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Metadata
slug: lidar-2025-qpu-restricted-anticoncentration-refutation
bibkey: lidar2025dadqc
doi: 10.48550/arXiv.2512.07127
url: https://arxiv.org/abs/2512.07127v1
triage: theorem
motivation_gids:
  - D5/S3/Quantum/Measurements/IQP/LidarRestrictedAnticoncentrationRefutation.result

Lidar’s QPU-restricted IQP anticoncentration conjecture

Problem

D. A. Lidar, “Digital-Analog-Digital Quantum Supremacy”, arXiv:2512.07127v1, p. 4, Conjecture 2, asks for positive constants , depending only on , such that every output string satisfies . The hardware graph is fixed, simple and -regular, is fixed, is uniform on its -factors, the angles are independently uniform on , and the one-qubit fields are arbitrary but fixed. The Library note quotes Definition 1 and Conjecture 2 verbatim and identifies Eqs. (17)–(20).

Motivation

The source’s Theorem 2 assumes Conjecture 2. A valid hardware family and one fixed field choice violating the uniform positive lower bound refute its universal scope. The motivation GID proves claim, which is the negation of that lower bound on the subsequence , .

Gap

Tier 1 external named open problem, preregistered in issue #13764. The preregistration records the source quotations, quantifiers, literature queries and refutation criterion. Its literature conclusion is not-found-in-searched-scope; it is not an exhaustive literature certificate. The supporting module supplies hardware factors and product-angle integration; the settling module connects these to the literal circuit probability.

Route

Set , , and every fixed field . Each of the blocks is with one edge removed, and the missing-edge endpoints are joined cyclically between adjacent blocks. The hardware adjacency is literal; hardware_degree_five checks its degree and factor_nonempty proves that the four-factor ensemble exists. The complement of a four-factor is a perfect matching. factor_block_twins finds in every block a nonadjacent pair with the same four neighbours.

circuit_amplitude_literal expands the tensor circuit, and factor_entangler_eq_CZ identifies its diagonal entangler with the graph phase up to a global phase. Partial trace and integration over the complementary angles give the twin conditional mean. The square-root moment contracts by per block. Product-angle periodicity absorbs the fixed fields and the output-bit shifts. Markov’s inequality gives, for every output and ,

The right side tends to zero, so no positive uniform exists.

Falsifier

The source conclusion would require one pair to work for every and every output string. result : claim proves that no such pair exists for this literal circuit and joint graph-angle measure. No alternate definition of output probability is used.

Evidence

The mathematical declarations are D5/S3/Quantum/Measurements/IQP/HardwareCircuitFactors and D5/S3/Quantum/Measurements/IQP/LidarRestrictedAnticoncentrationRefutation.result. The Scribe settling node carries OpenProblemResolutionClaim with Refuted. The mathematical truth and axiom closure are the Lean declarations; the graph enumeration below is independently rerunnable finite computation.

Triage

The settling module has admission_basis: open-problem-resolution (#13764); the supporting module has admission_basis: escape-witness, witnessed by OpLidarProductShift.pi_periodic_shift. Auxiliary bind-only declarations are used on the live path to the settlement. No digestion atom or cover is involved. Information-escape registration is paused under CLAUDE.md §3.9.

What the settlement shows

  • Proved in this delivery: forced twins in every four-factor of the displayed hardware family yield the product reduced-state calculation and its conditional mean. factor_block_twins, normalized_twin_conditional_mean, factor_literal_fractional_moment, literal_tail_bound and result connect that structure to the literal circuit and the uniform output-tail bound.
  • Proved in the supporting module: conditional_fractional_moment applies to any nonnegative integrable random variable on independent uniform angle pairs and an arbitrary probability space , when its conditional mean is . It gives ; fractional_markov gives the corresponding upper tail. These are the actual general hypotheses furnished by this proof. Open: a literal-circuit bridge for every hardware family with a positive density of forced twins. A positive-density count alone is not the delivered conditional-mean and joint-measure hypothesis.
  • Computed: at exactly , , enumeration gives and connected factors, so . The script, command, exit and hash appear below. Open in Lean: the uniform formulas and for all . The paper argument counts perfect matchings: no connector yields twelve local choices per block and connected complements; all connectors yields three local choices per block and disconnected complements. Local parity forces these two connector cases. This combinatorial argument is not a delivered kernel proof of the uniform counts.
  • Open: sufficient structural hypotheses restoring anticoncentration, including expansion or exclusion of forced twins. Open: the specific Zephyr hardware mentioned in the source. This settlement proves neither a Zephyr counterexample nor a restoring theorem.
  • Open and unaffected: Conjecture 1, the source’s average-case hardness assertion. No average-case hardness proof or refutation is delivered.
  • Proved: Conjecture 2 fails with its stated universal hardware scope. Open formal bridge / source consequence: Theorem 2 remains a conditional implication under its stated conjectures; the refuted general anticoncentration hypothesis cannot supply an unconditional supremacy conclusion. No Lean proof of the source’s complexity-theoretic implication or of a replacement ensemble is delivered.

Finite graph enumeration

Save the following exact script as enumerate-lidar-m3.py and run python3 enumerate-lidar-m3.py. Exit code: 0. SHA256: 75d1b2e73d588043fe7d12cfe120c60b51be2f9cfedd995a7422a93e3e31f516. Output: m=3; vertices=18; hardware_edges=45; F4=1755; connected=1728; probability=64/65.

from fractions import Fraction
m = 3
n = 6 * m
edges = set()
for i in range(m):
    for a in range(6):
        for b in range(a + 1, 6):
            if (a, b) != (4, 5):
                edges.add((6 * i + a, 6 * i + b))
    edges.add(tuple(sorted((6 * i + 5, 6 * ((i + 1) % m) + 4))))
adj = [set() for _ in range(n)]
for u, v in edges:
    adj[u].add(v)
    adj[v].add(u)
assert len(edges) == 15 * m and all(len(a) == 5 for a in adj)
def matchings(unmatched, chosen):
    if not unmatched:
        yield frozenset(chosen)
        return
    u = min(unmatched)
    for v in sorted(adj[u] & unmatched):
        yield from matchings(unmatched - {u, v}, chosen + [(min(u, v), max(u, v))])
def connected(es):
    a = [set() for _ in range(n)]
    for u, v in es:
        a[u].add(v)
        a[v].add(u)
    seen = {0}
    todo = [0]
    while todo:
        for v in a[todo.pop()] - seen:
            seen.add(v)
            todo.append(v)
    assert all(len(x) == 4 for x in a)
    return len(seen) == n
factors = [edges - set(M) for M in matchings(set(range(n)), [])]
assert len({frozenset(G) for G in factors}) == len(factors)
c = sum(connected(G) for G in factors)
assert len(factors) == 12 ** m + 3 ** m
assert c == 12 ** m
assert Fraction(c, len(factors)) == Fraction(4 ** m, 4 ** m + 1)
print(f'm={m}; vertices={n}; hardware_edges={len(edges)}; F4={len(factors)}; connected={c}; probability={Fraction(c, len(factors))}')

ASSUMED-UNVERIFIED

The literature reading in #13764 is scoped and source-attested. The uniform graph-count formulas, arbitrary positive-density hardware bridge, restoring conditions, Zephyr behaviour, average-case hardness and the source’s general complexity-theoretic implication are not kernel-certified by this delivery.