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Reproduce Table 1 of arXiv:2404.18809 #198
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…ed to build_placement_graph
orders_l = code.get_order(vecs_l[0]), code.get_order(vecs_l[1])
for vecs_r in lattice_vectors:
orders_r = code.get_order(vecs_r[0]), code.get_order(vecs_r[1])
if orders_r == orders_l[::-1]
vecs_r = vecs_r[::-1]
elif orders_r != orders_l: # required for L/R qubits to be placed on the same rectangular grid
continue
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By the way, if you want to play around with qubit placements, you can do something like code = qldpc.codes.BBCode(
{x: 6, y: 6},
x**3 + y + y**2,
y**3 + x + x**2,
)
folded_layout = True
vecs_l, vecs_r, shift_r, optimal_distance = get_optimal_layout_params(code, folded_layout, cheat=True)
get_qubit_pos = get_qubit_pos_func(code, folded_layout, vecs_l, vecs_r, shift_r) Now you can get the position of |
Since there is no search for optimality, should we rename the function |
Maybe rather than having a boolean |
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@jmlarson1 done. What do you think of the current version? |
this is in preparation for what is hopefully a larger speedup of recycling displacement calculations
@jmlarson1 let's discuss this sometime