Wolfgang Porod

Quantum cellular automata

The authors formulate a new paradigm for computing with cellular automata (CAS) composed of arrays of quantum devices-quantum cellular automata. Computing in such a paradigm is edge driven. Input, output, and power are delivered at the edge of the CA array only; no direct flow of information or energy to internal cells is required. Computing in this paradigm is also computing with the ground state. The architecture is so designed that the ground-state configuration of the array, subject to boundary conditions determined by the input, yields the computational result. The authors propose a specific realization of these ideas using two-electron cells composed of quantum dots. The charge density in the cell is very highly polarized (aligned) along one of the two cell axes, suggestive of a two-state CA. The polarization of one cell induces a polarization in a neighboring cell through the Coulomb interaction in a very non-linear fashion. Quantum cellular automata can perform useful computing. The authors show that AND gates, OR gates, and inverters can be constructed and interconnected.

Bistable saturation in coupled quantum dots for quantum cellular automata

A simple model quantum dot cell containing two electrons is analyzed as a candidate for quantum cellular automata implementations. The cell has eigenstates whose charge density is strongly aligned along one of two directions. In the presence of the electrostatic perturbation due to a neighboring cell, the ground state is nearly completely aligned (polarized) in one direction only. The polarization is a highly nonlinear function of the perturbing electrostatic fields and shows the strong bistable saturation important for cellular automation function.

Qualitative analysis and synthesis of a class of neural networks

The dynamic properties of a class of neural networks (which includes the Hopfield model as a special case) are investigated by studying the qualitative behavior of equilibrium points. The results fall into one of two categories: results pertaining to analysis (e.g., stability properties of an equilibrium, asymptotic behavior of solutions, etc.) and results pertaining to synthesis (e.g. the design of a neural network with prespecified equilibrium points which are asymptotically stable). Most (but not all) of the results presented are global, and their applicability is demonstrated by an example. >

Analysis and synthesis of a class of neural networks: linear systems operating on a closed hypercube

An investigation was conducted of the qualitative properties of a class of neural networks described by a system of first-order linear ordinary differential equations which are defined on a closed hypercube of the state space with solutions extended to the boundary of the hypercube. When solutions are located on the boundary of the hypercube, the system is said to be in a saturated mode. The class of systems considered retains the basic structure of the Hopfield model but is easier to analyze, synthesize, and implement. An efficient analysis method is developed which can be used to determine completely the set of asymptotically stable equilibrium points and the set of unstable equilibrium points. The latter set can be used to estimate the domains of attraction for the elements of the former set. The class of systems considered can easily be implemented in analog integrated circuits. The applicability of the results is demonstrated by means of several examples. >

Device and Architecture Outlook for Beyond CMOS Switches

Sooner or later, fundamental limitations destine complementary metal-oxide-semiconductor (CMOS) scaling to a conclusion. A number of unique switches have been proposed as replacements, many of which do not even use electron charge as the state variable. Instead, these nanoscale structures pass tokens in the spin, excitonic, photonic, magnetic, quantum, or even heat domains. Emergent physical behaviors and idiosyncrasies of these novel switches can complement the execution of specific algorithms or workloads by enabling quite unique architectures. Ultimately, exploiting these unusual responses will extend throughput in high-performance computing. Alternative tokens also require new transport mechanisms to replace the conventional chip wire interconnect schemes of charge-based computing. New intrinsic limits to scaling in post-CMOS technologies are likely to be bounded ultimately by thermodynamic entropy and Shannon noise.

Bistable saturation in coupled quantum‐dot cells

Model quantum dot cells are investigated as potential building blocks for quantum cellular automata architectures. Each cell holds a few electrons and interacts Coulombically with nearby cells. In acceptable cell designs, the charge density tends to align along one of two cell axes. Thus, a cell ‘‘polarization,’’ which can be used to encode binary information, is defined. The polarization of a cell is affected in a very nonlinear manner by the polarization of its neighbors. This interaction is quantified by calculating a cell–cell response function. Effects of nonzero temperature on the response of a model cell are investigated. The effects of multiple neighbors on a cell are examined and programmable logic gate structures based on these ideas are discussed.

Nanocomputing by field-coupled nanomagnets

Demonstrates through simulations the feasibility of using magnetically coupled nanometer-scale ferromagnetic dots for digital information processing. Microelectronic circuits provide the input and output of the magnetic nanostructure, but the signal is processed via magnetic dot-dot interactions. Logic functions can be defined by the proper placements of dots. We introduce a SPICE macromodel of interacting nanomagnets and use this tool to design and simulate the proposed nanomagnet logic units. This SPICE model allows us to simulate such magnetic information processing devices within the same framework as conventional electronic circuits.

Quantum cellular automata: the physics of computing with arrays of quantum dot molecules

We discuss the fundamental limits of computing using a new paradigm for quantum computation, cellular automata composed of arrays of coulombically coupled quantum dot molecules, which we term quantum cellular automata (QCA). Any logical or arithmetic operation can be performed in this scheme. QCAs provide a valuable concrete example of quantum computation in which a number of fundamental issues come to light. We examine the physics of the computing process in this paradigm. We show to what extent thermodynamic considerations impose limits on the ultimate size of individual QCA arrays. Adiabatic operation of the QCA is examined and the implications for dissipationless computing are explored.<<ETX>>

On-Chip Clocking for Nanomagnet Logic Devices

We report local control of nanomagnets that can be arranged to perform computation in a cellular automata-like architecture. This letter represents the first demonstration of deterministically placed quantum-dot cellular automata (QCA) devices (of any implementation), where devices are controlled by on-chip local fields.

Analysis and synthesis of a class of neural networks: variable structure systems with infinite grain

An investigation was conducted of the qualitative properties of a class of neural networks described by a system of first-order ordinary differential equations with discontinuous right hand side. An efficient synthesis procedure is developed for this class of neural networks. The class of systems considered may be used as a representation of the analog Hopfield model with the nonlinearities having infinite gain. Also, under appropriate assumptions, the output of the class of systems considered may be viewed as representing the behavior of the discrete Hopfield model. Thus the results give insight into the qualitative behavior of the analog as well as the discrete Hopfield models, and they provide a means of designing such models. The applicability of the present results is demonstrated by several specific examples. >