The value of the padded strategy #
lem:qld-global-success: the padded strategy of PaddedStrategy.lean wins the seeded low
individual degree test at (q, 4m, d, 1) with probability 1 - O(δ_combine + δ_Q + md/q).
The failure probability is the average over the verifier's samples of the conditional failure at
the two questions the sample generates (one_sub_povmValue_clGame), and the sample splits into the
ordered pair of types and the ambient triple (u, s, raw) (sum_sample_eq). Each of the nine type
pairs is bounded by an agreement defect of two families of POVMs indexed by the ambient triple,
averaged uniformly:
- a line type against
point, in either order, by the agreement of the line measurement read at the sample's point with the opposite party's padded point measurement, whichlem:qld-padded-linesbounds (one_sub_agreeSum_lineEval_pt_le,one_sub_agreeSum_pt_lineEval_le); pointagainstpointby the agreement of the two padded point measurements, whichlem:qld-combined-pointsbounds through the compressions (one_sub_agreeSum_pt_pt_le);- a line type against itself by polynomial separation
(
one_sub_sum_bornProb_le_avg_eval): the two line measurements disagree only if they disagree when read at a uniformly random parameter, up to(md + 1)/q, and that disagreement is bounded through the agreement trianglefact:triangle-for-simeqby the three defects above (one_sub_agreeSum_lineEval_lineEval_le); - the two cross pairs are always accepted.
The parameter of the sample's point is uniform on the line once the raw direction is fixed, because
translating the point along the line is a bijection of the sample space that fixes the line
(sum_lineEval_shift); a degenerate diagonal direction, for which this fails, has probability at
most 1/q.
In a bipartite model #
Stated in a bipartite model (Phase 5 of planning/mipco-track.md). The padded strategy is a pair of
families of POVMs in the expanded model N₀ = M.reg (Anc F m) (padStrat, in the players'
Matrix (Anc F m) (Anc F m) _), and the stage-4a interface is padStrat_value:
1 - δ_GS ≤ N₀.povmValue (clGame hm4) (padStrat hm hm4 hPA) (padStrat hm hm4 hPB) for a legally
supported projective strategy of value 1 - ε. The point measurement is the sandwich, read along
(alpha, beta), so the identical-point subtest is the first agreement bound of
combined_points_pts coarse-grained (sum_bornProb_le_fibre) and the line-point subtests are
padded_lines_consistency verbatim: no compression is needed, and the matrix route's
bornProb_extHat_ptComb_left/_right are gone. The decomposition of the failure probability into
the nine type pairs is the model form of one_sub_povmValue_clGame
(BipartiteModel.one_sub_povmValue_clGame, below); the per-sample families and the polynomial
separation are stated in any bipartite model with the players' algebras of N₀. deltaGS, the
error of lem:qld-global-success, is defined here (moved from PaddedLIDT.lean) so that the
interface can be stated with it.
The failure probability of a POVM strategy in the seeded test is the average over the
verifier's samples of the conditional failure at the two questions the sample generates, in a
bipartite model: the model form of MIPRE.LIDT.CL.one_sub_povmValue_clGame.
The error of lem:qld-global-success #
δ_GS, the error of lem:qld-global-success: the padded strategy's failure probability
in the seeded test at (q, 4m, d, 1).
Equations
Instances For
The verifier's ambient sample: the point, the seed and the raw direction.
Equations
- MIPRE.QLD.Amb F m = (MIPRE.LIDT.Point F (4 * m) × F × MIPRE.LIDT.Point F (4 * m))
Instances For
The families of measurements indexed by the ambient sample #
The padded point measurement at the sample's point.
Equations
- MIPRE.QLD.ptFam hS x = MIPRE.QLD.padPt hS x.1
Instances For
The strategy's line measurement of type ty at the line the sample generates.
Equations
- MIPRE.QLD.lineFam hm hm4 ty hS x = MIPRE.QLD.lineMeas hm hm4 ty hS (MIPRE.LIDT.CL.rep (MIPRE.QLD.lineDir hm4 ty x.2.1 x.2.2) x.1) x.2.1 (MIPRE.QLD.rawSet hm4 ty x.2.1 x.2.2)
Instances For
The line measurement read at the parameter of the sample's point.
Equations
- MIPRE.QLD.lineEvalFam hm hm4 ty hS x = MIPRE.POVMIn.map (fun (f : MIPRE.LIDT.LinePoly F (m * d + 1)) => f.eval (MIPRE.QLD.lineTau hm4 ty x.1 x.2.1 x.2.2)) (MIPRE.QLD.lineFam hm hm4 ty hS x)
Instances For
Averaging over the raw direction #
At a diagonal line question the strategy averages the padded line measurement over the fibre of the truncated direction, and the sample averages over the raw direction; the two together are the plain average over the raw direction.
The strategy's raw-direction average composed with the sample's is the plain average.
The line-point agreement is the padded consistency quantity #
The first player's pasted line measurement at the sample's data, coarse-grained by the combining map at the sample's point, against the second player's sandwich there, averaged over the fresh randomness.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The same with the players exchanged: the first player's sandwich against the second player's pasted line.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The summand of avgSubAB for the first player's line against the second player's point.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The summand of avgSubAB for the first player's point against the second player's line.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The inner sum of avgSubAB at a fixed padded point and raw direction, for the first player's
line.
The normalizations agree: the uniform average over the ambient sample is the average over the
seed of the padded average avgSubAB.
The agreement of the first player's line read at the sample's point with the second player's padded point measurement is the seed-average of the padded consistency quantity.
From the padded consistency to the agreement bounds #
In the expanded model the padded point measurement is the first player's sandwich read along
(alpha, beta), which is exactly the point side of padded_lines_consistency and a coarse-graining
of the sandwich whose agreement combined_points_pts bounds; nothing has to be compressed.
The two items of lem:qld-expanded-lines for the presentation of a line type.
The second item with the players exchanged: the first player's line read at the point against the second player's point measurement.
The collision probability of the X presentation of a line type is at most md/q + 1/q.
The first player's line against the second player's point, at a fixed seed:
lem:qld-padded-lines in the other register version, in the expanded model.
The first player's point against the second player's line, at a fixed seed.
The line-point subtests, the first player's line: the agreement of the first player's line measurement read at the sample's point with the second player's padded point measurement, averaged over the ambient sample, in the expanded model.
The line-point subtests, the second player's line.
The identical-point subtest #
A function of the two blocks of the sample's point, averaged over the ambient sample, is its average over the pair of blocks.
The identical-point subtest: the two padded point measurements agree up to δ_Q, by the
self-agreement item of lem:qld-combined-points (combined_points_pts), coarse-grained along
(alpha, beta): agreement only increases under a common coarse-graining.
The identical-line subtest #
Two distinct polynomial outcomes are told apart by reading both at a uniformly random parameter of
the line, up to (md + 1)/q; the parameter of the sample's point is uniform on the line once the
raw direction is fixed and the line is not degenerate, because translating the point along the
line is a bijection of the sample space that fixes the line and shifts the parameter.
The parameter is uniform on the line. For a quantity that depends on the sample's point only through the line it generates and the parameter of the point on it, averaging over a uniform parameter is averaging over the point, when moving the point along the line shifts its parameter by the same amount.
The disagreement of two polynomial measurements read at the parameter t.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The disagreement of the two line measurements read at the sample's point is the disagreement of the evaluated families.
At a fixed seed and raw direction, averaging the evaluated disagreement over the parameter is averaging it over the point, unless the direction is degenerate, in which case the average is at most one.
Degenerate lines are rare: over the seed and the raw direction, a line type other than
point describes the zero direction on at most a 1/q fraction of the samples.
The disagreement of two families, as the uniform average of the per-sample disagreements.
The identical-line agreement, through the triangle: the first player's line read at the sample's point agrees with the second player's, because each agrees with the padded point measurements there.
The nine subtests, and the value #
The failure weight of one ordered pair of types: the conditional failure of the padded strategy in the expanded model at the questions of the two types, averaged over the ambient sample.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The identical-line subtests.
A sum over the three question types.
The failure probability of the padded strategy is the average over the nine ordered type pairs of their failure weights.
lem:qld-global-success: the padded strategy wins the seeded low individual degree test at
(q, 4m, d, 1) with probability at least 1 - δ_GS, in the expanded model M.reg (Anc F m),
with δ_GS = 5 δ_combine + 4 δ_Q + (md + 1)/q and δ_combine = m² δ_P(ε, md/q + 1/q): the
stage-4a interface. For a projective strategy S : M.ProjStrat (qldGame hm) the hypotheses are
S.ψ_unit, hfail : 1 - S.value ≤ ε, S.projA, S.projB.