Solving a Tensor Problem in 2D Space

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In summary, the conversation discusses finding the covariant components of a contravariant vector field in a two dimensional space with a given metric tensor field. The covariant components are found using the contravariant components and the inverse of the metric tensor. The final result is that the vector field is equal to -3dq^1 - 4dq^2.
  • #1
atwood
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Homework Statement


A two dimensional space has a metric tensor field
[tex]g=dq^1 \otimes dq^1 + 2 dq^1 \otimes dq^2 + 2dq^2 \otimes dq^1 + 3dq^2 \otimes dq^2[/tex].

With the help of g, find the covariant components of the contravariant vector field
[tex]\textbf{v}=3\partial _1 -4\partial _2[/tex]

The Attempt at a Solution


Not much here as I don't really understand how this works.

g11=1, g12=2, g21=2, g22=3

[tex]\begin{center}G=\left(\begin{array}{ll} 1 & 2 \\ 2 & 3 \end{array}\right) \Rightarrow
G^{-1}=\left(\begin{array}{ll} {-3} & \ 2 \\ \ 2 & {-1} \end{array}\right)\end{center}[/tex]

g11=-3, g12=2, g21=2, g22=-1

Now the covariant components ai of v are given from the contravariant components ai like this:
a1=a1g11+a1g12=3*(-3)+3*2=-3
a2=a2g21+a2g22=(-4)*2+(-4)*(-1)=-4

So [tex]\textbf{v}=-3dq^1 -4dq^2[/tex]

Does this make any sense at all?
 
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  • #2
[itex]a^i=a_k g^{ik}[/itex], yes? So don't you mean [itex]a^1=a_1 g^{11}+a_2 g^{12}[/itex]?
 
  • #3
Right, of course. I should never ask anything when tired.

Thanks!
 

1. What is a tensor problem in 2D space?

A tensor problem in 2D space refers to a mathematical problem that involves manipulating and solving for tensors, which are multidimensional arrays or objects that describe the relationships between vectors and scalars in a specific coordinate system. In 2D space, these tensors are represented by two indices and can be used to represent various physical quantities, such as stress and strain in materials or fluid flow in a plane.

2. What are some common methods for solving tensor problems in 2D space?

Some common methods for solving tensor problems in 2D space include using vector calculus, matrix algebra, and differential equations. These methods can help manipulate and transform tensors to solve for unknown variables or to calculate important physical quantities.

3. What are the applications of solving tensor problems in 2D space?

Solving tensor problems in 2D space has various applications in fields such as physics, engineering, and computer graphics. For example, it can be used to analyze and predict the behavior of materials under stress, simulate fluid flow in computer-generated animations, or model the deformation of objects in 2D space.

4. What are some challenges in solving tensor problems in 2D space?

One of the main challenges in solving tensor problems in 2D space is the complexity of the calculations involved. Tensors can have multiple components and indices, making their manipulation and solution more cumbersome and time-consuming. Additionally, understanding the physical principles behind the problem and choosing the appropriate mathematical approach can also be challenging.

5. How can I improve my understanding and skills in solving tensor problems in 2D space?

To improve your understanding and skills in solving tensor problems in 2D space, it is important to have a strong foundation in mathematics, particularly in linear algebra and vector calculus. Additionally, practicing with different types of tensor problems and seeking guidance from experts in the field can also help improve your skills. Utilizing software and programming tools can also aid in visualizing and solving these problems more efficiently.

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