English
Related papers

Related papers: Quantum Annealing Machine based on Floating Gate A…

200 papers

Flash memory based on floating gate transistor is the most widely used memory technology in modern microelectronic applications. We recently proposed a new concept of multilayer graphene nanoribbon (MLGNR) and carbon nanotube (CNT) based…

Mesoscale and Nanoscale Physics · Physics 2016-11-15 Nahid M. Hossain , Md Belayat Hossain , Masud H. Chowdhury

Field-Programmable Gate Arrays (FPGAs) have asserted themselves as vital assets in contemporary computing by offering adaptable, reconfigurable hardware platforms. FPGA-based accelerators incubate opportunities for breakthroughs in areas,…

Quantum annealing is a method developed to solve combinatorial optimization problems by utilizing quantum bits. Solving such problems corresponds to minimizing a cost function defined over binary variables. However, in many practical cases,…

Quantum Physics · Physics 2025-06-26 Seiya Endo , Shohei Kawakatsu , Hiromichi Matsuyama , Kohei Suzuki , Yuichiro Matsuzaki

Quantum annealing is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. Quantum annealing in the Transverse Ising model, implemented on D-Wave QPUs, are…

Quantum Physics · Physics 2025-03-14 Elijah Pelofske

Optimal parameter setting for applications problems embedded into hardware graphs is key to practical quantum annealers (QA). Embedding chains typically crop up as harmful Griffiths phases, but can be used as a resource as we show here: to…

Quantum Physics · Physics 2021-01-04 Sergey Knysh , Eugeniu Plamadeala , Davide Venturelli

Quantum annealing aims at solving optimization problems efficiently by preparing the ground state of an Ising spin-Hamiltonian quantum mechanically. A prerequisite of building a quantum annealer is the implementation of programmable…

Quantum Gases · Physics 2020-11-10 Xingze Qiu , Peter Zoller , Xiaopeng Li

Drawing independent samples from high-dimensional probability distributions represents the major computational bottleneck for modern algorithms, including powerful machine learning frameworks such as deep learning. The quest for discovering…

Quantum Physics · Physics 2022-10-13 Marc Vuffray , Carleton Coffrin , Yaroslav A. Kharkov , Andrey Y. Lokhov

We have modified a commercial NOR flash memory array to enable high-precision tuning of individual floating-gate cells for analog computing applications. The modified array area per cell in a 180 nm process is about 1.5 um^2. While this…

Emerging Technologies · Computer Science 2016-10-10 F. Merrikh Bayat , X. Guo , H. A. Ommani , N. Do , K. K. Likharev , D. B. Strukov

Quantum annealing method has been widely attracted attention in statistical physics and information science since it is expected to be a powerful method to obtain the best solution of optimization problem as well as simulated annealing. The…

Disordered Systems and Neural Networks · Physics 2017-08-23 Shu Tanaka , Ryo Tamura

Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinatorial optimization problems. In recent years, advances in quantum technologies have enabled the development of small- and intermediate-scale…

Quantum Physics · Physics 2022-10-05 Sheir Yarkoni , Elena Raponi , Thomas Bäck , Sebastian Schmitt

We investigate gate-defined quantum dots in silicon on insulator nanowire field-effect transistors fabricated using a foundry-compatible fully-depleted silicon-on-insulator (FD-SOI) process. A series of split gates wrapped over the silicon…

Mesoscale and Nanoscale Physics · Physics 2020-12-02 Jingyu Duan , Michael A. Fogarty , James Williams , Louis Hutin , Maud Vinet , John J. L. Morton

Quantum annealing is an optimization technique which potentially leverages quantum tunneling to enhance computational performance. Existing quantum annealers use superconducting flux qubits with short coherence times, limited primarily by…

Scaling the number of qubits while maintaining high-fidelity quantum gates remains a key challenge for quantum computing. Presently, superconducting quantum processors with >50-qubits are actively available. For such systems,…

Recent experimental achievements have demonstrated the potential of neutral atom architectures for fault-tolerant quantum computing. These architectures feature the dynamic rearrangement of atoms during computation, enabling nearly…

Quantum Physics · Physics 2025-04-14 Yannick Stade , Ludwig Schmid , Lukas Burgholzer , Robert Wille

We investigate the use of quantum computing algorithms on real quantum hardware to tackle the computationally intensive task of feature selection for light-weight medical image datasets. Feature selection is often formulated as a k of n…

Quantum Physics · Physics 2025-02-27 Merlin A. Nau , Luca A. Nutricati , Bruno Camino , Paul A. Warburton , Andreas K. Maier

A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics…

Quantum annealing promises to solve complex combinatorial optimization problems faster than current transistor-based computer technologies. Although to date only one commercially-available quantum annealer is procurable, one can already…

Quantum Physics · Physics 2018-06-21 Helmut G. Katzgraber

Towards the scalable realization of a quantum computer, a quantum charge-coupled device (QCCD) based on ion shuttling has been considered a promising approach. However, the processes of detaching an ion from an array, reintegrating it, and…

Quantum Physics · Physics 2026-01-26 Ting Hsu , Wen-Han Png , Kuan-Ting Lin , Ming-Shien Chang , Guin-Dar Lin

As superconducting quantum processors increase in complexity, techniques to overcome constraints on frequency crowding are needed. The recently developed method of laser-annealing provides an effective post-fabrication method to adjust the…

Quantum simulation with adiabatic annealing can provide insight into difficult problems that are impossible to study with classical computers. However, it deteriorates when the systems scale up due to the shrinkage of the excitation gap and…