hdh 0.0.3

Hybrid Dependency Hypergraphs for quantum computation: translation, visualization, and partitioning.

hdh

Hybrid Dependency Hypergraphs for Quantum Computation
· MIT Licensed · Version 0.0.2 · Author: Maria Gragera Garces

Work in Progress — Preparing for 1.0

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What is HDH?

HDH (Hybrid Dependency Hypergraph) is an intermediate representation designed to describe quantum computations in a model-agnostic way. It provides a unified structure that makes it easier to:

• Translate quantum programs (e.g., from Qiskit or QASM) into a common hypergraph format
• Analyze and visualize the logical and temporal dependencies within a computation
• Partition workloads across devices using tools like METIS or KaHyPar, taking into account hardware and network constraints

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Current Capabilities

• Qiskit circuit translation
• OpenQASM 2.0 file parsing
• Graph-based printing and canonical formatting
• Partitioning with METIS using custom HDH-to-graph translation
• Model-specific abstractions for:
  • Quantum Circuits
  • Measurement-Based Quantum Computing (MBQC)
  • Quantum Walks
  • Quantum Cellular Automata (QCA)
• Analysis tools for:
  • Cut cost estimation across partitions
  • Partition size reporting
  • Parallelism tracking by time step
  • Integration with networkx and metis

Includes test examples for:

• Circuit translation (test_convert_from_qiskit.py)
• QASM import (test_convert_from_qasm.py)
• MBQC (mbqc_test.py)
• Quantum Walks (qw_test.py)
• Quantum Cellular Automata (qca_test.py)
• Protocol demos (teleportation_protocol_logo.py)

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Installation

pip install hdh

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Quickstart

From Qiskit

from qiskit import QuantumCircuit
from hdh.frontend.qiskit_loader import convert_qiskit_circuit_to_hdh

qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0, 1)

hdh = convert_qiskit_circuit_to_hdh(qc)
hdh.print()

From QASM file

from hdh.frontend.qasm_loader import convert_qasm_file_to_hdh

hdh = convert_qasm_file_to_hdh("test_qasm_file.qasm")
hdh.print()

Partitioning

from hdh.partitioning.metis_partition import compute_metis_partition

partition = compute_metis_partition(hdh, num_bins=2)
print(partition)

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Example Use Cases

• Visualize quantum protocols (e.g., teleportation)
• Analyze dependencies in quantum walk evolutions
• Explore entanglement flow in MBQC patterns
• Partition large circuits across heterogeneous QPUs

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Coming Soon

• Compatibility with Cirq, Braket, and Pennylane
• Full graphical UI for HDH visualization
• Native noise-aware binning strategies
• Better cut handling for distributed execution

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Tests and Demos

All tests are under tests/ and can be run with:

pytest

If you're interested in the HDH of a specific model, see:

• mbqc_test.py for MBQC circuits
• qca_test.py for Cellular Automata
• qw_test.py for Quantum Walks
• teleportation_protocol_logo.py for a protocol-specific demo

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Contributing

Pull requests welcome. Please open an issue or get in touch if you're interested in:

• SDK compatibility
• Optimization strategies
• Frontend tools (visualization, benchmarking)

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Citation

More formal citation and paper preprint coming soon. Stay tuned for updates.