Related papers: Towards scalable cryogenic quantum dot biasing usi…
Using accurate dissipative DFT-NEGF atomistic-simulation techniques within the Wannier-Function formalism, we give a fresh look at the possibility of sub-10 nm scaling for high-performance CMOS applications. We show that a combination of…
Continuously Variable Series Reactor (CVSR) can adjust the total reactance in an ac circuit using the saturation characteristic of the ferromagnetic core, shared by an ac and a dc winding. The bias magnetic flux produced by the dc winding…
This paper presents a programmable in-memory-computing processor, demonstrated in a 65nm CMOS technology. For data-centric workloads, such as deep neural networks, data movement often dominates when implemented with today's computing…
Self-assembled semiconductor quantum dots show remarkable optical and spin coherence properties, which have lead to a concerted research effort examining their potential as a quantum bit for quantum information science1-6. Here, we present…
Computing-in-Memory (CiM) architectures based on emerging non-volatile memory (NVM) devices have demonstrated great potential for deep neural network (DNN) acceleration thanks to their high energy efficiency. However, NVM devices suffer…
The memristor, because of its controllability over a wide dynamic range of resistance, has emerged as a promising device for data storage and analog computation. A major challenge is the accurate measurement of memristance over a wide…
Cryo-computing - both classical and quantum, is severely limited by the absence of a suitable cryo-memory. The challenge both in terms of energy efficiency and speed have been known for decades, but so far conventional technologies have not…
Executing quantum logic in cryogenic quantum computers requires a continuous energy supply from room-temperature control electronics. This dependence on external energy sources creates scalability limitations due to control channel density…
Magnetometers based on quantum mechanical processes enable high sensitivity and long-term stability without the need for re-calibration, but their integration into fieldable devices remains challenging. This paper presents a CMOS quantum…
Memristors are promising devices for scalable and low power, in-memory computing to improve the energy efficiency of a rising computational demand. The crossbar array architecture with memristors is used for vector matrix multiplication…
Quantum memristors represent a promising interface between quantum and neuromorphic computing, combining the nonlinear, memory-dependent behavior of classical memristors with the properties of quantum states. An optical quantum memristor…
Mass characterisation of emerging memory devices is an essential step in modelling their behaviour for integration within a standard design flow for existing integrated circuit designers. This work develops a novel characterisation platform…
This work presents a self-heating study of a 40-nm bulk-CMOS technology in the ambient temperature range from 300 K down to 4.2 K. A custom test chip was designed and fabricated for measuring both the temperature rise in the MOSFET channel…
This work describes preliminary steps towards nano-scale reservoir computing using quantum dots. Our research has focused on the development of an accumulator-based sensing system that reacts to changes in the environment, as well as the…
Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors. Its ability to…
Microwave devices capable of near-quantum-limited signal processing are essential components in the toolbox of solid-state quantum technologies. The manipulation and readout of single-photon microwave signals through amplifiers, mixers,…
Recent advancements in reservoir computing research have created a demand for analog devices with dynamics that can facilitate the physical implementation of reservoirs, promising faster information processing while consuming less energy…
We report the design-technology co-optimization (DTCO) scheme to develop a 28-nm cryogenic CMOS (Cryo-CMOS) technology for high-performance computing (HPC). The precise adjustment of halo implants manages to compensate the threshold voltage…
Microscopic imaging of local magnetic fields provides a window into the organizing principles of complex and technologically relevant condensed matter materials. However, a wide variety of intriguing strongly correlated and topologically…
In-memory computing (IMC) is an emerging non-von Neumann paradigm that leverages the intrinsic physics of memory devices to perform computations directly within the memory array. Among the various candidates, phase-change memory (PCM) has…