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Garth said:Why? I think it is quite applicable.
We have only been talking about weak fields [itex]\frac{GM}{rc^2} \sim 10^{-9}[/itex] and the oscillating observer only needs to travel less than an Earth radius:
~ 10-2 light secs, or perhaps ~ 10-1 light secs, where the orbital period ~ 80 minutes, and we are not talking about a weird topology induced by one observer zipping around a Black Hole or something, so doesn't your statement: "If I'm traveling inertially, then my clock reads the greatest amongst all clocks that have been traveling roughly the same path as me" hold?Yes, gravitational waves would introduce a slight modificaton to the metric, but basically the 'meat' of [itex]T_{\mu\nu}[/itex] is in the distribution of mass in the Schwarzschild solution.
Garth
Consider again my example of two points separated by a mountain. Or better yet, consider two points on an egg:
Code:
A
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B
There exists two path on the egg from A to B which are both geodesics but which have different lengths.
You are apparently still confusing "local maximum" with "global maximum". A geodesic path has the property that it's a local maximum (of time in space-time), or a local minimum (of distance in Euclidean space). A given geodesic is not necessary a global maximum (of time in space-time) or a global minimum (of distance). As Hurkyl points out, it is only for paths "near" the target path that you are guaranteed to have an extreme value. "Nearness" of paths is a somewhat abstract concept, while I could write down the intergal, it's probably not worthwhile to apply rigor at the moment.
Instead, it may be simpler and illuminating to consider a simpler problem - finding the minimum of a function.
Consider finding the minimum of a simple function f(x). If df/dx = 0, then the function is locally an extreme point of f(x), which could be a local minimum or a local maximum depending on the sign of the second derivative.
However the existence of a local minimum does not guarantee that that minimum is a global minimum. The local minimum is only a minimum for points "near" x. You actually need to compute f(x) at all points where df/dx = 0 to determine the global minimum. (You also need to address what happens at the two limits as x approaches +/- infinity, for that matter.)
Satisfying the Euler-Lagrange equations (or the geodesic equations) is equivalent to saying that df/dx = 0 in the function minimizing problem. It generates a local extreme point, and we can say that curves "near" the solution of the Euler-Lagrange equations will be local extreme points, but it does not guarantee that a specific solution will be the global maximum (or minimum) anymore than saying that df/dx = 0 will guarantee that a local max or min is a global max or min.
To guarantee that one has the absolute best maximum (or minimum), one must consider all of the extreme points (functions).
In flat space there is only one straight line connecting two points, but this is not true in general. When there is more than one straight line connecting two points, one must evaluate all of them before making any global statements.
This is probably not the only issue bothering you - your other issue is related to Mach's principle, IMO. But that's a separate issue. I think we need to take care of this one, first.