An efficient Julia framwork for Hierarchical Equations of Motion (HEOM) in open quantum systems
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Updated
Sep 11, 2024 - Julia
An efficient Julia framwork for Hierarchical Equations of Motion (HEOM) in open quantum systems
Variational Matrix Product Operator Monte Carlo
Quantum Toolbox in Julia
Tensor network simulations for finite temperature, open quantum system dynamics
Tensor network based quantum software framework: next generation
Project on studying Open Quantum System Models and simulating them using OQC Lucy Hardware.
MLQD is a Python Package for Machine Learning-based Quantum Dissipative Dynamics
Projeto que usa MPC (Modelo de controle preditivo) juntamente com o controle quântico para manipulação da função de onda apresentada na equação de Schrodinger, a base para mecânica quântica
A Python package to efficiently simulate non-Markovian open quantum systems with process tensors.
Package that defines commonly used spectral densities for Open Quantum Systems.
Collection of useful functions and types for the simulation of Quantum systems
A toolbox to interface reinforcement learning with quantum systems!
A tool to calculate lifetimes, average charge separation and dipole moments of excited states along DNA within the formalism of open quantum systems.
Code for my master thesis at the Scientific Computing chair @ TUM under the supervision of Prof. Christian Mendl
Semiclassical spin self organization v.2: Julia files & Bash scripts. The code was used to produce the results seen in https://arxiv.org/abs/2407.19706
Tensor network based quantum software framework for the NISQ era
Code and data for our paper in JPCL "One-Shot Trajectory Learning of Open Quantum Systems Dynamics" https://doi.org/10.1021/acs.jpclett.2c01242
Script for data generation and Code for our article "Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics"
Open quantum system dynamics using process tensor networks and iTEBD.
Floquet real-time renormalization group implemention in python for the single channel Kondo model
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