Related papers: Efficient Design Scheme of Superconducting Cavity
Single-photon detectors and nanoscale superconducting devices are two major candidates for realizing quantum technologies. Superconducting-nanowire single-photon detectors (SNSPDs) comprise these two solid-state and optic aspects enabling…
During 1999, four 700-MHz, medium-beta (b = 0.64), superconducting radio frequency (SCRF) cavities for a high-intensity proton linac project at Los Alamos National Laboratory (LANL) were manufactured by industry. The SCRF cavities were…
Recent developments in superconducting radio-frequency (SRF) research have focused primarily on high frequency elliptical cavities for electron accelerators. Advances have been made in both reducing RF surface resistance and pushing the…
Despite having advantageous superconducting properties, Nb3Sn superconducting radiofrequency (SRF) cavities still have practical challenges compared to Nb SRF cavities due to the brittle nature of Nb3Sn. Performance degradation can occur…
An apparatus and a method are described for plasma etching of the inner surface of superconducting radio frequency (SRF) cavities. Accelerator SRF cavities are formed into a variable-diameter cylindrical structure made of bulk niobium, for…
As the second stage of the CEPC-SPPC project, SPPC (Super Proton-Proton Collider) aims at exploring new physics beyond the Standard Model. The key design goal for the SPPC accelerator complex is to reach 75 TeV in center of mass energy with…
Two-dimensional, resonant scanners have been utilized in a large variety of imaging modules due to their compact form, low power consumption, large angular range, and high speed. However, resonant scanners have problems with non-optimal and…
Hybrid semiconductor/superconductor nanowires constitute a pervasive platform for studying gate-tunable superconductivity and the emergence of topological behavior. Their low-dimensionality and crystal structure flexibility facilitate novel…
To achieve high accuracy, convolutional neural networks (CNNs) are increasingly growing in complexity and diversity in layer types and topologies. This makes it very challenging to efficiently deploy such networks on custom processor…
Superconducting RadioFrequency (SRF) cavities have been developed for modern particle accelerator projects in the world. These cavities are mainly made of bulk niobium operated in superfluid or normal fluid helium. Due to the price increase…
The research of high energy and nuclear physics requires high power accelerators, and the superconducting radio-frequency (SRF) cavity is regarded as their engine. Up to now, the widely used practical and effective material for making the…
Networks of superconducting optoelectronic neurons are investigated for their near-term technological potential and long-term physical limitations. Networks with short average path length, high clustering coefficient, and power-law degree…
Careful design of semiconductor manufacturing equipment is crucial for ensuring the performance, yield, and reliability of semiconductor devices. Despite this, numerical optimization methods are seldom applied to optimize the design of such…
In this paper, collaborative use of relays to form a beamforming system and provide physical-layer security is investigated. In particular, decode-and-forward (DF) and amplify-and-forward (AF) relay beamforming designs under total and…
This paper deals with joint source-relay-destination beamforming (BF) design for an amplify-and-forward (AF) relay network. Considering the channel state information (CSI) from the relay to the destination is imperfect, we first aim to…
Spiking neural networks (SNNs) are powerful models of spatiotemporal computation and are well suited for deployment on resource-constrained edge devices and neuromorphic hardware due to their low power consumption. Leveraging attention…
Spiking Neural Networks (SNNs) event-driven nature enables efficient encoding of spatial and temporal features, making them suitable for dynamic time-dependent data processing. Despite their biological relevance, SNNs have seen limited…
With the increasing demand to deploy convolutional neural networks (CNNs) on mobile platforms, the sparse kernel approach was proposed, which could save more parameters than the standard convolution while maintaining accuracy. However,…
With the rising societal demand for more information-processing capacity with lower power consumption, alternative architectures inspired by the parallelism and robustness of the human brain have recently emerged as possible solutions. In…
The continue wave (CW) high current proton linac has wide applications as the front end of the high power proton machines. The low energy part is the most difficult one and there is no widely accepted solution yet. Based on the analysis of…