How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
An exponential-size constant-query base assignment tester
Statement
There is an absolute constant with the following property. For every Boolean circuit with input coordinates, of which are named, and non-input gates over the basis of Boolean circuits: basis, fan-in, size, and depth, presented together with its input-coordinate list , the construction below produces a constraint system of arity at most over the fixed alphabet such that:
- (Input coordinates and size.) The variables of are the table coordinates of a table , the table coordinates of a table , with , together with the named coordinates ; the number of constraints is at most for a fixed polynomial , and the whole system is enumerated by a deterministic algorithm in time polynomial in that number, using no randomness and no choices.
- (Assignment tester.) is an assignment tester with alphabet , arity bound and rejection ratio in the sense of Assignment tester and rejection ratio: every accepted input extends to a labeling with , and for every and every labeling of the non-input variables, , where the input coordinates of the system are the named coordinates themselves.
Facts & Assumptions
Given: a Boolean circuit with inputs and non-input gates, its named input list , and the constants , , , .
The circuit yields, with the wire variables whose first entries are the named input coordinates, a list of equations with supported on coordinate pairs and with at most four nonzero coefficients each; a well-formed circuit with a designated output has ; for every input , accepts if and only if the system has a solution whose first coordinates are , in which case each solution is the evaluation assignment for some completion of the named inputs, unique once all input bits are fixed; if fails an equation then a uniform has with probability exactly , where and ; the construction is deterministic and polynomial time in the gate list (Circuit satisfiability becomes linear-quadratic consistency).
The BLR rejection probability of a table equals the fraction of violated linearity constraints of its Hadamard system and is at least its distance from the nearest linear function, with no restriction on the acceptance probability; if that distance is less than the nearest linear function is unique (BLR rejection is proportional to distance from linearity, The BLR linearity test over F_2, Pointwise correctness under less than quarter noise).
The ideal tensor test and its self-corrected implementation use three and six table queries respectively; if and are at distances from the linear tables and and , the self-corrected test rejects with probability at least (Quadratic tensor consistency test, Quadratic tensor test rejects an inconsistent tensor).
A two-query self-correction of a table at distance from a linear function returns at the requested point with probability at least (Pointwise correctness under less than quarter noise, Two-query linear self-correction).
A map from circuits to constraint systems is an assignment tester with alphabet , arity bound and rejection ratio when it contains the named input coordinates and satisfies the perfect-completeness and proximity-soundness clauses; the value of a constraint system is the fraction of its listed constraints satisfied, with multiplicity (Assignment tester and rejection ratio).
Proof
Apply the construction of [F1] to , obtaining the wire variables with the named input coordinates first, followed by the other input coordinates, the coefficient vectors and right sides for , and the exact extension equivalence. The output system of this step has the variables that is, one variable for every table coordinate of the two Hadamard tables together with the named input coordinates of the circuit; the intended labeling is , , the -th input bit, for the evaluation vector of an accepted input.
List the following five families of constraints on the variables of step 1.1, each constraint being the tuple of the variables displayed together with the fixed binary relation displayed, where sums are in , is the -th unit vector, and , , , range over all choices:
The families have , , , and constraints respectively, and every constraint has arity at most over ; each relation is an explicit table over the binary alphabet and is determined by the circuit. Put Each of the four nonempty power-of-two family sizes divides , and when the comparison-family size divides as well. Duplicate every constraint in a nonempty family exactly times. Thus every nonempty family contributes constraints; the comparison family is empty when , and the total is then , otherwise . Since a well-formed circuit has , gives and hence . Therefore the constraint count is at most for the fixed polynomial , with . Enumerating the families, the coefficient vectors and the right sides — computed from the gate list, not queried — takes time polynomial in that output count. [F1, F5, step 1.1, construct, algebra]
Perfect completeness. Let and choose a completion of the named inputs witnessing acceptance and let be its evaluation vector from [F1], with first coordinates . Label , and by the corresponding bit, so that and return the linear values at every point. Every and constraint is satisfied because linear functions satisfy the BLR equation, every constraint is satisfied by the perfect completeness of the tensor test, every constraint is satisfied because as solves every equation of [F1], and every constraint is satisfied because . Hence for that labeling.
First soundness case: suppose the table of a labeling is at distance more than from every linear function. Then the fraction of violated constraints is the BLR rejection probability of , which by [F2] is at least that distance, hence exceeds ; after duplication this is still the violated fraction of the family. Since the total is at most , the system as a whole violates at least of its constraints, and because . The same argument applies to the table and the family .
Second soundness case: suppose both tables are at distance at most from linear functions, say from and from in the unique sense of [F2], and . Then by [F3] the self-corrected tensor test rejects with probability at least , and the constraints are exactly the outcomes of that test, one for each choice of ; hence at least of them are violated and the system violates at least of its constraints.
Third and fourth soundness cases: suppose in addition . If the vector does not satisfy every equation of [F1], then the fraction of with is exactly by the random subsum clause, and for each such the fraction of auxiliary points with is at least by [F4] applied to the two uniform points and ; hence at least of the constraints are violated and the system violates at least of its constraints. If instead satisfies every equation, then by the exact extension equivalence of [F1] the input prefix lies in . For , writing gives , and for each such the auxiliary point is uniform and independent of everything else, so by [F4] the fraction of with is at least ; hence at least of the constraints are violated, whence the system violates at least . For , an equation-satisfying means the empty input is accepted by [F1], so and the required bound is immediate; if the empty input is rejected then every fails an equation and the preceding subsum case applies.
Steps 3.1, 3.2, 3.3 and 3.4 cover every labeling: either a table is more than far from linear (step 3.2), or both are within of linear tables with (step 3.3), or and fails an equation (step 3.4, first part), or satisfies every equation and the comparison family charges the distance of from (step 3.4, second part). In each case with , and step 3.1 gives perfect completeness, so by [F5] the constructed system is an assignment tester with alphabet , arity bound and rejection ratio ; its size, explicitness and construction time are those of step 2.1.
Remarks
- Where the exponential size is spent. The constraints are not sampled: every random choice of every test is materialized once, so the system contains and table coordinates and constraints, with . That is exponentially larger than the circuit but still of the form , which is what this base tester asserts. A polynomial-size composition requires an additional robust input-preserving interface beyond this item.
- Why the input coordinates are compared directly. The comparison family reads the raw coordinate as a variable of the system and compares it with the self-corrected value of at ; this is the only place where the given input, rather than the decoded wire vector, enters, and it is what turns the exact extension equivalence of [F1] into the proximity clause of the tester. A decoding that satisfies the circuit but differs from on a fraction of the coordinates therefore forces violated comparison constraints, the mechanism by which the rejection ratio becomes proportional to the Hamming distance rather than merely positive.
- The constant . The threshold is fixed before the construction and is smaller than , so the nearest linear decoders are unique; it also leaves in the tensor test and in the subsum and comparison families, both bounded away from zero. Any smaller absolute threshold would do; the value is not optimised, only kept an absolute constant for later composition work.
Depends on
- Assignment tester and rejection ratio
- BLR rejection is proportional to distance from linearity
- Quadratic tensor test rejects an inconsistent tensor
- Circuit satisfiability becomes linear-quadratic consistency
- Quadratic tensor consistency test
- Two-query linear self-correction
- Pointwise correctness under less than quarter noise
- The BLR linearity test over F_2
- Character orthogonality, inversion and Parseval
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
17 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
- Arora and Barak, Computational Complexity: A Modern Approach, §18.4.3 Corollary 18.25 (exponential-sized PCP of proximity), printed pp. 384-385. (standard reference, not scraped)
- Irit Dinur, The PCP theorem by gap amplification, §5 Theorem 5.1, printed pp. 17-18. (standard reference, not scraped)