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A system of drift-diffusion equations for the electron, hole, and oxygene vacancy densities in a semiconductor, coupled to the Poisson equation for the electric potential, is analyzed in a bounded domain with mixed Dirichlet-Neumann…

Analysis of PDEs · Mathematics 2022-04-08 Clément Jourdana , Ansgar Jüngel , Nicola Zamponi

Phase-change memory (PCM) is a scalable and low latency non-volatile memory (NVM) technology that has been proposed to serve as storage class memory (SCM), providing low access latency similar to DRAM and often approaching or exceeding the…

Hardware Architecture · Computer Science 2020-12-01 Shihao Song , Anup Das

The growing prevalence of drift and shocks in modern decision environments exposes a gap between classical optimization theory and real-world practice. Standard models assume fixed objectives, yet organizations from hospitals to power grids…

Computational Finance · Quantitative Finance 2025-09-18 JINHO CHA

Drift in machine learning refers to the phenomenon where the statistical properties of data or context, in which the model operates, change over time leading to a decrease in its performance. Therefore, maintaining a constant monitoring…

Computation and Language · Computer Science 2023-09-08 Saeed Khaki , Akhouri Abhinav Aditya , Zohar Karnin , Lan Ma , Olivia Pan , Samarth Marudheri Chandrashekar

Using fully kinetic 3D simulations, the reconnection dynamics of asymmetric current sheets are examined at the Earth's magnetopause. The plasma parameters are selected to model MMS magnetopause diffusion region crossings with guide fields…

Non-Volatile Memory (NVM) cells are used in neuromorphic hardware to store model parameters, which are programmed as resistance states. NVMs suffer from the read disturb issue, where the programmed resistance state drifts upon repeated…

Neural and Evolutionary Computing · Computer Science 2022-01-28 Ankita Paul , Shihao Song , Twisha Titirsha , Anup Das

Phase-change materials (PCMs) are the subject of considerable interest because they have been recognized as potential active layers for next-generation non-volatile memory devices, known as Phase Change Random Access Memories (PRAMs). By…

Materials Science · Physics 2015-05-14 M. Micoulaut , J-Y. Raty , C. Otjacques , C. Bichara

We report on an astonishing switching synchronization phenomenon in one-dimensional memristive networks, which occurs when several memristive systems with different switching constants are switched from the high to low resistance state. Our…

Mesoscale and Nanoscale Physics · Physics 2016-10-31 V. A. Slipko , M. Shumovskyi , Y. V. Pershin

Properties of quantum dot based spin qubits have significant inter-device variability due to unavoidable presence of various types of disorder in semiconductor nanostructures. A significant source of this variability is charge disorder at…

Mesoscale and Nanoscale Physics · Physics 2025-11-20 Saeed Samadi , Łukasz Cywiński , Jan A. Krzywda

This paper gives an overview of recent progress in the brain inspired computing field with a focus on implementation using emerging memories as electronic synapses. Design considerations and challenges such as requirements and design…

Neural and Evolutionary Computing · Computer Science 2016-05-09 Sukru Burc Eryilmaz , Duygu Kuzum , Shimeng Yu , H. -S. Philip Wong

Elastic instabilities such as buckling and snapping have evolved into a powerful design principle, enabling memory, sequential shape morphing, and computing in metamaterials and devices. Modifying the post-buckling configurations or their…

Soft Condensed Matter · Physics 2025-09-10 Bernat Durà Faulí , Lennard Kwakernaak , Martin van Hecke

We discuss the nonlinear dynamics and fluctuations of interfaces with bending rigidity under the competing attractions of two walls with arbitrary permeabilities. This system mimics the dynamics of confined membranes. We use a two-dimension…

Soft Condensed Matter · Physics 2015-09-02 Thomas Le Goff , Paolo Politi , Olivier Pierre-Louis

Machine learning (ML) has entered the mobile era where an enormous number of ML models are deployed on edge devices. However, running common ML models on edge devices continuously may generate excessive heat from the computation, forcing…

Machine Learning · Computer Science 2022-07-11 Yang Zhou , Feng Liang , Ting-wu Chin , Diana Marculescu

This article summarizes key results of our work on experimental characterization and analysis of latency variation and latency-reliability trade-offs in modern DRAM chips, which was published in SIGMETRICS 2016, and examines the work's…

This paper deals with the issue of concept drift in supervised machine learn-ing. We make use of graphical models to elicit the visible structure of the dataand we infer from there changes in the hidden context. Differently from previous…

Machine Learning · Computer Science 2021-02-03 Luigi Riso , Marco Guerzoni

In this work we introduce a compact model for mushroom-type phase-change memory devices that incorporates the shape and size of the amorphous mark under different programming conditions, and is applicable to both projecting and…

Applied Physics · Physics 2025-08-11 Stephan Menzel , Benedikt Kersting , Rana Walied Ahmad , Abu Sebastian , Ghazi Sarwat Syed

Deep artificial neural networks famously struggle to learn from non-stationary streams of data. Without dedicated mitigation strategies, continual learning is associated with continuous forgetting of previous tasks and a progressive loss of…

Neurons and Cognition · Quantitative Biology 2025-12-29 Suzanne van der Veldt , Gido M. van de Ven , Sanne Moorman , Guillaume Etter

Cessation of flow in simple yield stress fluids results in a complex stress relaxation process that depends on the preceding flow conditions and leads to finite residual stresses. To assess the microscopic origin of this phenomenon, we…

Progress of silicon based technology is nearing its physical limit, as minimum feature size of components is reaching a mere 10 nm. The resistive switching behaviour of transition metal oxides and the associated memristor device is emerging…

Phase change memory (PCM) is an emerging high speed, high density, high endurance, and scalable non-volatile memory technology which utilizes the large resistivity contrast between the amorphous and crystalline phases of chalcogenide…

Emerging Technologies · Computer Science 2019-04-02 Raihan Sayeed Khan , Nadim H. Kanan , Jake Scoggin , Helena Silva , Ali Gokirmak