FloquetTB

A Python package for Floquet engineering of tight-binding models with topological property calculations.

Features

• Floquet Hamiltonian Calculation: Compute effective Floquet Hamiltonians using high-frequency expansion
• Topology Calculations: Calculate Wilson loops, Chern numbers, and Berry curvature
• Band Structure Plotting: Visualize Floquet band structures with spin projection
• Circular Polarization Support: Full support for circularly polarized light driving

Installation

pip install floquettb

Or install from source:

git clone https://github.com/yourusername/floquettb.git
cd floquettb
pip install -e .

Dependencies

• numpy >= 1.19.0
• scipy >= 1.5.0
• matplotlib >= 3.3.0
• pythtb == 1.8.0 (required, install separately)

Quick Start

from pythtb import tb_model
from floquettb import FloquetTB  # or: from floquettb.floquettb import FloquetTB
import numpy as np

# 1. Create a tight-binding model
lat = [[1.0, 0.0], [0.5, np.sqrt(3.0)/2.0]]
orb = [[1.0/3.0, 1.0/3.0], [2.0/3.0, 2.0/3.0]]
my_model = tb_model(2, 2, lat, orb, nspin=1)

# Set hoppings
t = 1.0
my_model.set_hop(-t, 0, 1, [0, 0])
my_model.set_hop(-t, 0, 1, [0, -1])
my_model.set_hop(-t, 0, 1, [-1, 0])

# 2. Convert to Floquet model
floquet_model = FloquetTB(my_model)

# 3. Apply circularly polarized light
omega = 10.0  # Driving frequency
A_drive = 1.0  # Driving amplitude
floquet_model.compute_floquet_hamiltonian(
    A=A_drive, 
    omega=omega, 
    polarization='circular_left', 
    order=2
)

# 4. Calculate topological properties
results = floquet_model.calculate_all_topology(
    mesh_size=101,
    occ=[0, 1],  # Occupied bands
    return_plots=True
)

print(f"Chern number: {results['chern_number']:.6f}")

# 5. Plot band structure
kpath = [[0.0, 0.0], [2.0/3.0, 1.0/3.0], [0.5, 0.5], [0.0, 0.0]]
fig, ax = floquet_model.plotbands(
    kpath=kpath, 
    label="Floquet Band Structure",
    A=A_drive, 
    omega=omega,
    proj_spin=False
)

API Reference

FloquetTB Class

Methods

• compute_floquet_hamiltonian(A, omega, polarization='circular_left', order=1): Compute effective Floquet Hamiltonian
• plotbands(kpath, label="Floquet Band Structure", n_points=300, A=None, omega=None, proj_spin=False): Plot band structure
• calculate_wilson_loop(mesh_size=51, occ=None, dir=1, start_k=[0.0, 0.0], contin=True, return_plot=False): Calculate Wilson loop
• calculate_chern_number(mesh_size=51, occ=None, start_k=[0.0, 0.0], dirs=None): Calculate Chern number
• calculate_berry_curvature(mesh_size=51, occ=None, start_k=[0.0, 0.0], dirs=None, return_plot=False, log=False): Calculate Berry curvature
• calculate_all_topology(mesh_size=51, occ=None, start_k=[0.0, 0.0], return_plots=False, log=False): Calculate all topological properties

Examples

See the examples/ directory for more detailed examples.

Citation

If you use FloquetTB in your research, please cite:

@software{floquettb2024,
  title={FloquetTB: A Python package for Floquet engineering of tight-binding models},
  author={Your Name},
  year={2024},
  url={https://github.com/yourusername/floquettb}
}

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Acknowledgments

This package is built on top of pythtb, a Python tight-binding package.