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A Scalable Pipeline for Processing Quantum Circuits Beyond 1,000,000 Qubits

0 starsPython

Quantum hardware now fault-tolerant without extra engineering

by KenographerPrim·Jul 11, 2026·4 points·2 comments

AI Analysis

Pass

Distributing closed-source binaries for quantum error correction claims zero scientific trust.

Weaknesses
  • Closed-source .pyd binaries prevent verification of the 'analytic' math claims.
  • Zero stars or forks suggests no community validation of the benchmark results.
Target Audience

Quantum computing researchers and hardware engineers

Post Description

Before you say it's impossible, please go try.

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CIQA, an analytic Quantum Error Correction code, is now freely accessible on GitHub alongside CIQS, the 'million-qubit compiler'.

Here's a brief overview of the stack:

1. CIQS - An analytic circuit transpilation pipeline (no heuristics, no tunable parameters). It passed the full IBM Benchpress transpilation suite (892/892 tests) in 75 minutes on older hardware, while Qiskit took 17+ hours. It scales linearly to 1M+ qubits on the same harness (that is one million and above).

2. CIQA - An analytic 1:5 QEC that enables full active computation and complete Pauli correction at depth on existing hardware. On real quantum hardware, it delivered a mean fidelity improvement of up to +0.832 over bare qubits. On the same hardware, it successfully ran the full Hayden-Preskill black hole circuit, preventing early decoherence, and enabling the first observation of black hole evaporation past the Page time.

CIQS and CIQA were validated on IBM Heron r2 during real, deep computation runs. Both natively handle quDits, and both are hardware-agnostic.

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CIQA is added to the CIQS GitHub repository as part of the full pipeline. CIQA can integrate any stack, but when paired with the CIQS compiler, the pipeline automatically isolates the CIQA encoding prefix (no extra coding needed).

All benchmarks are documented and public, alongside published papers. All links are in the GitHub README.

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## Note on CIQA's overhead

5 physical qubits from the [[5,1,3]] perfect quantum code layout + 2 dedicated ancilla qudits per logical block (one per channel) for syndrome extraction. For a 156-physical-qubit QPU: 156/7 ≈ 22.

For 156 physical qubits, CIQA delivers 22 fully protected logical qubits allowing deep computation on real QPU, today.

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What experiment will you attempt first with it? Feedback is welcome.

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