# GPUQT: An efficient linear-scaling quantum transport code fully implemented on graphics processing units

## TL;DR

GPUQT is a GPU-accelerated quantum transport code that enables efficient, linear-scaling calculations of electronic properties in large disordered systems using advanced numerical techniques.

## Contribution

The paper introduces GPUQT, a fully GPU-implemented quantum transport code that achieves linear scaling for large systems using novel numerical methods.

## Key findings

- Achieves linear scaling in computation time and memory usage.
- Successfully computes electronic transport properties in large disordered systems.
- Demonstrates practical usage with example applications.

## Abstract

We present GPUQT, a quantum transport code fully implemented on graphics processing units. Using this code, one can obtain intrinsic electronic transport properties of large systems described by a real-space tight-binding Hamiltonian together with one or more types of disorder. The DC Kubo conductivity is represented as a time integral of the velocity auto-correlation or a time derivative of the mean square displacement. Linear scaling (with respect to the total number of orbitals in the system) computation time and memory usage are achieved by using various numerical techniques, including sparse matrix-vector multiplication, random phase approximation of trace, Chebyshev expansion of quantum evolution operator, and kernel polynomial method for quantum resolution operator. We describe the inputs and outputs of GPUQT and give two examples to demonstrate its usage, paying attention to the interpretations of the results.