Tinie swMATH ID: 33751 Software Authors: R. Duda, J. Keski-Rahkonen, J. Solanpää, E. Räsänen Description: Tinie - a software package for electronic transport through two-dimensional cavities in a magnetic field. Quantum transport has far-reaching applications in modern electronics as it enables the control of currents in nanoscale systems such as quantum dots. In this paper we introduce tinie: a state-of-the-art quantum transport simulation framework, which can efficiently perform first-principle calculations based on the Landauer-Büttiker formalism. The computational repertoire of tinie includes calculations of transmission, conductivity, and currents running through arbitrary multi-terminal two-dimensional transport devices, with additional tools that enable the computation of the local density of states. The generality of tinie ranges from wide-band approximation calculations to investigating systems subject to an external magnetic field. The future prospects of tinie include the simulation of, e.g., two-dimensional cavities, quantum dots, or molecular junctions. The package is written in Python 3.6, and its well-documented modular structure is designed with an intent to create a platform suited for continuous expansion and development. With tinie it is possible to obtain specific information about the effects of impurities and imperfections in quantum devices, particularly between ballistic and diffusive transport regimes. Homepage: https://pypi.org/project/tinie/ Source Code: https://gitlab.com/compphys-public/tinie Dependencies: Python Keywords: Physics; arXiv_cond-mat.mes-hall; Python; magnetic field; quantum transport; low-dimensional systems; quantum dots Related Software: NanoTCAD ViDES; DDPy; NEMO5; SMEAGOL; transiesta; Kwant; nextnano; h5py; HDF5; NumPy; findiff; SciPy; itp2d; mpi4py; Python Cited in: 0 Publications Standard Articles 1 Publication describing the Software Year Tinie - a software package for electronic transport through two-dimensional cavities in a magnetic field R. Duda, J. Keski-Rahkonen, J. Solanpää, E. Räsänen 2020