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Core User Guide
1. Installation
2. Basics
3. Built-in & Random States & Operators
4. Calculating Quantities
5. Eigen-Solving & Other Linear Algebra
6. Distributed Parallelism - MPI
7. Time Evolution
Tensor Network Guide
1. Tensor Network Basics
2. Drawing Tensor Networks
3. 1D Tensor Networks & Algorithms
4. 2D Tensor Networks & Algorithms
5. Quantum Circuit Simulation
6. Tensor Network Design
Examples
1. 2D Antiferromagnetic Model Example
2. Quenching a Random Product State
3. MPI Interior Eigensolve with Lazy, Projected Operators
4. Example - Tensor Renormalization Group (TRG)
5. Tensor Network Random Unitary Evolution
6. Periodic DMRG and Calculations
7. MPS Evolution with TEBD
8. Basic MERA Manipulations & Optimization
9. Optimizing a Tensor Network using Tensorflow
10. Tensor Network Training of Quantum Circuits
11. Bayesian Optimizing QAOA Circuit Energy
Developer Notes
Changelog
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Tensor Network Guide
Tensor Network Guide
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1. Tensor Network Basics
1.1. Creating Tensors
1.2. Creating Tensor Networks
1.3. Contraction
1.4. Decomposition
1.5. Selection
1.6. Modification
2. Drawing Tensor Networks
2.1. Coloring
2.2. Highlighting indices
2.3. Highlighting
tids
2.4. Positioning tensors
2.5. Hyper-edges
2.6. Spanning trees
2.7. Interaction with
matplotlib
2.8. ‘Publication style’ figures
3. 1D Tensor Networks & Algorithms
3.1. Matrix Product States
3.2. Matrix Product Operators
3.3. Building Hamiltonians
3.4. Quick DMRG2 Intro
3.5. Quick TEBD Intro
3.6. Gates: compute local quantities and simulate circuits
4. 2D Tensor Networks & Algorithms
4.1. Structure of a 2D Tensor Network
4.2. Combining 2D Tensor Networks
4.3. Contracting 2D Tensor Networks
4.4. Computing Quantites
4.5. Specifying 2D Hamiltonians
4.6. Simple Update
4.7. Full Update
4.8. Global Autodiff Optmization
5. Quantum Circuit Simulation
5.1. Simulation Steps
5.2. Building the
Circuit
5.3. Forming the Target Tensor Network
5.4. Locally Simplifying the Tensor Network (the
simplify_sequence
kwarg)
5.5. Finding a Contraction Path (the
optimize
kwarg)
5.6. Performing the Contraction (the
backend
kwarg)
5.7. Performance Checklist
6. Tensor Network Design
6.1.
Tensor
6.2.
TensorNetwork
6.3. Structured (1D, 2D, …) Tensor Networks
6.4. Standard vs. Hyper Indices & Tensor Networks