TensorCircuit-NG: Agentic Quantum Research

From published quantum knowledge to executable research infrastructure. TensorCircuit-NG gives AI agents a high-performance runtime for scientific discovery, algorithm design, quantum simulation, execution optimization, validation, and research artifact generation.

~/research/discovery - bash

Agentic Research Capabilities

📄

arxiv-reproduce

Turns published methods into runnable, metadata-rich research artifacts with implementation and validation context.

performance-optimize

Optimizes scientific workloads through JIT compilation, vectorized execution, memory planning, and backend-aware performance tuning.

🔍

meta-explorer

Explores quantum algorithm architectures, ansatzes, and optimization strategies across multiple research frontiers.

🌹

tc-rosetta

Translates quantum workflows from Qiskit, PennyLane, and other frameworks into optimized TensorCircuit-NG implementations.

🎨

demo-generator

Turns scientific scripts and research results into interactive demos and shareable applications for exploration and communication.

⚖️

code-reviewer

Audits mathematical correctness, backend compatibility, reproducibility, and performance before research artifacts are delivered.

Get Started with Agentic TC-NG See ORBIT-Q benchmark evidence Return to Main Documentation