# Einstein Field equations for dummies

• alecrimi
The idea is that for every point on the path, there is a unique point on the path that is an extremal point.This is a bit more complex than the definition for extremal points, but it's still pretty simple.In summary, extremal proper time is maximal aging, and extremal path is the coordinate system used by the Universe.f

#### alecrimi

Hi all!
When we talk about the Einstein Field equations.
What do we mean with "extremal proper time" or "extremal path"?
Why "extremal" ?
and why "proper" ?

and why do we need to introduce the concept of "geodesic" ?
Cheers

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Why "extremal" ?
and why "proper" ?
They are jargon words. What else would you call them?

Space-time is tricky to talk about - these concepts help. Remember, you now have four dimensions ... eg. what would a "maxima" in 4D mean?
https://www.physicsforums.com/archive/index.php/t-488751.html

and why do we need to introduce the concept of "geodesic" ?
Same reason we have any kind of coordinate system - only the geodesic is the coordinate system used by the Universe... which makes it special.

In the context of proper time "extremal" mostly means maximal in practice. And proper time is what you measure with a wristwatch, or by aging. So you can think of "extremal proper time" as "maximal aging", usually.

However, there is a significant difference between "mostly means in practice" and "always means".

To understand more precisely the definition of extremal, first consider a function of a single variable, y = f(x)

An an extremal point, dy/dx = 0, i.e. the slope is horizontal.

Extremal points can be either a maximum, a minimum, or a saddle points.

If all this isn't a review, or if you lack calculus, you may need to do some further reading and research to fully understand this. (I'm sorry, but I don't know your background).

A quick example might help. Rather than draw graphs, which is the clearest, I'll use some well known simple equations:

y=x^2 has a minimum at x=0
y = -x^2 has a maximum at x=0
y = x^3 has a saddle point at x=0

We can apply similar definitions to functions of more than one variable, in which case we require all the derivatives to vanish to have an extremal point.

In the case of an extremal path, we do a bit of fancy mathematical footwork to extend the same basic definition we use with one variable to an infinite number of variables.