*JuliaCon 2020 | *`SymbolicTensors.jl`

– high-level tensor manipulation in Julia | Robert Rosati, https://www.youtube.com/watch?v=_b4JIv044GY

Here is example of video description, that can be made better looking. I already make timestamps for it, but since they are not incorporated into description when I write this, I will not use them. Also, I don’t use Markdown (?) quotation, because it often smooth over rough parts that I want to show.

BEGINING

Many numerical tensor manipulation packages exist (e.g. Einsum.jl), but treating tensors at a purely numeric level throws away a lot of potential optimizations.

Often, it’s possible to exploit the symmetries of a problem to dramatically reduce the calculation steps necessary, or perform some tensor contractions symbolically rather than numerically.

SymbolicTensors.jl is designed to exploit these simplifications to generate more efficient input into numeric tensor packages than you would write by hand. It based on SymPy.jl, sympy.tensor.tensor, and ITensors.jl. Time Stamps:

00:00 Welcome!

00:10 Help us add time stamps or captions to this video! See the description for details.

END

Changes are obvious.

BEGINING

Many numerical tensor manipulation packages exist (e.g. Einsum.jl), but treating tensors at a purely numeric level throws away a lot of potential optimizations. Often, it’s possible to exploit the symmetries of a problem to dramatically reduce the calculation steps necessary, or perform some tensor contractions symbolically rather than numerically.

SymbolicTensors.jl is designed to exploit these simplifications to generate more efficient input into numeric tensor packages than you would write by hand. It based on SymPy.jl, sympy.tensor.tensor, and ITensors.jl.

Time Stamps:

00:00 Welcome!

00:10 Help us add time stamps or captions to this video! See the description for details.

END