Routing with t|ket>

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Wrap tket's compilation unit framework to keep track of qubit mappings and work with generic devices.

Setup

Install the ReCirq package:

try:
    import recirq
except ImportError:
    !pip install -q git+https://github.com/quantumlib/ReCirq sympy~=1.6

Now import Cirq, ReCirq and the module dependencies:

import cirq
import recirq
import networkx as nx
from cirq.contrib.svg import SVGCircuit
import numpy as np
from pytket.predicates import CompilationUnit, ConnectivityPredicate
from pytket.passes import SequencePass, RoutingPass, DecomposeSwapsToCXs
from pytket.placement import GraphPlacement

Example circuit

We'll route a 3-regular circuit to Sycamore23. To try to clear up some of the confusion about which indices are which, we'll construct the initial circuit with LineQubits 10 through 19 which should be thought of as "logical indices".

from recirq.qaoa.problem_circuits import get_generic_qaoa_circuit
from recirq.qaoa.gates_and_compilation import compile_problem_unitary_to_arbitrary_zz, \
    compile_driver_unitary_to_rx

problem_graph = nx.random_regular_graph(d=3, n=10)
nx.set_edge_attributes(problem_graph, values=1, name='weight')
circuit_qubits = cirq.LineQubit.range(10, 20)
gammas = np.random.randn(2)
betas = np.random.randn(2)
circuit = get_generic_qaoa_circuit(
    problem_graph=problem_graph,
    qubits=circuit_qubits,
    gammas=gammas,
    betas=betas)
circuit = compile_problem_unitary_to_arbitrary_zz(circuit)
circuit = compile_driver_unitary_to_rx(circuit)
SVGCircuit(circuit)

svg

"Route" this circuit

Let's look at the "connectivity graph" of the circuit vs. that of the device

import cirq.contrib.routing as ccr

uncompiled_c_graph = ccr.get_circuit_connectivity(circuit)
nx.draw_networkx(uncompiled_c_graph)

png

import cirq_google as cg

dev_graph = ccr.gridqubits_to_graph_device(cg.Sycamore23.metadata.qubit_set)
nx.draw_networkx(dev_graph)

png

# alias for the device. If this notebook were wrapped
# in a function, `circuit` and `device` would be the arguments
device = cg.Sycamore23

Convert to pytket Device

The provided function doesn't work with GridDevice. We use existing functionality to turn Devices into graphs to provide a more robust solution.

import pytket
from recirq.qaoa.placement import _device_to_tket_device

tk_circuit = pytket.extensions.cirq.cirq_to_tk(circuit)
tk_device = _device_to_tket_device(device)
tk_circuit.qubits
[q[10], q[11], q[12], q[13], q[14], q[15], q[16], q[17], q[18], q[19]]
tk_device.coupling
[(grid[7, 3], grid[6, 3]),
 (grid[7, 3], grid[7, 4]),
 (grid[7, 3], grid[7, 2]),
 (grid[7, 3], grid[8, 3]),
 (grid[6, 3], grid[6, 2]),
 (grid[6, 3], grid[6, 4]),
 (grid[6, 3], grid[5, 3]),
 (grid[7, 4], grid[6, 4]),
 (grid[7, 4], grid[7, 5]),
 (grid[7, 4], grid[8, 4]),
 (grid[7, 2], grid[6, 2]),
 (grid[8, 3], grid[8, 4]),
 (grid[5, 4], grid[6, 4]),
 (grid[5, 4], grid[5, 3]),
 (grid[6, 4], grid[6, 5]),
 (grid[5, 3], grid[4, 3]),
 (grid[5, 3], grid[5, 2]),
 (grid[6, 1], grid[6, 2]),
 (grid[6, 1], grid[5, 1]),
 (grid[6, 2], grid[5, 2]),
 (grid[5, 1], grid[4, 1]),
 (grid[5, 1], grid[5, 2]),
 (grid[5, 1], grid[5, 0]),
 (grid[5, 2], grid[4, 2]),
 (grid[6, 5], grid[7, 5]),
 (grid[7, 5], grid[7, 6]),
 (grid[7, 5], grid[8, 5]),
 (grid[8, 4], grid[9, 4]),
 (grid[8, 4], grid[8, 5]),
 (grid[4, 1], grid[4, 2]),
 (grid[4, 2], grid[4, 3]),
 (grid[4, 2], grid[3, 2])]

Placement and routing pass

from pytket.predicates import CompilationUnit, ConnectivityPredicate
from pytket.passes import SequencePass, RoutingPass, DecomposeSwapsToCXs, PlacementPass
from pytket.placement import GraphPlacement
unit = CompilationUnit(tk_circuit, [ConnectivityPredicate(tk_device)])
passes = SequencePass([
    PlacementPass(GraphPlacement(tk_device)),
    RoutingPass(tk_device)])
passes.apply(unit)
valid = unit.check_all_predicates()
assert valid

The initial mapping

This maps from logical LineQubits to "physical" GridQubits

unit.initial_map
{q[10]: grid[6, 4],
 q[11]: grid[6, 2],
 q[12]: grid[7, 4],
 q[13]: grid[7, 3],
 q[14]: grid[5, 4],
 q[15]: grid[6, 3],
 q[16]: grid[7, 2],
 q[17]: grid[5, 2],
 q[18]: grid[5, 3],
 q[19]: grid[8, 3]}

Bookkept initial mapping

We "decode" our tket conventions back into Cirq idioms.

def tk_to_cirq_qubit(tk):
    ind = tk.index
    return cirq.LineQubit(ind[0]) if len(ind) == 1 else cirq.GridQubit(*ind)

initial_map = {tk_to_cirq_qubit(n1): tk_to_cirq_qubit(n2) for n1, n2 in unit.initial_map.items()}
initial_map
{cirq.LineQubit(10): cirq.GridQubit(6, 4),
 cirq.LineQubit(11): cirq.GridQubit(6, 2),
 cirq.LineQubit(12): cirq.GridQubit(7, 4),
 cirq.LineQubit(13): cirq.GridQubit(7, 3),
 cirq.LineQubit(14): cirq.GridQubit(5, 4),
 cirq.LineQubit(15): cirq.GridQubit(6, 3),
 cirq.LineQubit(16): cirq.GridQubit(7, 2),
 cirq.LineQubit(17): cirq.GridQubit(5, 2),
 cirq.LineQubit(18): cirq.GridQubit(5, 3),
 cirq.LineQubit(19): cirq.GridQubit(8, 3)}

The final mapping

This maps from logical LineQubits to final GridQubits

unit.final_map
{q[10]: grid[7, 4],
 q[11]: grid[7, 2],
 q[12]: grid[6, 4],
 q[13]: grid[6, 3],
 q[14]: grid[5, 4],
 q[15]: grid[8, 3],
 q[16]: grid[6, 2],
 q[17]: grid[5, 2],
 q[18]: grid[5, 3],
 q[19]: grid[7, 3]}
final_map = {tk_to_cirq_qubit(n1): tk_to_cirq_qubit(n2)
             for n1, n2 in unit.final_map.items()}
final_map
{cirq.LineQubit(10): cirq.GridQubit(7, 4),
 cirq.LineQubit(11): cirq.GridQubit(7, 2),
 cirq.LineQubit(12): cirq.GridQubit(6, 4),
 cirq.LineQubit(13): cirq.GridQubit(6, 3),
 cirq.LineQubit(14): cirq.GridQubit(5, 4),
 cirq.LineQubit(15): cirq.GridQubit(8, 3),
 cirq.LineQubit(16): cirq.GridQubit(6, 2),
 cirq.LineQubit(17): cirq.GridQubit(5, 2),
 cirq.LineQubit(18): cirq.GridQubit(5, 3),
 cirq.LineQubit(19): cirq.GridQubit(7, 3)}

The compilation unit applies the mapping

So our circuit qubits are now GridQubits

unit.circuit.qubits
[grid[5, 2],
 grid[5, 3],
 grid[5, 4],
 grid[6, 2],
 grid[6, 3],
 grid[6, 4],
 grid[7, 2],
 grid[7, 3],
 grid[7, 4],
 grid[8, 3]]

Convert the circuit back to Cirq

routed_circuit = pytket.extensions.cirq.tk_to_cirq(unit.circuit)
SVGCircuit(routed_circuit)

svg

Now it's nice and compiled

routed_c_graph = ccr.get_circuit_connectivity(routed_circuit)
nx.draw_networkx(routed_c_graph)

png

Check that circuits are equivalent

for op in routed_circuit.all_operations():
    if len(op.qubits) != 2:
        continue
    a, b = op.qubits
    assert a.is_adjacent(b)
import cirq.contrib.acquaintance as cca
def permute_gate(qubits, permutation):
    return cca.LinearPermutationGate(
        num_qubits=len(qubits),
        permutation={i: permutation[i] for i in range(len(permutation))}
    ).on(*qubits)

final_to_initial_map = {final_map[cq]: initial_map[cq]
                              for cq in circuit_qubits}
initial_qubits = [initial_map[cq] for cq in circuit_qubits]
final_permutation = [initial_qubits.index(final_to_initial_map[q])
                     for q in initial_qubits]
rcircuit_with_perm = routed_circuit.copy()
rcircuit_with_perm.append(permute_gate(initial_qubits, final_permutation))
expected = circuit.unitary(qubit_order=cirq.QubitOrder.explicit(circuit_qubits))
actual = rcircuit_with_perm.unitary(qubit_order=cirq.QubitOrder.explicit(initial_qubits))
cirq.testing.assert_allclose_up_to_global_phase(expected, actual, atol=1e-8)