Logic, Design & Organization of PTVD-SHAM; A Parallel Time Varying & Data Super-helical Access Memory

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📝 Original Info

  • Title: Logic, Design & Organization of PTVD-SHAM; A Parallel Time Varying & Data Super-helical Access Memory
  • ArXiv ID: 0707.1151
  • Date: 2015-03-13
  • Authors: Researchers from original ArXiv paper

📝 Abstract

This paper encompasses a super helical memory system's design, 'Boolean logic & image-logic' as a theoretical concept of an invention-model to 'store time-data' in terms of anticipating the best memory location ever for data/time. A waterfall effect is deemed to assist the process of potential-difference output-switch into diverse logic states in quantum dot computational methods via utilizing coiled carbon nanotubes (CCNTs) and carbon nanotube field effect transistors (CNFETs). A 'quantum confinement' is thus derived for a flow of particles in a categorized quantum well substrate with a normalized capacitance rectifying high B-field flux into electromagnetic induction. Multi-access of coherent sequences of 'qubit addressing' is gained in any magnitude as pre-defined for the orientation of array displacement. Briefly, Gaussian curvature of k<0 is debated in aim of specifying the 2D electron gas characteristics in scenarios where data is stored in short intervals versus long ones e.g. when k'>(k<0) for greater CCNT diameters, space-time continuum is folded by chance for the particle. This benefits from Maxwell-Lorentz theory in Minkowski's space-time viewpoint alike to crystal oscillators for precise data timing purposes and radar systems e.g., time varying self-clocking devices in diverse geographic locations. This application could also be optional for data depository versus extraction, in the best supercomputer system's locations, autonomously. For best performance in minimizing current limiting mechanisms including electromigration, a multilevel metallization and implant process forming elevated sources/drains for the circuit's staircase pyramidal construction, is discussed accordingly.

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Deep Dive into Logic, Design & Organization of PTVD-SHAM; A Parallel Time Varying & Data Super-helical Access Memory.

This paper encompasses a super helical memory system’s design, ‘Boolean logic & image-logic’ as a theoretical concept of an invention-model to ‘store time-data’ in terms of anticipating the best memory location ever for data/time. A waterfall effect is deemed to assist the process of potential-difference output-switch into diverse logic states in quantum dot computational methods via utilizing coiled carbon nanotubes (CCNTs) and carbon nanotube field effect transistors (CNFETs). A ‘quantum confinement’ is thus derived for a flow of particles in a categorized quantum well substrate with a normalized capacitance rectifying high B-field flux into electromagnetic induction. Multi-access of coherent sequences of ‘qubit addressing’ is gained in any magnitude as pre-defined for the orientation of array displacement. Briefly, Gaussian curvature of k<0 is debated in aim of specifying the 2D electron gas characteristics in scenarios where data is stored in short intervals versus long ones e.g. w

📄 Full Content

arXiv:0707.1151v6 [cs.AR] 2 Oct 2007 Computer Science & Engineering, Phase: Theor. Proj. Tec. Rep. (2007) Vol. 1, Rev. Ver. 6, 1-33 Proj. No.TXU001347562 Ext. on 02 Oct 2007 ————————————————————— Logic, Design & Organization of PTVD-SHAM; A Parallel Time Varying & Data Super-helical Access Memory By Philip Baback Alipour 1 , 2 , ∗, † 1-Category of Computer Sciences, Laboratory of Systems Technology, Research, Design & Development, Elm Tree Farm, Wallingfen Lane, Newport, Brough, HU15 1RF, UK 2- Computer Science & Engineering Departments, University of Hull, Cottingham Road, Hull Campus, East Yorkshire, HU6 7RX, UK Abstract. This paper encompasses a super helical memory system’s design, ‘Boolean logic & image-logic’ as a theoretical concept of an invention-model to ‘store time-data’ in terms of anticipating the best memory location ever for data/time. A waterfall effect is deemed to assist the process of potential-difference output-switch into diverse logic states in quantum dot computational methods via utilizing coiled carbon nan- otubes (CCNTs) and carbon nanotube field effect transistors (CNFETs). A ‘quantum confinement’ is thus derived for a flow of particles in a categorized quantum well sub- strate with a normalized capacitance rectifying high B-field flux into electromagnetic induction. Multi-access of coherent sequences of ‘qubit addressing’ is gained in any magnitude as pre-defined for the orientation of array displacement. Briefly, Gaussian curvature of k < 0 is debated in aim of specifying the 2D electron gas characteris- tics in scenarios where data is stored in short intervals versus long ones e.g., when k′ > (k < 0) for greater CCNT diameters, space-time continuum is folded by chance for the particle. This benefits from Maxwell-Lorentz theory in Minkowski’s space- time viewpoint alike to crystal oscillators for precise data timing purposes and radar systems e.g., time varying self-clocking devices in diverse geographic locations. This application could also be optional for data depository versus extraction in the best supercomputer system’s locations, autonomously. For best performance in minimizing current limiting mechanism including electromigration, a multilevel metallization and implant process forming elevated sources/drains for the circuit’s staircase pyramidal construction, is discussed accordingly. Keywords: image logic; depository vector; quantum bit; the special theory of relativity; carbon nanotube field effect transistor; two-dimensional electron gas ∗Author for correspondence (philipbaback orbsix@msn.com). †The original version of this paper was created in MS-Word software program, where the current version is reconstructed from the original paper in LaTeX editing environment for public review. I thank those anonymous administrators at ArXiv.org, rectifying file conversion problems on the previous versions of the paper since the 1st submission on 9 July 2007. 1 Principles and introduction 2 1 Principles and introduction Possessing the fact that multiple qubits can exhibit quantum entanglement (see e.g., qubit entanglement [27]), a solution to store the entangled Bell states of electrons from 2DEG system, moving free into the two-dimensional plane, now to some complex plane’s depository vector system defining storable qubit(s), is thus emerged in practice. Furthermore, binary values by binary variable biti, as input signal ∀Ain ∈{0, 1} by ratio to qubit variable as input signal Bin, are introduced via bit-frequency νbit ≡Ain Bint ˛˛˛˛˛˛ for Ain 8 < : 0 ∧= L±V 1 ∧= H±V 9 = ; for Bin : |Ψ⟩= n Y m=1 |Ψ⟩m , m = 1, 2, ..., n, (1.1) which is in the memory system’s product, hereby of importance to generate quantum efficiency for hot-electron spectra. With response to mathematical relations in defining the characteristics of the storage layers of the memory system (subsequent relation), relation (1.1), distributes into future relations (5.1) to (5.5), explaining events related to low-voltage differential signaling (LVDS) e.g., [38]. Specifically, these voltages are computed between components of the memory’s staircase levels in terms of Vin, addi- tion to stored charges possessing a quantized voltage ≥k mV amongst memory traps for Bin defined from wavefunction |ψ⟩’s Bell states. In possession of the previous relation, simplifying Bell states’ relations concern- ing collectable data points as quantum dots embedded in a 2DEG layer of the high electron mobility transistor (HEMT; for higher state of carrier’s mobility) and metal- oxide semiconductor field-effect transistor (MOSFET technology), did not require the study of spin conditions. The requirement to examine the four well-known Bell states’ scenarios during the course of entanglement in the 3D space where CNT coils remain, was also eliminated. In fact, from the point of particle confinement, a depository vec- tor emergence by some arbitrary angle for a storable qubit in the storage film, to the point of storing Boolean and qubit data as the lower layers of t

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