SSSS
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"Deep Learning and Quantum Programming" Spring School @ Song Shan Lake
Deep Learning and Quantum Programming: A Spring School
Song Shan Lake Spring School, features lectures, code challenge, install party and happy fatty night.
South Bay Interdisciplinary Science Center, Songshan Lake Materials Laboratory, Dongguan, China, 5th-10th May, 2019
Table of Contents
- Deep Learning
lecture_notes.pdfandslides/- Demo codes
- Poor man's computation graph:
computation_graph.py - Variational free energy with flow model:
realnvp/ - Hamiltonian inverse design with reverse mode AD:
schrodinger.py - Solving the fastest descent problem with NeuralODE
brachistochrone/
- Poor man's computation graph:
- Tensor Networks
- Julia language
- Quantum Computing with Yao.jl
- Lecture Note:
quantum_lecture_note.pdf - Slides:
google slides - Notebooks
- The solution to the graph embeding problem:
graph_embeding.ipynb - Quantum circuit computing with Yao.jl:
QC-with-Yao.ipynb,Yao-talk - Landscape of a quantum circuit:
variational_quantum_circuit.ipynb - Variational quantum eigensolver:
variational_quantum_circuit.ipynb - Matrix Product state inspired variational quantum eigensolver
VQE_action.ipynb - Quantum circuit born machine:
qcbm_gaussian.ipynb - Gradient vanishing problem:
variational_quantum_circuit.ipynbandVQE_action.ipynb - Mapping a quantum circuit to tensor networks:
qc_tensor_mapping.ipynb
- The solution to the graph embeding problem:
- Lecture Note:
Welcome for pull requests and issues!
Challenge
Song-Shan-Hu Sping School Coding Challenge
Preparation
Quick start
Installation
Julia
Usage
You can open this repo as a Julia package if you have julia installed:
- open your Julia REPL, press
] - type the following
(1.0) pkg> add https://github.com/QuantumBFS/SSSS.git
- press backspace
- type the following
julia> using SSSS
julia> notebooks()
License
The code is released under MIT License. The rest part is released under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)