A process algebraic model extending quantum potentials and trajectories into information processing methods for modeling particle formation, interaction and transformation, and for general application in non-Turing quantum computation

I and my group of colleagues and associates are working on a combined theoretic and experimental program in theroretical and applied physics. Our investigations aim to achieve progress in the following integrated problem areas:

[1] refining a process algebraic model, based upon and extending the theoretical model of quantum potential that defines an implicate order as a pre-spacetime ground for the emergence of all energetic phenomena including matter, dark matter and dark energy.

This research directly associates quantum potential model with string-net liquids as the foundation for the emergence of defined particles including photons, electrons, and all other Standard Model particles, as well as the foundation for topological orders and macroscopic-scale collective-ensembles involving quantum entanglement phenomena.

This approach provides a foundation for understanding the integral unity between general relativistic and quantum mechanical behaviors by providing a unified basis for non-locality and unity with a consistent interpretation of gravity as the fundamental dynamic underlying particle-wave phenomena including entanglement.

[2] extending this process algebraic model to provide an information-theoretic description of particle and condensed-matter physics and to enable definition of algorithms for computing low-energy transformations of select particle and nuclear structures, including topological-condensation processes extending to the pre-particle substrate of string-net liquids.

This enables the calculation of quantum potentials that will represent and physically implement a mechanism for controlling emergence and transmutation of semi-stable particles of photon, lepton and hadron classes.

[3] applying this computational model to the general space of non-algorithmic problems for which a topological dynamic model and a computable quantum potential operating upon such a topology can provide solutions. This provides a new form of computing that can be described as a non-Turing quantum computer architecture. A physical topological structure is involved, and this may be molecular and certainly micro-scalar, and moreover, reconfigurable through electronics and chemistry including biomolecular engineering. This structure enables the representation of a problem state as a topology with multiple wave-particle interactions, the evolution of which over time leads to definition and resolution of optimized paths that are representable in the process algebra of quantum potentials. The use of other computational mechanisms including Turing-type machines (both conventional and qubit-based) enables the final resolution among solution choices.

This non-Turing quantum computer model is closely aligned with both theoretical and experimental work in quantum biology and in the neuroscientific study of sensory processing, memory and cognitive processes in the brain.

We have established a formal program for future research investigations including experimental work to demonstrate and ultimately develop practical applications from this work. The practical applications include quantum computers for a large variety of problems not accessible by present-day computers (including Turing-type quantum computers), and also new forms of cybernetics (control and optimization) for large-scale networks of cooperative robots and predictive analysis of massive data collections and assimilations pertaining to socioeconomics.