Quantum field lens coding and classification algorithm to predict measurement outcomes

Quantum AI and hybrid simulators for a Universal Quantum Field Computation Model

“…The simulation problem begins when one wants to study events occurring in a thermodynamic system. The idea to simulate this system on the smallest possible scale, not smaller than the Planck length [2 , [7] , [8] , [9] , was proposed by R. Feynman [1 , 27] , as a quantum simulation model. Questions were raised and discussed around the possibility of building a universal computer capable of simulating the universe and answer fundamental questions about the physics of matter [1] .…”

“…The reason is, Hamiltonian models of physical interest can be expressed in locally interacting spins, e.g., Ising and Heisenberg models [38 , 40 , 54] . The fidelity and probability for measuring spin type Hamiltonians, range from an open system exhibiting disorder in noisy channels, to models that use photons, sampled and slave particles [7 , 26 , 52] . In [52] , shuffling the photons’ positions can detect multi-entangled photons with random probabilities.…”

“…This is an evolutionary Hamiltonian of the thermodynamic system. Same studies [7 , 52 , 54] propose the simulation of a desired Hamiltonian using trapped ions and super-conducting quantum circuits. Certain method objectives must be met to validate such model solutions as follows.…”

“… Compare models’ limitations and strengths as the 2nd objective. Visualize events, their probabilities and predict them reliably to determine system efficiency, and suggest alternative energy paths to achieve a desired Hamiltonian [7] (target state) of the system. The goal is to achieve a universal QFCM (UQFCM) for the strongest system state prediction ( Fig.…”

“…In this review, Ref. [7] is used to compare its findings with other method articles published on quantum simulation models that simulate QFThs in different fields of science employing cutting-edge methodologies to observe and predict any physical system event. Other supportive research articles used in this review: doi: 10.2139/ssrn.4239321 distributed in Elsevier e-Journals e.g., Comp.…”