{e}_j=\delta_{ij}##, and each vector can be uniquely written in terms of linear combinations of these Cartesian basis vectors,
$$\vec{v}=v^j \vec{e}_j.$$
Here the Einstein summation convention is used, i.e., over equal indices you have to sum. The numbers ##v^j## are the components of the vector ##\vec{v}## wrt. the Cartesian basis.

For the scalar product of two vectors you get
$$\vec{v} \cdot \vec{w} = (v^j \vec{e}_j) \cdot (w^k \vec{e}_k)= v^j w^k \delta_{jk}=w^j v^j.$$
This holds for the components wrt. any Cartesian basis. There is not any special "standard basis".
 
Last edited:
Physics news on Phys.org
  • #32
hutchphd said:
For elements of a 3D vector space space your statement is correct.

The configuration space for the Hamiltonian is a more general beast.
Please read this carefully and then see if your questions are put in better context:
https://en.wikipedia.org/wiki/Generalized_coordinates

The generalized coordinates for the Hamiltonian can be various. I believe they are required to be independent which always allows the inner product to be written in the familiar-looking diagonal sum. (This is stuff I learned 50 yrs ago so anybody feel free to correct me! )
This hints that the basis vectors are orthogonal which helps.

If i have 2 vectors a = aiei and b = biei then consider the basis vectors are not orthonormal then in the scalar product a.b i will end up with term like a1b2e1.e2 which means in this case a.b≠ aibi
 
  • #33
vanhees71 said:
For the scalar product of two vectors you get
vanhees71 said:
For the scalar product of two vectors you get
v→⋅w→=(vje→j)⋅(wke→k)=vjwkδjk=vjvj.
This holds for the components wrt. any Cartesian basis. There is not any special "standard basis".
I assume you mean ##\omega _j## in last

The "standard basis" is the name I was taught for the trivial set of n-tuples {(1,0,...,0),(0,1,...0),...(0,...,0,1)} associated with ##R^n## and the canonical coordinates.
 
  • Like
Likes   Reactions: vanhees71
  • #34
Sure, I've corrected it in the posting above.
 

Similar threads

  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 14 ·
Replies
14
Views
3K
  • · Replies 36 ·
2
Replies
36
Views
5K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 1 ·
Replies
1
Views
4K
Replies
5
Views
4K
  • · Replies 27 ·
Replies
27
Views
3K
  • · Replies 86 ·
3
Replies
86
Views
8K