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Compact, stable, and versatile laser-driven ion sources hold great promise for applications ranging from medicine to materials science and fundamental physics. While single-shot sources have demonstrated favorable beam properties, including…
KEKB completed all of the technical milestones, and had offered important insights into the flavor structure of elementary particles, especially the CP violation. The accelerator control system at KEKB and injector linac was initiated by a…
Laser wakefield acceleration modeling using the Lorentz-boosted frame technique in the particle-in-cell code has demonstrated orders of magnitude speedups. A convergence study was previously conducted in cases with external injection in the…
NV center is one of the most promising platforms in the field of quantum sensing. Magnetometry based on NV center, especially, has achieved a concrete development in regions of biomedicine and medical diagnostics. Improving the sensitivity…
A new type of ring-imaging Cherenkov counter, called TOP counter, has been developed for particle identification at the Belle II experiment to run at the SuperKEKB accelerator in KEK, Japan. The detector consists of 16 identical modules…
The Hyper-Kamiokande neutrino detector is set to begin construction in 2020, succeeding Super-Kamiokande as the world's largest water Cerenkov detector. Research and development are well underway for an integrated light injection system for…
We introduce a novel approach to improve unsupervised hashing. Specifically, we propose a very efficient embedding method: Gaussian Mixture Model embedding (Gemb). The proposed method, using Gaussian Mixture Model, embeds feature vector…
Collinear high-gradient ${\cal O} (GV/m)$ beam-driven wakefield methods for charged-particle acceleration could be critical to the realization of compact, cost-efficient, accelerators, e.g., in support of TeV-scale lepton colliders or…
Machine learning algorithms often struggle to control complex real-world systems. In the case of nuclear fusion, these challenges are exacerbated, as the dynamics are notoriously complex, data is poor, hardware is subject to failures, and…
The Ring-Imaging Cherenkov (RICH) detectors at LHCb have an intrinsic time resolution of better than 10 ps owing to the prompt Cherenkov radiation and focusing mirrors optics. While only spatial information has been used in the experiment…
A new scheme for bright hard x-ray emission from laser wakefield electron accelerator is reported, where pure nitrogen gas is adopted. Intense Betatron x-ray beams are generated from ionization injected K-shell electrons of nitrogen into…
The performance of many machine learning models depends on their hyper-parameter settings. Bayesian Optimization has become a successful tool for hyper-parameter optimization of machine learning algorithms, which aims to identify optimal…
Donor spin qubits in silicon offer one- and two-qubit gates with fidelities beyond 99%, coherence times exceeding 30 seconds, and compatibility with industrial manufacturing methods. This motivates the development of large-scale quantum…
We introduce the Bayesian Compiler Optimization framework (BaCO), a general purpose autotuner for modern compilers targeting CPUs, GPUs, and FPGAs. BaCO provides the flexibility needed to handle the requirements of modern autotuning tasks.…
On-chip coherent laser sources are crucial for the future of photonic integrated circuits, yet progress has been hindered by the complex interplay between material quality, device geometry, and performance metrics. We combine…
The experimental requirements in near future accelerators (e.g. High Luminosity-LHC) has stimulated intense interest in development of detectors with high precision timing capabilities. With this as a goal, a new detection concept called…
Light source is indispensable component in on-chip system. Compared with hybrid or heterogeneous integrated laser, monolithically integrated laser is more suitable for high density photonic integrated circuit (PIC) since the capability of…
From 2005 through 2012, the Fermilab Main Injector provided intense beams of 120 GeV protons to produce neutrino beams and antiprotons. Hardware improvements in conjunction with improved diagnostics allowed the system to reach sustained…
This research introduces a novel methodology for optimizing Bayesian Neural Networks (BNNs) by synergistically integrating them with traditional machine learning algorithms such as Random Forests (RF), Gradient Boosting (GB), and Support…
Particle accelerators are among some of the largest science experiments in the world and can consist of thousands of components with a wide variety of input ranges. These systems can easily become unwieldy optimization problems during…