ArticleNPJ quantum information2025
Contextual subspace variational quantum eigensolver calculation of the dissociation curve of molecular nitrogen on a superconducting quantum computer.
Article in NPJ quantum information, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Demonstration of efficient predictive surrogates for large-scale quantum processors.Nature communications · 2026Article
- Selected Configuration Interaction Using Time-Evolved Population Statistics.Journal of chemical theory and computation · 2026Article
- Quantum-machine-assisted drug discovery.npj drug discovery · 2026Review
- Photonic variational quantum eigensolver for NISQ-compatible quantum technology.Nano convergence · 2025Review
- Chemistry beyond the scale of exact diagonalization on a quantum-centric supercomputer.Science advances · 2025Article
- Accurate quantum-centric simulations of intermolecular interactions.Communications physics · 2025Article
- Synergizing quantum techniques with machine learning for advancing drug discovery challenge.Scientific reports · 2024Article
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Authors and funding
5 authors.
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Abstract
We present an experimental demonstration of the Contextual Subspace Variational Quantum Eigensolver on superconducting hardware. Calculating the potential energy curve of molecular nitrogen proves challenging for many conventional quantum chemistry techniques, since static correlation dominates in the dissociation limit. Our quantum simulations retain good agreement with the Full Configuration Interaction energy, outperforming all benchmarked single-reference wavefunction techniques in capturing the bond-breaking appropriately. Moreover, our methodology is competitive with multiconfigurational approaches but at a saving of quantum resource, meaning larger active spaces can be treated for a fixed qubit allowance. To achieve this result, we deploy an error mitigation/suppression strategy comprised of Dynamical Decoupling, Measurement-Error Mitigation and Zero-Noise Extrapolation. Circuit parallelization also provides passive noise-averaging and improves the effective shot yield to reduce the measurement overhead. Furthermore, we introduce a modified adaptive ansatz construction algorithm that incorporates hardware awareness into our variational circuits, minimizing the transpilation cost for the target qubit topology.
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