How I use sample rates and quant size

C is the channel capacity in bits per second;

B is the bandwidth of the channel in hertz (passband bandwidth in case of a modulated signal);

S is the average received signal power over the bandwidth (in case of a modulated signal, often denoted C, i.e. modulated carrier), measured in watts (or volts squared);

I confuse, I know. Channel capacity, C,  corresponds to my quant size. So when that gets bigger, it acts like the bandwidth, B,  is smaller. I treat it as if it is sampling larger chunks of the signal, thus moving along the phase gradient faster, as if the signal bandwidth were smaller.

So, light samples in larger units, and samples faster along the signal path. I set the quant size, and compute the effective bandwidth, the reverse of what engineers normally do.  It is this way because the vacuum is shaping the signal to fit a particular encoding, and is doing this with small, Shannon independent, sub channels as it marches up the quant chain.

When I scale the quants up, I am effectively making a Nyquist channel with a bandwidth way above the bandwidth = sum of B(i),  the vacuum vacuum sub channels, to collect fractional data.That fractional data gives me the S/N, which is the key variable. It says whether a spin or a charge will fit between quantum integers. It tells me what modes a wave may handle, when a particle will break up; or the cross channel noise, or quantization noise.

The quant sizes grow with the exponent rule, (3/2)**N, N are the collection i....N-1 of sub channels.  Light is (1/2+sqrt(5)/2)**N in the same way.  The two rates are interleaved and sorted going up the quant chain, light is a faster sampler, but not infinite.  What I end up with is a kind of Taylor series expansion around two points, for which I currently have no theory. Hence my call for mathematicians, we need a Taylor theory for M-dimensional center points, the matrix version of Taylor. The theory exists, I know, I took the matrix functionals class at one time in the past. Bellman wrote the book on matrix analysis.