arXiv (All)
open access
Exponential quantum advantage in processing massive classical data
Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In this work, we prove that a small quantum computer of polylogarithmic size can perform large-scale classification and dimension reduction on massive classical
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
- Hybrid quantum-classical algorithms for high performance computing#357463
- Demonstration of efficient predictive surrogates for large-scale quantum processors.#239670
- An in-principle super-polynomial quantum advantage for approximating combinatorial optimization problems via computational learning theory.#136047
- An Overview of Quantum Algorithms and their Impact#97292
- Practical Considerations for Processing Massive Classical Data via Quantum Oracle Sketching#1071329
Record · ID 1157271
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