QuPRS("kyu-parse") is a tool for Quantum Circuit tool integrate Path-sum Reduction and Solver.
In quantum computing, verifying whether an optimized or compiled quantum circuit is functionally equivalent to the original circuit is a crucial task. QuPRS aims to solve this problem, and its features include:
- Novel verification method: Based on pathsum, which is a circuit representation method different from traditional matrix products.
- Multiple verification strategies:
- Hybrid mode (RR + WMC): Combines the efficiency of reduction rules and the completeness of weighted model counting.
- Reduction rules only (RR): Extremely fast, suitable for circuits that can be simplified by local rules.
- WMC only: A powerful SAT-based method for more complex circuit structures.
- Seamless integration with Qiskit ecosystem: Circuits can be directly loaded from Qiskit
QuantumCircuitobjects or QASM files.
It is recommended to install QuPRS in a virtual environment.
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Create and activate a Conda virtual environment:
conda create --name QuPRS python=3.12 # Or your preferred Python version conda activate QuPRS -
Install
QuPRSusing pip:pip install QuPRS
or install
QuPRSlatest commit:pip install git+https://github.com/PhysicsQoo/QuPRS.git
This tool can build quantum circuit using path-sum formulation.
First, import the necessary components from the QuPRS library.
from QuPRS.pathsum import PathSumCreate a pathsum Circuit
You can create a PathSum.QuantumCircuit object directly:
qubit_num = 2
circuit = PathSum.QuantumCircuit(qubit_num)
circuit = circuit.h(0) # Apply Hadamard gate to qubit 0
circuit = circuit.h(0) # Apply Hadamard gate to qubit 0 again (H*H = I)
# Add more gates as needed
# e.g., circuit = circuit.cx(0, 1)pathsum supports importing circuits from QASM files or strings.
From a QASM file:
filename = "my_circuit.qasm"
# Ensure my_circuit.qasm exists and contains valid QASM code
# Example my_circuit.qasm:
# OPENQASM 2.0;
# include "qelib1.inc";
# qreg q[2];
# h q[0];
# cx q[0],q[1];
circuit = PathSum.load_from_qasm_file(filename)Or
qasm_str = """
OPENQASM 2.0;
include "qelib1.inc";
qreg q[2];
h q[0];
cx q[0],q[1];
"""
circuit = PathSum.load_from_qasm_str(qasm_str)QuPRS provides tools for checking the equivalence of two quantum circuits, potentially imported from Qiskit or QASM files.
Importing Circuits for Equivalence Checking You can load circuits from QASM files or define them directly using Qiskit for comparison.
- Load from QASM files
# Assuming circuit1.qasm and circuit2.qasm exist from QuPRS.interface.load_qiskit import load_circuit circuit1 = load_circuit("circuit1.qasm") circuit2 = load_circuit("circuit2.qasm")
- Direct import from Qiskit
QuantumCircuitobjects:from qiskit import QuantumCircuit # Define circuit1 using Qiskit circuit1 = QuantumCircuit(2) circuit1.h(1) circuit1.cx(0, 1) circuit1.h(1) # Define circuit2 using Qiskit circuit2 = QuantumCircuit(2) circuit2.cz(0, 1)
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Hybrid: Reduction Rules (RR) and Weighted Model Counting (WMC)
This method combines RR with WMC for equivalence checking.
from QuPRS import check_equivalence result = check_equivalence(circuit1, circuit2, method = "hybrid",)
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Using Reduction Rules (RR)
from QuPRS import check_equivalence result = check_equivalence(circuit1, circuit2, method = "reduction_rules",)
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WMC only (without RR)
To perform equivalence checking using only WMC, you need to disable the Reduction Rules switch.
from QuPRS import check_equivalence result = check_equivalence(circuit1, circuit2, method = "wmc_only",)
If you use QuPRS in your research, please consider citing it.
This code is associated with a forthcoming publication. Please cite this repository for now, and check back for the full paper citation.
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The original source code of this project is licensed under the MIT License.
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This project utilizes and depends on several third-party components and libraries, which are governed by their own licenses. For detailed copyright notices and the full license texts of these components, please see the NOTICE.md file.
This project utilizes gpmc, a binary component developed by Kenji Hashimoto, for parts of its Weighted Model Counting functionality.