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Composition of an edge system with an assignment tester
Definition
Fix a finite binary constraint graph over an alphabet of size , and form its blocks and ordered robust edge circuits using Shared codeword blocks and edge acceptance circuits. Each active vertex has a block , where . For an edge , let be its robust circuit, with its two formal input pieces and in the specified endpoint order.
Let be the deterministic two-piece assignment-tester construction of A two-piece constant-query PCP of proximity. Apply to with these two named input lists. Write its Boolean constraint system as , let be its named raw input variables, and put . The system has arity at most six; all variables in , including the verifier's external and private proof-table variables, are local auxiliary variables.
For every edge, is a positive integer. Indeed, gives , so this local instance has . In the construction in A two-piece constant-query PCP of proximity, the comparison family then has rows, and each of the nine test families is padded to rows. Thus . If the edge set is nonempty, set This is a well-defined positive integer because the edge set is finite and each . If , define to have no variables and no constraints.
Suppose . The output variable set consists of the active vertex blocks together with a fresh private copy of every for each edge . Map the first named piece of coordinatewise to and the second coordinatewise to . When is a loop, , so both formal pieces map coordinatewise to the same block. Map each auxiliary variable to its private copy . Call the resulting map on gadget variables . Thus endpoint bits are shared across all incident edge gadgets, while every other gadget variable is private to one edge.
For each ordered constraint , with , put exactly copies of in the output constraint list. The composition is the Boolean constraint system on the variables just described and the multiset union of these lists. It has arity at most six. Repetitions in tuples and duplicate constraints are retained, as allowed by Assignment tester and rejection ratio. Every edge contributes exactly constraints, so the total list has constraints.
For any labeling of the output variables, let be its pullback to along . Since duplicating every row of by the same factor preserves its violated fraction, for nonempty Conversely, any collection of local gadget labelings that agrees on every variable identification made by the maps , including the two formal pieces of a loop, combines into a unique output labeling, because all other variables have edge-private names. If the original graph is edgeless, the output has the empty constraint list and unsatisfiability zero under the empty-system convention of Assignment tester and rejection ratio.
Remarks
Dinur's §5.1 Definition 5.1 introduces edge circuits, shares their endpoint variables across assignment-tester outputs, keeps local auxiliary variables private, and assumes equal gadget constraint counts; Lemma 1.8 analyzes that composition. This definition uses the same sharing pattern with the local two-piece Boolean assignment tester and arity-six constraint systems. It achieves equal counts explicitly by taking the least common multiple of the positive finite gadget sizes. Arora–Barak Corollary 18.35 gives the qCSP view of a PCP of proximity, and the proof of Lemma 18.30 uses shared codeword blocks and edge-private proof variables. Those citations motivate this construction; its local assignment-tester properties are supplied by A two-piece constant-query PCP of proximity.
The construction is choice-free: the local tester and robust circuits are deterministic, and the least common multiple and all variable renamings are computed from finite explicit lists. No axiom of choice is used.
Depends on
Used by
Dependency tree · two levels
18 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Irit Dinur, The PCP Theorem by Gap Amplification, §5.1, Definition 5.1 (composition), Lemma 1.8 and its proof (standard reference, not scraped)
- Sanjeev Arora and Boaz Barak, Computational Complexity: A Modern Approach, §18.5.2, Corollary 18.35 and proof of Lemma 18.30 (standard reference, not scraped)