Expand description
§Structure of tensors
In contrast to the common design of having tensors and tensor networks, this library allows arbitrary nesting of tensors. This means that the children of tensor networks can themselves be tensor networks again. We call tensors with children “composite tensors” and those without children “leaf tensors”.
§Composite tensors
Composite tensors are the equivalent to tensor networks, as they own a list of
tensors that are their children. However, these child tensors can also be
composite, allowing for a hierarchical tree structure. The outer legs of a
composite tensor can be obtained by the external_tensor method.
§Leaf tensors
Leaf tensors have legs with corresponding bond dimensions and can optionally have data.
§Rationale
The idea for this recursive design is natural: When looking only at the outer (i.e. open) legs of a tensor network, it can be seen as a plain tensor again. It has legs with sizes and it has data (that is obtained by contracting the tensor network).
In addition, this format is useful for multi-level parallelization based on partitioning the network: For example, the top level could be a composite tensor, where each children is assigned to one compute node. Each children is also again a composite tensor, where each children is assigned to one core. Finally, each of those children is again a composite tensor that is an actual tensor network (i.e., with leaf tensors as children).
Re-exports§
pub use crate::_tutorial as table_of_contents;