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Hilbert metric

Hilbert metric is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Hilbert metric rather than just read about it. In short: In mathematics, the Hilbert metric, also known as the Hilbert projective metric, is an explicitly defined distance function on a bounded convex subset of the n-dimensional Euclidean space Rn. It was introduced by David Hilbert (1895) as a generalization of Cayley's formula for the distance in the Cayley–Klein model of hyperbolic geometry, where the convex set is the n-dimensional open unit ball.

Key takeaways

  • Hilbert metric belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Hilbert metric to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Hilbert metric from memory before moving on to harder problems.

Reference excerpt

In mathematics, the Hilbert metric, also known as the Hilbert projective metric, is an explicitly defined distance function on a bounded convex subset of the n-dimensional Euclidean space Rn. It was introduced by David Hilbert (1895) as a generalization of Cayley's formula for the distance in the Cayley–Klein model of hyperbolic geometry, where the convex set is the n-dimensional open unit ball. Hilbert's metric has been applied to Perron–Frobenius theory and to constructing Gromov hyperbolic spaces.

Definition Let Ω be a convex open domain in a Euclidean space that does not contain a line. Given two distinct points A and B of Ω, let X and Y be the points at which the straight line AB intersects the boundary of Ω, where the order of the points is X, A, B, Y. Then the Hilbert distance d(A, B) is the logarithm of the cross-ratio of this quadruple of points:

d ( A , B ) = log ⁡ ( | Y A | | Y B | | X B | | X A | ) . {\displaystyle d(A,B)=\log \left({\frac {|YA|}{|YB|}}{\frac {|XB|}{|XA|}}\right).}

The function d is extended to all pairs of points by letting d(A, A) = 0 and defines a metric on Ω. If one of the points A and B lies on the boundary of Ω then d can be formally defined to be +∞, corresponding to a limiting case of the above formula when one of the denominators is zero. A variant of this construction arises for a closed convex cone K in a Banach space V (possibly, infinite-dimensional). In addition, the cone K is assumed to be pointed, i.e. K ∩ (−K) = {0} and thus K determines a partial order ≤ K {\displaystyle \leq _{K}} on V. Given any vectors v and w in K ∖{0}, one first defines

M ( v / w ) = inf { λ : v ≤ K λ w } , m ( v / w ) = sup { μ : μ w ≤ K v } . {\displaystyle M(v/w)=\inf\{\lambda :v\leq _{K}\lambda w\},\quad m(v/w)=\sup\{\mu :\mu w\leq _{K}v\}.}

The Hilbert pseudometric on K ∖{0} is then defined by the formula

d ( v , w ) = log ⁡ M ( v / w ) m ( v / w ) . {\displaystyle d(v,w)=\log {\frac {M(v/w)}{m(v/w)}}.}

It is invariant under the rescaling of v and w by positive constants and so descends to a metric on the space of rays of K, which is interpreted as the projectivization of K (in order for d to be finite, one needs to restrict to the interior of K). Moreover, if K ⊂ R × V is the cone over a convex set Ω,

K = { ( t , t x ) : t ∈ R , x ∈ Ω } , {\displaystyle K=\{(t,tx):t\in \mathbb {R} ,x\in \Omega \},}

then the space of rays of K is canonically isomorphic to Ω. If v and w are vectors in rays in K corresponding to the points A, B ∈ Ω then these two formulas for d yield the same value of the distance.

Examples In the case where the domain Ω is a unit ball in Rn, the formula for d coincides with the expression for the distance between points in the Cayley–Klein model of hyperbolic geometry, up to a multiplicative constant. If the cone K is the positive orthant in Rn then the induced metric on the projectivization of K is often called simply Hilbert's projective metric. This cone corresponds to a domain Ω which is a regular simplex of dimension n − 1.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Hilbert metric

Start with the simplest possible case. Write down what Hilbert metric claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Hilbert metric before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Hilbert metric ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Hilbert metric

In research
Hilbert metric appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Hilbert metric in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Hilbert metric is common in secondary-school and first-year university syllabi. It links to neighbouring topics Metric geometry, so understanding it makes those chapters shorter.
In everyday life
Look for Hilbert metric outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Hilbert metric in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Hilbert metric means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Hilbert metric out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Hilbert metric in simple terms?

In mathematics, the Hilbert metric, also known as the Hilbert projective metric, is an explicitly defined distance function on a bounded convex subset of the n-dimensional Euclidean space Rn. It was introduced by David Hilbert (1895) as a generalization of Cayley's formula for the distance in the C…

Why does Hilbert metric matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Hilbert metric?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Hilbert metric.

Tags

  • Metric geometry

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