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Classical Potts random clusters and planar loop transfer
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Categories, Functors and Natural Transformations
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Connectedness
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Countability and Uncountability
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Free Modules, Exact Sequences, Projective and Injective Modules
- Graphs, Walks and Connectivity
- Limits of Real Functions
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Metric Spaces
- Modules, Submodules, Quotient Modules and the Isomorphism Theorems
- Monoidal Categories and Monoidal Functors
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- Plane Graphs, Euler's Formula and the Five Colour Theorem
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Subspaces, Products, and Quotients
- Suprema and Infima
- Temperley–Lieb Diagram Algebra and Catalan Basis
- Tensor Products of Modules
- The Topology of Euclidean Space
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Trees, Forests and Spanning Trees
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
3 · Logical flowchart
4 · Definitions, postulates, theorems and proofs
Finite Potts and Fortuin–Kasteleyn weights
Definition
Let be a finite simple graph, so is finite and is a set of two-element subsets of . Fix an integer , write , and assign to each edge a finite activity . A spin configuration is a function . Its unnormalized Potts weight and partition function are For , let , and let be its number of connected components, counting isolated vertices; equivalently, these are the equivalence classes generated by the endpoint pairs of edges in . Put , with empty product . The unnormalized Fortuin–Kasteleyn (FK) weight and partition function are Both normalizers are finite and positive: the spin sum is finite with every term at least , while the empty-edge FK term is . These are finite mathematical weights; no physical units or empirical status are assigned.
Finite Edwards–Sokal coupling and correlation identity
Statement
Let be a finite simple graph, let be an integer, and let each edge activity be finite and nonnegative. Use the Potts weight and FK weight from the finite definitions. Define The normalized joint law has Potts marginal and FK marginal , with . Conditional on an edge set of positive probability, the colors of its connected components are independent and uniform on . Thus for every , where means that and lie in the same component of .
Statement references
Facts & Assumptions
Given: A finite simple graph , integer , and finite activities .
Finite Potts and Fortuin–Kasteleyn weights: the spin weight is , the FK weight of is , and both finite normalizers are positive.
Proof
For fixed , summing over all chooses, independently for each edge, either its absent factor or its present factor . Distributivity of the finite product therefore gives . Summing this equality over the finite set gives .
Fix . The product is zero unless the spins agree across every edge in . Equality propagates along each finite path, so the admissible configurations are exactly those constant on each connected component of . Assigning one of colors independently to each of its components gives exactly such configurations, each with weight . Hence , including when this weight is zero. Summing over gives .
The common total is positive by [F1], so dividing by it defines a probability law. The finite marginal sums in steps 1.1 and 1.2 show that its spin and edge marginals are respectively and , and that .
For a fixed with positive FK probability, every spin assignment constant on its components has the same joint weight . By step 1.2 there are such assignments, so the conditional law is uniform on them; this is equivalent to assigning independent uniform colors to the components.
If are connected in , step 2.2 makes their colors equal with conditional probability . If they are in distinct components, their independent uniform colors agree with probability . Averaging over the FK marginal from step 2.1 yields .
Finite FK boundary wiring
Definition
Let be a finite simple graph, let be an integer, and give each edge a finite activity . Choose a set of boundary vertices and an equivalence relation on . The relation specifies which boundary vertices are identified before any edges are occupied. For , let be the least equivalence relation on containing every pair in and both endpoints of every edge in . Write and , with empty product . Define The free boundary choice is the discrete relation on (each boundary vertex is a singleton); the wired classes are the equivalence classes of , with a fully wired boundary given by one class when . Thus counts components after the prescribed identifications and occupied edges, including isolated vertices and boundary classes. The sum is finite and positive because its empty-edge term is . For discrete , and . This is a mathematical partition polynomial; no wired Potts spin marginal is asserted.
Definition references
Finite FK connectivity-state transfer
Definition
Input a finite simple graph , integer , finite activities , a total edge order , and boundary data consisting of a set and an equivalence relation on . The relation identifies prescribed boundary vertices before any edge is processed; its singleton classes give free boundary and its non-singleton classes give the wired classes. A vertex incident to no edge is isolated. Put . At time , the active frontier consists of the initially active boundary vertices together with vertices introduced at a processed edge, minus those already forgotten. A state is a set partition of the active frontier. Its blocks record equivalence generated by the initial boundary relation and processed present edges. A coefficient vector assigns a nonnegative real weight to each such partition.
Initialize the frontier as with partition and coefficient ; if , this is the empty partition. For , perform the following operations in order.
- Introduce each endpoint of that is not yet active as a singleton block.
- For each state of coefficient , add to the same state (the edge is absent) and add to (the edge is present), where and merges the blocks containing and and leaves all other blocks unchanged. If already share a block, . Thus and the edge operator is .
- Forget vertices whose last incident edge is . When removing a vertex empties its block, delete that block and multiply its coefficient by once; otherwise just remove the vertex from its block. If several vertices in a block are forgotten at this step, the factor is applied only when the last active member is removed.
After all edges are processed, forget any remaining active vertices by the same rule and return the coefficient of the empty partition. This includes boundary vertices with no incident edge; each surviving wired component is then counted once. Discrete gives free boundary, while non-singleton classes implement the stated wired boundary condition. A planar-strip annotation consists of a plane embedding, an ordered frontier list at every update, a noncrossing initial relation , and the condition that every reachable connectivity partition is noncrossing. For an ordered frontier, “noncrossing” means that no two different blocks contain alternating points with in one block and in the other. When are adjacent frontier points , write for ; these are the noncrossing connectivity states and adjacent-block joins used for planar transfer. The general procedure stores all set partitions when no such annotation is supplied. All arithmetic is exact; each input has finitely many edge updates and finitely many partitions at every frontier.
Definition references
Correctness of the finite FK connectivity transfer
Statement
For every finite simple graph , integer , finite activities , edge order, boundary set , and equivalence relation on , the finite FK connectivity-transfer procedure terminates after finitely many operations and returns exactly where counts equivalence classes generated by and the endpoint pairs of occupied edges. In the free case, where is discrete, by the finite Potts/FK definition, so the transfer returns the finite FK partition function exactly.
Statement references
Facts & Assumptions
Given: A finite simple graph , integer , finite activities , an ordered edge list , boundary set , and equivalence relation on .
Finite FK connectivity-state transfer: initialize the frontier with boundary partition and factor for each isolated vertex outside ; each edge branches into absent weight and present weight with the endpoint blocks merged; a block receives one factor when its last active vertex is forgotten, including at final cleanup.
Finite FK boundary wiring: is the number of equivalence classes generated by and the endpoints of edges in , and .
Finite Potts and Fortuin–Kasteleyn weights: when is discrete, and the resulting partition function is , including isolated vertices.
Proof
Let and let count vertices outside that are isolated in . For each edge subset , form the graph on the initially present boundary vertices and the endpoints introduced by time , impose , and retain the present edges in . Let be the resulting equivalence partition restricted to the active frontier, and let count its equivalence classes containing no active vertex. The coefficient vector after time satisfies At the only subset is empty, every boundary vertex is active, their partition is , and . The initialized coefficient is , so the invariant holds.
Assume the invariant after edges. Introducing a new endpoint as a singleton agrees with adding that previously unseen vertex to the partial graph; a boundary endpoint is already present in the initial relation . For each partial subset , the two subsets at the next edge are exactly and . The absent choice preserves the partition and weight; the present choice multiplies by and merges precisely the endpoint blocks. Thus gives the two required contributions, even when were already equivalent through or previous edges.
When vertices at their last incident edge are forgotten, no future edge is incident to them. If their block still has an active vertex, that equivalence class can connect to future edges through that vertex and is not yet closed. If removing a vertex empties its block, every boundary vertex in its -class was already initially active and is now absent as well; no future edge can meet any member of the class. The class is therefore final, and the algorithm multiplies by exactly once at this first emptying. This updates and preserves the invariant. After the last edge, terminal cleanup applies the same criterion to the remaining blocks, which have no future incident edges.
For each full present-edge subset , let be the number of blocks still active just before terminal cleanup. Every equivalence class generated by and is counted exactly once: isolated vertices outside contribute , classes closed earlier contribute , and the remaining blocks each contribute one factor in cleanup. Therefore , and summing the invariant from step 1.1 with these cleanup factors over gives the returned scalar .
Each of the finitely many edges is processed once; every active frontier is finite and has finitely many set partitions, and terminal cleanup removes finitely many vertices. Hence the procedure terminates. For discrete , [F3] identifies with .
Classical FK medial-loop normalization
Statement
Let be a finite connected simple plane graph, let be its face set, and choose its unbounded face as the free exterior face. All vertices are free: no boundary vertices are identified or fixed. Fix an integer and finite edge activities . For , write and let count its connected components, including isolated vertices. Let be the dual multigraph with one vertex for each face and one dual edge crossing each primal edge ; loops and parallel edges are retained. Set and let count the connected components of the spanning dual subgraph , counting isolated faces; the unbounded exterior face is one dual vertex counted once.
The medial graph has one four-valent vertex at each primal-dual edge crossing, joined along the corners of the overlay. At each crossing label the four medial half-edges in cyclic order, with on the primal-edge sides and on the dual-edge sides. For , smooth by the noncrossing pairs and ; for , smooth by and . Equivalently, these curves are the boundary of , formed from disjoint small vertex disks and narrow bands along the edges in . Define as the number of connected boundary loops of ; this also covers a one-vertex graph with no edges. No extra exterior wiring or boundary weight is imposed. Then The loop value is . This is a finite mathematical identity; it asserts no semisimplicity, representation faithfulness, trace, categorification, or empirical claim.
Statement references
Finite Potts and Fortuin–Kasteleyn weights
The plane dual multigraph, with a vertex for each face and one crossing edge for each primal edge
For a plane graph with components, , including the null graph
Temperley–Lieb planar diagram data and endomorphism modules
Stacking is associative and horizontal juxtaposition is strict monoidal
Every connected component of an open subset of is open and polygonally connected
Facts & Assumptions
Given: A finite connected simple plane graph , its fixed plane embedding, integer , finite activities , and free vertices and exterior face.
Finite Potts and Fortuin–Kasteleyn weights: is spanning, counts every component including isolated vertices, and .
Plane embeddings of finite simple graphs, their faces, facial boundary walks and lengths (counting a bridge twice), and planar graphs: a plane graph is a finite simple graph with polygonal edge arcs meeting only at shared endpoints; its faces are the regions of the complement.
The plane dual multigraph, with a vertex for each face and one crossing edge for each primal edge and Every connected plane graph has a plane dual multigraph, and when that dual is simple the reciprocal embedding identifies the double dual with the original graph: each face gives one dual vertex and every primal edge has one crossing dual edge, with loops and parallel edges allowed.
For a plane graph with components, , including the null graph: for a plane subgraph with components, , including isolated vertices and the null graph.
Temperley–Lieb planar diagram data and endomorphism modules: stacking places the left factor above the right factor; each closed cycle removed in a composition contributes the loop value .
Stacking is associative and horizontal juxtaposition is strict monoidal: these diagram compositions are well-defined and associative for every commutative coefficient ring and every .
Every connected component of an open subset of is open and polygonally connected (Every connected component of an open subset of is open and polygonally connected).
Proof
Fix . The drawing of is a finite union of points and closed line segments, hence is closed in . Its complement is open, so each of its face components is open and polygonally connected by [F7]. The original faces are vertices of . Two such faces lie in the same face of exactly when they are connected by dual edges corresponding to . A dual path crosses only absent primal edges and therefore stays in the complement of . Conversely, a path between two original face points inside one face of can be chosen polygonal; perturb its finitely many segments to avoid primal vertices and to cross edge interiors transversely. Because it avoids , every crossed edge lies in , so the crossed dual edges form a path in . Thus the faces of correspond bijectively to the components counted by .
Apply [F4] to the spanning plane subgraph . Its vertex set is , its edge set is , its component count is , and by step 1.1 its face count is . Therefore , or .
View the fixed embedding on the sphere by adding the point at infinity. By [F4] the plane subgraph has finitely many faces; choose one point in each. For every vertex , including each vertex isolated in , choose a closed polygonal disk so that the disks are pairwise disjoint and avoid all the chosen face points. Choose pairwise disjoint attachment intervals on each , one for each edge incident to and in the cyclic order of the embedding. For each , choose a closed polygonal rectangular band around the part of its polygonal arc outside its endpoint disks; make the bands pairwise disjoint, disjoint from all nonendpoint disks, and attach them to the corresponding intervals. These choices are possible with sufficiently small radii and widths because the graph is finite and edge arcs meet only at shared endpoints. Let be the union of these disks and bands. Each band joins exactly its two endpoint disks, and distinct bands otherwise remain disjoint, so the connected components of correspond exactly to those of , including isolated-vertex disks; hence there are . Its boundary is a finite disjoint union of simple polygonal circles. In particular, the one-vertex graph with no edges gives one disk and one boundary loop. At a primal-dual crossing, the two sides of an occupied-edge band join the medial half-edges as and ; when the edge is absent, there is no band there and the two face-side sectors join as and . The cyclic ordering of the attachment intervals fixes these local continuations, so gives exactly the smoothings in the Statement and has loops. Inside each face of , the disk-and-band pieces form collars along the facial boundary side occurrences: each band side is a polygonal strip, and intervening vertex-disk sectors join consecutive strips in cyclic order. Repeated vertices or edges in a facial boundary walk are treated as separate side occurrences, so a bridge's two sides remain distinct; an isolated vertex gives a punctured-disk collar in its unique incident face. Choose all radii and widths small enough that distinct collars meet only at their prescribed continuations within the same face. Trimming them leaves a nonempty core , since the selected point of lies outside . The core is connected: for finite points use the polygonal path in the plane face supplied by [F7], perturb the path to meet the finitely many polygonal collar sides transversely, and replace each excursion into a collar by a parallel path just outside along that collar's connected -facing boundary, with the vertex-disk sector prescribing the continuation at each turn. For the unbounded face, is bounded; outside a sufficiently large disk its complement contains the whole exterior, and a ray there joins finite points to the point at infinity in the one-point compactification. Thus the same connected core includes infinity. Each face therefore leaves exactly one nonempty component of . Since contains , these trimmed faces are all the components of ; by step 1.1 their number is . The regions of are the interiors of the components of together with those complementary components, so there are regions.
Subdivide each of the disjoint polygonal boundary loops from step 2.2 at at least three distinct points and regard the result as a finite simple plane graph , with one cycle component per loop. Each cycle has the same number of vertices and edges, so , and has connected components. By [F4], its complement therefore has regions. These are the regions counted in step 2.2, hence and .
Adding the identities in steps 2.1 and 3.1 yields . Since , its positive square root is nonzero, and . This equality also holds when an activity is zero, because both corresponding terms vanish.
Each subset selects exactly one of the two noncrossing smoothings at every medial vertex, so summing the termwise identity of step 4.1 over gives the displayed loop formula. In any fixed rectangular decomposition, the local smoothings are Temperley–Lieb diagrams; [F5] fixes the left-above-right and conventions, and [F6] makes the stacked product independent of parentheses. Thus the local loop weight is exactly , without invoking a trace or any representation-theoretic property.
Remarks
The local smoothing convention is shown below. The four ends are listed cyclically; are primal-side half-edges and are dual-side half-edges. The occupied pairing is used when and the absent pairing when . The crossing pairing is never used. The proof counts connected components and regions; it does not infer the partition identity from the picture.
The FK connectivity join in the transfer algorithm is an idempotent partition operation. It is not the Temperley–Lieb cup-cap generator, whose square contributes a factor .
5 · Examples, experiments and counterexamples
None yet.
Sources
- Geoffrey R. Grimmett, The Random-Cluster Model
- Hugo Duminil-Copin, Geometric Representations of Lattice Spin Models, Cours Peccot lecture notes
- Linnea Grans-Samuelsson, Lawrence Liu, Yifei He, Jesper Lykke Jacobsen, and Hubert Saleur, The action of the Virasoro algebra in the two-dimensional Potts and loop models at generic Q