Overview
Spenso
A comprehensive Python tensor library for symbolic and numerical tensor computations, with a focus on physics applications.
Overview
The Spenso Python API provides powerful tools for:
- Tensor Algebra: Dense and sparse tensors with flexible data types
- Symbolic Computation: Integration with Symbolica for tensors with symbolic expressions
- Network Operations: Tensor networks for optimized computation graphs
- Physics Applications: Built-in support for HEP tensors (gamma matrices, color structures, etc.)
- Performance: Compiled evaluators for high-speed numerical computation
Contributors
- Lucien Huber mail@lucien.ch
Classes
CompiledTensorEvaluator |
A compiled and optimized evaluator for maximum performance tensor evaluation |
ExecutionMode |
Execution modes for tensor network evaluation |
LibraryTensor |
A library tensor class optimized for use in tensor libraries and networks. |
Representation |
A representation in the sense of group representation theory for tensor indices. |
Slot |
A tensor index slot combining a representation with an abstract index |
Tensor |
A tensor class that can be either dense or sparse with flexible data types |
TensorEvaluator |
An optimized evaluator for symbolic tensor expressions |
TensorFunctionLibrary |
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TensorIndices |
A tensor structure with abstract indices for symbolic tensor operations |
TensorLibrary |
A library for registering and managing tensor templates and structures. |
TensorName |
A symbolic name for tensor functions and structures |
TensorNamespace |
Enumeration for different tensor namespaces in physics |
TensorNetwork |
A tensor network representing computational graphs of tensor operations |
TensorStructure |
A tensor structure without abstract indices, defined purely by representations |