Physical reservoir computing is an innovative idea for using physical phenomena as computational resources. Recent research has revealed that information processing techniques can improve the performance, but for practical applications, it is equally important to study the level of performance with a simple design that is easy to construct experimentally. We focus on a reservoir composed of independent hysteretic systems as a model suitable for the practical implementation of physical reservoir computing. In this paper, we discuss the appropriate design of this reservoir, its performance, and its limitations. This research will serve as a practical guideline for constructing hysteresis-based reservoirs.
OSC-Qasm is a cross-platform, Python-based, OSC interface for executing Qasm code. It serves as a simple way to connect creative programming environments like Max (with The QAC Toolkit) and Pure Data with real quantum hardware, using the Open Sound Control protocol. In this paper, the authors introduce the context and meaning of developing a tool like this, and what it can offer to creative artists.
Southeast Asian Association for regional Co-operation was established in 1967 for the region's socio-economic development. Now it has been working as a single economic body and has become the sixth-largest economy in the world and third largest in Asia. It constitutes the third-largest population in the world that is effectively connected through physical and digital means. This study aims to develop a theoretical understanding of the concept of regional Integration and to analyze the trends of regional integration suitable for the South East Asian region specifically. It focuses on the ASEAN's Triple-Cs Principle to deeply analyze its journey of regional economic integration. This Principle, basically, describe the existing strategic patterns of economic integration specifically used in the ASEAN countries to maintain their territorial integrity and increase socio-economic development in the world’s most diverse region. It further shows that how ASEAN remained consistently committed to regional integration since its initiation, for that purpose, how ASEAN worked on the journey of regional connectivity. And, How the advancement in the digital arena, is constantly increasing the regional connectivity (through digital means) and has become a backbone for the process of regional integration in the Asian region. Finally, how regional connectivity brings Peace, Progress, and Prosperity in the South East Asia. Further, it also helps to analyze that how much the existing patterns of Asian regionalism are conducive for socio-economic development. This study is divided into the following sections; the first section briefly describes the central theories of regionalism. In addition, it extensively describes the concept of region, regionalism, and regional integration and the importance of regional integration in the Asian region. The second section of the study explains the details of the Triple-Cs Principle of ASEAN for regional integration. The third section describes how ASEAN followed the Triple-Cs principle during its journey towards regional economic integration in different phases. Finally, it concludes with certain recommendations
Sanmitra Banerjee, Mahdi Nikdast, Sudeep Pasricha
et al.
We propose a novel hardware-aware magnitude pruning technique for coherent photonic neural networks. The proposed technique can prune 99.45% of network parameters and reduce the static power consumption by 98.23% with a negligible accuracy loss.
In this reply, we will provide our impersonal, point-to-point responses to the major criticisms (in bold and underlined) in arXiv:1909.12464. Firstly, we will identify a number of (imperceptibly hidden) mistakes in the Comment in understanding/interpreting our physical model. Secondly, we will use a 3rd-party experiment carried out in 1961 (plus other 3rd-party experiments thereafter) to further support our claim that our invented Phi memristor is memristive in spite of the existence of a parasitic inductor effect. Thirdly, we will analyse this parasitic effect mathematically, introduce our work-in-progress (in nanoscale) and point out that this parasitic inductor effect should not become a big worry since it can be completely removed in the macro-scale devices and safely neglected in the nano-scale devices.
Andrew Adamatzky, Antoni Gandia, Alessandro Chiolerio
A fungal skin is a thin flexible sheet of a living homogeneous mycelium made by a filamentous fungus. The skin could be used in future living architectures of adaptive buildings and as a sensing living skin for soft self-growing/adaptive robots. In experimental laboratory studies we demonstrate that the fungal skin is capable for recognising mechanical and optical stimulation. The skin reacts differently to loading of a weight, removal of the weight, and switching illumination on and off. These are the first experimental evidences that fungal materials can be used not only as mechanical `skeletons' in architecture and robotics but also as intelligent skins capable for recognition of external stimuli and sensorial fusion.
Ling Qiu, Mahabubul Alam, Abdullah Ash-Saki
et al.
Variational algorithm using Quantum Approximate Optimization Algorithm (QAOA) can solve the prime factorization problem in near-term noisy quantum computers. Conventional Variational Quantum Factoring (VQF) requires a large number of 2-qubit gates (especially for factoring a large number) resulting in deep circuits. The output quality of the deep quantum circuit is degraded due to errors limiting the computational power of quantum computing. In this paper, we explore various transformations to optimize the QAOA circuit for integer factorization. We propose two criteria to select the optimal quantum circuit that can improve the noise resiliency of VQF.
Efficient simulation of probabilistic memristors and their networks requires novel modeling approaches. One major departure from the conventional memristor modeling is based on a master equation for the occupation probabilities of network states [arXiv:2003.11011 (2020)]. In the present article, we show how to implement such master equations in SPICE - a general-purpose circuit simulation program. In the case studies, we simulate the dynamics of ac-driven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice codes are included.
In this position paper, we present a discussion on neuromorphic computing and especially the learning/training algorithm to design a series of brains with different memristive values to solve complex ill-posed inverse problems based on a Finite Element(FE) method. First, the neuromorphic computing is addressed and we focus on a type of memristive circuit computing that falls into the scope of neuromorphic computing. Secondly based on reference [1] in which the complex dynamics of the complex memristive circuit was studied, we design a method and an approach to train the memristive circuit so that the memristive values are optimally obtained.
Smaller, smarter and faster edge devices in the Internet of things era demands secure data analysis and transmission under resource constraints of hardware architecture. Lightweight cryptography on edge hardware is an emerging topic that is essential to ensure data security in near-sensor computing systems such as mobiles, drones, smart cameras, and wearables. In this article, the current state of memristive cryptography is placed in the context of lightweight hardware cryptography. The paper provides a brief overview of the traditional hardware lightweight cryptography and cryptanalysis approaches. The contrast for memristive cryptography with respect to traditional approaches is evident through this article, and need to develop a more concrete approach to developing memristive cryptanalysis to test memristive cryptographic approaches is highlighted.
Проведен геометрический и топологический анализ металлооксида с минимальным известным содержанием кислорода CsO, образующегося из кислородсодержащего расплава металлического Cs. Для определения кластеров-прекурсоров кристаллических структур использованы специальные алгоритмы разложения структурных графов на кластерные субструктуры (пакет программ ToposPro). Определены участвующие в самосборке кристаллических структур кластеры-прекурсоры: трехоктаэдрические кластеры CsO, октаэдрические кластеры Cs, тетраэдрические кластеры Cs. Реконструированы симметрийный и топологический коды процессов самосборки кристаллических структур из кластеров-прекурсоров в виде: первичная цепь микрослой микрокаркас.
The memristive crossbar aims to implement analog weighted neural network, however, the realistic implementation of such crossbar arrays is not possible due to limited switching states of memristive devices. In this work, we propose the design of an analog deep neural network with binary weight update through backpropagation algorithm using binary state memristive devices. We show that such networks can be successfully used for image processing task and has the advantage of lower power consumption and small on-chip area in comparison with digital counterparts. The proposed network was benchmarked for MNIST handwritten digits recognition achieving an accuracy of approximately 90%.
Samuel J. Ellis, Titus H. Klinge, James I. Lathrop
We introduce a new motif for constructing robust digital logic circuits using input/output chemical reaction networks. These chemical circuits robustly handle perturbations in input signals, initial concentrations, rate constants, and measurements. In particular, we show that all combinatorial circuits and several sequential circuits enjoy this robustness. Our results complement existing literature in the following three ways: (1) our logic gates read their inputs catalytically which make `fanout' gates unnecessary; (2) formal requirements and rigorous proofs of satisfaction are provided for each circuit; and (3) robustness of every circuit is closed under modular composition.
Ileskhan Kalysh, Olga Krestinskaya, Alex Pappachen James
This paper proposes four quadrant analog multiplier using CMOS-memristor circuit. Currently, there are plenty of analog multipliers using resistors and CMOS transistors. They can attain perfect multiplication but have several disadvantages such as lower processing speed, higher power consumption and larger chip areas. Memristor based circuits are introduced to resolve the mentioned drawbacks. In this paper current mode four quadrant multiplier based on squaring circuits is taken as a framework, and CMOS transistors are replaced with memristors. The circuit design is simulated with SPICE, and variability analysis and performance variation with temperature is performed. The proposed circuit allows faster processing with retained data while dissipating less power retaining the multiplication characteristics.
Fazel Sharifi, Atiyeh Panahi, Mohammad Hossein Moaiyeri
et al.
This paper investigates the use of carbon nanotube field effect transistors (CNFETs) for the design of ternary full adder cells. The proposed circuits have been designed based on the unique properties of CNFETs such as having desired threshold voltages by adjusting diameter of the CNFETs gate nanotubes. The proposed circuits are examined using HSPICE simulator with the standard 32 nm CNFET technology. The proposed methods are simulated at different conditions such as different supply voltages, different temperature and operational frequencies. Simulation results show that the proposed designs are faster than the state of the art CNFET based ternary full adders.
With the advent of big data and deep learning, computation power has become a bottleneck for many applications. Network-on-Chip (NoC) has been proposed to enable multiprocessor acceleration for deep learning computation, and efficient arbitration is a key issue for high performance. In this paper, an arbitration scheme based on interference of wave is proposed. In this scheme, home node sends out multiple tokens in different frequencies, and nodes that are competing for bus can capture token by sending out wave that cancels its specific wave token. In this scheme, speed-of-light arbitration can be achieved, and full information is available to all nodes in arbitration.
A novel processing-in-storage (PRinS) architecture based on Resistive CAM (ReCAM) is described and proposed for Smith-Waterman (S-W) sequence alignment. The ReCAM massively-parallel compare operation finds matching base-pairs in a fixed number of cycles, regardless of sequence length. The ReCAM PRinS S-W algorithm is simulated and compared to FPGA, Xeon Phi and GPU-based implementations, showing at least 4.7x higher throughput and at least 15x lower power dissipation.
Laszlo Bela Kish, Kamran Entesari, Claes-Goran Granqvist
et al.
The statistical-physics-based Kirchhoff-law-Johnson-noise (KLJN) key exchange offers a new and simple unclonable system for credit/debit card chip authentication and payment. The key exchange, the authentication and the communication are unconditionally secure so that neither mathematics- nor statistics-based attacks are able to crack the scheme. The ohmic connection and the short wiring lengths between the chips in the card and the terminal constitute an ideal setting for the KLJN protocol, and even its simplest versions offer unprecedented security and privacy for credit/debit card chips and applications of physical unclonable functions.
This document presents a studies of the stochastic behavior of D-Wave qubits, qubit cells, and qubit chains. The purpose of this paper is to address the algorithmic behavior of execution rather than the physical behavior, though they are related. The measurements from an actual D-Wave adiabatic quantum computer are compare with calculated measurements from a theoretical adiabatic quantum computer running with an effective temperature of zero. In this way the paper attempts to shed light on how the D-Wave's behavior effects how well it minimizes its objective function and why the D-Wave performs as it does.