Recognition: 2 theorem links
· Lean TheoremIn-Situ Simultaneous Magic State Injection on Arbitrary CSS qLDPC Codes
Pith reviewed 2026-05-10 18:52 UTC · model grok-4.3
The pith
Logical magic states can be prepared directly inside any CSS qLDPC code using only syndrome extraction resources.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The authors claim that an in-situ magic state injection protocol exists for arbitrary CSS qLDPC codes, where logical magic states are prepared within the memory block using only ancilla qubits required for syndrome extraction, as verified by examples on the bivariate bicycle code and hypergraph product code with reported injection error rates of 1.62e-3 and lower under depolarizing and asymmetric noise.
What carries the argument
Repurposing the syndrome extraction circuit for simultaneous preparation of multiple logical magic states inside the qLDPC block.
Load-bearing premise
The scheme works in a regime where the contribution of correlated injection errors is negligible compared to other error sources.
What would settle it
A noise simulation or hardware test that shows the correlated error rate during simultaneous magic state injection to be substantially higher than the 1% of injection error reported in the paper.
Figures
read the original abstract
Quantum low-density parity-check (qLDPC) codes can encode many logical qubits within a single code block at low physical qubit overhead, yet magic state injection into such codes remains largely underexplored. Existing state injection proposals for qLDPC codes predominantly follow an external prepare-and-transfer paradigm, in which raw magic states are prepared outside the target code block and subsequently injected via inter-code operations. We propose the first \emph{in-situ} magic state injection: a scheme in which logical magic states are directly prepared within a qLDPC memory block, only using resources required for syndrome extraction. We show that our scheme is generalizable to any CSS qLDPC code, with examples of circuit-level simulations on the $[[144,12,12]]$ Bivariate Bicycle (BB) code and the $[[225,9,4]]$ Hypergraph Product code. We focus on a regime where correlated injection errors are negligible. In the BB code, this corresponds to a configuration that simultaneously injects four logical $|Y\rangle$ states. Under a uniform depolarizing noise model with physical error rate $10^{-3}$, this achieves an injection error rate of $1.62 \times 10^{-3}$ per logical qubit, while the correlated-error contribution is only $2 \times 10^{-5}$ per logical qubit (about $1\%$ of the injection error rate). Under a hardware-motivated asymmetric noise model where single-qubit gate errors are $10\%$ of two-qubit gate errors, the injection error rate per logical qubit falls to $ 6.7 \times 10^{-4} $, below the error rate ($ 10^{-3} $) of the two-qubit gates used to encode the magic states. Its simplicity allows our scheme to be applied to arbitrary CSS qLDPC codes using only the ancilla qubits native to syndrome extraction, and yield a reduction in space overhead relative to both prepare-and-transfer approaches and surface-code-based magic state injection schemes.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript proposes the first in-situ magic state injection scheme for arbitrary CSS qLDPC codes, preparing logical magic states directly inside the memory block using only native syndrome-extraction ancillas. It asserts that the scheme generalizes to any CSS qLDPC code and supports this with circuit-level simulations on the [[144,12,12]] bivariate bicycle code (simultaneously injecting four logical |Y⟩ states) and the [[225,9,4]] hypergraph product code, reporting per-logical-qubit injection error rates of 1.62×10^{-3} (depolarizing noise at p=10^{-3}) and 6.7×10^{-4} (asymmetric noise), with correlated-error contributions at ~1% of the total.
Significance. If the generality claim holds, the approach offers a meaningful reduction in space overhead relative to prepare-and-transfer injection or surface-code methods by reusing syndrome ancillas. The concrete error-rate numbers under both uniform depolarizing and hardware-motivated asymmetric noise models, together with the explicit regime of negligible correlated errors, supply useful benchmarks for qLDPC-based fault-tolerant architectures.
major comments (2)
- [General construction and claim of generality] The central generality claim (that the scheme applies to any CSS qLDPC code without extra resources or code-specific modifications) rests on a high-level description plus simulations restricted to the BB and HGP families. An explicit, code-agnostic construction—e.g., a procedure expressed solely in terms of the parity-check matrix and ancilla scheduling that works for arbitrary CSS codes—is required to confirm that no implicit reliance on BB/HGP stabilizer weights, connectivity, or four-qubit |Y⟩ simultaneity exists.
- [Simulation results and noise models] Circuit-level simulation section: the exact circuit construction for in-situ |Y⟩ preparation, the precise noise-model definitions (including how single-qubit vs. two-qubit error rates are applied during injection), and the data-exclusion rules used to obtain the quoted error rates (1.62×10^{-3} and 6.7×10^{-4}) must be provided in sufficient detail for independent reproduction; without them the numerical results cannot be verified as independent checks rather than artifacts of the chosen configuration.
minor comments (2)
- [Abstract and introduction] The abstract states that correlated injection errors are negligible in the chosen BB configuration; the main text should quantify the precise threshold at which this approximation breaks and whether the same regime can be identified for arbitrary CSS codes.
- [Noise model definitions] Notation for the asymmetric noise model (ratio of single- to two-qubit gate errors) should be defined once and used consistently when reporting the 6.7×10^{-4} figure.
Simulated Author's Rebuttal
We thank the referee for their careful reading of our manuscript and for the constructive feedback. We address each major comment below. Where the comments identify areas requiring greater explicitness, we have revised the manuscript accordingly.
read point-by-point responses
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Referee: [General construction and claim of generality] The central generality claim (that the scheme applies to any CSS qLDPC code without extra resources or code-specific modifications) rests on a high-level description plus simulations restricted to the BB and HGP families. An explicit, code-agnostic construction—e.g., a procedure expressed solely in terms of the parity-check matrix and ancilla scheduling that works for arbitrary CSS codes—is required to confirm that no implicit reliance on BB/HGP stabilizer weights, connectivity, or four-qubit |Y⟩ simultaneity exists.
Authors: We thank the referee for this observation. The scheme is constructed to depend only on the CSS property (to identify the logical Pauli operators and the controlled-phase or controlled-Hadamard operations that prepare the magic state on the data qubits) together with the ancilla qubits and measurement schedule already required for syndrome extraction; no additional qubits or code-family-specific connectivity assumptions are used. To make this fully explicit and address the request for an algorithmic description, the revised manuscript adds a new subsection that states the injection procedure directly in terms of the parity-check matrices H_X and H_Z and the standard ancilla scheduling. The procedure is written as a sequence of steps that any CSS qLDPC code can follow without reference to stabilizer weights, graph structure, or the particular choice of injecting four states simultaneously (the latter is used only in the BB simulation to illustrate multi-logical-qubit injection). We believe this addition removes any ambiguity while leaving the underlying scheme unchanged. revision: yes
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Referee: [Simulation results and noise models] Circuit-level simulation section: the exact circuit construction for in-situ |Y⟩ preparation, the precise noise-model definitions (including how single-qubit vs. two-qubit error rates are applied during injection), and the data-exclusion rules used to obtain the quoted error rates (1.62×10^{-3} and 6.7×10^{-4}) must be provided in sufficient detail for independent reproduction; without them the numerical results cannot be verified as independent checks rather than artifacts of the chosen configuration.
Authors: We agree that the original simulation section lacked sufficient detail for independent reproduction. The revised manuscript expands Section 4 and adds an appendix containing the full circuit diagrams (including all single- and two-qubit gates applied to data and ancilla qubits during the injection round), the exact noise-model specifications (depolarizing model applies equal X/Y/Z probabilities to each gate; asymmetric model sets single-qubit error probability to 0.1 times the two-qubit error probability, with errors applied after every gate), and the post-selection rules (runs are retained only if no syndrome errors are detected on the ancilla measurements performed during injection; logical error rates are then obtained by averaging the decoded outcome over 10^7 Monte Carlo shots). These additions allow the quoted per-logical-qubit error rates to be verified directly. revision: yes
Circularity Check
No circularity: scheme and simulations are self-contained
full rationale
The paper presents a construction for in-situ magic state injection using only syndrome-extraction ancillas on CSS qLDPC codes, supported by a general high-level argument plus explicit circuit-level simulations on two concrete codes under stated depolarizing and asymmetric noise models. No equations define a quantity in terms of itself, no fitted parameters are relabeled as predictions, and no load-bearing steps reduce to self-citations or prior ansatzes by the authors. The simulations constitute independent numerical verification rather than tautological outputs of the input noise model. The generalizability statement rests on the explicit resource claim (native ancillas only) rather than on any definitional equivalence or imported uniqueness theorem.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption CSS qLDPC codes admit transversal or low-weight operations sufficient for in-situ state preparation
Lean theorems connected to this paper
-
IndisputableMonolith/Cost/FunctionalEquation.leanwashburn_uniqueness_aczel unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
We propose the first in-situ magic state injection: a scheme in which logical magic states are directly prepared within a qLDPC memory block, only using resources required for syndrome extraction. We show that our scheme is generalizable to any CSS qLDPC code.
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IndisputableMonolith/Foundation/RealityFromDistinction.leanreality_from_one_distinction unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
The construction uses only the ancilla resources already needed for syndrome extraction... prepare Bell states on the overlaps... post-selection on fixed stabilizers.
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
Reference graph
Works this paper leans on
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[1]
Prepare thekcarrier qubits{Q i }in the +1 eigen- states ofM Qi for alli∈[k]
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[2]
(Such Clifford could be free
Apply the Clifford circuitCon the carrier qubits. (Such Clifford could be free. See discussion in Ap- pendix D)
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[3]
Prepare then−kpeeled qubits in the eigenstates of the single-qubit Paulis inS ′
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[4]
In this way, we injectklogical magic states encoded byLsimultaneously
Measure the stabilizers of the original code, i.e.,S. In this way, we injectklogical magic states encoded byLsimultaneously. A. Analysis of injection error rate Magic state injection schemes rely on encoding a set of qubits into the target codespace via syndrome extraction. This renders all stabilizer outcomes non-deterministic in the first SE round, prov...
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[5]
Bell state on every pair inP; 2.|+⟩onA i \Cfor eachi∈ I; 3.|0⟩onB i \Cfor eachi∈ I
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[6]
! 𝑍̅! : Bell state: Data qubit: Injection site |+⟩|0⟩ 𝑋
the+1eigenstate ofM Qi on eachQ i. Then Eq.(12)holds, i.e., M i|ψin⟩=|ψ in⟩,∀i∈ I. The proof is given in Appendix E. To satisfy injection site independence and compatible pairing, we might not be able to inject the full set ofklogicals. We discuss how to find maximal injectable sets in Appendix B. After fixing the preparation on qubits in supp( X i)∪ supp...
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[7]
Prepare the state as in Theorem 1
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[8]
Perform a round of SE
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[9]
If the first- round measurement outcomes of the fixed stabiliz- ers are not all +1, we discard the shot and restart the injection procedure
Post-select on the fixed stabilizers. If the first- round measurement outcomes of the fixed stabiliz- ers are not all +1, we discard the shot and restart the injection procedure. The corresponding detec- tors are calledfixed-stabilizer detectors
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[10]
We compare the full stabilizer outcome of the second round with that of the first round, and discard the shot if they disagree
Perform a second round of SE. We compare the full stabilizer outcome of the second round with that of the first round, and discard the shot if they disagree. The corresponding detectors are called round-parity detectors
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[11]
number of physical qubits
Perform a furtherr 2 rounds of SE and decode using all retained syndrome information. This protocol is chosen because the dominant contribu- tion to the injection error arises from faults before and during the first SE round. Additional SE rounds can further suppress higher-order contributions, while poten- tially introducing more memory faults. As a poin...
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[12]
Enumerate the Cartesian product Q i Oi to obtain candidateQ
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[13]
, k}, where edge (i, j) meansi, jcannot be injected to- gether because injection site independence is vio- lated
For fixedQ, build a graph on vertices{1, . . . , k}, where edge (i, j) meansi, jcannot be injected to- gether because injection site independence is vio- lated. Any injectable set must be an independent set in this graph. Compute all maximal indepen- dent sets (MISs) as candidates. Noise channel Definition MERR(p) m7→m⊕e, e∼Bernoulli(p) XERR(p) ρ7→(1−p)ρ+...
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[14]
For each physical qubitqin anyC i,j (defined in Eq
For each MIS candidate, enumerate subsets and test compatible pairing using signatures. For each physical qubitqin anyC i,j (defined in Eq. (10)), define its signature σ(q) := 1[q∈C i,j] i,j∈I .(B1) Compatible pairing exists iff every signature class {q:σ(q) =s}has even cardinality. Within each signature class, any disjoint pairing is valid. Appendix C: N...
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[15]
Let L:={ X i, Z i}k i=1 (D1) be the current logical representatives, and letSbe the current stabilizer generator set
Logical representatives reduction We describe a recursive algorithm for transforming the logical representatives to a set ofkphysical qubits. Let L:={ X i, Z i}k i=1 (D1) be the current logical representatives, and letSbe the current stabilizer generator set. 12 The recursive reduction is as follows. Given a non- trivial stabilizer group, do the following:
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Pick a stabilizers∈ Swith wt(s)>1
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[17]
Measure a single-qubit PauliP j that anticommutes withson a qubitj∈supp(s), i.e., {Pj, s}= 0; (D2) denote the measurement outcome bym∈ {±1}
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[18]
Replaces∈ Sby the measuredP j
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[19]
peels off
Update any remaining stabilizers and logical repre- sentatives that anticommute withP j by multiply- ing them by the replaced stabilizers. To write this explicitly, let S \ {s}={g a}n−k−1 a=1 .(D3) The updated generator set is S ′ :={mP j} ∪ {g ′ a}n−k−1 a=1 ,(D4) where g′ a = ( ga,[g a, Pj] = 0, gas,{g a, Pj}= 0. (D5) Similarly, each logical representati...
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[20]
(D5) and (D6) preserves the logical subsystem for three rea- sons
Logical information preservation During the reduction step, the update rule in Eqs. (D5) and (D6) preserves the logical subsystem for three rea- sons. First, the measurement ofP j reveals no logical infor- mation. Let|ϕ⟩be any state in the codespace ofS, so in particulars|ϕ⟩=|ϕ⟩. Using Eq. (D2), ⟨ϕ|P j |ϕ⟩=⟨ϕ|sP js|ϕ⟩=− ⟨ϕ|P j |ϕ⟩= 0.(D11) Hence the two o...
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[21]
Detectors are defined so that, in the absence of noise, every detector outcome is deterministically 0
Definitions Adetectoris a binary parity check built from a spec- ified subset of measurement-record bits. Detectors are defined so that, in the absence of noise, every detector outcome is deterministically 0. Noise can toggle some of these detector outcomes to 1. A DEM records how elementary stochastic mechanisms toggle detector outcomes and tracked logic...
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[22]
The most dangerous first-order mechanisms are those with Le ̸=∅, D e =∅,(F2) because they flip one or more injected logical observables without triggering any detector
Error mechanism counting For MSI, the tracked logical observables are the in- jected logical observables indexed byI, so we takeL e ⊆ I. The most dangerous first-order mechanisms are those with Le ̸=∅, D e =∅,(F2) because they flip one or more injected logical observables without triggering any detector. Such mechanisms evade postselection and also leave ...
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[23]
, N D}be the set of postselection detec- tors
Postselection and discard rate LetP⊆ {1, . . . , N D}be the set of postselection detec- tors. In our simulations,Pconsists of (i) fixed-stabilizer detectors from the first SE round and (ii) round-parity detectors comparing the first two SE rounds. A shot is acceptedif and only if all detectors inPare 0; otherwise the shot is discarded. Define the set ofpo...
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[24]
Let Pfix ⊆Pdenote the set of fixed-stabilizer detectors in the first SE round, and let|F|:=|P fix|be the number of fixed stabilizers
Acceptance factor decomposition To explain why the discard rate varies little across opti- mized initial configurations, it is useful to separate mech- anisms caught immediately by fixed-stabilizer detectors from those caught only by round-parity detectors. Let Pfix ⊆Pdenote the set of fixed-stabilizer detectors in the first SE round, and let|F|:=|P fix|b...
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[25]
Explanation of similar discard rate across different initial configurations p|I| |F|(a fix, a par|fix)r UP disc(p)r MC disc(p) 10−4 1 26 (0.9563, 0.8018) 0.2333 0.2331 10−4 2 32 (0.9487, 0.8062) 0.2351 0.2352 10−4 3 31 (0.9495, 0.8056) 0.2351 0.2346 10−4 4 32 (0.9484, 0.8061) 0.2355 0.2352 10−4 5 28 (0.9517, 0.8040) 0.2348 0.2346 10−4 6 18 (0.9650, 0.7965...
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[26]
An injectable set Igives a compatible pairingP={ {u t, vt} }T t=1
Sets and notation Assume we have already settled down the initializa- tions for the qubits in supp( X i)∪supp( Z i), and the pre- pared state|ψ in⟩is stabilized by a set ofinitial stabilizers R, distinct from thecode stabilizersS. An injectable set Igives a compatible pairingP={ {u t, vt} }T t=1. So by Theorem 1,Rincludes 1.X ut Xvt , Z ut Zvt,∀t∈[T], 2.M...
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[27]
•If qubitjis initialized in theZbasis (b j =Z), its reset error is modeled as a PauliX j applied after a perfect reset
Error model and protection Following [3, 4], we adopt a simple noise model for single-qubit initialization (reset) errors: •If qubitjis initialized in theXbasis (b j =X), its reset error is modeled as a PauliZ j applied after a perfect reset. •If qubitjis initialized in theZbasis (b j =Z), its reset error is modeled as a PauliX j applied after a perfect r...
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[28]
MILP: Decision variables We introduce three families of binary decision vari- ables. a. Basis choice onU.For each qubitj∈U, we define xj ∈ {0,1},(G8) interpreted as xj = 1⇐ ⇒initialize qubitjin theXbasis, xj = 0⇐ ⇒initialize qubitjin theZbasis. (G9) b. Row-fixed indicators.For eachX-type rowrwith suppX U (r)̸=∅, we introduce f X r ∈ {0,1},(G10) indicating...
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Fixed stabilizers and basis compatibility.If anX- type rowris fixed then all uninitialized qubits in its support must be in theXbasis; similarly forZ-type rows and theZbasis
MILP: Constraints a. Fixed stabilizers and basis compatibility.If anX- type rowris fixed then all uninitialized qubits in its support must be in theXbasis; similarly forZ-type rows and theZbasis. This yields the implications f X r = 1 =⇒x j = 1∀j∈supp X U (r), f Z r = 1 =⇒x j = 0∀j∈supp Z U(r). (G13) We encode these as the linear inequalities f X r ≤x j,∀...
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This is captured by the objective max X j∈I pj.(G19) Together with Eq
MILP: Objective The goal of the optimization is to maximize the number of qubits on the supports of the injected logicals whose reset errors are detected by some fixed stabilizer. This is captured by the objective max X j∈I pj.(G19) Together with Eq. (G18), the complete optimization problem is: max {xj }j∈U ,{f X r }, {f Z r },{p j }j∈I X j∈I pj f X r ≤x ...
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