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  • Optoelectronic Intelligence
    arXiv.cs.ET Pub Date : 2020-10-17
    Jeffrey M. Shainline

    To design and construct hardware for general intelligence, we must consider principles of both neuroscience and very-large-scale integration. For large neural systems capable of general intelligence, the attributes of photonics for communication and electronics for computation are complementary and interdependent. Using light for communication enables high fan-out as well as low-latency signaling across

  • Quantum computing approach to railway dispatching and conflict management optimization on single-track railway lines
    arXiv.cs.ET Pub Date : 2020-10-16
    Krzysztof Domino; Mátyás Koniorczyk; Krzysztof Krawiec; Konrad Jałowiecki; Bartłomiej Gardas

    We consider a railway dispatching problem: delay and conflict management on a single-track railway line. We examine the issue of train dispatching consequences caused by the arrival of an already delayed train to the segment being considered. This is a computationally hard problem and its solution is needed in a very short time in practice. We introduce a quadratic unconstrained binary optimization

  • QDLC -- The Quantum Development Life Cycle
    arXiv.cs.ET Pub Date : 2020-10-15
    Nivedita Dey; Mrityunjay Ghosh; Subhra Samir kundu; Amlan Chakrabarti

    The magnificence grandeur of quantum computing lies in the inherent nature of quantum particles to exhibit true parallelism, which can be realized by indubitably fascinating theories of quantum physics. The possibilities opened by quantum computation (QC) is no where analogous to any classical simulation as quantum computers can efficiently simulate the complex dynamics of strongly correlated inter-facial

  • A Novel Quantum Algorithm for Ant Colony Optimization
    arXiv.cs.ET Pub Date : 2020-10-14
    Mrityunjay Ghosh; Nivedita Dey; Debdeep Mitra; Amlan Chakrabarti

    Ant colony optimization is one of the potential solutions to tackle intractable NP-Hard discrete combinatorial optimization problems. The metaphor of ant colony can be thought of as the evolution of the best path from a given graph as a globally optimal solution, which is unaffected by earlier local convergence to achieve improved optimization efficiency. Earlier Quantum Ant Colony Optimization research

  • Teaching Quantum Computing through a Practical Software-driven Approach: Experience Report
    arXiv.cs.ET Pub Date : 2020-10-12
    Mariia Mykhailova; Krysta M. Svore

    Quantum computing harnesses quantum laws of nature to enable new types of algorithms, not efficiently possible on traditional computers, that may lead to breakthroughs in crucial areas like materials science and chemistry. There is rapidly growing demand for a quantum workforce educated in the basics of quantum computing, in particular in quantum programming. However, there are few offerings for non-specialists

  • Using the Parameterized Quantum Circuit combined with Variational-Quantum-Eigensolver (VQE) to create an Intelligent social workers' schedule problem solver
    arXiv.cs.ET Pub Date : 2020-10-12
    Atchade Parfait Adelomou; Elisabet Golobardes Ribe; Xavier Vilasis Cardona

    The social worker scheduling problem is a class of combinatorial optimization problems that combines scheduling with routing issues. These types of problems with classical computing can only be solved, in the best of cases, in an approximate way and significantly when the input data does not grow considerably. Today, the focus on the quantum computer should no longer be only on its enormous computing

  • Thermal-Aware Compilation of Spiking Neural Networks to Neuromorphic Hardware
    arXiv.cs.ET Pub Date : 2020-10-09
    Twisha Titirsha; Anup Das

    Hardware implementation of neuromorphic computing can significantly improve performance and energy efficiency of machine learning tasks implemented with spiking neural networks (SNNs), making these hardware platforms particularly suitable for embedded systems and other energy-constrained environments. We observe that the long bitlines and wordlines in a crossbar of the hardware create significant current

  • Phase Configuration Learning in Wireless Networks with Multiple Reconfigurable Intelligent Surfaces
    arXiv.cs.ET Pub Date : 2020-10-09
    George C. Alexandropoulos; Sumudu Samarakoon; Mehdi Bennis; Merouane Debbah

    Reconfigurable Intelligent Surfaces (RISs) are recently gaining remarkable attention as a low-cost, hardware-efficient, and highly scalable technology capable of offering dynamic control of electro-magnetic wave propagation. Their envisioned dense deployment over various obstacles of the, otherwise passive, wireless communication environment has been considered as a revolutionary means to transform

  • Reconfigurable Intelligent Surfaces and Machine Learning for Wireless Fingerprinting Localization
    arXiv.cs.ET Pub Date : 2020-10-07
    Cam Ly Nguyen; Orestis Georgiou; Gabriele Gradoni

    Reconfigurable Intelligent Surfaces (RISs) promise improved, secure and more efficient wireless communications. We propose and demonstrate how to exploit the diversity offered by RISs to generate and select easily differentiable radio maps for use in wireless fingerprinting localization applications. Further, we apply machine learning feature selection methods to prune the large state space of the

  • Symbolic Verification of Quantum Circuits
    arXiv.cs.ET Pub Date : 2020-10-05
    Mingsheng Ying; Zhengfeng Ji

    This short note proposes a symbolic approach for representing and reasoning about quantum circuits using complex, vector or matrix-valued Boolean expressions. A major benefit of this approach is that it allows us to directly borrow the existing techniques and tools for verification of classical logic circuits in reasoning about quantum circuits.

  • WoLFRaM: Enhancing Wear-Leveling and Fault Tolerance in Resistive Memories using Programmable Address Decoders
    arXiv.cs.ET Pub Date : 2020-10-06
    Leonid Yavits; Lois Orosa; Suyash Mahar; João Dinis Ferreira; Mattan Erez; Ran Ginosar; Onur Mutlu

    Resistive memories have limited lifetime caused by limited write endurance and highly non-uniform write access patterns. Two main techniques to mitigate endurance-related memory failures are 1) wear-leveling, to evenly distribute the writes across the entire memory, and 2) fault tolerance, to correct memory cell failures. However, one of the main open challenges in extending the lifetime of existing

  • A Concentration-Time Hybrid Modulation Scheme for Molecular Communications
    arXiv.cs.ET Pub Date : 2020-10-05
    Mustafa Can Gursoy; Daewon Seo; Urbashi Mitra

    Significant inter-symbol interference (ISI) challenges the achievement of reliable, high data-rate molecular communication via diffusion. In this paper, a hybrid modulation based on pulse position and concentration is proposed to mitigate ISI. By exploiting the time dimension, molecular concentration and position modulation (MCPM) increases the achievable data rate over conventional concentration and

  • Robust High-dimensional Memory-augmented Neural Networks
    arXiv.cs.ET Pub Date : 2020-10-05
    Geethan Karunaratne; Manuel Schmuck; Manuel Le Gallo; Giovanni Cherubini; Luca Benini; Abu Sebastian; Abbas Rahimi

    Traditional neural networks require enormous amounts of data to build their complex mappings during a slow training procedure that hinders their abilities for relearning and adapting to new data. Memory-augmented neural networks enhance neural networks with an explicit memory to overcome these issues. Access to this explicit memory, however, occurs via soft read and write operations involving every

  • Resonant Energy Recycling SRAM Architecture
    arXiv.cs.ET Pub Date : 2020-10-05
    Riadul Islam; Biprangshu Saha; Ignatius Bezzam

    Although we may be at the end of Moore's law, lowering chip power consumption is still the primary driving force for the designers. To enable low-power operation, we propose a resonant energy recovery static random access memory (SRAM). We propose the first series resonance scheme to reduce the dynamic power consumption of the SRAM operation. Besides, we identified the requirement of supply boosting

  • Quantum Bayesian decision-making*
    arXiv.cs.ET Pub Date : 2020-10-05
    Michael de Oliveira; Luis Soares Barbosa

    As a compact representation of joint probability distributions over a dependence graph of random variables, and a tool for modelling and reasoning in the presence of uncertainty, Bayesian networks are of great importance for artificial intelligence to combine domain knowledge, capture causal relationships, or learn from incomplete datasets. Known as a NP-hard problem in a classical setting, Bayesian

  • The Fourier signatures of memristive hysteresis
    arXiv.cs.ET Pub Date : 2020-10-03
    Y. V. Pershin; C. -C. Chien; M. Di Ventra

    While resistors with memory, sometimes called memristive elements (such as ReRAM cells), are often studied under conditions of periodic driving, little attention has been paid to the Fourier features of their memory response (hysteresis). Here we demonstrate experimentally that the hysteresis of memristive systems can be unambiguously distinguished from the linear or non-linear response of systems

  • Non-Markovian Momentum Computing: Universal and Efficient
    arXiv.cs.ET Pub Date : 2020-10-02
    Kyle J. Ray; Gregory W. Wimsatt; Alexander B. Boyd; James P. Crutchfield

    All computation is physically embedded. Reflecting this, a growing body of results embraces rate equations as the underlying mechanics of thermodynamic computation and biological information processing. Strictly applying the implied continuous-time Markov chains, however, excludes a universe of natural computing. We show that expanding the toolset to continuous-time hidden Markov chains substantially

  • Realization of p_valued Deutsch quantum gates
    arXiv.cs.ET Pub Date : 2020-09-30
    Claudio Moraga

    In this report reversible Toffoli and quantum Deutsch gates are extended to the p_valued domain. Their structural parameters are determined and their behavior is proven. Both conjunctive and disjunctive control strategies with positive and mixed polarities are introduced for the first time in a p_valued domain. The design is based on elementary Muthukrishnan_Stroud quantum gates, hence the realizability

  • Post-Quantum Error-Correction for Quantum Annealers
    arXiv.cs.ET Pub Date : 2020-09-30
    Ramin Ayanzadeh; John Dorband; Milton Halem; Tim Finin

    We present a general post-quantum error-correcting technique for quantum annealing, called multi-qubit correction (MQC), that views the evolution in an open-system as a Gibs sampler and reduces a set of (first) excited states to a new synthetic state with lower energy value. After sampling from the ground state of a given (Ising) Hamiltonian, MQC compares pairs of excited states to recognize virtual

  • Temporal State Machines: Using temporal memory to stitch time-based graph computations
    arXiv.cs.ET Pub Date : 2020-09-29
    Advait Madhavan; Matthew Daniels; Mark Stiles

    Race logic, an arrival-time-coded logic family, has demonstrated energy and performance improvements for applications ranging from dynamic programming to machine learning. However, the ad hoc mappings of algorithms into hardware result in custom architectures making them difficult to generalize. We systematize the development of race logic by associating it with the mathematical field called tropical

  • A Machine Learning-based Approach to Detect Threats in Bio-Cyber DNA Storage Systems
    arXiv.cs.ET Pub Date : 2020-09-28
    Federico Tavella; Alberto Giaretta; Mauro Conti; Sasitharan Balasubramaniam

    Data storage is one of the main computing issues of this century. Not only storage devices are converging to strict physical limits, but also the amount of data generated by users is growing at an unbelievable rate. To face these challenges, data centres grew constantly over the past decades. However, this growth comes with a price, particularly from the environmental point of view. Among various promising

  • Reliability-Performance Trade-offs in Neuromorphic Computing
    arXiv.cs.ET Pub Date : 2020-09-26
    Twisha Titirsha; Anup Das

    Neuromorphic architectures built with Non-Volatile Memory (NVM) can significantly improve the energy efficiency of machine learning tasks designed with Spiking Neural Networks (SNNs). A major source of voltage drop in a crossbar of these architectures are the parasitic components on the crossbar's bitlines and wordlines, which are deliberately made longer to achieve lower cost-per-bit. We observe that

  • Design and Evaluation of a Receiver for Wired Nano-Communication Networks
    arXiv.cs.ET Pub Date : 2020-09-24
    Oussama Abderrahmane Dambri; Soumaya Cherkaoui

    In this paper, we propose a bio-inspired receiver, which detects the electrons transmitted through a nanowire, then, it converts the detected information into a blue light using bioluminescence. Using light allows the designed receiver to also act as a relay for the nearest gateway (photo-detector). We simulate the construction of the nanowire, present its electrical characteristics and calculate its

  • Collective and synchronous dynamics of photonic spiking neurons
    arXiv.cs.ET Pub Date : 2020-09-24
    Takahiro Inagaki; Kensuke Inaba; Timothée Leleu; Toshimori Honjo; Takuya Ikuta; Koji Enbutsu; Takeshi Umeki; Ryoichi Kasahara; Kazuyuki Aihara; Hiroki Takesue

    Nonlinear dynamics of spiking neural networks has recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective spiking dynamics of neurons, the fine control of spiking dynamics is desirable for neuromorphic devices. Here we show that photonic spiking neurons implemented

  • TIGER: Topology-aware Assignment using Ising machines Application to Classical Algorithm Tasks and Quantum Circuit Gates
    arXiv.cs.ET Pub Date : 2020-09-21
    Anastasiia Butko; Ilyas Turimbetov; George Michelogiannakis; David Donofrio; Didem Unat; John Shalf

    Optimally mapping a parallel application to compute and communication resources is increasingly important as both system size and heterogeneity increase. A similar mapping problem exists in gate-based quantum computing where the objective is to map tasks to gates in a topology-aware fashion. This is an NP-complete graph isomorphism problem, and existing task assignment approaches are either heuristic

  • TSV Extrusion Morphology Classification Using Deep Convolutional Neural Networks
    arXiv.cs.ET Pub Date : 2020-09-22
    Brendan Reidy; Golareh Jalilvand; Tengfei Jiang; Ramtin Zand

    In this paper, we utilize deep convolutional neural networks (CNNs) to classify the morphology of through-silicon via (TSV) extrusion in three dimensional (3D) integrated circuits (ICs). TSV extrusion is a crucial reliability concern which can deform and crack interconnect layers in 3D ICs and cause device failures. Herein, the white light interferometry (WLI) technique is used to obtain the surface

  • Analysing and Measuring the Performance ofMemristive Integrating Amplifiers
    arXiv.cs.ET Pub Date : 2020-09-21
    Jiaqi Wang; Alexander Serb; Christos Papavassiliou; Sachin Maheshwari; Themistoklis Prodromakis

    Recording reliably extracellular neural activities isan essential prerequisite for the development of bioelectronicsand neuroprosthetic applications. Recently, a fully differential,2-stage, integrating pre-amplifier was proposed for amplifyingand then digitising neural signals. The amplifier featured a finelytuneable offset that was used as a variable threshold detector.Given that the amplifier is

  • Closed-loop spiking control on a neuromorphic processor implemented on the iCub
    arXiv.cs.ET Pub Date : 2020-09-01
    Jingyue Zhao; Nicoletta Risi; Marco Monforte; Chiara Bartolozzi; Giacomo Indiveri; Elisa Donati

    Despite neuromorphic engineering promises the deployment of low latency, adaptive and low power systems that can lead to the design of truly autonomous artificial agents, the development of a fully neuromorphic artificial agent is still missing. While neuromorphic sensing and perception, as well as decision-making systems, are now mature, the control and actuation part is lagging behind. In this paper

  • Enabling Resource-Aware Mapping of Spiking Neural Networks via Spatial Decomposition
    arXiv.cs.ET Pub Date : 2020-09-19
    Adarsha Balaji; Shihao Song; Anup Das; Jeffrey Krichmar; Nikil Dutt; James Shackleford; Nagarajan Kandasamy; Francky Catthoor

    With growing model complexity, mapping Spiking Neural Network (SNN)-based applications to tile-based neuromorphic hardware is becoming increasingly challenging. This is because the synaptic storage resources on a tile, viz. a crossbar, can accommodate only a fixed number of pre-synaptic connections per post-synaptic neuron. For complex SNN models that have many pre-synaptic connections per neuron,

  • On the spatiotemporal behavior in biology-mimicking computing systems
    arXiv.cs.ET Pub Date : 2020-09-18
    János Végh; Ádám J. Berki

    The payload performance of conventional computing systems, from single processors to supercomputers, reached its limits the nature enables. Both the growing demand to cope with "big data" (based on, or assisted by, artificial intelligence) and the interest in understanding the operation of our brain more completely, stimulated the efforts to build biology-mimicking computing systems from inexpensive

  • ACSS-q: Algorithmic complexity for short strings via quantum accelerated approach
    arXiv.cs.ET Pub Date : 2020-09-18
    Aritra Sarkar; Koen Bertels

    In this research we present a quantum circuit for estimating algorithmic complexity using the coding theorem method. This accelerates inferring algorithmic structure in data for discovering causal generative models. The computation model is restricted in time and space resources to make it computable in approximating the target metrics. The quantum circuit design based on our earlier work that allows

  • Exploring a Double Full-Stack Communications-Enabled Architecture for Multi-Core Quantum Computers
    arXiv.cs.ET Pub Date : 2020-09-17
    Santiago RodrigoNaNoNetworking Center in Catalonia - Universitat Politècnica de Catalunya; Sergi AbadalNaNoNetworking Center in Catalonia - Universitat Politècnica de Catalunya; Eduard AlarcónNaNoNetworking Center in Catalonia - Universitat Politècnica de Catalunya; Carmen G. AlmudeverQuTech - Delft University of Technology

    Being a very promising technology, with impressive advances in the recent years, it is still unclear how quantum computing will scale to satisfy the requirements of its most powerful applications. Although continued progress in the fabrication and control of qubits is required, quantum computing scalability will depend as well on a comprehensive architectural design considering a multi-core approach

  • Reconfigurable Intelligent Surface (RIS) Assisted Wireless Coverage Extension: RIS Orientation and Location Optimization
    arXiv.cs.ET Pub Date : 2020-09-17
    Shuhao Zeng; Hongliang Zhang; Boya Di; Zhu Han; Lingyang Song

    Recently, reconfigurable intelligent surfaces (RIS) have attracted a lot of attention due to their capability of extending cell coverage by reflecting signals toward the receiver. In this letter, we analyze the coverage of a downlink RIS-assisted network with one base station (BS) and one user equipment (UE). Since the RIS orientation and the horizontal distance between the RIS and the BS have a significant

  • What Have Google's Random Quantum Circuit Simulation Experiments Demonstrated about Quantum Supremacy?
    arXiv.cs.ET Pub Date : 2020-09-15
    Jack K. Horner; John F. Symons

    Quantum computing is of high interest because it promises to perform at least some kinds of computations much faster than classical computers. Arute et al. 2019 (informally, "the Google Quantum Team") report the results of experiments that purport to demonstrate "quantum supremacy" -- the claim that the performance of some quantum computers is better than that of classical computers on some problems

  • Modulated Signals in Chemical Reaction Networks
    arXiv.cs.ET Pub Date : 2020-09-14
    Titus H. Klinge; James I. Lathrop

    Electrical engineering and molecular programming share many of the same mathematical foundations. In this paper, we show how to send multiple signals through a single pair of chemical species using modulation and demodulation techniques found in electrical engineering. Key to our construction, we provide chemical implementations of classical linear band-pass and low-pass filters with induced differential

  • Probabilistic Resistive Switching Device modeling based on Markov Jump processes
    arXiv.cs.ET Pub Date : 2020-09-14
    Vasileios Ntinas; Antonio Rubio; Georgios Ch. Sirakoulis

    In this work, a versatile mathematical framework for multi-state probabilistic modeling of Resistive Switching (RS) devices is proposed for the first time. The mathematical formulation of memristor and Markov jump processes are combined and, by using the notion of master equations for finite-states, the inherent probabilistic time-evolution of RS devices is sufficiently modeled. In particular, the

  • MERAM: Non-Volatile Cache Memory Based on Magneto-Electric FETs
    arXiv.cs.ET Pub Date : 2020-09-14
    Shaahin Angizi; Navid Khoshavi; Andrew Marshall; Peter Dowben; Deliang Fan

    Magneto-Electric FET (MEFET) is a recently developed post-CMOS FET, which offers intriguing characteristics for high speed and low-power design in both logic and memory applications. In this paper, for the first time, we propose a non-volatile 2T-1MEFET memory bit-cell with separate read and write paths. We show that with proper co-design at the device, cell and array levels, such a design is a promising

  • Circuit Design for K-coloring Problem and it's Implementation on Near-term Quantum Devices
    arXiv.cs.ET Pub Date : 2020-09-13
    Amit Saha; Debasri Saha; Amlan Chakrabarti

    Now-a-days in Quantum Computing, implementation of quantum algorithm has created a stir since Noisy Intermediate-Scale Quantum (NISQ) devices are out in the market. Researchers are mostly interested in solving NP-complete problems with the help of quantum algorithms for its speed-up. As per the work on computational complexity by Karp, if any of the NP-complete problem can be solved then any other

  • Reactive fungal wearable
    arXiv.cs.ET Pub Date : 2020-09-11
    Andrew Adamatzky; Anna Nikolaidou; Antoni Gandia; Alessandro Chiolerio; Mohammad Mahdi Dehshib

    Smart wearables sense and process information from the user's body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in soft electronics. Organic electronics and bioelectronics, especially with living substrates, offer a great opportunity to incorporate parallel sensing and

  • Modeling networks of probabilistic memristors in SPICE
    arXiv.cs.ET Pub Date : 2020-09-11
    V. J. Dowling; V. A. Slipko; Y. V. Pershin

    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.

  • Mapping the XY Hamiltonian onto a Network of Coupled Lasers
    arXiv.cs.ET Pub Date : 2020-09-10
    Mostafa Honari-Latifpour; Mohammad-Ali Miri

    In recent years there has been a growing interest in the physical implementation of classical spin models through networks of optical oscillators. However, a key missing step in this mapping is to formally prove that the dynamics of such a nonlinear dynamical system is toward minimizing a global cost function which is equivalent with the spin model Hamiltonian. Here, we introduce a minimal dynamical

  • Simphony: An open-source photonic integrated circuit simulation framework
    arXiv.cs.ET Pub Date : 2020-07-23
    Sequoia Ploeg; Hyrum Gunther; Ryan M. Camacho

    We present Simphony, a free and open-source software toolbox for abstracting and simulating photonic integrated circuits, implemented in Python. The toolbox is both fast and easily extensible; plugins can be written to provide compatibility with existing layout tools, and device libraries can be easily created without a deep knowledge of programming. We include several examples of photonic circuit

  • Forecasting timelines of quantum computing
    arXiv.cs.ET Pub Date : 2020-09-10
    Jaime Sevilla; C. Jess Riedel

    We consider how to forecast progress in the domain of quantum computing. For this purpose we collect a dataset of quantum computer systems to date, scored on their physical qubits and gate error rate, and we define an index combining both metrics, the generalized logical qubit. We study the relationship between physical qubits and gate error rate, and tentatively conclude that they are positively correlated

  • Digital Signal Processing for Molecular Communication via Chemical Reactions-based Microfluidic Circuits
    arXiv.cs.ET Pub Date : 2020-09-10
    Dadi Bi; Yansha Deng

    Chemical reactions-based microfluidic circuits are expected to provide new opportunities to perform signal processing functions over molecular domain. To realize this vision, in this article, we exploit and present the digital signal processing capabilities of chemical reactions-based microfluidic circuits. Aiming to facilitate microfluidic circuit design, we describe a microfluidic circuit using a

  • Mitiq: A software package for error mitigation on noisy quantum computers
    arXiv.cs.ET Pub Date : 2020-09-09
    Ryan LaRose; Andrea Mari; Peter J. Karalekas; Nathan Shammah; William J. Zeng

    We introduce an open-source software package for error mitigation in quantum computation using zero-noise extrapolation. Error mitigation techniques improve computational performance (with respect to noise) with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Our error mitigation package interfaces with multiple quantum computing

  • Low-cost Active Dry-Contact Surface EMG Sensor for Bionic Arms
    arXiv.cs.ET Pub Date : 2020-09-05
    Asma M. Naim; Kithmin Wickramasinghe; Ashwin De Silva; Malsha V. Perera; Thilina Dulantha Lalitharatne; Simon L. Kappel

    Surface electromyography (sEMG) is a popular bio-signal used for controlling prostheses and finger gesture recognition mechanisms. Myoelectric prostheses are costly, and most commercially available sEMG acquisition systems are not suitable for real-time gesture recognition. In this paper, a method of acquiring sEMG signals using novel low-cost, active, dry-contact, flexible sensors has been proposed

  • SlackQ : Approaching the Qubit Mapping Problem with A Slack-aware Swap Insertion Scheme
    arXiv.cs.ET Pub Date : 2020-09-04
    Chi Zhang; Yanhao Chen; Yuwei Jin; Wonsun Ahn; Youtao Zhang; Eddy Z. Zhang

    The rapid progress of physical implementation of quantum computers paved the way for the design of tools to help users write quantum programs for any given quantum device. The physical constraints inherent in current NISQ architectures prevent most quantum algorithms from being directly executed on quantum devices. To enable two-qubit gates in the algorithm, existing works focus on inserting SWAP gates

  • Virtualized Logical Qubits: A 2.5D Architecture for Error-Corrected Quantum Computing
    arXiv.cs.ET Pub Date : 2020-09-04
    Casey Duckering; Jonathan M. Baker; David I. Schuster; Frederic T. Chong

    Current, near-term quantum devices have shown great progress in recent years culminating with a demonstration of quantum supremacy. In the medium-term, however, quantum machines will need to transition to greater reliability through error correction, likely through promising techniques such as surface codes which are well suited for near-term devices with limited qubit connectivity. We discover quantum

  • Ultrafast non-volatile flash memory based on van der Waals heterostructures
    arXiv.cs.ET Pub Date : 2020-09-03
    Lan Liu; Yi Ding; Jiayi Li; Chunsen Liu; Peng Zhou

    Flash memory has become a ubiquitous solid-state memory device, it is widely used in portable digital devices, computers, and enterprise applications. The development of the information age has put forward higher requirements for memory speed and retention performance. Here, we demonstrate an ultrafast non-volatile memory based on MoS2/h-BN/multi-layer graphene (MLG) van der Waals heterostructures

  • CONTRA: Area-Constrained Technology Mapping Framework For Memristive Memory Processing Unit
    arXiv.cs.ET Pub Date : 2020-09-02
    Debjyoti Bhattacharjee; Anupam Chattopadhyay; Srijit Dutta; Ronny Ronen; Shahar Kvatinsky

    Data-intensive applications are poised to benefit directly from processing-in-memory platforms, such as memristive Memory Processing Units, which allow leveraging data locality and performing stateful logic operations. Developing design automation flows for such platforms is a challenging and highly relevant research problem. In this work, we investigate the problem of minimizing delay under arbitrary

  • Fully analog memristive circuits for optimization tasks: a comparison
    arXiv.cs.ET Pub Date : 2020-09-02
    Forrest C. Sheldon; Francesco Caravelli; Carleton Coffrin

    We introduce a Lyapunov function for the dynamics of memristive circuits, and compare the effectiveness of memristors in minimizing the function to widely used optimization software. We study in particular three classes of problems which can be directly embedded in a circuit topology, and show that memristors effectively attempt at (quickly) extremizing these functionals.

  • Turning machines
    arXiv.cs.ET Pub Date : 2020-09-02
    Irina Kostitsyna; Cai Wood; Damien Woods

    Molecular robotics is challenging, so it seems best to keep it simple. We consider an abstract molecular robotics model based on simple folding instructions that execute asynchronously. Turning Machines are a simple 1D to 2D folding model, also easily generalisable to 2D to 3D folding. A Turning Machine starts out as a line of connected monomers in the discrete plane, each with an associated turning

  • On resistive spiking of fungi
    arXiv.cs.ET Pub Date : 2020-09-01
    Andrew Adamatzky; Alessandro Chiolerio; Georgios Sirakoulis

    We study long-term electrical resistance dynamics in mycelium and fruit bodies of oyster fungi P. ostreatus. A nearly homogeneous sheet of mycelium on the surface of a growth substrate exhibits trains of resistance spikes. The average width of spikes is c.~23~min and the average amplitude is c.~1~kOhm. The distance between neighbouring spikes in a train of spikes is c.~30~min. Typically there are 4-6

  • AIDX: Adaptive Inference Scheme to Mitigate State-Drift in Memristive VMM Accelerators
    arXiv.cs.ET Pub Date : 2020-09-01
    Tony Liu; Amirali Amirsoleimani; Fabien Alibart; Serge Ecoffey; Dominique Drouin; Roman Genov

    An adaptive inference method for crossbar (AIDX) is presented based on an optimization scheme for adjusting the duration and amplitude of input voltage pulses. AIDX minimizes the long-term effects of memristance drift on artificial neural network accuracy. The sub-threshold behavior of memristor has been modeled and verified by comparing with fabricated device data. The proposed method has been evaluated

  • A Survey of Molecular Communication in Cell Biology: Establishing a New Hierarchy for Interdisciplinary Applications
    arXiv.cs.ET Pub Date : 2020-08-31
    Dadi Bi; Apostolos Almpanis; Adam Noel; Yansha Deng; Robert Schober

    Molecular communication (MC) engineering is inspired by the use of chemical signals as information carriers in cell biology. The biological nature of chemical signaling makes MC a promising methodology for interdisciplinary applications requiring communication between cells and other microscale devices. However, since the life sciences and communications engineering fields have distinct approaches

  • Direct CMOS Implementation of Neuromorphic Temporal Neural Networks for Sensory Processing
    arXiv.cs.ET Pub Date : 2020-08-27
    Harideep Nair; John Paul Shen; James E. Smith

    Temporal Neural Networks (TNNs) use time as a resource to represent and process information, mimicking the behavior of the mammalian neocortex. This work focuses on implementing TNNs using off-the-shelf digital CMOS technology. A microarchitecture framework is introduced with a hierarchy of building blocks including: multi-neuron columns, multi-column layers, and multi-layer TNNs. We present the direct

  • The Computational Capacity of Memristor Reservoirs
    arXiv.cs.ET Pub Date : 2020-08-31
    Forrest C. Sheldon; Artemy Kolchinsky; Francesco Caravelli

    Reservoir computing is a machine learning paradigm in which a high-dimensional dynamical system, or \emph{reservoir}, is used to approximate and perform predictions on time series data. Its simple training procedure allows for very large reservoirs that can provide powerful computational capabilities. The scale, speed and power-usage characteristics of reservoir computing could be enhanced by constructing

  • Reversible Computing with Fast, Fully Static, Fully Adiabatic CMOS
    arXiv.cs.ET Pub Date : 2020-08-28
    Michael P. Frank; Robert W. Brocato; Brian D. Tierney; Nancy A. Missert; Alexander H. Hsia

    To advance the energy efficiency of general digital computing far beyond the thermodynamic limits that apply to conventional digital circuits will require utilizing the principles of reversible computing. It has been known since the early 1990s that reversible computing based on adiabatic switching is possible in CMOS, although almost all of the "adiabatic" CMOS logic families in the literature are

  • Low-Cost Performance-Efficient Field-Programmable Pin-Constrained Digital Microfluidic Biochip
    arXiv.cs.ET Pub Date : 2020-08-31
    Alireza Abdoli; Sedigheh Farhadtoosky; Ali Jahanian

    Digital microfluidic biochips (DMFBs) are revolutionary biomedical devices towards diagnostics and point-of-care applications; the chips provide the capability of performing wide ranges of biochemistry and laboratory procedures, offering various opportunities among which to mention are automation, miniaturization and cost-affordability of bioassays. There have been various digital microfluidic biochips

  • Floating-Point Multiplication Using Neuromorphic Computing
    arXiv.cs.ET Pub Date : 2020-08-30
    Karn Dubey; Urja Kothari; Shrisha Rao

    Neuromorphic computing describes the use of VLSI systems to mimic neuro-biological architectures and is also looked at as a promising alternative to the traditional von Neumann architecture. Any new computing architecture would need a system that can perform floating-point arithmetic. In this paper, we describe a neuromorphic system that performs IEEE 754-compliant floating-point multiplication. The

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