How can I solve for a vector in a tensor equation involving dot products?

AI Thread Summary
To solve for vector **b** in the tensor equation **a** ⋅ **b** = **c** ⋅ **d**, additional constraints are necessary due to the nature of the dot product, which results in a scalar. The equation implies a contraction of vectors on both sides, making it impossible to isolate **b** without more information. A simple two-dimensional example illustrates that two equations are required to solve for two unknowns. Therefore, without imposing further conditions or obtaining additional equations, finding **b** is not feasible. Constraints are essential for solving vector equations in tensor analysis.
zephyr5050
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Homework Statement



I'm currently trying to work through some issues I'm having with tensor and vector analysis. I have an equation of the form
$$\textbf{a} \bullet \textbf{b} = \textbf{c} \bullet \textbf{d}$$
where all quantities here are vectors. I want to solve for ##\textbf{b}## by finding an equation of the form
$$\textbf{b} = \overline{\textbf{T}} \bullet \textbf{d}$$
where ##\overline{\textbf{T}}## is a tensor. However I'm not sure the proper mathematical procedure to go about this. Any suggestions?

Homework Equations



That's what I'm here for.

The Attempt at a Solution



No idea.
 
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Hi. You can't possibly do that without imposing more constraints on your vector:
In tensor language, the vectors are contracted on both sides so you can't "solve" for b.
This may be confusing because a⋅b looks like a vector expression but it's really a scalar; if you want to solve for a vector you need a vector expression.
Look at the simplest example in 2 dimensions:
a⋅b = cd ⇔a1b1 + a2b2 = c1d1 + c2d2
You see that you would need two equations to solve for the two variables b1 and b2 , and for every additional dimension you need an additional constraint...
 
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