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To date, linear accelerators (linacs) as electron sources used to produce ionizing radiation for industrial purposes have been limited to less than 100 kW. When the electron beam is used directly, this is sufficient for most potential…

Accelerator Physics · Physics 2022-02-17 Thomas K. Kroc

In order to mitigate the effects of electrical breakdown (which have been found to occur in SLAC X-band traveling wave structures) standing wave structures are being considered for the NLC linac. At SLAC, structures consisting of 15 cells…

Accelerator Physics · Physics 2007-05-23 R. M. Jones , R. H. Miller , J. W. Wang , P. B. Wilson

Lateral inhibitory connections have been observed in the cortex of the biological brain, and has been extensively studied in terms of its role in cognitive functions. However, in the vanilla version of backpropagation in deep learning, all…

Computer Vision and Pattern Recognition · Computer Science 2022-08-16 Lei Jiang , Yongqing Liu , Shihai Xiao , Yansong Chua

Low gain avalanche detectors can measure charged particle fluences with high speed and spatial precision, and are a promising technology for radiation monitoring and dosimetry. A detector has been tested in a medical linac where single…

Instrumentation and Detectors · Physics 2022-02-17 Tommaso Isidori , Patrick McCavana , Brendan McClean , Ronan McNulty , Nicola Minafra , Naomi Raab , Luke Rock , Christophe Royon

Radiation impacts are a current challenge with computing on superconducting-based quantum devices because they can lead to widespread correlated errors across the device. Such errors can be problematic for quantum error correction (QEC)…

Radio frequency (RF) superconductivity has become a key technology for many modern particle accelerators. One of its most salient features of this technology is the ability of superconducting RF cavities to deliver high accelerating…

Accelerator Physics · Physics 2020-04-16 Hasan Padamsee

Undesirable electron field emission (a.k.a. dark current) in high gradient RF photocathode guns deteriorates the quality of photoemission current and limits the operational gradient. To improve the understanding of dark current emission, a…

Underground physics experiments such as dark matter direct detection need to keep control of the background contribution. Hosting these experiments in underground facilities helps to minimize certain background sources such as the cosmic…

Computational Physics · Physics 2021-03-02 Iñaki Rodríguez-García , Miguel Cárdenas-Montes

The Laser Interferometer Space Antenna (LISA) will observe gravitational waves in a regime that differs sharply from what ground-based detectors such as LIGO handle. Instead of searching for rare signals buried in loud instrumental noise,…

General Physics · Physics 2026-04-20 Jericho Cain

Suppression of beam losses is essential for successful operation of high-intensity linac. Historically, the values of the field amplitudes and phases of the side-coupled, 805-MHz LANSCE linac modules are maintained using a well-known…

Accelerator Physics · Physics 2020-02-26 Y. K. Batygin , F. E. Shelley , H. A. Watkins

The emergence of new nanoscale technologies has imposed significant challenges to designing reliable electronic systems in radiation environments. A few types of radiation like Total Ionizing Dose (TID) effects often cause permanent damages…

Machine Learning · Computer Science 2022-01-06 Eduardo Weber Wachter , Server Kasap , Sefki Kolozali , Xiaojun Zhai , Shoaib Ehsan , Klaus McDonald-Maier

Disentangling coherent and incoherent effects in the photoemission spectra of strongly correlated materials is generally a challenging problem due to the involvement of numerous parameters. In this study, we employ machine learning…

Superconductivity · Physics 2024-12-17 K. H. Bohachov , A. A. Kordyuk

Photorealistic simulation plays a crucial role in applications such as autonomous driving, where advances in neural radiance fields (NeRFs) may allow better scalability through the automatic creation of digital 3D assets. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Shanlin Sun , Bingbing Zhuang , Ziyu Jiang , Buyu Liu , Xiaohui Xie , Manmohan Chandraker

In current accelerators, numerous parameters and monitored values are to be adjusted and evaluated, respectively. In addition, fine adjustments are required to achieve the target performance. Therefore, the conventional…

Accelerator Physics · Physics 2024-01-29 Gaku Mitsuka , Shinnosuke Kato , Naoko Iida , Takuya Natsui , Masanori Satoh

One potential drawback of using aggregated performance measurement in machine learning is that models may learn to accept higher errors on some training cases as compromises for lower errors on others, with the lower errors actually being…

Machine Learning · Computer Science 2023-12-21 Li Ding , Lee Spector

Higher order modes (HOMs) are simulated with finite element and finite difference computer codes for the ILC superconducting cavities. In particular, HOMs in KEK's Ichiro type of cavity and Cornell University's Reentrant design are focused…

Accelerator Physics · Physics 2014-11-18 C. Glasman , R. M. Jones

Tracing of the magnetic field with Velocity Gradient Technique (VGT) allows observers to probe magnetic field directions with spectroscopic data. In this paper, we employ the method of Principal Component Analysis (PCA) to extract the…

Astrophysics of Galaxies · Physics 2018-07-25 Yue Hu , Ka Ho Yuen , A. Lazarian

Ionizing radiation has been shown to reduce the performance of superconducting quantum circuits. In this report, we evaluate the expected contributions of different sources of ambient radioactivity for typical superconducting qubit…

In the NLC (Next Linear Collider) small misalignments in each of the individual accelerator structures (or the accelerator cells) will give rise to wakefields which kick the beam from its electrical axis. This wakefield can cause BBU (Beam…

Accelerator Physics · Physics 2009-03-12 R. M. Jones , N. M. Kroll , R. H. Miller , T. O. Raubenheimer , G. V. Stupakov

Quantum Machine Learning (QML) is considered to be one of the most promising applications of near term quantum devices. However, the optimization of quantum machine learning models presents numerous challenges arising from the imperfections…

Machine Learning · Computer Science 2022-05-17 Owen Lockwood