Soundness of oracularization #
Item 2 of blueprint thm:oracularization (lem:oracular-soundness), at the level of games: a
synchronous strategy of value at least 1 - ε for MIPRE.SeededGame.oracular yields one of
value at least 1 - 24√ε for the doubled input game.
The loss carries the single square root that repair 1 of rem:oracularization-repairs
insists on -- an earlier revision of the blueprint wrote poly(ε), which the campaign found
"not merely imprecise but false as stated". It is spent in exactly one place,
MIPRE.sum_ntr_mul_ge; everything before it is linear in ε.
The shape of the argument #
- The extracted strategy (
soundStrategy) is the two isolated players' own measurements, relabelled alongOAns.singlePartso that an oracle-shaped answer is grouped into one distinguished outcome. Relabelling is what makes them measurements rather than sub-measurements, which is the game-level residue of repair 3;SyncStrategy.pushdoes it, and a sum over a fibre is a projection because distinct outcomes are orthogonal. - The budget (
budget) is all that is taken from the hypothesis. Each of the nine ordered role pairs carries a ninth of the question weight, so at any one of them a set of outcome pairs the decider rejects carries mass at most9εon average over the seed. Three instances (gammaTerm_budget,betaTerm_budget,alphaTerm_budget) are used: the oracle's own pair is accepted, and each isolated player agrees with the oracle's component. - The closeness estimate (
sqDist_le, fromMIPRE.sum_hsNormSq_sub_le) bounds the squared Hilbert--Schmidt distance between the oracle's relabelled measurement and the product of the two isolated players' by three times the sum of the two disagreements -- linearly, with no square root. - The value comparison (
valSeed_ge, fromMIPRE.sum_ntr_mul_ge) is where the square root enters, and one more Cauchy--Schwarz takes the average inside it.
For a synchronous strategy the state is the normalized trace, so the paper's state-dependent
≈_δ is the normalized Hilbert--Schmidt distance of MIPRE/Foundations/Distances.lean; see
blueprint rem:distance-state. MIPRE/Foundations/Closeness.lean is that calculus.
Scope #
Nothing here inhabits MIPRE.Oracularization: that is done at the level of verifiers, in
Foundations/Pipeline/Oracularization.lean, whose bipartite soundness rests on
Foundations/OracularTensor.lean rather than on the synchronous argument here. The complexity
clause, the bounded parse and its grouping, the truncation to B_𝒟(n) and the level accounting
are all statements about a verifier and none of them appears at this level;
rem:oracular-game-level records that.
Relabelling an oracularized answer #
An oracularized answer read as a pair: an oracle's answer is the pair it is, and an
isolated player's answer is grouped into the distinguished outcome (default, default).
Instances For
An oracularized answer read as a single answer: an isolated player's answer is itself, and
an oracle's pair is grouped into the distinguished outcome default.
Equations
- (MIPRE.OAns.single a).singlePart = a
- (MIPRE.OAns.pair a b).singlePart = default
Instances For
Averages over the seed #
Both question distributions are pushforwards of the uniform distribution on the seed space, so every sum against them is an average over seeds.
The input game's distribution, against a test function: an average over the seed.
The oracularized game's distribution, against a test function: an average over the ordered pair of roles and the seed.
The three relabelled families, and the extracted strategy #
The oracle's measurement, read as a measurement on answer pairs: the shape failures are
grouped into the distinguished outcome (default, default), which is what makes it a
measurement rather than a sub-measurement (repair 3 of rem:oracularization-repairs, at the
game level).
Equations
- MIPRE.SeededGame.oFam N z p = (N.push MIPRE.OAns.pairPart).M (MIPRE.Role.oracle, z) p
Instances For
Alice's own measurement, with the oracle-shaped answers grouped into default.
Equations
- MIPRE.SeededGame.cFam N x a = (N.push MIPRE.OAns.singlePart).M (MIPRE.Role.alice, x) a
Instances For
Bob's own measurement, with the oracle-shaped answers grouped into default.
Equations
- MIPRE.SeededGame.dFam N y b = (N.push MIPRE.OAns.singlePart).M (MIPRE.Role.bob, y) b
Instances For
The isolated players' measurements as one projective measurement on the doubled input game's questions.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The extracted strategy for the input game: the two isolated players keep their own measurements.
Equations
- MIPRE.SeededGame.soundStrategy N = { d := N.d, d_pos := ⋯, P := MIPRE.SeededGame.sideMeas N }
Instances For
The two values, as averages over the seed #
The extracted strategy's value.
The oracularized value.
The total mass of the oracularized game: one.
The rejection budget #
Everything the argument takes from 1 - ε ≤ val(oracular) is this: at any one ordered pair of
roles, a set of outcome pairs the decider rejects carries mass at most 9ε on average over the
seed. The 9 is the number of ordered role pairs.
Relabelled sums, unrelabelled #
Each budget below is stated about the relabelled families, and the budget lemma is about the strategy's own operators. This is the translation: a sum over a set of relabelled outcome pairs is the sum over the outcome pairs whose labels land in that set.
The three rejection sets, and their budgets #
The decider's checks that the argument uses are three: the oracle's own pair must satisfy the
input predicate, and each isolated player's answer must agree with the oracle's corresponding
component. Each is a set of outcome pairs on which oaccepts is false, so each carries mass at
most 9ε.
The outcome pairs on which the oracle's Alice-component and Alice's own answer disagree. It also contains every shape mismatch, which the decider rejects anyway.
Equations
- MIPRE.SeededGame.TAlice = {uv : MIPRE.OAns A × MIPRE.OAns A | ¬uv.1.pairPart.1 = uv.2.singlePart}
Instances For
The outcome pairs on which the oracle's Bob-component and Bob's own answer disagree.
Equations
- MIPRE.SeededGame.TBob = {uv : MIPRE.OAns A × MIPRE.OAns A | ¬uv.1.pairPart.2 = uv.2.singlePart}
Instances For
The outcome pairs, at a seed, on which the oracle repeats an answer the input predicate rejects.
Equations
- MIPRE.SeededGame.TGame z = Finset.image (fun (u : MIPRE.OAns A) => (u, u)) {u : MIPRE.OAns A | S.D (S.LA z) (S.LB z) u.pairPart.1 u.pairPart.2 = false}
Instances For
The three budgets, on the relabelled families #
Each budget is now a statement about the relabelled families oFam, cFam, dFam: the
oracle's own answer is accepted, and each isolated player agrees with the oracle's component,
all but 9ε of the time.
Equations
- MIPRE.SeededGame.EAliceAgree = Finset.image (fun (p : A × A) => (p, p.1)) Finset.univ
Instances For
Equations
- MIPRE.SeededGame.EBobAgree = Finset.image (fun (p : A × A) => (p, p.2)) Finset.univ
Instances For
The oracle's disagreement with Alice, as a mass on the strategy's own outcomes.
The oracle's disagreement with Bob.
The mass the oracle puts on pairs the input predicate rejects.
The three families are projective measurements #
The per-seed quantities #
The squared Hilbert--Schmidt distance, at one seed, between the oracle's relabelled measurement and the product of the two isolated players'.
Equations
- MIPRE.SeededGame.sqDist N z = ∑ p : A × A, MIPRE.hsNormSq (MIPRE.SeededGame.cFam N (S.LA z) p.1 * MIPRE.SeededGame.dFam N (S.LB z) p.2 - MIPRE.SeededGame.oFam N z p)
Instances For
The oracle's disagreement with Bob at one seed.
Equations
- MIPRE.SeededGame.alphaTerm N z = ∑ p : A × A, MIPRE.ntr (MIPRE.SeededGame.oFam N z p * (1 - MIPRE.SeededGame.dFam N (S.LB z) p.2))
Instances For
The oracle's disagreement with Alice at one seed.
Equations
- MIPRE.SeededGame.betaTerm N z = ∑ p : A × A, MIPRE.ntr (MIPRE.SeededGame.oFam N z p * (1 - MIPRE.SeededGame.cFam N (S.LA z) p.1))
Instances For
The mass the oracle puts on pairs the input predicate rejects, at one seed.
Equations
- MIPRE.SeededGame.gammaTerm N z = ∑ p : A × A with S.D (S.LA z) (S.LB z) p.1 p.2 = false, MIPRE.ntr (MIPRE.SeededGame.oFam N z p)
Instances For
The closeness estimate at one seed, linear in the two disagreements.
The value comparison at one seed, where the square root is spent.
The three budgets, averaged over the seed #
Soundness #
Soundness of oracularization (item 2 of blueprint thm:oracularization), at the level
of games: a synchronous strategy of value at least 1 - ε for the oracularized game yields
one of value at least 1 - 24 √ε for the doubled input game. The loss carries the single
square root of repair 1 of rem:oracularization-repairs, and it is spent in exactly one place,
MIPRE.sum_ntr_mul_ge.