Bartiq is a library that allows one to analyze quantum algorithms and calculate symbolic expressions for quantum resource estimates (QRE).
To install bartiq run: pip install bartiq.
In order to install it from source clone the repo by running git clone https://github.com/PsiQ/bartiq.git and then run pip install . from the main directory.
# Clone bartiq repo (you can use SSH link as well)
git clone https://github.com/PsiQ/bartiq.git
cd bartiq
pip install .In bartiq we can take a quantum algorithm expressed as a collection of subroutines, each with its costs expressed as symbolic expressions, and compile it to get cost expression for the whole algorithm.
As an example we can use Alias Sampling – an algorithm proposed by Babbush et al.. Here's how it's depicted in the paper:
In order to quickly get started with bartiq, you can load Alias Sampling as an example routine and use it as follows (click here to download alias_sampling_basic.json):
import json
from bartiq import compile_routine, evaluate
from qref import SchemaV1
with open("docs/data/alias_sampling_basic.json", "r") as f:
routine_dict = json.load(f)
uncompiled_routine = SchemaV1(**routine_dict)
compiled_routine = compile_routine(uncompiled_routine).routine
assignments = {"L": 100, "mu": 10}
evaluated_routine = evaluate(compiled_routine, assignments).routineNow in order to inspect the results you can do:
print(compiled_routine.resources["T_gates"].value)
print(evaluated_routine.resources["T_gates"].value)which returns both symbolic the expression for the T-count as well as result for specific values of L and mu:
4*L + 8*L/multiplicity(2, L) + 4*mu + swap.O(log2(L)) - 8
swap.O(log2(100)) + 832
To go step by step through the process and see how you can use bartiq for your algorithms, please take a look at our tutorials, starting with basic example.
Documentation for bartiq can be found here.