Quokka-Sharp

Prerequisite

• Install GPMC

Follow instructions in GPMC git to install GPMC.

• Install pip

INSTALLATION

and then you can install Quokka# as a python module via pip:

pip install quokka_sharp

Usage

Quokka# provides two kinds of funcionalities: one is to simulate a quantum circuit, the other is to check the equivalence of two circuits.

We work in one of two posible bases: Pauli or Computations.

For equivalence checking we allow one of 4 techniques for the Pauli basis: "id", "id_2n", "id_noY", "2n" For equivalence checking check we allow one only 1 technique for the computational basis: "id" "id": creats a cyclic check, such that the final state is constraind to be identical to the initial state. "id_2n": uses "id" and add constraits on the initial state such that a basis of size 2n is checked. "id_noY": uses "id" and add constraits on the initial state such that there will be no Y. "2n": makes 2n independant calls, each checking one initial state in the 2n basis.

Please first set the wanted timeout (in seconds) using export TIMEOUT, for example:

export TIMEOUT=3600

All the input circuits should be in QASM format. Here are some simple walkthroughs to use the tool. The eq_run.py and sim_run.py (used for the bencmarks) can be used to compare the diffrent variations of the tool and provide further examples.

import quokka_sharp as qk
import tempfile

# the path of the WMC tool
tool_invocation = "/Users/GPMC/bin/gpmc -mode=1"
'''
Simulation
'''
# Parse the circuit
circuit1 = qk.encoding.QASMparser(qasmfile1, True)
# Set the input state to be all zero state.
cnf.leftProjectAllZero()
# Encode the circuit (for computational base instaed of cliffordt, use `computational_basis = True`)
cnf = qk.encoding.QASM2CNF(circuit1, computational_basis = False)
# Choose firstzero or allzero
cnf.add_measurement("firstzero")
# Export to benchmarks
cnf.write_to_file("circ.cnf")
prob = qk.Simulate(tool_invocation, "circ.cnf")
prob = abs(prob) # since the tool returns a complex number
## if `computational_basis = True` add
# prob = prob*prob
print(prob)

'''
Equivalence checking
'''
# Parse the circuit
circuit1 = qk.encoding.QASMparser(qasmfile1, True)
# Parse another circuit
circuit2 = qk.encoding.QASMparser(qasmfile2, True)
# Get (circuit1)^dagger(circuit2)
circuit2.dagger()
circuit1.append(circuit2)
# Get CNF for the merged circuit (for computational base instaed of cliffordt, use `computational_basis = True`)
cnf = qk.encoding.QASM2CNF(circuit1, computational_basis = False)
# Users can change the path for the cnf files by setting a different parameter to cnf_file_root, otherwise it would be in the tempfile.
# Users can set a different number N of paralleling processes. The default value is 16.
res = qk.CheckEquivalence(tool_path, cnf, check = "id", cnf_file_root = tempfile.gettempdir(), N=16)

• extention of the encodings Now the encoding support a universal gate set: CNOT, CZ, H, S, T, RX, RZ. If you want to add direct encoding of other gates, you should first install the package sympy by

  pip install sympy

and add new encoding in ./encoding/cliffordt2cnf_py_codegen.py or in ./encoding/comput2cnf_py_codegen.py, depending on the base used. then run one of the following comands corespondingly:

python3 cliffordt2cnf_py_codegen.py>cliffordt2cnf.py

or

python3 comput2cnf_py_codegen.py>comput2cnf.py

Benchmarks

Users can test the equivalence checking functionality of the tool by running eq_bench.sh under the folder experiment:

./eq_bench.sh

and test the simulation of the tool by running

./sim_bench.sh

This script tests all both random circuits and quantum algorithms under ./experiment/benchmark with the equivalent cases (optimized circuits) and three kinds of errors: 1 gate-missing, bit flip in CNOT gate and phase shift in a rotation gate (with shifting error 1e-4 and 1e-7).