qlbm 0.0.4

Quantum Algorithms for Lattice Boltzmann Methods.

qlbm

qlbm is a package for the development, simulation, and analysis of Quantum Lattice Boltzmann Methods.

This library contains building blocks for constructing quantum circuits for LBMs and connects the circuits with quantum software infrastructure. qlbm provides a platform for an end-to-end development environment, including:

• Parsing human-readable JSON specifications for QLBMs
• Constructing quantum circuits in Qiskit that implement QLBMs
• Compiling quantum circuits to quantum computer and simulator platforms with Qiskit and Pytket
• Simulating quantum circuits on classical hardware with Qiskit and Qulacs
• Visualizing results in Paraview
• Analyzing the properties , scalability, and performance of quantum algorithms

qlbm is a rapidly evolving, research-oriented piece of software, written almost entirely in Python. A detailed documentation of qlbm is available at here.

PyPI installation

qlbm can be installed through pip. We recommend th euse of a Python 3.11 virtual environment:

python3.11 -m venv qlbm-cpu-venv
pip install --upgrade pip
pip install qlbm

Local installation

To install from source, first clone the repository:

git clone [e-mail]:QCFD-Lab/qlbm.git

We again recommend to install and use the current version of qlbm in a Python 3.11 virtual environment. To set up the virtual environment, you can run following installation:

python3.11 -m venv qlbm-cpu-venv
source qlbm-cpu-venv/bin/activate
pip install -e .[cpu,dev]

Alternatively, you can use the make script provided for this purpose, which will create the environment from scratch as well:

make install-cpu
source qlbm-cpu-venv/bin/activate

qlbm additionally supports several other options, including GPU and MPI simulation. There are also Docker container images in the Docker directory. Due to how quickly the code base is evolving, we recommend using the CPU option for stability purposes.

Algorithms and Usage

Currently, qlbm supports two algorithms:

• The Collisionless QLBM described in Efficient and fail-safe quantum algorithm for the transport equation (arXiv:2211.14269) by M.A. Schalkers and M. Möller.
• The Space-Time QLBM described in On the importance of data encoding in quantum Boltzmann methods by M.A. Schalkers and M. Möller.

The demos directory contains several use cases for simulating and analyzing these algorithms. Each demo requires minimal setup once the virtual environment has been configured. Consult the README.md file in the demos directory for further details.

Note on visualization: we rely on Paraview for visualizing the flow field of the simulation. You can install Paraview from this link.

Configuration

qlbm uses quantum circuits to simulate systems that users can specify in simple JSON configuration files. For instance, the following configuration describes a 2D system of 64x32 gridpoints, 4 discrete velocities per dimension, and with 3 solid objects placed in the fluid domain:

{
  "lattice": {
    "dim": {
      "x": 64,
      "y": 32
    },
    "velocities": {
      "x": 4,
      "y": 4
    }
  },
  "geometry": [
    {
      "x": [18, 20],
      "y": [6, 25],
      "boundary": "specular"
    },
    {
      "x": [23, 25],
      "y": [3, 17],
      "boundary": "bounceback"
    },
    {
      "x": [28, 29],
      "y": [16, 29],
      "boundary": "specular"
    }
  ]
}