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In-memory analog matrix computing (AMC) with resistive random-access memory (RRAM) represents a highly promising solution that solves matrix problems in one step. However, the existing AMC circuits each have a specific connection topology…
Circuit elements within magnonic computers generally operate using signals that are either amplitude or phase modulated (AM or PM). We propose a simple all-magnon circuit element capable of converting between these two types of encoding. We…
Some of the most arduous and error-prone aspects of precision resummed calculations are related to the partonic hard process, having nothing to do with the resummation. In particular, interfacing to parton-distribution functions, combining…
We describe a hybrid analog-digital computing approach to solve important combinatorial optimization problems that leverages memristors (two-terminal nonvolatile memories). While previous memristor accelerators have had to minimize analog…
Magnonics has been receiving significant attention in magnetism and spintronics because of its premise for devices using spin current carried by magnons, quanta of spin-wave excitations of a macroscopically ordered magnetic media. Although…
In this work faster unsigned multiplication has been achieved by using a combination of High Performance Multiplication [HPM] column reduction technique and implementing a N-bit multiplier using 4 N/2-bit multipliers (recursive…
Conventional boost converters are essential to connect low-voltage energy source such as battery with high voltage DC bus in Electric Vehicles due to its simple construction and high conversion efficiency. However, large output capacitor…
Cavity magnonics deals with the interaction of magnons - elementary excitations in magnetic materials - and confined electromagnetic fields. We introduce the basic physics and review the experimental and theoretical progress of this young…
CNOT gates are fundamental to quantum computing, as they facilitate entanglement, a crucial resource for quantum algorithms. Certain classes of quantum circuits are constructed exclusively from CNOT gates. Given their widespread use, it is…
Although vast amounts of information are conveyed by photons in optical fibers, the majority of data processing is performed electronically, creating the infamous 'information bottleneck' and consuming energy at an increasingly…
Researchers and designers are facing problems with memory and power walls, considering the pervasiveness of Von-Neumann architecture in the design of processors and the problems caused by reducing the dimensions of deep sub-micron…
This work presents COmPOSER, an open-source, end-to-end framework for RF/mm-wave design automation that translates target specifications into optimized circuits with layouts. It unifies schematic synthesis, layout generation for actives and…
This paper proposes an low power approximate multiplier architecture for deep neural network (DNN) applications. A 4:2 compressor, introducing only a single combination error, is designed and integrated into an 8x8 unsigned multiplier. This…
The population analysis and estimation of merger rates of compact binaries is one of the important topics in gravitational wave (GW) astronomy. The primary ingredient in these analyses is the population-averaged sensitive volume. Typically,…
The paper aims to emphasise how switched systems can be analysed with elementary techniques which require only undergraduate-level linear algebra and differential equations. It is also emphasised how math software can become useful for…
Quantum computing opens exciting opportunities for kernel-based machine learning methods, which have broad applications in data analysis. Recent works show that quantum computers can efficiently construct a model of a classifier by…
Signal processing in wireless communications, such as precoding, detection, and channel estimation, are basically about solving inverse matrix problems, which, however, are slow and inefficient in conventional digital computers, thus…
Nanoscale amplification of non-linear processes in solid-state devices opens novel applications in nano-electronics, nano-medicine or high energy conversion for example. Coupling few nano-joules laser energy at a nanometer scale for strong…
Random matrices are fundamental in photonic computing because of their ability to model and enhance complex light interactions and signal processing capabilities. In manipulating classical light, random operations are utilized for random…
Hybrid magnonics, exploring the coupling between magnons and quantum systems, is an exciting field for developing next-generation information technologies. Achieving a strong and tunable magnon-magnon coupling (MMC) in confined nanomagnets…