I think one could down the hardware to gates, then convert that to a partial difference equation (time discrete). In F_2 sum is "xor" and product is "and". "and" is bilinear. But it is not a universal gate. Don't shoot the pianist, but gpt suggestion is passing from linear to affine algebra. There traslating by 1 (traslation being summing, xor) is "not" and is an affine map, just as "and" is affine in each argument because being linear. Nice thing is that affine maps can be encoded as linear ones one dimension higher so "nand" can be seen as bilinear form acting on two 2D args (homogeneous bit coordinates in F^2*F^2), that is a twice covariant tensor. That tensor can be expressed less efficientely as a twice covariant, once contravariant one. The advantage of that being that you can map a circuit of "nands" to a tensor network of same topology so a big linear map L, so the difference operator becomes L-Id and that leads to the difference equation. mathse speaks confusingly both of difference and differential equations. Take this as a napkin reconstruction idea, not an account of what Feynman actually did (note also the above assumes RAM as part of the state of the CPU as "cache"/"mega-register-bank" and no I/O so model passes from Mealy machine to a fixed iterative transition function acting on initialized internal memory).

Well it was 36 years ago and not sure where he is but I’m sending him positive vibes (he was old when I met him)!