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Vietoris–Rips complex

Vietoris–Rips complex 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 Vietoris–Rips complex rather than just read about it. In short: In topology, the Vietoris–Rips complex, also called the Vietoris complex or Rips complex, is a way of forming a topological space from distances in a set of points. It is an abstract simplicial complex that can be defined from any metric space M and distance δ by forming a simplex for every finite set of points that has diameter no more than δ.

Vietoris–Rips complex — main illustration
Vietoris–Rips complex — illustration

Key takeaways

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

Reference excerpt

In topology, the Vietoris–Rips complex, also called the Vietoris complex or Rips complex, is a way of forming a topological space from distances in a set of points. It is an abstract simplicial complex that can be defined from any metric space M and distance δ by forming a simplex for every finite set of points that has diameter no more than δ. That is, it is a family of finite subsets of M, in which we think of a subset of k points as forming a (k − 1)-dimensional simplex (an edge for two points, a triangle for three points, a tetrahedron for four points, etc.); if a finite set S has the property that the distance between every pair of points in S is at most δ, then we include S as a simplex in the complex.

History The Vietoris–Rips complex was originally called the Vietoris complex, for Leopold Vietoris, who introduced it as a means of extending homology theory from simplicial complexes to metric spaces. After Eliyahu Rips applied the same complex to the study of hyperbolic groups, its use was popularized by Mikhail Gromov (1987), who called it the Rips complex. The name "Vietoris–Rips complex" is due to Jean-Claude Hausmann (1995).

Relation to Čech complex The Vietoris–Rips complex is closely related to the Čech complex (or nerve) of a set of balls, which has a simplex for every finite subset of balls with nonempty intersection. In a geodesically convex space Y, the Vietoris–Rips complex of any subspace X ⊂ Y for distance δ has the same points and edges as the Čech complex of the set of balls of radius δ/2 in Y that are centered at the points of X. However, unlike the Čech complex, the Vietoris–Rips complex of X depends only on the intrinsic geometry of X, and not on any embedding of X into some larger space. As an example, consider the uniform metric space M3 consisting of three points, each at unit distance from each other. The Vietoris–Rips complex of M3, for δ = 1, includes a simplex for every subset of points in M3, including a triangle for M3 itself. If we embed M3 as an equilateral triangle in the Euclidean plane, then the Čech complex of the radius-1/2 balls centered at the points of M3 would contain all other simplexes of the Vietoris–Rips complex but would not contain this triangle, as there is no point of the plane contained in all three balls. However, if M3 is instead embedded into a metric space that contains a fourth point at distance 1/2 from each of the three points of M3, the Čech complex of the radius-1/2 balls in this space would contain the triangle. Thus, the Čech complex of fixed-radius balls centered at M3 differs depending on which larger space M3 might be embedded into, while the Vietoris–Rips complex remains unchanged. If any metric space X is embedded in an injective metric space Y, the Vietoris–Rips complex for distance δ and X coincides with the Čech complex of the balls of radius δ/2 centered at the points of X in Y. Thus, the Vietoris–Rips complex of any metric space M equals the Čech complex of a system of balls in the tight span of M.

Relation to hyperbolic groups

Equipped with the word metric relative to a generating set, a finitely generated group G is a metric space. The associated Vietoris-Rips complex is a finite-dimensional locally finite simplicial complex on which G acts geometrically, i.e. properly discontinuously and with compact quotient. This action is faithful, with finite stabilizers. Moreover, if G is torsion-free, the action if free. When G is hyperbolic, for δ large enough the associated Vietoris-Rips complex is contractible. This implies that the group is of type F∞, is finitely presented and of finite cohomological dimension.

Relation to unit disk graphs and clique complexes The Vietoris–Rips complex for δ = 1 contains an edge for every pair of points that are at unit distance or less in the given metric space. As such, its 1-skeleton is the unit disk graph of its points. It contains a simplex for every clique in the unit disk graph, so it is the clique complex or flag complex of the unit disk graph. More generally, the clique complex of any graph G is a Vietoris–Rips complex for the metric space having as points the vertices of G and having as its distances the lengths of the shortest paths in G.

Other results If M is a closed Riemannian manifold, then for sufficiently small values of δ the Vietoris–Rips complex of M, or of spaces sufficiently close to M, is homotopy equivalent to M itself. Chambers, Erickson & Worah (2008) describe efficient algorithms for determining whether a given cycle is contractible in the Rips complex of any finite point set in the Euclidean plane.

Applications As with unit disk graphs, the Vietoris–Rips complex has been applied in computer science to model the topology of ad hoc wireless communication networks. One advantage of the Vietoris–Rips complex in this application is that it can be determined only from the distances between the communication nodes, without having to infer their exact physical locations. A disadvantage is that, unlike the Čech complex, the Vietoris–Rips complex does not directly provide information about gaps in communication coverage, but this flaw can be ameliorated by sandwiching the Čech complex between two Vietoris–Rips complexes for different values of δ. An implementation of Vietoris–Rips complexes can be found in the TDAstats R package. Vietoris–Rips complexes have also been applied for feature-extraction in digital image data; in this application, the complex is built from a high-dimensional metric space in which the points represent low-level image features. The collection of all Vietoris–Rips complexes is a commonly applied construction in persistent homology and topological data analysis, and is known as the Rips filtration.

Notes

References

Illustrations

Vietoris–Rips complex: A Vietoris–Rips complex of a set of 23 points in the Euclidean plane. This complex has sets of up to four points: the points themselves (shown as red circles), pairs of points (black edges), triples of points (pale blue triangles), and quadruples of points (dark blue tetrahedrons).
A Vietoris–Rips complex of a set of 23 points in the Euclidean plane. This complex has sets of up to four points: the points themselves (shown as red circles), pairs of points (black edges), triples of points (pale blue triangles), and quadruples of points (dark blue tetrahedrons).
Vietoris–Rips complex: The Vietoris-Rips complex of 
  
    
      
        
          Z
        
        ,
        {
        −
        1
        ,
        +
        1
        }
      
    
    {\displaystyle \mathbb {Z} ,\{-1,+1\}}
  
, with 
  
    
      
        δ
        =
        2
      
    
    {\displaystyle \delta =2}
The Vietoris-Rips complex of Z , { − 1 , + 1 } {\displaystyle \mathbb {Z} ,\{-1,+1\}} , with δ = 2 {\displaystyle \delta =2}

Worked examples

Example 1 — a first encounter with Vietoris–Rips complex

Start with the simplest possible case. Write down what Vietoris–Rips complex 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 Vietoris–Rips complex 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 Vietoris–Rips complex 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 Vietoris–Rips complex

In research
Vietoris–Rips complex 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 Vietoris–Rips complex 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
Vietoris–Rips complex is common in secondary-school and first-year university syllabi. It links to neighbouring topics Algebraic topology, Geometric graph theory, Simplicial sets, so understanding it makes those chapters shorter.
In everyday life
Look for Vietoris–Rips complex 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 Vietoris–Rips complex in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Vietoris–Rips complex 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 Vietoris–Rips complex out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Vietoris–Rips complex in simple terms?

In topology, the Vietoris–Rips complex, also called the Vietoris complex or Rips complex, is a way of forming a topological space from distances in a set of points. It is an abstract simplicial complex that can be defined from any metric space M and distance δ by forming a simplex for every finite…

Why does Vietoris–Rips complex 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 Vietoris–Rips complex?

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 Vietoris–Rips complex.

Tags

  • Algebraic topology
  • Geometric graph theory
  • Simplicial sets

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