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Nanoelectronic devices
Published in David Crawley, Konstantin Nikolić, Michael Forshaw, 3D Nanoelectronic Computer Architecture and Implementation, 2020
Quantum cellular automata (QCA) offer an alternative computing architecture to CMOS technology [119]. QCA systems consist of arrays of cells. Each cell affects its neighbouring cells through an (electric or magnetic) field and they normally have no other connections. Typical cellular automata (CA) systems are electronic QCAs (EQCA) and magnetic QCAs (MQCA). Furthermore, Josephson Junction Persistent Current Bits (JJPCB) and even Rapid Single Flux Quantum (RSFQ) circuits have been described as cellular automata. For encoding logic states, these systems use: EQCAs, the spatial distribution of electric charges within a cell [120–22]; MQCAs, the direction of magnetic moments [123]; JJPCBs, the direction of the current in a superconducting loop [124, 125] and RSFQs, single-flux-quantum voltage pulses [126, 127], see figure 4.11. Mutual cell interactions can be used to propagate and compute binary [125, 128] (or, in some cases, quantum) information. Every CA cell is supposed to evolve into a stable state that is determined by the properties of the neighbouring cells (and perhaps by external fields). Arrays of CA cells can be seen as computing circuits, where the state of an array is mapped to a computation. The potential advantages of this concept over conventional transistor-based logic are: high speed, insensitivity to electrical disturbances and cosmic rays, ease of fabrication, very good scaling potential (possibly down to molecular sizes), room temperature operation and low power. Unfortunately, these advantages do not all exist in the same device.
Fundamentals, Modeling, and Application of Magnetic Tunnel Junctions
Published in Brajesh Kumar Kaushik, Nanoscale Devices, 2018
Ramtin Zand, Arman Roohi, Ronald F. DeMara
Aggressive Metal Oxide Semiconductor (MOS) technology scaling in digital circuits has resulted in important challenges including a significant increase in leakage currents, short-channel effects, and drain saturation growth while reducing the power supply voltage for digital applications. Furthermore, by extensions to sub-10-nm regimes, error resiliency has become a major challenge for the microelectronics industry, particularly mission-critical systems, e.g., space and terrestrial applications. Therefore, emerging devices and technologies have attracted considerable attention in recent years as an alternative to CMOS-based technologies such as spintronic [1–6], resistive random access memory (RRAM) [7–10], phase-change memory (PCM) [11,12], and quantum cellular automata (QCA) [13–18]. Among promising devices, the 2014 Magnetism Roadmap [19] identifies nanomagnetic devices as capable post-CMOS candidates, of which magnetic tunnel junctions (MTJs) are considered one of the most promising technologies spanning both logic [20–22] and memory functionalities [23–25]. MTJs are characterized by non-volatility, near-zero standby power, high integration density, and radiation hardness as a technology progression from CMOS. Moreover, MTJs can be readily integrated at the back-end process of the CMOS fabrication due to their vertical structure [26,27].
A Brief Study on Quantum Walks and Quantum Mechanics
Published in Thiruselvan Subramanian, Archana Dhyani, Adarsh Kumar, Sukhpal Singh Gill, Artificial Intelligence, Machine Learning and Blockchain in Quantum Satellite, Drone and Network, 2023
Sapna Renukaradhya, Preethi, Rupam Bhagawati, Thiruselvan Subramanian
As a consequence of this investigation, Feynman’s writings [23] take into consideration the discretisation of the Dirac equation, and a model is developed as a result of this investigation. It has been tried to be recreated in the setting of the quantum Turing computer stopping by many writers, including Meyer [24], Watrous, and others [25,26]. Also in Ref. [25], reasoning about space-bounded quantum computing techniques, where it was connected with quantum cellular automata, it was replicated with a little alteration using measurement methods, and it was also linked with quantum cellular automata. Ambainis et al. [26] created and tested it as a practical computing tool that conformed to a formal presenting style, which they called “formal presentation style”.
A Novel Co-Planar Five Input Majority Gate Design in Quantum-Dot Cellular Automata
Published in IETE Technical Review, 2022
Animesh Srivastava, Rajeevan Chandel
A local electric field is required for the control of potential barriers of the tunnelling junctions. The electric field respectively controls the lowering and raising of the potential barriers for electron movement and the siege of the motion. A QCA cell can exist in three different states, depending on the potential barrier. Polarization (P) is the state in which a QCA cell exists. Cell achieves a Null State when the barrier is low; this provides the electrons with the freedom to select dots. Polarization corresponding to logic 1 has value P = +1, and for logic 0 value of P = −1, which is achieved when the potential barrier is raised (shown in Figure 1). Unlike the movement of electrons in CMOS-based circuits, repulsion due to the Columbic force helps in the interaction [17] between quantum cellular automata cells.