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Due to the massive parallel computing capability and outstanding image and signal processing performance, cellular neural network (CNN) is one promising type of non-Boolean computing system that can outperform the traditional digital logic…

Emerging Technologies · Computer Science 2016-09-21 Chenyun Pan , Azad Naeemi

Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking…

Emerging Technologies · Computer Science 2016-11-15 Abhronil Sengupta , Yong Shim , Kaushik Roy

Efficient manipulation of magnetic order with electric current pulses is desirable for achieving fast spintronic devices. The Rashba-Edelstein effect, wherein a spin polarization is electrically induced in noncentrosymmetric systems,…

Materials Science · Physics 2024-07-01 Leandro Salemi , Marco Berritta , Ashis K. Nandy , Peter M. Oppeneer

Neuromorphic computing systems overcome the limitations of traditional von Neumann computing architectures. These computing systems can be further improved upon by using emerging technologies that are more efficient than CMOS for neural…

Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial…

Applied Physics · Physics 2020-07-14 J. Grollier , D. Querlioz , K. Y. Camsari , K. Everschor-Sitte , S. Fukami , M. D. Stiles

We describe and analyze a cellular nonlinear network based on magnetic nanostructures for image processing. The network consists of magneto-electric cells integrated onto a common ferromagnetic film - spin wave bus. The magneto-electric…

Disordered Systems and Neural Networks · Physics 2015-05-13 Alexander Khitun , Mingqiang Bao , Kang L. Wang

Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform everyday. This has recently resulted in a seismic shift in the field of…

Emerging Technologies · Computer Science 2017-12-22 Abhronil Sengupta , Kaushik Roy

This project explores the use of non-volatile synapses in neuromorphic computing for pattern recognition tasks through a comprehensive simulation-based approach. The main approach is through spintronic synapses, which leverage the…

Mesoscale and Nanoscale Physics · Physics 2025-01-08 Luis Sosa , Minhyeok Wi , Miguel Barrera , Imran Nasrullah , Yingying Wu

Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing…

Disordered Systems and Neural Networks · Physics 2015-06-17 Mrigank Sharad , D. Fan , Kaushik Roy

We present artificial neural network design using spin devices that achieves ultra low voltage operation, low power consumption, high speed, and high integration density. We employ spin torque switched nano-magnets for modelling neuron and…

Disordered Systems and Neural Networks · Physics 2012-08-16 Mrigank Sharad , Charles Augustine , Georgios Panagopoulos , Kaushik Roy

Spintronic logic devices require efficient spin-charge interconversion: converting charge current to spin current and spin current to charge current. In spin-orbit materials that are regarded as the most promising candidate for spintronic…

Materials Science · Physics 2024-01-30 Zixu Wang , Zhizhong Chen , Rui Xu , Hanyu Zhu , Ravishankar Sundararaman , Jian Shi

Orbital currents and accumulation provide a new avenue to boost spintronic effects in nanodevices. Here we use interconversion effects between charge current and orbital angular momentum to demonstrate a dramatic increase in the magnon spin…

Mesoscale and Nanoscale Physics · Physics 2024-01-03 J. A. Mendoza-Rodarte , M. Cosset-Chéneau , B. J. van Wees , M. H. D. Guimarães

The Rashba-Edelstein effect stems from the interaction between the electron's spin and its momentum induced by spin-orbit interaction at an interface or a surface. It was shown that the inverse Rashba-Edelstein effect can be used to convert…

Mesoscale and Nanoscale Physics · Physics 2016-06-27 M. B. Jungfleisch , W. Zhang , J. Sklenar , W. Jiang , J. E. Pearson , J. B. Ketterson , A. Hoffmann

We investigate the inverse Edelstein effect in a non-homogeneous system consisting of a ferromagnetic layer coupled to a Rashba two-dimensional electron gas. Within a semiclassical Boltzmann framework, we derive analytical expressions for…

Mesoscale and Nanoscale Physics · Physics 2026-05-18 Irene Gaiardoni , Mattia Trama , Alfonso Maiellaro , Claudio Guarcello , Francesco Romeo , Roberta Citro

The Rashba interaction induced when inversion symmetry is broken in solids is a key interaction connecting spin and charge for realizing novel magnetoelectric cross-correlation effects. Here, we theoretically explore the optical properties…

Mesoscale and Nanoscale Physics · Physics 2016-02-15 Junya Shibata , Akihito Takeuchi , Hiroshi Kohno , Gen Tatara

This paper presents a rotation-invariant embedded platform for simulating (neural) cellular automata (NCA) in modular robotic systems. Inspired by previous work on physical NCA, we introduce key innovations that overcome limitations in…

Neural and Evolutionary Computing · Computer Science 2025-10-10 Dominik Woiwode , Jakob Marten , Bodo Rosenhahn

Neuromorphic computing promises revolutionary improvements over conventional systems for applications that process unstructured information. To fully realize this potential, neuromorphic systems should exploit the biomimetic behavior of…

In altermagnets, time-reversal symmetry breaking spin-polarizes electronic states, while total magnetization remains zero. In addition, at altermagnetic surfaces Rashba-spin orbit coupling is activated due to broken inversion symmetry,…

The Rashba spin-orbit coupling effect, primarily arising from structural-inversion asymmetry in periodic crystals, has garnered considerable attention due to its tunability and potential applications in spintronics. Its capability to…

Materials Science · Physics 2024-04-24 Arjyama Bordoloi , A. C. Garcia-Castro , Zachary Romestan , Aldo H. Romero , Sobhit Singh

This paper proposes a spintronic neuron structure composed of a heterostructure of magnets and a piezoelectric with a magnetic tunnel junction (MTJ). The operation of the device is simulated using SPICE models. Simulation results illustrate…

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