arXiv (All)
open access
KrMM Recurrences: HPC-Enhanced Estimators for Nonlinear Classical Shadows
While quantum technologies are rapidly evolving, near-term applications heavily rely on hybrid quantum-classical paradigms. Among these, the classical shadows framework has gained a lot of traction, not only for quantum information science, but also for the development and verification of quantum ha
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
- KrMM Recurrences: HPC-Enhanced Estimators for Nonlinear Classical Shadows#1381187
- Deep thermalization and Hilbert space ergodicity#1078319
- Optimal classical shadow estimation of unitary channels at Heisenberg limit#1141568
- Fast surrogate modelling of EIT in atomic quantum systems using LSTM neural networks#1035322
- Hyperbolic Restricted Boltzmann Machine Neural Quantum State#1061937
Record · ID 1401638
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