hamqasbench-hamiltonian-qas-benchmark

name	hamqasbench-hamiltonian-qas-benchmark
description	Hamiltonian-informed diagnostic benchmark for Quantum Architecture Search (QAS). Organizes molecules into structural tiers via Pauli operator fingerprints, computational basis representation, and ground-state entanglement. Detects failure modes invisible to energy-only metrics: over-parameterization, eigenstate commitment, representation bottleneck, topology-induced routing failure. Activation: QAS benchmark, Hamiltonian structure, quantum architecture search evaluation, circuit structure analysis, variational circuit diagnostics
metadata	{"arxiv_id":"2607.04845","published":"2026-07-06","authors":"HamQASBench authors","tags":["quantum","architecture-search","benchmark","hamiltonian","variational"]}

HamQASBench: Hamiltonian-Informed QAS Benchmark

Core Methodology

Problem: Existing QAS benchmarks organize by molecular identity or qubit count — criteria agnostic to Hamiltonian structure. They rely solely on energy accuracy, which cannot detect structural failures (over-parameterization, eigenstate commitment under degeneracy, representation bottleneck).

Solution: HamQASBench organizes 11 molecules into 5 structural tiers via fingerprints from:

1. Pauli operator basis — Hamiltonian term structure
2. Computational basis representation — sparsity patterns
3. Ground-state entanglement — per-qubit entanglement analysis

Key diagnostic tools:

• Post-hoc critical-structure extraction: identifies minimal circuits consistent with each tier's requirements
• Per-qubit entanglement analysis
• Pairwise state fidelity (beyond energy accuracy)

Failure Modes Detected

Failure Mode	Regime	Detection Method
Over-parameterization	Minimalism regime	Critical-structure extraction vs actual circuit size
Eigenstate commitment	Degenerate systems	Pairwise state fidelity
Representation bottleneck	Strongly correlated systems	Per-qubit entanglement analysis
Topology-induced routing failure	Hardware-constrained search	Circuit topology vs Hamiltonian structure
Search space growth	Scalability	Circuit complexity vs qubit count

Usage Patterns

Pattern 1: QAS Method Evaluation

When evaluating a QAS method, use Hamiltonian-informed tiering instead of molecule-by-molecule benchmarking:

1. Extract Pauli fingerprints from target Hamiltonian
2. Assign molecule to structural tier (1-5)
3. Run QAS method, measure per-tier performance
4. Apply critical-structure extraction to check minimal circuit consistency
5. Compute per-qubit entanglement and pairwise fidelity

Pattern 2: Detecting Structural Failures

When energy accuracy looks good but results are suspect:

1. Check per-qubit entanglement distribution vs expected
2. Run pairwise state fidelity between QAS output and known structure
3. Extract minimal circuit from result and compare to tier requirements
4. Flag over-parameterization if circuit >> minimal requirement

Pattern 3: Hardware-Aware QAS

When evaluating QAS under hardware topology constraints:

1. Map Hamiltonian structure to device topology
2. Identify routing conflicts (structure vs connectivity mismatch)
3. Measure topology-induced performance degradation per tier

Activation Keywords

• quantum architecture search benchmark
• Hamiltonian-informed benchmark
• QAS evaluation
• variational circuit structure analysis
• quantum circuit diagnostics
• ground-state entanglement analysis
• QAS failure mode detection
• 量子架构搜索基准
• 哈密顿量结构分析

Tools Used

• terminal: Run benchmarking scripts, analyze results
• write_file: Create benchmark configurations
• search_files: Check existing QAS skills

Related Skills

• quantum-neural-architecture-search — QAS methodology
• magic-informed-quantum-architecture-search — magic-state-based QAS
• zero-shot-quantum-nas — zero-shot QAS approach
• quantum-ml-patterns — QML evaluation patterns