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Welcome to Bartiq

Intro

Bartiq is a library that allows one to analyze quantum algorithms and calculate symbolic expressions for quantum resource estimates (QRE).

Installation

To install bartiq run: pip install bartiq. For more details follow instructions on the installation page.

Quick start

In Bartiq we 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 use Alias Sampling – an algorithm proposed by Babbush et al. ⧉. Here's how it's depicted in the paper:

Alias Sampling

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 Routine, compile_routine, evaluate
from bartiq.integrations import qref_to_bartiq

with open("alias_sampling_basic.json", "r") as f:
    routine_dict = json.load(f)

uncompiled_routine = qref_to_bartiq(routine_dict)
compiled_routine = compile_routine(uncompiled_routine)

assignments = ["L=100", "mu=10"]

evaluated_routine = evaluate(compiled_routine, assignments)

Now 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 the symbolic expression for the T-count as well as the 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

Next steps

  • For a more comprehensive step-by-step examples, please see tutorials.
  • If you are interested in learning more about how bartiq works under the hood, please see the concepts tab in the menu.
  • For common issues, please check troubleshooting section.
  • You can find reference documentation for the public API of bartiq's python package, please go to reference.