Features¶
At the moment PlanqTN is nascent and has rough edges, a lot more features are planned including logical operators, non-Pauli symmetries, operator pushing, more graph state transformations, representing parameterized code families, a public database to share tensor network constructions and weight enumerators. If you have more ideas, open an issue, we'd love to hear it!
| Feature | Library | Studio |
|---|---|---|
| Build tensor networks - Create and construct tensor networks from basic components | ||
| Create a tensor network manually from smaller encoding tensors with predefined Pauli stabilizers. | Library docs | Studio docs |
| Create a custom LEGO based on parity check matrix. | Library docs | Studio docs |
| Undo/redo for most operations. | - | Studio docs |
| Transform tensor networks - Apply various transformations to modify and manipulate tensor networks | ||
| Fuse LEGOs into a single LEGO. | - | Studio docs |
| ZX calculus transformations on Z and X repetition code LEGOs: | - | Studio docs |
| Fuse legos. | - | Studio docs |
| Bialgebra and inverse bialgebra rule. | - | Studio docs |
| Unfuse: | - | Studio docs |
| Pull out a leg of the same color. | - | Studio docs |
| Unfuse to legs. | - | Studio docs |
| Unfuse to two LEGOs. | - | Studio docs |
| Change color by adding Hadamard LEGOs on legs. | - | Studio docs |
| Graph state transformations: Z-repetition code LEGOs are graph nodes that need to be connected through links with a Hadamard LEGO on it. | - | Studio docs |
| Create complete graph from nodes. | - | Studio docs |
| Connect nodes with a central node. | - | Studio docs |
| "Resize" groups of LEGOs - reposition based on the resized bounding box of selected LEGOs. | - | Studio docs |
| Analyze tensor networks - Perform calculations and analysis on tensor networks including weight enumerators and operator pushing-based highlighting | ||
| Zero installation calculations: PlanqTN Studio is deployed as a cloud native architecture on Google Cloud and Supabase, and you can run small calculations for free! | - | Studio docs |
| Local kernel using Docker, with Kubernetes and Supabase to run jobs only limited by your resources. | - | Studio docs |
| Calculate Pauli stabilizers (parity check matrix) of a tensor network. | Library docs | Studio docs |
| Calculate coset weight enumerators. | Library docs | - |
| Weight enumerator polynomial calculations: | Library docs | Studio docs |
| Brute force scalar weight enumerator polynomial (WEP) for a single tensor. | Library docs | Studio docs |
| Tensor WEP for a single tensor with specified open legs. | Library docs | Studio docs |
| Truncated WEP - only calculate up to a certain weight, this speeds up the contraction significantly, making the tensors very sparse. | Library docs | Studio docs |
| MacWilliams dual (normalizer WEP) for scalar WEP. | Library docs | Studio docs |
| Using Cotengra calculate a hyper-optimized contraction schedule for any tensor network. | Library docs | Studio docs |
| Operator pushing and matching: | - | Studio docs |
| Highlighting tensor network stabilizer legs (dangling legs). | - | Studio docs |
| Highlight local stabilizers on individual tensors. | - | Studio docs |
| Export tensor network as Python code and continue working on it on your own computer. | - | Studio docs |
| Export parity check matrices as numpy array. | - | Studio docs |
| Export parity check matrix for QDistRnd for distance calculations. | - | Studio docs |
| Run multiple jobs in parallel. | - | Studio docs |
| Share tensor networks - Export and share tensor network constructions | ||
| Share/save your canvas as JSON file. | - | Studio docs |
| Share/bookmark your canvas as a URL. | - | Studio docs |