Supplementary Material for paper "Shaking Up Quantum Simulators with Fuzzing and Rigour"

This repository provides tools for constructing quantum circuits and validating quantum validators using the Alloy modeling language to encode standard quantum gates.

For a more detailed description, refer to the README.md file.

Repository Contents

Alloy-model - Contains our formal specification of quantum gates

xml_seeds - Test circuits generated with Alloy, used in our paper

execution Logs - Detailed simulation results

post-processing - Analysis results organized by experiment type:

Chi-square and Jensen-Shannon Divergence analysis

Memory utilization benchmarks

Shot count optimization data

Quantum invariant demonstrations

.├── Alloy-model│   ├── README.md│   └── standard_gate_library.als├── README.md├── execution_logs├── fuzzQ.py├── post-processing│   ├── chi_js│   ├── invariants│   │   ├── GHZ│   │   ├── Idempotence│   │   └── Symmetry│   ├── memory│   │   └── xml_instances│   ├── shots│   └── state_vectors_mismatch_Accumulation_of_Numerical_Errors│       └── 3q15g_noSwap└── xml_seeds

Parsing Standard Gates

The Alloy model, Alloy-model/standard_gate_library.als, encodes standard quantum gates such as XGate, HGate, and CXGate. Using the Alloy tool, we generate XML-based test seeds representing valid quantum circuits that adhere to the model’s constraints.  

The Python script fuzzQ.py processes these XML instances, converting them into executable Qiskit quantum circuits. It then simulates the circuits across various backends, providing detailed measurement results (outcome probabilities) to facilitate the assessment and validation of quantum algorithms.  

Usage

python fuzzQ.py

The script processes Alloy-generated XML instances, converts them to executable quantum circuits, and simulates them to provide measurement outcome probabilities.

Batch Processing

Process multiple circuits using the included shell script:

./process_xml.sh