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V=12 Cuboctahedron. Images: A critical points scheme for Generating uniformly distributed points on a sphere
Author:
Roman Chijner
Topic:
Algebra
,
Calculus
,
Circle
,
Difference and Slope
,
Differential Calculus
,
Differential Equation
,
Equations
,
Optimization Problems
,
Geometry
,
Function Graph
,
Intersection
,
Linear Programming or Linear Optimization
,
Mathematics
,
Sphere
,
Surface
,
Vectors
A system of points on a sphere S of radius R “induces” on the sphere S
0
of radius R
0
three different sets of points, which are
geometric medians (GM)
-local
maxima
,
minima
and
saddle
points sum of distance function f(x). The angular coordinates of the spherical distribution of a system of points -
local minima
coincide with the original system of points.
Distribution of points Pi
,
test Point
,
Max
/
min
/
saddle
-
Critical points
on a sphere. Vectors ∇f and ∇g at these points. ● max Tetrakis hexahedron:
n=14
●
min Cuboctahedron:
n=12
●
sad Rhombicuboctahedron:
n=24
Distribution of points Pi
,
test Point
,
Max
/
min
/
saddle
-
Critical points
on a sphere. Vectors ∇f and ∇g at these points. ● max Tetrakis hexahedron:
n=14
●
min Cuboctahedron:
n=12
●
sad Rhombicuboctahedron:
n=24
Two-variable function f(φ,θ) over a rectangular region: - π ≤φ ≤ π; -π/2≤θ≤π/2.
Isolines and Intersection points of implicit functions over a rectangular region: - π ≤φ ≤ π; -π/2≤θ≤π/2.
Critical Points
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