This package contains Python classes for each type of circuit (and various parallelized versions) we discuss in our arXiv preprint.
- Bucket brigade circuits (
src/bucket_brigade_circuits.py) - Basic circuits (
src/basic_circuits.py) - Hybrid circuits (
src/hybrid_circuits.py) - Double qRAM circuits (
src/double_qram_circuits.py)
To run the data generation scripts:
- numpy
To run the analysis notebooks:
Within each class are formulae for the computation of relevant resources such as number of logical qubits, T-gates, Clifford gates, etc. All circuits inherit from a parent class qRAMCircuit, which itself inherits from a more general Circuit base class (both found in src/circuit.py).
The file src/surface_code.py contains a surface code class that eats circuits and produces the resource estimates. Currently only defect-based estimates are implemented, with lattice surgery methods to be implemented at some point in the future.
Here is a simple example:
from basic_circuits import LargeWidthSmallDepth
from surface_code import SurfaceCode
# Instantiate a surface code with some physical assumptions (gate errors, cycle time)
surf_code = SurfaceCode(p_in=1e-4, p_g=1e-5, t_sc=200e-9)
# Create a circuit
circ = LargeWidthSmallDepth(35, 33)
# Compute resource estimates; returned as dictionaries of parameters
defect_est = surf_code.defect_compute_resources(circ)The script scripts/generate_paper_data.py will produce all the data as it appears in our paper. The relevant data is also included in data/ and the analysis notebooks are in analysis/.
Contact odimatteo AT triumf DOT ca for questions/comments, or create an issue if you find any bugs.