hdh 0.2

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

Hybrid Dependency Hypergraphs for Quantum Computation

· MIT Licensed · · Author: Maria Gragera Garces

Work in Progress - Preparing for 1.0

Documentation can be found at: https://grageragarces.github.io/HDH/

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What is HDH?

HDH (Hybrid Dependency Hypergraph) is an intermediate directed hypergraph-based representation designed to encode the dependecies arising in any quantum workload. It provides a unified structure that makes it easier to:

• Translate quantum programs (e.g., a circuit or a mbqc pattern) into a unified hypergraph format
• Analyze and visualize the logical and temporal dependencies within a computation
• Partition workloads across devices, taking into account hardware and network constraints

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Current Capabilities

• Qiskit, Braket, Cirq and Pennylane circuit mappings to HDHs
• OpenQASM 2.0 file parsing
• Model-specific abstractions for:
  • Quantum Circuits
  • Measurement-Based Quantum Computing (MBQC)
  • Quantum Walks
  • Quantum Cellular Automata (QCA)
• Capability to partition HDHs and evaluate partitions

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Installation

pip install hdh

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Quickstart

From Qiskit

from qiskit import QuantumCircuit
from hdh.converters import from_qiskit
from hdh.visualize import plot_hdh

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

hdh = from_qiskit(qc)

plot_hdh(hdh)

From QASM file

from hdh.converters import from_qasm
from hdh.visualize import plot_hdh

qasm_path = os.path.join(os.path.dirname(__file__), 'test_qasm_file.qasm')
hdh = from_qasm('file', qasm_path)

plot_hdh(hdh)

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Tests and Demos

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

pytest

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Contributing

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

• SDK compatibility
• Frontend tools (visualization, benchmarking)

or if you've found a bug!

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Citation

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