相关论文: Efficient Design Scheme of Superconducting Cavity
Recirculating energy recovery linacs are a promising technology for delivering high power particle beams ($\sim$GW) while only requiring low power ($\sim$kW) RF sources. This is achieved by decelerating the used bunches and using the energy…
Superconductor-semiconductor nanowire hybrid structures are useful in fabricating devices for quantum information processing. While selective area growth (SAG) offers the flexibility to grow semiconductor nanowires in arbitrary geometries,…
Engineering the Hamiltonian of a quantum system is fundamental to the design of quantum systems. Automating Hamiltonian design through gradient-based optimization can dramatically accelerate this process. However, computing the gradients of…
In this short review we describe the process of designing a superconducting circuit device for quantum information applications. We discuss the factors that must be considered to implement a desired effective Hamiltonian on a device. We…
We introduce a numerical procedure which permits to drastically accelerate the design of multimode photonic crystal resonators. Specifically, we demonstrate that the optical response of an important class of such nanoscale structures is…
A semi-empirical method that allows us to predict intensity of generated field emission in superconducting RF cavities is described. Spatial, angular and energy distributions of the generated radiation are calculated with the FISHPACT code.…
We consider design optimization of passively mode-locked two-section semiconductor lasers that incorporate intracavity grating spectral filters. Our goal is to develop a method for finding the optimal wavelength location for the filter in…
Hybrid beamforming is a promising technology to improve the energy efficiency of massive MIMO systems. In particular, subarray hybrid beamforming can further decrease power consumption by reducing the number of phase-shifters. However,…
Theory of the superconductor-insulator-superconductor (S-I-S) multilayer structure in superconducting accelerating cavity application is reviewed. The theoretical field limit, optimum layer thicknesses and material combination, and surface…
Superconducting nanowire single-photon detectors (SNSPDs) were integrated with plasmonic nanostructures to enhance the absorption efficiency of superconducting BSCCO stripes. A numerical investigation of optimized nanocavity array (NCAI)…
Cavities with high quality (Q) factor and small mode-volume are crucial to realize high performance nanolasers suitable for optical interconnects. In this work, we propose a novel one-dimensional photonic crystal nanobeam cavity design with…
Designing messenger RNA (mRNA) sequences for a fixed target protein requires searching an exponentially large synonymous space while optimizing properties that affect stability and downstream performance. This is challenging because…
Experts in different accelerator laboratories accumulated wide experience in RFQ designing. Nevertheless new tasks on high-power, high-energy CW linac designing (for example, for ADT applications) were appeared recently. Such accelerators…
Superconducting radio-frequency (SRF) cavities offer a promising platform for quantum computing due to their long coherence times, yet integrating nonlinear elements like transmons for control often introduces additional loss. We report a…
Superconducting nanowire single-photon detectors promise efficient (~100%) and fast (~Gcps) detection of light at the single-photon level. They constitute one of the building blocks to realize integrated quantum optical circuits in a…
Simulation-driven shape optimisation (SDSO) of marine propellers is often obstructed by high-dimensional design spaces stemming from its complex geometry and baseline parameterisation, which leads to the notorious curse of dimensionality.…
RNA design aims to identify RNA sequences that fold into a target secondary structure. This task is challenging in terms of computational efficiency. Most existing methods focus on either minimum free energy (MFE)-based or ensemble-based…
In this paper, we propose a computational framework for the optimal design of broadband absorbing materials composed of plasmonic nanoparticle arrays. This design problem poses several key challenges: (1) the complex multi-particle…
The design of many-core neuromorphic hardware is getting more and more complex as these systems are expected to execute large machine learning models. To deal with the design complexity, a predictable design flow is needed to guarantee…
Spiking neural networks (SNNs) that mimic information transmission in the brain can energy-efficiently process spatio-temporal information through discrete and sparse spikes, thereby receiving considerable attention. To improve accuracy and…