Qyantram: A Transparent and Verifiable Quantum Computing Platform

Most quantum circuit platforms focus on idealized circuit assembly and simulation, hiding hardware compilation, error identification, and variational model training behind black-box operations. QYANTRAM addresses this gap through an open platform comprising four subsystems, built around evidence-backed results and independent verification. Its staged compilation pipeline makes every transformation traceable, while the router publishes rejected SWAP candidates and their scores for transparent decision-making. Verification exploits inactive qubits remaining in the |0> state, reducing complexity from 2^N to 2^k for k active qubits. This mathematically exact reduction enables full pre-compilation verification on 127- and 156-qubit layouts, achieving approximately 10,000x speed-ups with execution times below one millisecond. The error identification engine exhaustively evaluates all Pauli error patterns without sampling, matching closed-form predictions within 2.8e-17. Its machine-learning engine achieves numerical agreement within 2.0e-15 of qiskit.quantum_info while training 25-50 times faster. The router introduces approximately 1.27x more SWAP gates than Qiskit's SABRE due to its omission of optimization, trading routing efficiency for complete decision transparency and traceability.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-02
DOI
https://doi.org/10.48550/arxiv.2611.03262
Primary Topic
Quantum Computing Algorithms and Architecture
Type
preprint
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preprint

Qyantram: A Transparent and Verifiable Quantum Computing Platform

Uday Wad, Sharyu Kekane, Abhushan Bokade, Sadique Khatib et al.
arXiv (Cornell University)
Quantum Computing Algorithms and Architecture
preprint

Qyantram: A Transparent and Verifiable Quantum Computing Platform

Uday Wad, Sharyu Kekane, Abhushan Bokade, Sadique Khatib, S. M. Kamalapur, Y. D. Bhise
preprint en

Abstract

Most quantum circuit platforms focus on idealized circuit assembly and simulation, hiding hardware compilation, error identification, and variational model training behind black-box operations. QYANTRAM addresses this gap through an open platform comprising four subsystems, built around evidence-backed results and independent verification. Its staged compilation pipeline makes every transformation traceable, while the router publishes rejected SWAP candidates and their scores for transparent decision-making. Verification exploits inactive qubits remaining in the |0> state, reducing complexity from 2^N to 2^k for k active qubits. This mathematically exact reduction enables full pre-compilation verification on 127- and 156-qubit layouts, achieving approximately 10,000x speed-ups with execution times below one millisecond. The error identification engine exhaustively evaluates all Pauli error patterns without sampling, matching closed-form predictions within 2.8e-17. Its machine-learning engine achieves numerical agreement within 2.0e-15 of qiskit.quantum_info while training 25-50 times faster. The router introduces approximately 1.27x more SWAP gates than Qiskit's SABRE due to its omission of optimization, trading routing efficiency for complete decision transparency and traceability.

arXiv (Cornell University)
Quantum Computing Algorithms and Architecture
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Qyantram: A Transparent and Verifiable Quantum Computing Platform — Uday Wad, Sharyu Kekane, et al. · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS