A Z3 discrete time crystal is realized in superconducting qutrits using native chiral interactions, producing robust period-tripling independent of initial state.
Technology and performance benchmarks of IQM’s 20-qubit quantum computer
9 Pith papers cite this work. Polarity classification is still indexing.
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Introduces QCalEval benchmark showing best zero-shot VLM score of 72.3 on quantum calibration plots, with fine-tuning and in-context learning effects varying by model type.
A new method for unitary synthesis on quantum hardware cuts CNOT gates by up to 36% and compiles up to 553 times faster than standard tools on square and heavy-hex lattices.
QIML uses a quantum-trained Q-Prior to enhance classical autoregressive predictions of spatiotemporal chaos, improving accuracy by up to 17.25% and full-spectrum fidelity by up to 29.36% while enabling stable forecasts for 3D turbulent channel flow.
Cross-Kerr coupling in the two-photon bosonic regime of a SQUID-coupled phase qubit never vanishes due to potential asymmetry and coupler nonlinearity, with explicit limits on the number of coherent states needed for the approximation.
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
A hardware-calibrated truncated QFT reduces gate count 31-44% at 30 qubits while bounding total variation distance error by O(2^{-d}) and outperforming full QFT under moderate noise.
Supervised ML trained on simulated gate set tomography data predicts noise models to build cross-hardware quantum emulators, validated by matching H2 unitary coupled cluster energy results to real hardware within 0.128% relative error.
A QDMI-based adapter for IQM quantum hardware enables reusable integration with Slurm and Qiskit in HPC centers, with open-source code provided.
citing papers explorer
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A Qutrit Time Crystal Stabilized with Native Chiral Interactions
A Z3 discrete time crystal is realized in superconducting qutrits using native chiral interactions, producing robust period-tripling independent of initial state.
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QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding
Introduces QCalEval benchmark showing best zero-shot VLM score of 72.3 on quantum calibration plots, with fine-tuning and in-context learning effects varying by model type.
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Architecture-aware Unitary Synthesis
A new method for unitary synthesis on quantum hardware cuts CNOT gates by up to 36% and compiles up to 553 times faster than standard tools on square and heavy-hex lattices.
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Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantage
QIML uses a quantum-trained Q-Prior to enhance classical autoregressive predictions of spatiotemporal chaos, improving accuracy by up to 17.25% and full-spectrum fidelity by up to 29.36% while enabling stable forecasts for 3D turbulent channel flow.
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Two-photon coupling via Josephson element II: Interaction dressing, cross-Kerr coupling, and limits of low-energy bosonic model
Cross-Kerr coupling in the two-photon bosonic regime of a SQUID-coupled phase qubit never vanishes due to potential asymmetry and coupler nonlinearity, with explicit limits on the number of coherent states needed for the approximation.
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Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
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Phase-Fidelity-Aware Truncated Quantum Fourier Transform for Scalable Phase Estimation on NISQ Hardware
A hardware-calibrated truncated QFT reduces gate count 31-44% at 30 qubits while bounding total variation distance error by O(2^{-d}) and outperforming full QFT under moderate noise.
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Designing a Machine Learning-Driven, Cross-Hardware Emulator for Noisy Quantum Computers with Gate-Based Protocols
Supervised ML trained on simulated gate set tomography data predicts noise models to build cross-hardware quantum emulators, validated by matching H2 unitary coupled cluster energy results to real hardware within 0.128% relative error.
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Practical HPCQC Integration with QDMI: A Real-Hardware Case Study with IQM Systems
A QDMI-based adapter for IQM quantum hardware enables reusable integration with Slurm and Qiskit in HPC centers, with open-source code provided.