pyproject.toml

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "quickstart-pennylane"
version = "1.0.0"
description = "Quantum Federated Learning with PennyLane and Flower"
license = "Apache-2.0"
authors = [
    { name = "SECQUOIA Research Group", website = "https://secquoia.github.io/" },
    { name = "David Bernal Neira", email = "dbernaln@purdue.edu" },
    { name = "Daniel Anoruo", email = "danoruo1@students.towson.edu" },
    { name = "Alan Yi", email = "yi161@purdue.edu" }
]
dependencies = [
    "flwr[simulation]>=1.27.0",
    "flwr-datasets[vision]>=0.6.0",
    "torch==2.8.0",
    "torchvision==0.23.0",
    "pennylane==0.41.1",
    "autoray>=0.6,<0.7",
]

[tool.hatch.build.targets.wheel]
packages = ["."]

[tool.flwr.app]
publisher = "flwrlabs"

[tool.flwr.app.components]
serverapp = "quickstart_pennylane.server_app:app"
clientapp = "quickstart_pennylane.client_app:app"

[tool.flwr.app.config]
num-server-rounds = 10
batch-size = 32
local-epochs = 2
learning-rate = 0.001
fraction-train = 1.0
fraction-evaluate = 0.5

# Quantum circuit configuration
n-qubits = 4
n-layers = 3