- Viewing computational linguistics from the length across linear algebra and linear structure
- Quantum algorithms and the necessary infra were being developed; and in the 2010s programmable quantum computers became showing up

Quantum is done over the complexes, which makes the normal linguistics done with the reals more powerful.

want to infer the probability distribution of words based on their letters

- Linearity breaks down: letter combinations in not commutative; and P(letter C) + P(letter A) != P(letters CA)

instead of encoding letters as one-hot vectors; we encode these letters with matrices: adds more dimensions

- immediate benefits:
- noncommutivity of matricies is a PLUS
- words is just the composed results into another 2x2 matricies
## then, to map into probability distrubtion, we map the matrix into a partial trace

- immediate benefits:

## things

create bounds from the problem: letters

improve upon optimization scheme in a quantum rhelm

implement this scheme on a quantum computer: https://arxiv.org/pdf/1710.10248.pdf

task: NTJ reading; come up with the needed novelty