synthetic differential geometry
Introductions
from point-set topology to differentiable manifolds
geometry of physics: coordinate systems, smooth spaces, manifolds, smooth homotopy types, supergeometry
Differentials
Tangency
The magic algebraic facts
Theorems
Axiomatics
(shape modality $\dashv$ flat modality $\dashv$ sharp modality)
$(ʃ \dashv \flat \dashv \sharp )$
dR-shape modality$\dashv$ dR-flat modality
$ʃ_{dR} \dashv \flat_{dR}$
(reduction modality $\dashv$ infinitesimal shape modality $\dashv$ infinitesimal flat modality)
$(\Re \dashv \Im \dashv \&)$
fermionic modality$\dashv$ bosonic modality $\dashv$ rheonomy modality
$(\rightrightarrows \dashv \rightsquigarrow \dashv Rh)$
\array{ && id &\dashv& id \ && \vee && \vee \ &\stackrel{fermionic}{}& \rightrightarrows &\dashv& \rightsquigarrow & \stackrel{bosonic}{} \ && \bot && \bot \ &\stackrel{bosonic}{} & \rightsquigarrow &\dashv& Rh & \stackrel{rheonomic}{} \ && \vee && \vee \ &\stackrel{reduced}{} & \Re &\dashv& \Im & \stackrel{infinitesimal}{} \ && \bot && \bot \ &\stackrel{infinitesimal}{}& \Im &\dashv& \& & \stackrel{\text{étale}}{} \ && \vee && \vee \ &\stackrel{cohesive}{}& ʃ &\dashv& \flat & \stackrel{discrete}{} \ && \bot && \bot \ &\stackrel{discrete}{}& \flat &\dashv& \sharp & \stackrel{continuous}{} \ && \vee && \vee \ && \emptyset &\dashv& \ast }
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Models
Models for Smooth Infinitesimal Analysis
smooth algebra ($C^\infty$-ring)
formal smooth ∞-groupoid?
differential equations, variational calculus
Chern-Weil theory, ∞-Chern-Weil theory
Cartan geometry (super, higher)
An isometry is a function that preserves a metric, either in the sense of a metric space or in the sense of a Riemannian manifold.
An isometry $f\colon (X,d) \to (X',d')$ between metric spaces is a function $f\colon X \to X'$ between the underyling sets that respects the metrics in that $d = f^* d'$. More explicitly, $d'(f(a),f(b)) = d(a,b)$ for any points $a,b$ in $X$.
The same idea holds for extended quasi-pseudo-generalisations of metric spaces.
An isometry $f\colon (X,g) \to (X',g')$ between Riemannian manifolds is a morphism $f\colon X \to X'$ between the underlying manifolds that respects the metrics in that $g = f^* g'$. More explicitly, $g'(f_*v,f_*w) = g(v,w)$ for any tangent vectors $v,w$ on $X$.
Global isometries are the isomorphisms of metric spaces or Riemannian manifolds. An isometry is global if it is a bijection whose inverse is also an isometry. Between metric spaces, isometries are necessarily injections and bijective isometries necessarily have isometries as inverses, so global isometries between metric spaces are also called surjective isometries; this does not work for Riemannian manifolds (where the inverse of an isometry need not be a morphism of manifolds), nor does it work for pseudometric spaces (where an isometry need not be injective).
In practice, isometries $E \to F$ between normed vector spaces tend to be affine maps. The following theorem gives a precise meaning to this.
A norm on a vector space is strictly convex if, whenever ${\|u\|} = 1 = {\|v\|}$, we have ${\|t u + (1-t)v\|} \lt 1$ for some (hence all!) $t$ in the range $0 \lt t \lt 1$. In brief, no sphere contains a line segment. Examples of strictly convex spaces include spaces of type $L^p$ for $1 \lt p \lt \infty$.
Let $f \colon E \to F$ an isometry between normed vector spaces, and suppose $F$ is strictly convex. Then $f$ is affine.
To say that $f \colon E \to F$ is affine means that $f$ preserves linear combinations of the form $t x + (1-t)y$. It suffices to consider only the case where $0 \lt t \lt 1$ and, by continuity considerations, only the case of dyadic rationals between $0$ and $1$. Continuing this train of thought, it suffices to prove that $f(\frac1{2}(x + y)) = \frac1{2}(f(x) + f(y))$ for all $x, y$.
In the case of strict convexity, midpoints $\frac1{2}(u+v)$ are determined in terms of the norm, as the unique point $w$ such that
The midpoint satisfies these equations for any normed vector space, but the uniqueness is a consequence of strict convexity. For if there were two such points $w, w'$, then for some point $w''$ on the line segment between them, we would have ${\|w'' - u\|} \lt \frac1{2}{\|u-v\|}$, and ${\|w''-v\|} \leq \frac1{2}{\|u-v\|}$ by ordinary convexity. But these two inequalities taken together would violate the triangle inequality.
As a result, since $f$ is an isometry, $w = f(\frac1{2}(x+y))$ is forced to be the midpoint between $f(x)$ and $f(y)$ if $F$ is strictly convex. This completes the proof.
If $F$ is not strictly convex, then isometries need not be affine. For example, consider $E = \mathbb{R}$, and $F = \mathbb{R}^2$ equipped with the $l_\infty$ (max) norm. For any contractive map $\phi \colon \mathbb{R} \to \mathbb{R}$, e.g., any smooth function with ${|\phi'|} \leq 1$, the map $E \to F$ sending $x$ to $(x, \phi(x))$ is easily seen to be an isometry.
If however $f$ is a surjective isometry between normed vector spaces, then $f$ is affine, by the Mazur-Ulam theorem.
Last revised on December 11, 2017 at 11:24:58. See the history of this page for a list of all contributions to it.