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Atlas / Mathematics / The Geometry Thread

Field · Emerged 1854

Riemannian Geometry

What is geometry when a space is known only from the inside, in any number of dimensions?

4 chapters4 min read6 turning points1 open problem

Branched from
Differential Geometry of Surfaces + Non-Euclidean Geometry
Branched into
Geometric Analysis + Geometric Topology
Figures
Bernhard Riemann, Gregorio Ricci-Curbastro, Tullio Levi-Civita, Sumner Myers, John Nash, Richard Hamilton

In brief

Riemannian geometry studies spaces of any number of dimensions that are curved from the inside, with no surrounding space for them to bend in. A space is given only by a rule for measuring tiny distances at each point. Everything else (straight lines, angles, areas, curvature) is derived from that rule.

It is the geometry of Einstein's gravity, where spacetime itself is curved, and it is the common setting for most of modern geometry. Euclid's flat space, the sphere and the hyperbolic plane all become special cases of one framework.

Key ideas

ManifoldEnters 1854 (published 1868)

A space that looks like ordinary Rn\mathbb{R}^n up close but may be curved or closed up overall, the way the Earth's surface looks flat locally.

MetricEnters 1854 (published 1868)

The rule ds2=∑gij dxidxjds^2 = \sum g_{ij}\,dx^i dx^j for measuring small lengths at each point. A Riemannian manifold is a manifold together with a metric, and all of its geometry flows from gijg_{ij}.

Parallel transportEnters 1917

A way of carrying a direction along a path without turning it. Around a closed loop in a curved space, it comes back rotated, and that rotation is what curvature is.

Sectional curvature

The Gaussian curvature of a two-dimensional slice through a point. In higher dimensions, curvature is a whole family of numbers, one for each such slice.

Ricci curvatureEnters 1900

An average of sectional curvatures, measuring how the volume of a small ball deviates from flat space. It is the curvature in Einstein's field equations, and the one that Ricci flow evolves.

Chapter I

A Lecture at the Seam

On 10 June 1854, the young Bernhard Riemann gave the qualifying lecture that would let him teach at Göttingen. Candidates proposed three topics and the faculty chose one. Gauss, then 77, skipped the two safe topics and picked the third: the foundations of geometry.

Riemann's answer used almost no formulas. A space, he proposed, is a manifold of any number of dimensions, and its geometry is given by a rule for measuring small lengths at each point:

ds2=∑i,jgij(x) dxi dxj.ds^2 = \sum_{i,j} g_{ij}(x)\,dx^i\,dx^j .

This is exactly Gauss's first fundamental form, freed from surfaces and from two dimensions. It is also free of any surrounding space: the metric gijg_{ij} is all there is. From it, Riemann defined a curvature at every point and in every two-dimensional direction.

This is why the field has two parents. From differential geometry it took the intrinsic viewpoint: geometry measured from inside. From non-Euclidean geometry it took the lesson that flatness is a choice, not a law. Spaces of constant curvature cover all three classical geometries in one family: zero curvature for Euclid, positive for the sphere, negative for Lobachevsky and Bolyai. Riemann even suggested that the geometry of physical space was a question for physics.

The lecture was published only in 1868, two years after his death. By then Beltrami had shown hyperbolic geometry to be consistent, and readers were ready for it.

Chapter II

The Calculus of Tensors

Riemann's sketch needed machinery. Elwin Christoffel supplied part of it in 1869. Gregorio Ricci-Curbastro and Tullio Levi-Civita supplied the rest in 1900, with their absolute differential calculus, now called tensor calculus. It makes it possible to write geometric statements that remain true whatever coordinates are chosen. In 1917 Levi-Civita added parallel transport: a way of carrying a direction along a curve in a curved space.

The payoff arrived from outside mathematics. Einstein spent years learning this calculus, with help from his friend Marcel Grossmann, to write general relativity (1915). In it, gravity is the curvature of a four-dimensional Riemannian-type spacetime. That link between a mathematical turning point and a physical one is exactly the kind of connection this atlas draws between its maths and physics maps.

Chapter III

A Closer Look: An Arrow That Comes Back Rotated

Curvature in any dimension can be detected by parallel transport, carrying a direction along a path without ever turning it. Try it on a sphere of radius RR.

Stand at the North Pole holding an arrow pointing along a line of longitude towards Africa. Walk straight down that meridian to the equator, keeping the arrow pointing "south", straight ahead. At the equator turn left and walk a quarter of the way round the globe, not rotating the arrow at all: it now points sideways, perpendicular to your path. Then walk straight back up to the pole along the new meridian. The arrow never turned, yet at the pole it points in a direction 90°90° away from where it started.

The rotation measures the curvature enclosed by the loop. The triangle you walked covers one eighth of the sphere, an area of 4πR28=πR22\frac{4\pi R^2}{8} = \frac{\pi R^2}{2}, and

rotation angle=K×Area=1R2⋅πR22=π2,\text{rotation angle} = K \times \text{Area} = \frac{1}{R^2} \cdot \frac{\pi R^2}{2} = \frac{\pi}{2} ,

exactly a right angle. On a flat plane the arrow would return unrotated. The same idea works in any dimension and needs no surrounding space. Levi-Civita's parallel transport is how curvature is defined in Riemannian geometry, and in general relativity it is how gravity turns the axis of a gyroscope orbiting the Earth, an effect measured by the Gravity Probe B satellite.

Chapter IV

Curvature and Shape

The twentieth century asked how local curvature constrains global shape. If a space is positively curved everywhere, must it be small and closed, like a sphere? If it is negatively curved, must it be large and open? Theorems of this kind, from Hadamard, Cartan and Hopf onward, made up comparison geometry. A landmark came in 1941, when Sumner Myers proved that a complete space whose Ricci curvature stays above a positive constant must close up on itself, with a bounded diameter, just as a sphere does.

Two results changed the field's footing. In 1956 John Nash proved that every Riemannian manifold can be placed isometrically in some Euclidean space. Riemann's abstraction had lost nothing, since every intrinsic geometry does occur on some concrete shape, in enough dimensions. In 1982 Richard Hamilton introduced the Ricci flow:

∂gij∂t=−2Rij.\frac{\partial g_{ij}}{\partial t} = -2R_{ij} .

It lets a metric evolve over time, smoothing out its bumps the way heat flow evens out temperature. Hamilton's hope was that any three-dimensional space would flow toward a perfectly uniform geometry, which would reveal its topology. The flow could develop singularities, places where it pinches and breaks down, and getting past them took another twenty years. That story continues in geometric topology.

Applications

Where it is used

  • Relativity and GPS↗ Physics · General Relativity

    Gravity is curvature, and satellites notice

    General relativity describes gravity as the curvature of a four-dimensional spacetime with a Riemannian-type metric. It is not only theory. GPS satellite clocks run about 38 microseconds per day fast relative to clocks on the ground: roughly +45 from weaker gravity, minus 7 from orbital speed. Without correcting for it, positions would drift by kilometres within a day.

    › Sources (1)
  • Machine learning

    Information geometry and the natural gradient

    The set of all probability distributions in a statistical model forms a manifold, with a natural Riemannian metric (the Fisher information). Following gradients in that metric rather than in flat coordinates, the natural gradient, makes learning algorithms insensitive to how a model happens to be parametrised.

    › Sources (1)
    • Amari, S. (1998). Natural gradient works efficiently in learning. Neural Computation 10(2): 251–276.
  • Medical imaging↗ Biology

    Averaging diffusion tensors in brain scans

    Diffusion tensor MRI records, at every point of the brain, a positive-definite matrix describing how water diffuses along nerve fibres. Those matrices form a curved space. Averaging or interpolating them with a Riemannian metric instead of naively avoids artefacts and keeps them physically valid.

    › Sources (1)
    • Pennec, X., Fillard, P. & Ayache, N. (2006). A Riemannian framework for tensor computing. International Journal of Computer Vision 66(1): 41–66.

Open problems

Where the map runs out

Open

The Hopf conjecture on S2×S2S^2 \times S^2

Open as of 2026.

Heinz Hopf asked in the 1930s whether S2×S2S^2 \times S^2, the product of two ordinary spheres, can be given a metric of strictly positive sectional curvature. That would mean it curves "like a sphere" in every two-dimensional direction at every point. The obvious product metric fails: planes that mix the two factors have curvature exactly zero.

Why it is hard

Very few compact spaces with positive curvature are known at all, and almost no general methods produce new ones. Small perturbations of the product metric cannot make every mixed plane positive at once. At the same time, no known obstruction rules it out, because the space passes every test anyone has thought of.

What resolving it unlocks

Either answer would sharpen what positive curvature forces on the shape of a space, one of the central themes of the field. A "no" would supply a new obstruction. A "yes" would supply a new construction method, and possibly many new examples.

› Sources (1)
  • Berger, M. (2003). A Panoramic View of Riemannian Geometry. Springer.

Further reading

  1. Lee, J. M. (2018). Introduction to Riemannian Manifolds (2nd ed.). Springer.

    A clear modern textbook, from the definitions through the major comparison theorems.

  2. do Carmo, M. P. (1992). Riemannian Geometry. Birkhäuser.

    A compact classic, the natural sequel to do Carmo's book on curves and surfaces.

  3. Berger, M. (2003). A Panoramic View of Riemannian Geometry. Springer.

    A survey of the whole field's landscape, results and open problems, with few proofs. Best for orientation.