Have published a new theoretical framework for photonic computing / data storage that draws on Bruce Peret's RS2 dimensional algebra and Gopi Krishna Vijaya's work bridging Goethean and RS traditions. Sharing it here since this community's foundations made the work possible.
How this came about:
While studying computing and photonics, I became struck by the recognition that photonic computing represents the next technological frontier—yet the field faces a fundamental bottleneck. Currently, we can build photonic chips that perform binary processes (similar to adaptive lenses that darken in sunlight) and we use light brilliantly in fiber optics to connect processing units. But a truly light-based computing technology would need to do everything silicon can do, including storing data as persistent memory.
This is precisely where the industry is stuck. Light wants to propagate, not stay put. The conventional approach fights this nature by building ever-better "cages" for photons—optical cavities, slow-light media, delay lines—with limited success.
This is something I was intensely fascinated with as a teenager learning about the physical sciences in school. What would happen, I wondered, if you could create a box whose inner walls are all perfect mirrors -- could you catch light inside? Short of an idea to use two-way mirror glass and a high power light source, I can't see how you could effectively capture a photon.
The framework's core idea:
What happens if we invert the problem? Rather than capturing and storing light, could we store its absence—stable topological structures (phase singularities, optical vortices) defined by their boundaries. The hole becomes the data.
This is where RS2 proved essential. The division algebra hierarchy (ℝ→ℂ→ℍ→𝕆) provided the mathematical language to describe dimensional transitions from propagating light (2D, complex) to stable helical structures (4D+ quaternion/octonion). Gopi's paper on Goethean light science offered the philosophical grounding: darkness as a positive polar principle rather than mere absence.
As a visual example, there is a phenomena that occurs in properly treated swimming pool water whereby if you are able to observe an unoccupied pool, you will find that the clean and clear pool water is actually incredibly active: there can be seen areas in the volume of water that seem to roil/boil in place. As closely as I have been able to directly observe and perceive it as such, it looks to be to be a macroscopic manifestation of 3d motion and interaction of the same. What's important to note is that you don't actually see the boiling mass of accumulated chemicals interacting without first noticing the shadow that this roiling mass produces on the bottom or walls of the pool. If your eyes are keen and you understand how light bends when you look into it, you can then backtrack to the area in the pool that is the source of the disturbance in the water causes the shadow. There you will see something like a hazy kind of cloud. If you focus you can see outward scalar expansion from a single point, inward contraction, toroidal flow, and in the mix you can even see what seem like shadows of bugs on the surface of the water but are not, I'll leave it to you and your curiosity to try and find out what types of things those little zips/zings of motions look like in the field that is the water in the swimming pool. But for our purposes, the shadow of this mass liquid activity is important because of the edges and delineation between the circular shadow and the refracted light encircling the shadow on the pool floor.
DNA serves as the proof of concept in nature—data storage that demonstrably stores and emits coherent photons at room temperature using groove structures (dark regions) read by boundary-sensing proteins. Nature solved this problem billions of years ago.
What this is and isn't:
As with my other post on Qualia Algebra, this isn't an extension of RS2 theory per se, but rather an application of the RS2 framework to a specific engineering problem. The paper presents testable predictions and a five-phase experimental validation pathway. It may be wrong—but it offers a different angle on a problem the mainstream is struggling with.
The full document, with annotated bibliography, is available here: https://github.com/QAv2/topological-photonic-computing