Abstract

We prove a complexity classification for Holant problems defined by an arbitrary set of complex-valued symmetric constraint functions on Boolean variables. This is to specifically answer the question: Is the Fisher-Kasteleyn-Temperley (FKT) algorithm under a holographic transformation (Valiant, SIAM J. Comput. 37(5), 1565–1594 2008) a universal strategy to obtain polynomial-time algorithms for problems over planar graphs that are intractable on general graphs? There are problems that are #P-hard on general graphs but polynomial-time solvable on planar graphs. For spin systems (Kowalczyk 2010) and counting constraint satisfaction problems (#CSP) (Guo and Williams, J. Comput. Syst. Sci. 107, 1–27 2020), a recurring theme has emerged that a holographic reduction to FKT precisely captures these problems. Surprisingly, for Holant, we discover new planar tractable problems that are not expressible by a holographic reduction to FKT. In particular, a straightforward formulation of a dichotomy for planar Holant problems along the above recurring theme is false. A dichotomy theorem for #CSPd, which denotes #CSP where every variable appears a multiple of d times, has been an important tool in previous work. However the proof for the #CSPd dichotomy violates planarity, and it does not generalize to the planar case easily. In fact, due to our newly discovered tractable problems, the putative form of a planar #CSPd dichotomy is false when d ≥ 5. Nevertheless, we prove a dichotomy for planar #CSP2. In this case, the putative form of the dichotomy is true. (This is presented in Part II of the paper.) We manage to prove the planar Holant dichotomy relying only on this planar #CSP2 dichotomy, without resorting to a more general planar #CSPd dichotomy for d ≥ 3. A special case of the new polynomial-time computable problems is counting perfect matchings (#PM) over k-uniform hypergraphs when the incidence graph is planar and k ≥ 5. The same problem is #P-hard when k = 3 or k = 4, which is also a consequence of our dichotomy. When k = 2, it becomes #PM over planar graphs and is tractable again. More generally, over hypergraphs with specified hyperedge sizes and the same planarity assumption, #PM is polynomial-time computable if the greatest common divisor (gcd) of all hyperedge sizes is at least 5. It is worth noting that it is the gcd, and not a bound on hyperedge sizes, that is the criterion for tractability.

Highlights

  • The Fisher-Kasteleyn-Temperley (FKT) algorithm [29, 30, 41] is a classical gem that counts perfect matchings over planar graphs in polynomial time. This was an important milestone in a decades-long research program by physicists in statistical mechanics to determine what is known as Exactly Solved Models [3, 28,29,30, 33,34,35, 39, 41, 49,50,51]

  • The FKT algorithm stood as the polynomial-time algorithm for any counting problem over planar graphs that is #P-hard over general graphs

  • For a wide variety of problems, such as those expressible as a #CSP, holographic reductions to the FKT algorithm is a universal technique for turning problems that are #P-hard in general to P-time solvable over planar graphs

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Summary

Introduction

The Fisher-Kasteleyn-Temperley (FKT) algorithm [29, 30, 41] is a classical gem that counts perfect matchings over planar graphs in polynomial time. For a wide variety of problems, such as those expressible as a #CSP, holographic reductions to the FKT algorithm is a universal technique for turning problems that are #P-hard in general to P-time solvable over planar graphs. Some natural problems, such as counting perfect matchings (#PM), are not expressible as a point on the Tutte polynomial or a #CSP, and #PM is provably not expressible within the special case of vertex assignment models [23, 24, 40] This is the problem for which FKT was designed, and is the basis of Valiant’s matchgates and holographic reductions. If we go back to the #CSP setting, holographic algorithms with matchgates become universal again [8], despite the fact that it is designed for the Holant setting This generalizes the previous classification theorem [26] from symmetric constraint functions to general (not necessarily symmetric) constraint functions. Partial results have been obtained for Holantc problems [2] or Holant problems with non-negatively weighted signatures [36]

Problems and Definitions
Holographic Reduction
Counting Constraint Satisfaction Problems
Realization
Tractable Signature Sets
Some Known Dichotomies
Redundant Signature Matrices and Related Hardness Results
Characterization of A - and P-transformable Signatures
Characterization of M -transformable Signatures
Mixing with Vanishing Signatures
Related Lemmas
Single Signature Dichotomy
Lemmas Applied to Non-Degenerate Signatures in the Inductive Step
Lemmas Applied to Degenerate Signatures in the Inductive Step
Proof of the Single Signature Dichotomy
Mixing P2 and M4—Equalities and Matchgates in the Z Basis
Lemmas Related to M4 and P2
11 Dichotomy Theorem when F Contains an Odd Arity Signature
If x y
13 An Application of Cyclotomic Field
14 No-Mixing of a Pair of Signatures of Even Arity
15 No-Mixing of Even Arity Signature Set
We already have
16 Dichotomy Theorem for an Even-Arity Signature
Full Text
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