arXiv (All)
open access
Optimal Quantum Likelihood Estimation
A hybrid quantum-classical algorithm is a computational scheme in which quantum circuits are used to extract information that is then processed by a classical routine to guide subsequent quantum operations. These algorithms are especially valuable in the noisy intermediate-scale quantum (NISQ) era,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Optimal Quantum Likelihood Estimation#920218
- Quantum Algorithms for Computational Fluid Dynamics#1145129
- Hybrid Quantum Temporal Convolutional Networks#1041455
- Evidence for effectively constant shot complexity in the quantum approximate optimization algorithm without per-instance optimization#925814
- Strategy optimization for Bayesian quantum parameter estimation with finite copies: Adaptive greedy, parallel, sequential, and general strategies#1012124
Record · ID 924449
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive