Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-quantum-chemistry
Quantum Chemistry is awesome. Throw your textbook in the garbage, light the garbage can on fire, and blend the ashes into your cold brew almond milk latte and read this.
https://github.com/twoXes/awesome-quantum-chemistry
Last synced: 3 days ago
JSON representation
-
Tools
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- DeepQMC/PauliNet
- FermiNet
- Hande
- :bookmark_tabs: Publication
- PySCF
- :bookmark_tabs: Publication
- :bookmark_tabs: Documentation
- PSi4
- :bookmark_tabs: Documentation
- QMCTorch
- NWChem
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication - Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks
- :floppy_disk: Github
- :floppy_disk: : GitHub
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication - neural-network solution of the electronic Schrödinger equation
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :floppy_disk: GitHub Code
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication
- :bookmark_tabs: Publication - neural-network solution of the electronic Schrödinger equation
-
References
-
ml_collections ConfigDict
- Fermionic neural-network states for ab-initio electronic structure
- QUANTUM MONTE-CARLO INTEGRATION: THE FULL ADVANTAGE IN MINIMAL CIRCUIT DEPTH
- A MLIR Dialect for Quantum Assembly Languages
- Variational Principles in Quantum Monte Carlo: The Troubled Story of Variance Minimization
- Fermionic neural-network states for ab-initio electronic structure
- Data Driven Science & Engineering:Machine Learning, Dynamical Systems and Control
- Better, Faster Fermionic Neural Networks
- Quantum Entanglement in Deep Learning Architectures
- Solving Many-Electron Schrodinger Equation Using Deep Neural Networks
- Variational neural network ansatz for steady states in open quantum systems
- Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems
- Quantum Chemical Approaches in Structure-Based Virtual Screening and Lead Optimization
- Solving the Quantum Many-Body Problem with Artificial Neural Networks
- Optimizing Neural Networks with Kronecker-factored Approximate Curvature
- MontePython: Implementing Quantum Monte Carlo using Python
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
- "Ab-Initio Solution of the Many-Electron Schroedinger Equation with Deep Neural Networks" - FermiNet
- Fermionic neural-network states for ab-initio electronic structure
- Quantum Entanglement in Deep Learning Architectures
- Solving Many-Electron Schrodinger Equation Using Deep Neural Networks
- Variational neural network ansatz for steady states in open quantum systems
- Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems
- Fermionic neural-network states for ab-initio electronic structure
- Fermionic neural-network states for ab-initio electronic structure
-
-
[Solving the Quantum Many-Body Problem with Artificial Neural Networks (2016)](https://arxiv.org/pdf/1606.02318.pdf)
- code version from the authors
- version of the paper in Jupyter Notebook
- many-body quantum state
- Hilbert space - made-simple-20160428/), as well as the typicality of a small number of physical states, are then the blocks on which modern approaches build upon to solve the many-body [Schrödinger’s equation](https://plus.maths.org/content/schrodinger-1) with a limited amount of classical resources.
- "Ab-Initio Solution of the Many-Electron Schroedinger Equation with Deep Neural Networks"
- wavefunctions - _Optics_and_Modern_Physics_(OpenStax)/07%3A_Quantum_Mechanics/7.02%3A_Wavefunctions) of atoms and molecules using a [variational Monte Carlo](https://pubs.acs.org/doi/10.1021/acs.jctc.0c00147) approach.
-
Machine Learning the Schrodinger Equation
-
[Setup.py](https://github.com/deepmind/ferminet/blob/jax/setup.py)
- Kfac - - [Kfac Paper](https://arxiv.org/pdf/1503.05671.pdf) :blue_book:
-
[Base Config.py](https://github.com/deepmind/ferminet/blob/jax/ferminet/base_config.py)
Categories
Tools
49
References
48
[Solving the Quantum Many-Body Problem with Artificial Neural Networks (2016)](https://arxiv.org/pdf/1606.02318.pdf)
6
[Base Config.py](https://github.com/deepmind/ferminet/blob/jax/ferminet/base_config.py)
5
Machine Learning the Schrodinger Equation
1
[Setup.py](https://github.com/deepmind/ferminet/blob/jax/setup.py)
1
Sub Categories