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The detailed reconstruction of neural anatomy for connectomics studies requires a combination of resolution and large three-dimensional data capture provided by serial section electron microscopy (ssEM). The convergence of high throughput…

Computer Vision and Pattern Recognition · Computer Science 2017-11-21 Arthur W. Wetzel , Jennifer Bakal , Markus Dittrich , David G. C. Hildebrand , Josh L. Morgan , Jeff W. Lichtman

Reconfigurable intelligent surface (RIS) can effectively control the wavefront of the impinging signals and has emerged as a cost-effective promising solution to improve the spectrum and energy efficiency of wireless systems. Most existing…

Information Theory · Computer Science 2022-06-07 Yiming Liu , Erwu Liu , Rui Wang , Binyu Lu , Zhu Han

Objective:This study introduces a residual error-shifting mechanism that drastically reduces sampling steps while preserving critical anatomical details, thus accelerating MRI reconstruction. Approach:We propose a novel diffusion-based SR…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Mojtaba Safari , Shansong Wang , Zach Eidex , Qiang Li , Erik H. Middlebrooks , David S. Yu , Xiaofeng Yang

Advanced integration technologies greatly enhance the prospects and reliability of practical quantum sensors, atomic clocks, and quantum information technologies. The performance and proliferation of these devices at chip-scale is…

Nyquist wavelength division (de)multiplexing (N-WDM) is a highly promising technique for next-generation high-speed elastic networks. In N-WDM, Nyquist filtering is an essential function that governs the channel spectral efficiency.…

Integrated photonic technologies have recently shown significant advances, enabling the possibility to implement reconfigurable interferometers with increasing size. One of the main tasks to fully exploit the capabilities of reconfigurable…

Quantum Physics · Physics 2026-05-12 Denis Stanev , Nicolò Spagnolo , Fabio Sciarrino

This paper presents verification and implementation methods that have been developed for the design of the BrainScaleS-2 65nm ASICs. The 2nd generation BrainScaleS chips are mixed-signal devices with tight coupling between full-custom…

Hardware Architecture · Computer Science 2020-03-26 Andreas Grübl , Sebastian Billaudelle , Benjamin Cramer , Vitali Karasenko , Johannes Schemmel

Inverse design, the process of matching a device or process parameters to exhibit a desired performance, is applied in many disciplines ranging from material design over chemical processes and to engineering. Machine learning has emerged as…

Machine Learning · Computer Science 2022-08-31 Michel Frising , Jorge Bravo-Abad , Ferry Prins

Neuromorphic computing leveraging spiking neural network has emerged as a promising solution to tackle the security and reliability challenges with the conventional cyber-physical infrastructure of microgrids. Its event-driven paradigm…

Emerging Technologies · Computer Science 2024-08-13 Yubo Song , Subham Sahoo , Xiaoguang Diao

Recently, many works have focused on the characterization of non-linear dimensionality reduction methods obtained by quantizing linear embeddings, e.g., to reach fast processing time, efficient data compression procedures, novel…

Information Theory · Computer Science 2016-12-30 Laurent Jacques , Valerio Cambareri

The integration density of photonic integrated circuits has been limited by light coupling between waveguides. Traditional approaches to layout the waveguide with high density are based on refractive index engineering to suppress the light…

The nonlinear Fourier transform has the potential to overcome limits on performance and achievable data rates which arise in modern optical fiber communication systems when nonlinear interference is treated as noise. The periodic nonlinear…

Signal Processing · Electrical Eng. & Systems 2020-12-24 Jan-Willem Goossens , Hartmut Hafermann , Yves Jaouën

We present a comprehensive numerical investigation into the radio frequency (RF) field behavior within miniaturized all-glass and hybrid vapor cell geometries designed for Rydberg atom-based electrometry. Using full-vector finite element…

As next-generation implantable brain-machine interfaces become pervasive on edge device, incrementally learning new tasks in bio-plasticity ways is urgently demanded for Neuromorphic chips. Due to the inherent characteristics of its…

Emerging Technologies · Computer Science 2023-12-01 Zifan Ning , Chaojin Chen , Xiang Cheng , Wangzi Yao , Tielin Zhang , Bo Xu

Existing high-performance computing (HPC) interconnection architectures are based on high-radix switches, which limits the injection/local performance and introduces latency/energy/cost overhead. The new wafer-scale packaging and high-speed…

Hardware Architecture · Computer Science 2024-08-27 Yinxiao Feng , Kaisheng Ma

The realisation of an universal quantum computer will require the operation of thousands to millions of qubits. The possibility of using existing industrial semiconductor fabrication techniques and infrastructure for up-scaling and…

To improve the performance of reprogramming in wireless sensor network, we present a novel reprogramming structure and constructive interference-based dissemination protocol (CIDP) to transmit the patch through out the network fast and…

Networking and Internet Architecture · Computer Science 2016-04-25 Bing Hu

Density functional theory (DFT) embedding provides a formally exact framework for interfacing correlated wave-function theory (WFT) methods with lower-level descriptions of electronic structure. Here, we report techniques to improve the…

Chemical Physics · Physics 2015-06-12 Jason D. Goodpaster , Taylor A. Barnes , Frederick R. Manby , Thomas F. Miller

New generation radio interferometers encode signals from thousands of antenna feeds across large bandwidth. Channelizing and correlating this data requires networking capabilities that can handle unprecedented data rates with reasonable…

Instrumentation and Methods for Astrophysics · Physics 2016-08-16 Kevin Bandura , Jean-Francois Cliche , Matt Dobbs , Adam Gilbert , David Ittah , Juan Mena Parra , Graeme Smecher

Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Their additive…