610 research outputs found
Quantitative transformation for implementation of adder circuits in physical systems
© 2015 Elsevier Ireland Ltd. Computing devices are composed of spatial arrangements of simple fundamental logic gates. These gates may be combined to form more complex adding circuits and, ultimately, complete computer systems. Implementing classical adding circuits using unconventional, or even living substrates such as slime mould Physarum polycephalum, is made difficult and often impractical by the challenges of branching fan-out of inputs and regions where circuit lines must cross without interference. In this report we explore whether it is possible to avoid spatial propagation, branching and crossing completely in the design of adding circuits. We analyse the input and output patterns of a single-bit full adder circuit. A simple quantitative transformation of the input patterns which considers the total number of bits in the input string allows us to map the respective input combinations to the correct outputs patterns of the full adder circuit, reducing the circuit combinations from a 2:1 mapping to a 1:1 mapping. The mapping of inputs to outputs also shows an incremental linear progression, suggesting its implementation in a range of physical systems. We demonstrate an example implementation, first in simulation, inspired by self-oscillatory dynamics of the acellular slime mould P. polycephalum. We then assess the potential implementation using plasmodium of slime mould itself. This simple transformation may enrich the potential for using unconventional computing substrates to implement digital circuits
A knowledge-based approach to VLSI-design in an open CAD-environment
A knowledge-based approach is suggested to assist a designer in the increasingly complex task of generating VLSI-chips from abstract, high-level specifications of the system. The complexity of designing VLSI-circuits has reached a level where computer-based assistance has become indispensable. Not all of the design tasks allow for algorithmic solutions. AI technique can be used, in order to support the designer with computer-aided tools for tasks not suited for algorithmic approaches. The approach described in this paper is based upon the underlying characteristics of VLSI design processes in general, comprising all stages of the design. A universal model is presented, accompanied with a recording method for the acquisition of design knowledge - strategic and task-specific - in terms of the design actions involved and their effects on the design itself. This method is illustrated by a simple design example: the implementation of the logical EXOR-component. Finally suggestions are made for obtaining a universally usable architecture of a knowledge-based system for VLSI-design
Quantum autoencoders via quantum adders with genetic algorithms
The quantum autoencoder is a recent paradigm in the field of quantum machine
learning, which may enable an enhanced use of resources in quantum
technologies. To this end, quantum neural networks with less nodes in the inner
than in the outer layers were considered. Here, we propose a useful connection
between approximate quantum adders and quantum autoencoders. Specifically, this
link allows us to employ optimized approximate quantum adders, obtained with
genetic algorithms, for the implementation of quantum autoencoders for a
variety of initial states. Furthermore, we can also directly optimize the
quantum autoencoders via genetic algorithms. Our approach opens a different
path for the design of quantum autoencoders in controllable quantum platforms
Towards Physarum Binary Adders
Plasmodium of \emph{Physarum polycephalum} is a single cell visible by
unaided eye. The plasmodium's foraging behaviour is interpreted in terms of
computation. Input data is a configuration of nutrients, result of computation
is a network of plasmodium's cytoplasmic tubes spanning sources of nutrients.
Tsuda et al (2004) experimentally demonstrated that basic logical gates can be
implemented in foraging behaviour of the plasmodium. We simplify the original
designs of the gates and show --- in computer models --- that the plasmodium is
capable for computation of two-input two-output gate and
three-input two-output . We assemble the
gates in a binary one-bit adder and demonstrate validity of the design using
computer simulation.Comment: Biosystems (2010), in press. Please download final version of the
paper from the Publishers's sit
Option Pricing using Quantum Computers
We present a methodology to price options and portfolios of options on a
gate-based quantum computer using amplitude estimation, an algorithm which
provides a quadratic speedup compared to classical Monte Carlo methods. The
options that we cover include vanilla options, multi-asset options and
path-dependent options such as barrier options. We put an emphasis on the
implementation of the quantum circuits required to build the input states and
operators needed by amplitude estimation to price the different option types.
Additionally, we show simulation results to highlight how the circuits that we
implement price the different option contracts. Finally, we examine the
performance of option pricing circuits on quantum hardware using the IBM Q
Tokyo quantum device. We employ a simple, yet effective, error mitigation
scheme that allows us to significantly reduce the errors arising from noisy
two-qubit gates.Comment: Fixed a typo. This article has been accepted in Quantu
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