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QASM2 Circuit Optimization with PyZX: Handling 'if' and 'reset' Errors
Hello everyone,
I’m currently working on circuit optimization using the pyzx library. My goal is to take a QASM2 circuit as input, optimize it, and return the optimized circuit.
However, I'm encountering issues with certain QASM2 grammar elements, particularly "if" and "reset" statements. I get the following error:
TypeError: Invalid specification c0==1
I'm trying to determine whether this issue is due to the pyzx library not fully supporting the QASM2 grammar or if there's something wrong with my approach.
Here is the function I’ve written to optimize the circuit:
def optimize(circuit: str) -> str:
"""
Optimize a circuit.
@param: circuit to optimize in QASM2
@return: optimized circuit.
"""
c = zx.Circuit.from_qasm(circuit)
g = c.to_graph()
zx.full_reduce(g, quiet=True)
c_opt = zx.extract_circuit(g.copy())
int_str = zx.Circuit.to_qasm(c_opt)
return int_strAnd here is an example of a circuit that leads to the error:
OPENQASM 2.0;
include "qelib1.inc";
qreg q[18];
creg c[14];
h q[0];
h q[1];
h q[2];
h q[3];
h q[4];
h q[5];
cx q[0],q[6];
cx q[1],q[8];
cx q[2],q[10];
cx q[3],q[6];
cx q[3],q[7];
cx q[4],q[8];
cx q[4],q[9];
cx q[5],q[10];
cx q[5],q[11];
x q[6];
x q[8];
x q[9];
x q[10];
x q[11];
reset q[13];
reset q[14];
reset q[15];
reset q[16];
reset q[17];
measure q[12] -> c[12];
measure q[0] -> c[0];
measure q[1] -> c[1];
measure q[2] -> c[2];
measure q[3] -> c[3];
measure q[4] -> c[4];
measure q[5] -> c[5];
measure q[6] -> c[6];
measure q[7] -> c[7];
measure q[8] -> c[8];
measure q[9] -> c[9];
measure q[10] -> c[10];
measure q[11] -> c[11];
Is this a limitation of the pyzx library in handling the full QASM2 grammar, or am I missing something in the code?
Any guidance or suggestions would be greatly appreciated! Thank you in advance.
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4
Posted by lgh •
The issue with your code is that it's trying to use non-unitary operations in a unitary-only framework. To address this, you can use unitary reconstruction, which introduces new qubits and applies the principle of deferred measurement. I wrote a library that does exactly this.
The problem with your code is that the resets have no effect, since you're not applying any operations to the reset qubits. Here's an equivalent reset-free code that you can use:
OPENQASM 2.0;
include "qelib1.inc";
qreg q[18];
creg c[14];
h q[0];
h q[1];
h q[2];
h q[3];
h q[4];
h q[5];
CX q[0], q[6];
CX q[1], q[8];
CX q[2], q[10];
CX q[3], q[6];
CX q[3], q[7];
CX q[4], q[8];
CX q[4], q[9];
CX q[5], q[10];
CX q[5], q[11];
x q[6];
x q[8];
x q[9];
x q[10];
x q[11];
measure q[12] -> c[12];
measure q[0] -> c[0];
measure q[1] -> c[1];
measure q[2] -> c[2];
measure q[3] -> c[3];
measure q[4] -> c[4];
measure q[5] -> c[5];
measure q[6] -> c[6];
measure q[7] -> c[7];
measure q[8] -> c[8];
measure q[9] -> c[9];
measure q[10] -> c[10];
measure q[11] -> c[11];For more information on unitary reconstruction and how to integrate it into your software, you can check out the tutorial on Dynamic Quantum Circuits: https://juliaeda.github.io/DynamicQuantumCircuits.jl/dev/tutorial/#tutorial
If you have any questions or suggestion please open an issue. I am currently working on a OpenQASM 3 parser, as there are some bugs in the OpenQASM 2 parser (such as CX needing to be capitalized)
For you to integrate the unitary reconstruction into your software, you can follow Example 2 from the juliacall package.
https://pypi.org/project/juliacall/
