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Updated: Oct 9, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

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Coarse-grained tight-binding models.

Tian-Xiang Liu¹, Li Mao¹, Mats-Erik Pistol²

¹School of Physics and Technology, Wuhan University, Wuhan 430072, People's Republic of China.

Journal of Physics. Condensed Matter : an Institute of Physics Journal

|December 17, 2021

Summary

This summary is machine-generated.

This study introduces a new method to speed up tight-binding calculations for large systems by connecting atomistic and quasi-continuous models. The approach significantly reduces computation time for electronic structure calculations with minimal loss in accuracy.

Keywords:

coarse-grained semiconductors tight-binding models

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Area of Science:

Computational physics
Materials science
Condensed matter physics

Background:

Calculating electronic structures of large systems is computationally intensive.
Empirical atomistic models like tight-binding struggle with system size limitations.
Weakly bound extended electronic states are difficult to treat computationally.

Purpose of the Study:

To develop a method for accelerating tight-binding calculations for large systems.
To bridge the gap between atomistic and quasi-continuous models.
To improve the efficiency of electronic structure calculations.

Main Methods:

Dividing the structure into diagonalizable blocks of unit cells.
Constructing a tight-binding Hamiltonian using a truncated basis.
Retaining low-energy states near band edges and ignoring high-energy states.

Main Results:

Achieved computation time reduction to less than 5% of the full calculation for a GaAs/AlAs quantum well.
Maintained accuracy with errors below 1% for electronic structure calculations.
Demonstrated a tenfold speedup in density of states calculations with minimal accuracy loss.

Conclusions:

The proposed method effectively speeds up tight-binding calculations for large systems.
The trade-off between computation time and accuracy can be managed.
This approach enables more efficient study of electronic structures in large-scale materials.