PeaQPerf0rmance Circuits

Inspiration

We used our quantum programming skills to tackle the BlueQubit peak circuits challenge.

What it does

The code (located in main.py) loads .qasm files and processes them to solve the challenge.

How we built it

We primarily used Python, along with the Qiskit and BlueQubit libraries.

The repository can be found here. It contains the code developed to solve the BlueQubit Challenge.
The .qasm files are located in the qasm folder, and the main challenge-solving code can be found in main.py while the local packages are in the local src folder.

Getting Started

To test the code, please install the required libraries by running:

pip install -r /path/to/requirements.txt

Next, fill in the .env file with the required token. This file is automatically loaded when running main.py. Once that is done, execute the following command:

python main.py

Note: The code will save the output to a file for inspection, as well as print it to the terminal.

Challenges we ran into

We successfully found a method for solving the P1–P3 .qasm files and are currently working on resolving the P4–P6 circuits.

We tried using the quimb package to find efficient Tensor Networks approximations, which also gave the correct bitstring for problems 1-3. However, the approximations did not produce a sampling that was similar to that of the peaked original circuit for problems 4-6.