The fundamentally suprising thing about the smallest matter when have studied is that it does not continue to get smaller and smaller forever, it turns out that everthing is maded out of somewhat "fundamental building blocks" that are in many ways indivisible. These particles exist in certain configuration that are also descrete. Futher myster comes from the fact that these configurations aren't constant or mutually exclusive, but rather super imposed. The state of a give particle can be measured and collaped into one of the super imposed states, but along with that, we lose information about the momentum of said particle via Heisenberg's uncertainty principle.

My undergraduate physics degree informs the way I view optimization quite agressively. I find the classical mechanics and deterministic optimization as containing many similarites. Both subjects break problems down into relationship between variables, using physical equations in the first one, and using system interactions in the second. Both use linear algebra to structure their problems, and (usually) use numerical methods to get qunatitative results. For the most part time can be considered just one of the dimensions of the problems statement.

Both problems also have similar concepts of "Lagrangians" that only further show their combined development.

Through my strict belief in Warren Powells work in stochastic optimization, the transition from deterministic optimization and stochastic optimzationation is a compelete expansion of scope. Really, a deterministic optimization model within a stocastic simulation, is the most straight forward conversion. The simulation marching forward in time, using the deterministi model to inform the immedate decision, only to be run again once new information is revealed. This singles out time as a special dimention in a way that can be ignored in the deterministic case

Though not the primary feature of Quantum Mechanics or it's general analysis and appliction, we find that the time dimension, especially the before after measurement, is important to the conceptual understanding of the physical analysis.

In stochastic optimization, the decision is made, the new information enters the system (the waveform is collapsed) and the decision is made once more.

Both of these extensions of their previous disciplines, the quantum and stochastic respecitively, harness the foundations that are established in their proceeding disciplines. They take what came before and abstract dynamics on top of their nacient brothers, and in their simplest case collapse down into their previous disiciplines.