Proteinoids, or thermal proteins, are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. In aqueous solutions proteinoids swell into hollow microspheres. These microspheres produce endogenous burst of electrical potential spikes and change patterns of their electrical activity in response to illumination. We report results of detailed investigation on the effects of white cold light on the spiking of proteinoids. We study how different types and intensities of light determine proteinoids' spiking amplitude, period, and pattern. The results of this study will be utilised to evaluate proteinoids for their potential as optical sensors and their application in unconventional computing.
The synthesis approaches for quantum circuits typically aim at minimizing the number of lines or gates. Given the tight restrictions on those logical resources in physical implementations, we propose to view the problem fundamentally different: Given noisy gates and a fixed number of lines, how can we use them to perform a computation as precisely as possible? In this paper we show approximate circuits can be deployed for computations with limited resources. Performing experiments on a QC simulator, we show that under the influence of noise, approximate circuits can have lower error-rates than exact circuits.
Akhilesh S P Khope, Anirban Samanta, Xian Xiao
et al.
In this review paper, we present an elaborate discussion on wavelength selective switches and their demonstrations. We also review packaging and electronic photonic integration of switches; a topic neglected in other review papers. We also cover wavelength locking which is paramount in switching networks with many tunable filters.
In this work we propose an effective preconditioning technique to accelerate the steady-state simulation of large-scale memristor crossbar arrays (MCAs). We exploit the structural regularity of MCAs to develop a specially-crafted preconditioner that can be efficiently evaluated utilizing tensor products and block matrix inversion. Numerical experiments demonstrate the efficacy of the proposed technique compared to mainstream preconditioners.
Numerous neural network circuits and architectures are presently under active research for application to artificial intelligence and machine learning. Their physical performance metrics (area, time, energy) are estimated. Various types of neural networks (artificial, cellular, spiking, and oscillator) are implemented with multiple CMOS and beyond-CMOS (spintronic, ferroelectric, resistive memory) devices. A consistent and transparent methodology is proposed and used to benchmark this comprehensive set of options across several application cases. Promising architecture/device combinations are identified.
A commonly accepted feature of an excitable medium is that a local excitation leads to a propagation of circular or spiral excitation wave-fronts. This is indeed the case in fully excitable medium. However, with a decrease of an excitability localised wave-fragments emerge and propagate ballistically. Using FitzhHugh-Nagumo model we numerically study how excitation wave-fronts behave in a geometrically constrained medium and how the wave-fronts explore a random planar graph. We uncover how excitability controls propagation of excitation in angled branches, influences arrest of excitation entering a sudden expansion, and determines patterns of traversing of a random planar graph by an excitation waves.
Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised in making the actin network executing specific computing circuits. The propagation of localisations on a single actin filament is experimentally unfeasible, therefore we propose a `relaxed' version of the computing on actin networks by considering excitation waves propagating on actin bundles. We show that by using an arbitrary arrangement of electrodes it is possible to implement two-inputs-one-output circuits. Frequencies of the Boolean gates' detection in actin network match an overall distribution of gates discovered in living substrates.
Quantum-dot cellular automata (QCAs) offer a diffusive computing paradigm with picosecond transmission speed, making them an ideal candidate for moving diffusive computing to real-world applications. By implementing a trainable associative memory neural network into this substrate, we demonstrate that high-speed, high-density associative memory is feasible through QCAs. The presented design occupies $415\text{nm}^2$ per neuron, which translates to circa $240 \text{ billion neurons/cm}^2$, or $28\text{GB/cm}^2$ of memory storage, offering a real possibility for large-scale associative memory circuits. Results are presented from simulation, demonstrating correct working behaviour of the associative memory in single neurons, two-neuron and four-neuron arrays.
This paper presents RDCSim, an interactive simulator for reaction--diffusion chemistry (RDC) research, being developed as part of an ongoing project studying how humans interact with unconventional computing systems. While much research into the computational properties of RDC makes use of simulations, the development of multiple RDC simulations across different research groups can lead to results that are harder to reproduce. By automating the storage of parameter values alongside simulation results, RDCSim aims to make reproducing RDC results painless. This paper presents the functionality of RDCSim, and verifies the behaviour of the underlying chemical simulation using two seminal examples from the RDC literature: logical AND gates and chemical diodes.
With the increase of the speed of computers, timing and power requirements are becoming crucial for memory devices. The main objective of the paper is to modify 180nm CMOS sense amplifier design by using memristive devices and improve the design in terms of on-chip area, power efficiency, resistance to temperatures and speed. To achieve this, NOT gates in the circuit were constructed using memristor and CMOS. The main aim of the paper is to check the effect of memristors on characteristics of sense amplifier. The design was tested on Conventional Current Sense Amplifier (CSA) circuit. Changes in power, area, sensing delay and offset are reported in the paper.
We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction, as well as an overview over the physical mechanism that lead to memristive behavior. This review is meant to guide nonpractitioners in the field of memristive circuits and their connection to machine learning and neural computation.
Stochastic computing, a form of computation with probabilities, presents an alternative to conventional arithmetic units. Magnetic Tunnel Junctions (MTJs), which exhibit probabilistic switching, have been explored as Stochastic Number Generators (SNGs). We provide a perspective of the energy requirements of such an application and design an energy-efficient and data-sensitive MTJ-based SNG. We discuss its benefits when used for stochastic computations, illustrating with the help of a multiplier circuit, in terms of energy savings when compared to computing with the baseline MTJ-SNG.
Probabilistic Neural Network (PNN) is a feed-forward artificial neural network developed for solving classification problems. This paper proposes a hardware implementation of an approximated PNN (APNN) algorithm in which the conventional exponential function of the PNN is replaced with gated threshold logic. The weights of the PNN are approximated using a memristive crossbar architecture. In particular, the proposed algorithm performs normalization of the training weights, and quantization into 16 levels which significantly reduces the complexity of the circuit.
We present a collection of results concerning the structure of reversible gate classes over non-binary alphabets, including (1) a reversible gate class over non-binary alphabets that is not finitely generated (2) an explicit set of generators for the class of all gates, the class of all conservative gates, and a class of generalizations of the two (3) an embedding of the poset of reversible gate classes over an alphabet of size $k$ into that of an alphabet of size $k+1$ (4) a classification of gate classes containing the class of $(k-1,1)$-conservative gates, meaning gates that preserve the number of occurrences of a certain element in the alphabet.
System and synthetic biology are rapidly evolving systems, but both lack tools such as those used in engineering environments to shift the their focus from the design of parts (details) to the design of systems (behaviors); to aggravate, there are insufficient theoretical justifications on the computational limits of biological systems. To diminish these deficiencies, we present theoretical results over the Turing-equivalence of metabolic systems, defines rules for translations of algorithms into metabolic P systems and presents a software tool to assist the task in an automatic way.
The recent development in analog computation is reviewed in this paper. Analog computation was used in many applications where power and energy efficiency is of paramount importance. It is shown that by using innovative architecture and circuit design, analog computation systems can achieve much higher energy efficiency than their digital counterparts, as they are able to exploit the computational power inherent to the devices and physics. However, these systems do suffer from some disadvantages, such as lower accuracy and speed, and designers have come up with novel approaches to overcome them. The paper provides an overview of analog computation systems, from basic components such as memory and arithmetic elements, to architecture and system design.
A remark concerning the temporal adverb już and its French equivalentsGenerally speaking, this contrastive study of the Polish temporal adverb już and the French déjà is based around the idea that już and déjà have an invariant meaning but it is also true that they follow different idiosyncratic usages. This article has two parts. First, the authors show the usages of już which are equivalent to those of déjà. These usages appear when już and déjà are put in a specific verbal context. The authors describe the four cases in which już and déjà are equivalent: “precocity of event”, existential usage, iterative-continuative usage, experiential perfect usage. Secondly, the authors analyze four cases in which the Polish adverb już can’t be translated by the French déjà. These incompatibilities can be explained by either morphological idiosyncrasy or the conventionalization of deictic meaning of już, which is absent of déjà.
Self-sustaining nonlinear oscillators of practically any type can function as latches and registers if Boolean logic states are represented physically as the phase of oscillatory signals. Combinational operations on such phase-encoded logic signals can be implemented using arithmetic negation and addition followed by amplitude limiting. With these, general-purpose Boolean computation using a wide variety of natural and engineered oscillators becomes potentially possible. Such phase-encoded logic shows promise for energy efficient computing. It also has inherent noise immunity advantages over traditional level-based logic.
James G. H. Whiting, Ben P. J. de Lacy Costello, Andrew Adamatzky
We experimentally derived a unique one-to-one mapping between a range of selected bioactive chemicals and patterns of oscillations of the slime mould's extacellular electrical potential.
We report on a new paradigm of information display that greatly extends the utility and versatility of current optoelectronic displays. The main innovation is to let a display of high refresh rate optically broadcast so-called atom frames, which are designed through non-negative matrix factorization to form bases for a class of images, and different viewers perceive selfintended images by using display-synchronized viewing devices and their own human visual systems to fuse appropriately weighted atom frames. This work is essentially a scheme of temporal psychovisual modulation in visible spectrum, using an optoelectronic modulator coupled with a biological demodulator.