Evaluating Verified Autonomy in Quantum Engineering

arXiv:2609.17439 · quant-ph, cs.AI · Submitted 2026-09-15 · Read on arXiv

quant-ph, cs.AI

Submitted: 2026-09-15

Updated: 2026-09-15

Comments: 10 pages, 4 figures

Code: https://github.com/harbor-framework/harbor

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 20× in this paper · explained in 2 episodes
• Calibration — 17× in this paper · explained in 7 episodes
• Verification — 5× in this paper · explained in 2 episodes
• Benchmarking — 4× in this paper · explained in 3 episodes
• Entanglement — 4× in this paper · explained in 3 episodes
• Agentic System — 3× in this paper · explained in 2 episodes
• Model Context Protocol — 3× in this paper
• AI Agents — 2× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Agentic AI — 2× in this paper · explained in 1 episode
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Admissibility — 1× in this paper · explained in 2 episodes
• Agent Harness — 1× in this paper · explained in 2 episodes
• Agentic AI systems — 1× in this paper · explained in 1 episode
• Agentic Workflows — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Hamiltonian Learning — 1× in this paper · explained in 2 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Quantum Circuits — 1× in this paper · explained in 2 episodes
• Quantum Physics — 1× in this paper · explained in 10 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Assessing requirements to scale to practical quantum advantage
• How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits
• Vibe Calibration: Autonomous Bring-up of a 112-Qubit Superconducting Quantum Processor by a Skill-Orchestrating Language Agent
• Towards autonomous quantum physics research using LLM agents with access to intelligent tools
• Agentic AI for Scientific Reasoning in Autonomous Quantum Sensing Experiments
• Lowering the implementation barrier of neutral-atom quantum computing with agentic workflows
• QAgent: An LLM-based Multi-Agent System for Autonomous OpenQASM programming
• Autonomous Quantum Simulation through Large Language Model Agents
• QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding
• QuantumBench: A Benchmark for Quantum Problem Solving
• Surface code logical operations on a superconducting quantum processor
• Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
• Quantum computing with Qiskit
• gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy
• AutomationBench

Related papers

• Reconquering Bell sampling on qudits: stabilizer learning and testing, quantum pseudorandomness bounds, and more
• Encrypted clones can leak: Classification of informative subsets in Quantum Encrypted Cloning
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• Theory of quantum-enhanced interferometry with general Markovian light sources
• A convergent hierarchy of spectral gap certificates for qubit Hamiltonians
• Universal Bound and Phase Transition in Many-Body Fermionic Non-Gaussianity