Remark 26: Cohen et al. Scheme Recovery #
Statement #
The Cohen et al. scheme for logical measurement is recovered as a special case of the hypergraph gauging procedure (Rem_17).
Given a CSS stabilizer code and an irreducible X logical operator L:
- Restrict Z-type checks to the support of L → defines hypergraph H = (V_L, E_L)
- The only nontrivial element in ker(∂) is the all-ones vector (= L)
- Cohen et al. = hypergraph gauging with d layers
- Cross et al. = fewer layers with sufficient Cheeger expansion
- Joint measurement = adding edges between individual graphs
Main Results #
restrictedZCheckIncident: incidence relation for Z-checks restricted to supp(L)restrictedBoundaryMap: the boundary map of the restricted hypergraphIsIrreducibleXLogical: irreducible X logical operator definitionzCheck_restricted_support_even: commutation implies even overlap (row evenness)prodX_centralizer_of_even_overlap: prodX(S) is in centralizer when S has even overlapcoboundary_ker_gives_centralizer_pair: ker(δ) elements give centralizer factorizationskernel_restricted_boundary_trivial: kernel triviality from irreducibilitylayeredIncident: the d-layer incidence combining inter/intra-layer edgescohen_layered_all_ones_measures_L: all-ones Gauss product measures LjointIncident: joint incidence for measuring products of logicalsjoint_gauss_product_measures_product: joint measurement by adding edges
Restricted hypergraph from Z-checks on logical support #
The support of L as a finset of qubits (X-support).
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A Z-type check index: a check with no X-support.
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- CohenEtAlSchemeRecovery.isZTypeCheck C i = ((C.check i).xVec = 0)
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- CohenEtAlSchemeRecovery.isZTypeCheck_decidable C i = inferInstanceAs (Decidable ((C.check i).xVec = 0))
The Z-type check indices that have nonempty intersection with supp(L).
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- CohenEtAlSchemeRecovery.relevantZChecks C L = {i : C.I | CohenEtAlSchemeRecovery.isZTypeCheck C i ∧ ((C.check i).supportZ ∩ CohenEtAlSchemeRecovery.logicalSupport L).Nonempty}
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The incidence relation for the restricted hypergraph: qubit q is incident to Z-check i iff q ∈ supp(L) and the check has Z-action at q.
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- CohenEtAlSchemeRecovery.restrictedZCheckIncident C L q i = (q ∈ CohenEtAlSchemeRecovery.logicalSupport L ∧ (C.check i).zVec q ≠ 0 ∧ CohenEtAlSchemeRecovery.isZTypeCheck C i)
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- One or more equations did not get rendered due to their size.
The restricted hypergraph boundary map: ∂ : Z₂^{E_L} → Z₂^{V_L}.
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The restricted hypergraph coboundary map: δ : Z₂^{V_L} → Z₂^{E_L}.
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Irreducible X logical operators #
An X-type logical operator: pure X-type (zVec = 0), in the centralizer, not a stabilizer, and not identity.
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- CohenEtAlSchemeRecovery.IsXTypeLogical C L = (L.zVec = 0 ∧ C.isLogicalOp L)
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An irreducible X logical operator: an X-type logical that cannot be written as a product of two lower-weight X-type operators that are both in the centralizer.
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- One or more equations did not get rendered due to their size.
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Commutation and kernel properties for the restricted hypergraph #
If L is pure X-type and commutes with all checks, then for each Z-type check s_j, the Z-support of s_j intersected with supp(L) has even cardinality (row evenness). This is because ⟨L, s_j⟩_symp = Σ_q L.xVec(q) · s_j.zVec(q) = 0 (commutation), and L.xVec(q) = 1 iff q ∈ supp(L), so the sum counts |S_Z(s_j) ∩ supp(L)| mod 2.
Pure X operators in the centralizer #
For a CSS code, a pure X-type operator prodX(S) is in the centralizer iff for each Z-type check s_j, the intersection |S ∩ supp_Z(s_j)| is even. X-type checks commute automatically (both pure X-type).
For a CSS code, prodX(S) commutes with a Z-type check s_j iff |S ∩ supp_Z(s_j)| is even.
For a CSS code, prodX(S) is in the centralizer iff S has even overlap with every Z-type check's support.
Coboundary kernel elements give centralizer factorizations #
The key algebraic step: an element f ∈ ker(δ) of the restricted coboundary map (where δ is the transpose of the boundary map ∂) gives a factorization of L into two pure X-type centralizer elements. Specifically, if f : Q → ZMod 2 satisfies δf = 0 (meaning for each relevant Z-check j, #{q : f(q)=1 and q incident to j} is even), then prodX(supp(f) ∩ V_L) is in the centralizer of C.
An element f in the kernel of the restricted coboundary map (i.e., for each
relevant Z-check j, the number of vertices q with f(q) ≠ 0 incident to j is
even) gives a pure X-type operator prodX(supp(f) ∩ V_L) that commutes with
all Z-type checks, via prodX_centralizer_of_even_overlap.
This is the key step connecting the linear algebra of the restricted hypergraph to the PauliOp centralizer structure.
ProdX helper lemmas for the kernel triviality proof #
Z₂ rank-nullity for incidence matrices #
The key linear algebra step: for an incidence relation between finite types V and E,
the boundary map ∂ = M · and coboundary map δ = Mᵀ · satisfy
dim(ker(δ)) + |E| = dim(ker(∂)) + |V|
via Matrix.rank_transpose and rank-nullity. This is used to show that if
ker(∂) has dimension ≥ 2, then (given |V| ≥ |E|) ker(δ) also has dimension ≥ 2.
Z₂ rank-nullity for incidence matrices.
dim(ker(δ)) + |E| = dim(ker(∂)) + |V|, where ∂ = M · and δ = Mᵀ ·.
This follows from Matrix.rank_transpose and LinearMap.finrank_range_add_finrank_ker.
Given dim(ker(boundary)) ≥ 2 and |E| ≤ |V|, and any w ∈ ker(coboundary), there exists g ∈ ker(coboundary) with g ≠ 0 and g ≠ w.
Kernel triviality: the core structural property #
For an irreducible X logical L, the kernel of ∂ on the restricted hypergraph consists only of 0 and the all-ones vector on E_L. The argument proceeds in two steps:
Step 1 (rank-nullity): If ker(∂) has dimension ≥ 2 (i.e., contains a
nontrivial γ besides 0 and all-ones), then ker(δ) also has dimension ≥ 2
(given |V_L| ≥ |E_L|), yielding a nontrivial vertex function f ∈ ker(δ)
with f ≠ 0 and f ≠ all-ones. This uses rank(∂) = rank(δ) (since δ = ∂^T
via Matrix.rank_transpose) and z2_finrank_ker_formula.
Step 2 (irreducibility contradiction): Such f gives a factorization
L = prodX(supp(f)) · prodX(V_L \ supp(f)) where both factors are in the
centralizer (by coboundary_ker_gives_centralizer_pair). Irreducibility
then forces one factor to have weight ≥ wt(L) or be identity, meaning
supp(f) = ∅ or supp(f) = V_L, contradicting f ≠ 0 and f ≠ all-ones.
Core incidence on subtype and lifting #
The core incidence on subtypes: vertex in VL incident to check in EL iff zVec ≠ 0.
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- CohenEtAlSchemeRecovery.coreIncident C L q i = ((C.check ↑i).zVec ↑q ≠ 0)
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- CohenEtAlSchemeRecovery.coreIncident_decidable C L q i = inferInstanceAs (Decidable ((C.check ↑i).zVec ↑q ≠ 0))
Lift a function on VL to a function on Q by extending with zeros.
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- CohenEtAlSchemeRecovery.liftVL L g q = if hq : q ∈ CohenEtAlSchemeRecovery.logicalSupport L then g ⟨q, hq⟩ else 0
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The lift is injective.
The lift is supported on VL.
Lift of 0 is 0.
Lift of all-ones on VL.
If g ∈ ker(coreCoboundary), then liftVL g ∈ ker(restrictedCoboundary). This holds because the restricted incidence is trivial outside VL and EL.
Coboundary from boundary step (rank-nullity).
If ker(restricted ∂) contains two EL-supported linearly independent elements,
and |VL| ≥ |EL|, then ker(restricted δ) contains a VL-supported element
f ≠ 0 with ∃ q ∈ VL, f q = 0. This replaces the former hypothesis
hcoboundary_from_boundary using the Z₂ rank-nullity theorem.
If γ ∈ ker(∂) and γ' agrees with γ on relevant checks and is 0 on irrelevant ones, then γ' ∈ ker(∂) as well.
The complement of a kernel element (relative to all-ones on relevant checks) is also in the kernel.
γ and its complement on relevant checks sum to the all-ones vector.
Kernel triviality from irreducibility.
For an irreducible X logical operator L of a CSS stabilizer code C, the kernel of the restricted boundary map ∂ : Z₂^{E_L} → Z₂^{V_L} consists only of 0 and the all-ones vector on E_L (corresponding to L itself).
The proof combines two ingredients:
- Coboundary kernel → centralizer factorization: Any nontrivial f ∈ ker(δ)
gives a factorization L = prodX(supp(f)) · prodX(V_L \ supp(f)) with both
factors in the centralizer (by
coboundary_ker_gives_centralizer_pair). - Irreducibility contradiction: Such a factorization contradicts the irreducibility of L (both factors have weight < wt(L) unless trivial).
The Z₂-rank-nullity step (coboundary_from_boundary_step) proves that if
ker(∂) has a nontrivial element besides 0 and the all-ones vector,
then ker(δ) contains a nontrivial element f with f ≠ 0 and f ≠ all-ones-on-V_L.
This uses dim(ker(δ)) = |V_L| - |E_L| + dim(ker(∂)) ≥ 2 when
|V_L| ≥ |E_L|, via Matrix.rank_transpose and z2_finrank_ker_formula.
Cohen et al. d-layer construction as hypergraph gauging #
The Cohen et al. construction creates d copies of the logical support vertices, connects copies of the same vertex across layers via path graphs (chains), and joins vertices within each layer via the same hypergraph structure.
This is the layered incidence relation on Q × Fin d. The hypergraph gauging framework from Rem_17 applies directly to this layered incidence, giving pure X-type commuting Gauss operators and kernel characterization.
The Cohen et al. layered vertex type: d copies of the qubit set Q.
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- CohenEtAlSchemeRecovery.CohenVertex Q d = (Q × Fin d)
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The inter-layer edge type: connects copies of the same vertex in consecutive layers.
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- CohenEtAlSchemeRecovery.InterLayerEdge Q d = (Q × Fin (d - 1))
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The intra-layer edge type: replicates the original check structure within each layer.
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- CohenEtAlSchemeRecovery.IntraLayerEdge I d = (I × Fin d)
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The combined edge type for the Cohen construction.
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The incidence relation for the layered construction. A vertex (q, ℓ) in the layered graph is incident to:
- Inter-layer edge (q', k): q = q' and ℓ ∈ {k, k+1} (path graph connection)
- Intra-layer edge (i, ℓ'): ℓ = ℓ' and q is incident to check i in restricted hypergraph
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The Cohen et al. scheme is recovered as hypergraph gauging (Rem_17) applied to the layered incidence with d copies.
The all-ones Gauss subset product measures L: its xVec restricts to 1 on all
vertex qubits by hyperGaussSubsetProduct_xVec_vertex, and it is pure X-type
by hyperGaussSubsetProduct_zVec.
The Gauss operators are pure X-type (hyperGaussLawOp_zVec) and mutually
commute (hyperGaussLaw_commute). The kernel of the layered boundary map
characterizes which operators can be measured (ker_boundary_iff_commutes_all_gaussLaw).
Cross et al. modification: fewer layers with Cheeger expansion #
The Cross et al. modification uses R < d layers of dummy vertices. This is recovered by choosing fewer layers in the hypergraph gauging construction while maintaining sufficient expansion (Cheeger constant ≥ 1, Rem_4/Rem_11) in the inter-layer graph.
By Lemma 3 (deformed_distance_ge_min_cheeger_d): with Cheeger constant h(G) of the
inter-layer graph, the deformed code distance satisfies d* ≥ min(h(G), 1) · d.
When h(G) ≥ 1 (sufficient expansion, SufficientExpansion), d* ≥ d (distance
fully preserved, deformed_distance_ge_d_sufficient_expansion).
The path graph on R vertices: vertices are Fin R, edges connect consecutive vertices. This is the inter-layer connectivity graph in the Cross et al. modification.
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- CohenEtAlSchemeRecovery.pathGraphAdj_decidable R a b = inferInstanceAs (Decidable (↑a + 1 = ↑b ∨ ↑b + 1 = ↑a))
The Cross et al. scheme applies the same layered construction with R ≤ d layers. The Gauss product for coefficient c gives a pure X-type operator with c as its vertex X-vector, by the hypergraph gauging framework (Rem_17).
The path graph adjacency relation is symmetric.
The path graph adjacency is irreflexive.
The path graph on R vertices as a SimpleGraph.
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- CohenEtAlSchemeRecovery.pathGraph R = { Adj := fun (a b : Fin R) => CohenEtAlSchemeRecovery.pathGraphAdj R a b, symm := ⋯, loopless := ⋯ }
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For the Cross et al. scheme with R layers: the edge boundary of any valid subset S satisfies |∂S| ≥ c · |S| for any c ≤ h(P_R), connecting the Cheeger constant of the path graph to the distance bound from Lemma 3.
Joint measurement of products via edge addition #
Given two systems (Q₁, E₁, incident₁) and (Q₂, E₂, incident₂), the joint system has vertices Q₁ ⊕ Q₂ and edges E₁ ⊕ E₂ ⊕ B (where B are bridge edges connecting the two systems). The key property is that the joint Gauss product measures the product of the individual logicals L₁ ⊗ L₂.
The joint incidence: combines the two individual incidence relations with bridge edges connecting specified pairs across Q₁ and Q₂.
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- CohenEtAlSchemeRecovery.jointIncident incident₁ incident₂ bridgeQ1 bridgeQ2 (Sum.inl q₁) (Sum.inl e₁) = incident₁ q₁ e₁
- CohenEtAlSchemeRecovery.jointIncident incident₁ incident₂ bridgeQ1 bridgeQ2 (Sum.inr q₂) (Sum.inr (Sum.inl e₂)) = incident₂ q₂ e₂
- CohenEtAlSchemeRecovery.jointIncident incident₁ incident₂ bridgeQ1 bridgeQ2 (Sum.inl q₁) (Sum.inr (Sum.inr b)) = (q₁ = bridgeQ1 b)
- CohenEtAlSchemeRecovery.jointIncident incident₁ incident₂ bridgeQ1 bridgeQ2 (Sum.inr q₂) (Sum.inr (Sum.inr b)) = (q₂ = bridgeQ2 b)
- CohenEtAlSchemeRecovery.jointIncident incident₁ incident₂ bridgeQ1 bridgeQ2 q e = False
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Adding bridge edges enables joint measurement: the joint Gauss subset product for coefficient (c₁, c₂) on Q₁ ⊕ Q₂ gives a pure X-type operator that restricts to c₁ on Q₁ and c₂ on Q₂, measuring L₁ ⊗ L₂.