Classification Using a Two-Qubit Quantum Chip

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

“…This processing is part of an I/O data control mechanism in Table 4 . Higher layers of prediction are developed based on the recorded ST probability data and its distribution focused using QF lenses, and distance-based classifiers [7] , [8] , [9] , [10] , [29] , [30] , [31] , Section 1.1. From Eq.…”

“…This representation opposed the classical observation of massive scales defined in Newtonian physics [1] . Relation to other fields of science, such as in chemistry [16] , QAI algorithms [29] , [30] , [31] , 44 , 45] are required to plot a detailed observation and quantification of energy and matter in the system [1] . Among which, is the study of a spin Hamiltonian in LQFThs [5 , 16] , nuclear magnetic resonance (NMR) [26] , BEC with ground states as a quantum phase transition (QPT) [7] , [8] , [9] , 25] , and other related QFCMs [3 , 4 , 21] .…”

“…QFCMs as input and their comparisons as output are controlled at the IDS step to decide whether a UQFCM outcome can be achieved. The selected models by IDS are [3] , [4] , [5] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [17] , [18] , [19] , 23 , [29] , [30] , [31] , 36 , 38 , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] , 59 , 60] . The more its SMDB and encoders use classifiers from a QAI classification system, the more the IDS identifies a hybrid of classical and QFCM at decoding to make a strong prediction.…”

“…P. B. A. and T. A. G. thank Dr. T. Lu for comments on the scalar field models, dimensions and photonics on the QDF model development, Dr. M. Laca for comments on QDF model’s four measurement variables [7] , [8] , [9] , [10] , [11] , Dr. N. Neumann remarks on QAI classifiers [29 , 30] , and the late Dr. F. Diacu for comment on phase transitions to parameterize their quantum probabilities in the QDF model [7] , [8] , [9] , [10] , [11] . All of which, in this review, were compared to QFTh models to propose and develop a universal QFCM.…”

“…The solution to a UQFCM is to simulate physical systems on any scale using QAI with strong prediction results over , corelated to results, performed by specific models [7] , [8] , [9] , 45] . This presents a high in distinguishing and classifying particle states based on their distance-based classifiers [7 , [28] , [29] , [30] . Classifiers measure distance between data points and assign weights to a class to generate energy scores.…”