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2,018 results on '"Chen C. S."'

1. Stable Weight Updating: A Key to Reliable PDE Solutions Using Deep Learning

Author

Noorizadegan, A., Cavoretto, R., Young, D. L., and Chen, C. S.

Subjects
Computer Science - Artificial Intelligence, Mathematics - Numerical Analysis
Abstract

Background: Deep learning techniques, particularly neural networks, have revolutionized computational physics, offering powerful tools for solving complex partial differential equations (PDEs). However, ensuring stability and efficiency remains a challenge, especially in scenarios involving nonlinear and time-dependent equations. Methodology: This paper introduces novel residual-based architectures, namely the Simple Highway Network and the Squared Residual Network, designed to enhance stability and accuracy in physics-informed neural networks (PINNs). These architectures augment traditional neural networks by incorporating residual connections, which facilitate smoother weight updates and improve backpropagation efficiency. Results: Through extensive numerical experiments across various examples including linear and nonlinear, time-dependent and independent PDEs we demonstrate the efficacy of the proposed architectures. The Squared Residual Network, in particular, exhibits robust performance, achieving enhanced stability and accuracy compared to conventional neural networks. These findings underscore the potential of residual-based architectures in advancing deep learning for PDEs and computational physics applications.

Published
2024

2. Highway Networks for Improved Surface Reconstruction: The Role of Residuals and Weight Updates

Author

Noorizadegan, A., Hon, Y. C., Young, D. L., and Chen, C. S.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Surface reconstruction from point clouds is a fundamental challenge in computer graphics and medical imaging. In this paper, we explore the application of advanced neural network architectures for the accurate and efficient reconstruction of surfaces from data points. We introduce a novel variant of the Highway network (Hw) called Square-Highway (SqrHw) within the context of multilayer perceptrons and investigate its performance alongside plain neural networks and a simplified Hw in various numerical examples. These examples include the reconstruction of simple and complex surfaces, such as spheres, human hands, and intricate models like the Stanford Bunny. We analyze the impact of factors such as the number of hidden layers, interior and exterior points, and data distribution on surface reconstruction quality. Our results show that the proposed SqrHw architecture outperforms other neural network configurations, achieving faster convergence and higher-quality surface reconstructions. Additionally, we demonstrate the SqrHw's ability to predict surfaces over missing data, a valuable feature for challenging applications like medical imaging. Furthermore, our study delves into further details, demonstrating that the proposed method based on highway networks yields more stable weight norms and backpropagation gradients compared to the Plain Network architecture. This research not only advances the field of computer graphics but also holds utility for other purposes such as function interpolation and physics-informed neural networks, which integrate multilayer perceptrons into their algorithms.

Published
2024

3. Two-Dimensional Phase-Fluctuating Superconductivity in Bulk-Crystalline NdO$_{0.5}$F$_{0.5}$BiS$_2$

Author

Chen, C. S., Küspert, J., Biało, I., Mueller, J., Chen, K. W., Zou, M. Y., Mazzone, D. G., Bucher, D., Tanaka, K., Ivashko, O., Zimmermann, M. v., Wang, Qisi, Shu, Lei, and Chang, J.

Subjects
Condensed Matter - Superconductivity
Abstract

We present a combined growth and transport study of superconducting single-crystalline NdO$_{0.5}$F$_{0.5}$BiS$_2$. Evidence of two-dimensional superconductivity with significant phase fluctuations of preformed Cooper pairs preceding the superconducting transition is reported. This result is based on three key observations. (1) The resistive superconducting transition temperature $T_c$ (defined by resistivity $\rho \rightarrow 0$) increases with increasing disorder. (2) As $T\rightarrow T_c$, the conductivity diverges significantly faster than what is expected from Gaussian fluctuations in two and three dimensions. (3) Non-Ohmic resistance behavior is observed in the superconducting state. Altogether, our observations are consistent with a temperature regime of phase-fluctuating superconductivity. The crystal structure with magnetic ordering tendencies in the NdO$_{0.5}$F$_{0.5}$ layers and (super)conductivity in the BiS$_2$ layers is likely responsible for the two-dimensional phase fluctuations. As such, NdO$_{0.5}$F$_{0.5}$BiS$_2$ falls into the class of unconventional ``laminar" bulk superconductors that include cuprate materials and 4Hb-TaS$_2$.

Published
2024
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4. Power-Enhanced Residual Network for Function Approximation and Physics-Informed Inverse Problems

Author

Noorizadegan, Amir, Young, D. L., Hon, Y. C., and Chen, C. S.

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Mathematics - Analysis of PDEs
Abstract

In this study, we investigate how the updating of weights during forward operation and the computation of gradients during backpropagation impact the optimization process, training procedure, and overall performance of the neural network, particularly the multi-layer perceptrons (MLPs). This paper introduces a novel neural network structure called the Power-Enhancing residual network, inspired by highway network and residual network, designed to improve the network's capabilities for both smooth and non-smooth functions approximation in 2D and 3D settings. By incorporating power terms into residual elements, the architecture enhances the stability of weight updating, thereby facilitating better convergence and accuracy. The study explores network depth, width, and optimization methods, showing the architecture's adaptability and performance advantages. Consistently, the results emphasize the exceptional accuracy of the proposed Power-Enhancing residual network, particularly for non-smooth functions. Real-world examples also confirm its superiority over plain neural network in terms of accuracy, convergence, and efficiency. Moreover, the proposed architecture is also applied to solving the inverse Burgers' equation, demonstrating superior performance. In conclusion, the Power-Enhancing residual network offers a versatile solution that significantly enhances neural network capabilities by emphasizing the importance of stable weight updates for effective training in deep neural networks. The codes implemented are available at: \url{https://github.com/CMMAi/ResNet_for_PINN}.

Published
2023
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6. Spin excitations in the quantum dipolar magnet Yb(BaBO$_3$)$_3$

Author

Jiang, C. Y., Yang, Y. X., Gao, Y. X., Wan, Z. T., Zhu, Z. H., Shiroka, T., Chen, C. S., Wu, Q., Li, X., Jiao, J. C., Chen, K. W., Bao, Y., Tian, Z. M., and Shu, L.

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

We report results of magnetization, specific-heat and muon-spin relaxation measurements on single crystals of disorder-free Yb$^{3+}$ triangular lattice Yb(BaBO$_3$)$_3$. The magnetization experiments show anisotropic magnetic properties with Curie-Weiss temperatures $\theta_{\perp}=-1.40$~K ($H \perp c$) and $\theta_{\parallel}=-1.16$~K ($H \parallel c$) determined from low temperature data. The absence of both long-range antiferromagnetic order and spin freezing is confirmed down to 0.27 K at zero field. A two-level Schottky anomaly due to the opening of the ground-state Kramers doublet is observed from the low-temperature specific-heat measurements when the applied magnetic fields $\mu_0H >0.7$~T. At zero field, the increase of both $C_{\rm mag}/T$ and the muon spin relaxation rate $\lambda$ below 1~K is due to the electronic spin excitations, which often exist in quantum magnets where dipole-dipole interaction creates an anisotropy of magnetic properties. The spin excitation is also supported by the unusual maximum of field dependence of $\lambda$ due to the field-induced increase of the density of excitations. We argue that dipolar interaction is dominant and induces the spin dynamics in the quantum magnet Yb(BaBO$_3$)$_3$., Comment: accepted by Phys. Rev. B

Published
2022
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7. Fluctuating magnetic droplets immersed in a sea of quantum spin liquid

Author

Zhu, Z. H., Pan, B. L., Nie, L. P., Ni, J. M., Yang, Y. X., Chen, C. S., Huang, Y. Y., Cheng, E. J., Yu, Y. J., Hillier, A. D., Chen, X. H., Wu, T., Zhou, Y., Li, S. Y., and Shu, L.

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science, Condensed Matter - Superconductivity
Abstract

The search of quantum spin liquid (QSL), an exotic magnetic state with strongly-fluctuating and highly-entangled spins down to zero temperature, is a main theme in current condensed matter physics. However, there is no smoking-gun evidence for deconfined spinons in any QSL candidate so far. The disorders and competing exchange interactions may prevent the formation of an ideal QSL state on frustrated spin lattices. Here we report comprehensive and systematic measurements of the magnetic susceptibility, ultra-low temperature specific heat, muon spin relaxation (muSR), nuclear magnetic resonance (NMR), and thermal conductivity for NaYbSe2 single crystals, in which Yb3+ ions with effective spin-1/2 form a perfect triangular lattice. All these complementary techniques find no evidence of long-range magnetic order down to their respective base temperatures. Instead, specific heat, muSR and NMR measurements suggest the coexistence of quasi-static and dynamic spins in NaYbSe2. The scattering from these quasi-static spins may cause the absence of magnetic thermal conductivity. Thus, we propose a scenario of fluctuating ferrimagnetic droplets immersed in a sea of QSL. This may be quite common on the way pursuing an ideal QSL, and provides a brand-new platform to study how a QSL state survives impurities and coexists with other magnetically ordered states.

Published
2021

8. Muon spin rotation and relaxation study on topological noncentrosymmetric superconductor PbTaSe$_2$

Author

Zhu, Z. H., Tan, C., Zhang, J., Biswas, P. K., Hillier, A. D., Wang, M. X., Yang, Y. X., Chen, C. S., Ding, Z. F., Li, S. Y., and Shu, L.

Subjects
Condensed Matter - Superconductivity
Abstract

Topological superconductivity is an exotic phenomenon due to the symmetry-protected topological surface state, in which a quantum system has an energy gap in the bulk but supports gapless excitations confined to its boundary. Symmetries including central and time-reversal (TRS), along with their relations with topology, are crucial for topological superconductivity. We report muon spin relaxation/rotation ($\mu$SR) experiments on a topological noncentrosymmetric superconductor PbTaSe$_2$ to study its TRS and gap symmetry. Zero-field $\mu$SR experiments indicate the absence of internal magnetic field in the superconducting state, consistent with previous $\mu$SR results. Furthermore, transverse-field $\mu$SR measurements reveals that the superconducting gap of PbTaSe$_2$ is an isotropic three-dimensional fully-gapped single-band. The fully-gapped results can help understand the pairing mechanism and further classify the topological superconductivity in this system.

Published
2021
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10. Overview of KAGRA: Detector design and construction history

Author

Akutsu, T., Ando, M., Arai, K., Arai, Y., Araki, S., Araya, A., Aritomi, N., Aso, Y., Bae, S. -W., Bae, Y. -B., Baiotti, L., Bajpai, R., Barton, M. A., Cannon, K., Capocasa, E., Chan, M. -L., Chen, C. -S., Chen, K. -H., Chen, Y. -R., Chu, H. -Y., Chu, Y-K., Eguchi, S., Enomoto, Y., Flaminio, R., Fujii, Y., Fukunaga, M., Fukushima, M., Ge, G. -G., Hagiwara, A., Haino, S., Hasegawa, K., Hayakawa, H., Hayama, K., Himemoto, Y., Hiranuma, Y., Hirata, N., Hirose, E., Hong, Z., Hsieh, B. -H., Huang, G. -Z., Huang, P. -W., Huang, Y. -J., Ikenoue, B., Imam, S., Inayoshi, K., Inoue, Y., Ioka, K., Itoh, Y., Izumi, K., Jung, K., Jung, P., Kajita, T., Kamiizumi, M., Kanda, N., Kang, G. -W., Kawaguchi, K., Kawai, N., Kawasaki, T., Kim, C., Kim, J., Kim, W., Kim, Y. -M., Kimura, N., Kita, N., Kitazawa, H., Kojima, Y., Kokeyama, K., Komori, K., Kong, A. K. H., Kotake, K., Kozakai, C., Kozu, R., Kumar, R., Kume, J., Kuo, C. -M., Kuo, H. -S., Kuroyanagi, S., Kusayanagi, K., Kwak, K., Lee, H. -K., Lee, H. -W., Lee, R. -K., Leonardi, M., Lin, C. -Y., Lin, F. -L., Lin, L. C. -C., Liu, G. -C., Luo, L. -W., Marchio, M., Michimura, Y., Mio, N., Miyakawa, O., Miyamoto, A., Miyazaki, Y., Miyo, K., Miyoki, S., Morisaki, S., Moriwaki, Y., Nagano, K., Nagano, S., Nakamura, K., Nakano, H., Nakano, M., Nakashima, R., Narikawa, T., Negishi, R., Ni, W. -T., Nishizawa, A., Obuchi, Y., Ogaki, W., Oh, J. J., Oh, S. -H., Ohashi, M., Ohishi, N., Ohkawa, M., Okutomi, K., Oohara, K., Ooi, C. -P., Oshino, S., Pan, K. -C., Pang, H. -F., Park, J., Arellano, F. E. Peña, Pinto, I., Sago, N., Saito, S., Saito, Y., Sakai, K., Sakai, Y., Sakuno, Y., Sato, S., Sato, T., Sawada, T., Sekiguchi, T., Sekiguchi, Y., Shibagaki, S., Shimizu, R., Shimoda, T., Shimode, K., Shinkai, H., Shishido, T., Shoda, A., Somiya, K., Son, E. J., Sotani, H., Sugimoto, R., Suzuki, T., Tagoshi, H., Takahashi, H., Takahashi, R., Takamori, A., Takano, S., Takeda, H., Takeda, M., Tanaka, H., Tanaka, K., Tanaka, T., Tanioka, S., Martin, E. N. Tapia San, Telada, S., Tomaru, T., Tomigami, Y., Tomura, T., Travasso, F., Trozzo, L., Tsang, T. T. L., Tsubono, K., Tsuchida, S., Tsuzuki, T., Tuyenbayev, D., Uchikata, N., Uchiyama, T., Ueda, A., Uehara, T., Ueno, K., Ueshima, G., Uraguchi, F., Ushiba, T., van Putten, M. H. P. M., Vocca, H., Wang, J., Wu, C. -M., Wu, H. -C., Wu, S. -R., Xu, W. -R., Yamada, T., Yamamoto, Ka., Yamamoto, Ko., Yamamoto, T., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoshioka, T., Yuzurihara, H., Zeidler, S., Zhao, Y., and Zhu, Z. -H.

Subjects
Physics - Instrumentation and Detectors, Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology
Abstract

KAGRA is a newly built gravitational-wave telescope, a laser interferometer comprising arms with a length of 3\,km, located in Kamioka, Gifu, Japan. KAGRA was constructed under the ground and it is operated using cryogenic mirrors that help in reducing the seismic and thermal noise. Both technologies are expected to provide directions for the future of gravitational-wave telescopes. In 2019, KAGRA finished all installations with the designed configuration, which we call the baseline KAGRA. In this occasion, we present an overview of the baseline KAGRA from various viewpoints in a series of of articles. In this article, we introduce the design configurations of KAGRA with its historical background., Comment: 33 pages, 10 figures

Published
2020

11. First cryogenic test operation of underground km-scale gravitational-wave observatory KAGRA

Author

KAGRA Collaboration, Akutsu, T., Ando, M., Arai, K., Arai, Y., Araki, S., Araya, A., Aritomi, N., Asada, H., Aso, Y., Atsuta, S., Awai, K., Bae, S., Baiotti, L., Barton, M. A., Cannon, K., Capocasa, E., Chen, C-S., Chiu, T-W., Cho, K., Chu, Y-K., Craig, K., Creus, W., Doi, K., Eda, K., Enomoto, Y., Flaminio, R., Fujii, Y., Fujimoto, M. -K., Fukunaga, M., Fukushima, M., Furuhata, T., Hagiwara, A., Haino, S., Hasegawa, K., Hashino, K., Hayama, K., Hirobayashi, S., Hirose, E., Hsieh, B. H., Huang, C-Z., Ikenoue, B., Inoue, Y., Ioka, K., Itoh, Y., Izumi, K., Kaji, T., Kajita, T., Kakizaki, M., Kamiizumi, M., Kanbara, S., Kanda, N., Kanemura, S., Kaneyama, M., Kang, G., Kasuya, J., Kataoka, Y., Kawai, N., Kawamura, S., Kawasaki, T., Kim, C., Kim, J., Kim, J. C., Kim, W. S., Kim, Y. -M., Kimura, N., Kinugawa, T., Kirii, S., Kitaoka, Y., Kitazawa, H., Kojima, Y., Kokeyama, K., Komori, K., Kong, A. K. H., Kotake, K., Kozu, R., Kumar, R., Kuo, H-S., Kuroyanagi, S., Lee, H. K., Lee, H. M., Lee, H. W., Leonardi, M., Lin, C-Y., Lin, F-L., Liu, G. C., Liu, Y., Majorana, E., Mano, S., Marchio, M., Matsui, T., Matsushima, F., Michimura, Y., Mio, N., Miyakawa, O., Miyamoto, A., Miyamoto, T., Miyo, K., Miyoki, S., Morii, W., Morisaki, S., Moriwaki, Y., Morozumi, T., Murakami, I., Musha, M., Nagano, K., Nagano, S., Nakamura, K., Nakamura, T., Nakano, H., Nakano, M., Nakao, K., Namai, Y., Narikawa, T., Naticchioni, L., Quynh, L. Nguyen, Ni, W. -T., Nishizawa, A., Obuchi, Y., Ochi, T., Oh, J. J., Oh, S. H., Ohashi, M., Ohishi, N., Ohkawa, M., Okutomi, K., Ono, K., Oohara, K., Ooi, C. P., Pan, S-S., Park, J., Arellano, F. E. Peña, Pinto, I., Sago, N., Saijo, M., Saito, Y., Saitou, S., Sakai, K., Sakai, Y., Sasai, M., Sasaki, M., Sasaki, Y., Sato, N., Sato, S., Sato, T., Sekiguchi, Y., Seto, N., Shibata, M., Shimoda, T., Shinkai, H., Shishido, T., Shoda, A., Somiya, K., Son, E. J., Suemasa, A., Suzuki, T., Tagoshi, H., Tahara, H., Takahashi, H., Takahashi, R., Takamori, A., Takeda, H., Tanaka, H., Tanaka, K., Tanaka, T., Tanioka, S., Martin, E. N. Tapia San, Tatsumi, D., Terashima, S., Tomaru, T., Tomura, T., Travasso, F., Tsubono, K., Tsuchida, S., Uchikata, N., Uchiyama, T., Ueda, A., Uehara, T., Ueki, S., Ueno, K., Uraguchi, F., Ushiba, T., van Putten, M. H. P. M., Vocca, H., Wada, S., Wakamatsu, T., Watanabe, Y., Xu, W-R., Yamada, T., Yamamoto, A., Yamamoto, K., Yamamoto, S., Yamamoto, T., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoon, T. H., Yoshioka, T., Yuzurihara, H., Zeidler, S., and Zhu, Z. -H.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology, Physics - Instrumentation and Detectors
Abstract

KAGRA is a second-generation interferometric gravitational-wave detector with 3-km arms constructed at Kamioka, Gifu in Japan. It is now in its final installation phase, which we call bKAGRA (baseline KAGRA), with scientific observations expected to begin in late 2019. One of the advantages of KAGRA is its underground location of at least 200 m below the ground surface, which brings small seismic motion at low frequencies and high stability of the detector. Another advantage is that it cools down the sapphire test mass mirrors to cryogenic temperatures to reduce thermal noise. In April-May 2018, we have operated a 3-km Michelson interferometer with a cryogenic test mass for 10 days, which was the first time that km-scale interferometer was operated at cryogenic temperatures. In this article, we report the results of this "bKAGRA Phase 1" operation. We have demonstrated the feasibility of 3-km interferometer alignment and control with cryogenic mirrors., Comment: 23 pages, 11 figures

Published
2019
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12. Vibration isolation system with a compact damping system for power recycling mirrors of KAGRA

Author

Akiyama, Y., Akutsu, T., Ando, M., Arai, K., Arai, Y., Araki, S., Araya, A., Aritomi, N., Asada, H., Aso, Y., Bae, S., Baiotti, L., Barton, M. A., Cannon, K., Capocasa, E., Chen, C-S., Chiu, T-W., Cho, K., Chu, Y-K., Craig, K., Dattilo, V., Doi, K., Enomoto, Y., Flaminio, R., Fujii, Y., Fujimoto, M. -K., Fukunaga, M., Fukushima, M., Furuhata, T., Haino, S., Hasegawa, K., Hashimoto, Y., Hashino, K., Hayama, K., Hirayama, T., Hirose, E., Hsieh, B. H., Huang, C-Z., Ikenoue, B., Inoue, Y., Ioka, K., Itoh, Y., Izumi, K., Kaji, T., Kajita, T., Kakizaki, M., Kamiizumi, M., Kanbara, S., Kanda, N., Kanemura, S., Kang, G., Kasuya, J., Kawai, N., Kawasaki, T., Kim, C., Kim, W. S., Kim, J., Kim, J. C., Kimura, N., Kirii, S., Kitaoka, Y., Kitazawa, H., Kojima, Y., Kokeyama, K., Komori, K., Kong, A., Kotake, K., Kozu, R., Kumar, R., Kuo, H-S., Kuroki, S., Kuroyanagi, S., Lee, H. K., Lee, H. M., Lee, H. W., Leonardi, M., Lin, C-Y., Lin, F-L., Liu, G. C., Marchio, M., Matsui, T., Michimura, Y., Mio, N., Miyakawa, O., Miyamoto, A., Miyoki, S., Morii, W., Morisaki, S., Moriwaki, Y., Musha, M., Nagano, S., Nagano, K., Nakamura, K., Nakamura, T., Nakano, H., Nakano, M., Narikawa, T., Quynh, L. Nguyen, Ni, W. -T., Nishizawa, A., Obuchi, Y., Oh, J., Oh, S. H., Ohashi, M., Ohishi, N., Ohkawa, M., Okutomi, K., Ono, K., Oohara, K., Ooi, C. P., Pan, S-S., Paoletti, F., Park, J., Passaquieti, R., Arellano, F. E. Peña, Sago, N., Saito, S., Saito, Y., Sakai, K., Sakai, Y., Sasai, M., Sato, S., Sato, T., Sekiguchi, T., Sekiguchi, Y., Shibata, M., Shimoda, T., Shinkai, H., Shishido, T., Shoda, A., Someya, N., Somiya, K., Son, E. J., Suemasa, A., Suzuki, T., Tagoshi, H., Tahara, H., Takahashi, H., Takahashi, R., Takeda, H., Tanaka, H., Tanaka, K., Tanaka, T., Tanioka, S., SanMartin, E. N. Tapia, Tomaru, T., Tomura, T., Travasso, F., Tsubono, K., Tsuchida, S., Uchikata, N., Uchiyama, T., Uehara, T., Ueno, K., Uraguchi, F., Ushiba, T., van Putten, M. H. P. M., Vocca, H., Wakamatsu, T., Watanabe, Y., Xu, W-R., Yamada, T., Yamamoto, K., Yamamoto, S., Yamamoto, T., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoshioka, T., Yuzurihara, H., Zeidler, S., and Zhu, Z. -H.

Subjects
Physics - Instrumentation and Detectors, General Relativity and Quantum Cosmology
Abstract

A vibration isolation system called Type-Bp system used for power recycling mirrors has been developed for KAGRA, the interferometric gravitational-wave observatory in Japan. A suspension of the Type-Bp system passively isolates an optic from seismic vibration using three main pendulum stages equipped with two vertical vibration isolation systems. A compact reaction mass around each of the main stages allows for achieving sufficient damping performance with a simple feedback as well as vibration isolation ratio. Three Type-Bp systems were installed in KAGRA, and were proved to satisfy the requirements on the damping performance, and also on estimated residual displacement of the optics.

Published
2019
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14. KAGRA: 2.5 Generation Interferometric Gravitational Wave Detector

Author

Akutsu, T., Ando, M., Arai, K., Arai, Y., Araki, S., Araya, A., Aritomi, N., Asada, H., Aso, Y., Atsuta, S., Awai, K., Bae, S., Baiotti, L., Barton, M. A., Cannon, K., Capocasa, E., Chen, C-S., Chiu, T-W., Cho, K., Chu, Y-K., Craig, K., Creus, W., Doi, K., Eda, K., Enomoto, Y., Flaminio, R., Fujii, Y., Fujimoto, M. -K., Fukunaga, M., Fukushima, M., Furuhata, T., Haino, S., Hasegawa, K., Hashino, K., Hayama, K., Hirobayashi, S., Hirose, E., Hsieh, B. H., Huang, C-Z., Ikenoue, B., Inoue, Y., Ioka, K., Itoh, Y., Izumi, K., Kaji, T., Kajita, T., Kakizaki, M., Kamiizumi, M., Kanbara, S., Kanda, N., Kanemura, S., Kaneyama, M., Kang, G., Kasuya, J., Kataoka, Y., Kawai, N., Kawamura, S., Kawasaki, T., Kim, C., Kim, J., Kim, J. C., Kim, W. S., Kim, Y. -M., Kimura, N., Kinugawa, T., Kirii, S., Kitaoka, Y., Kitazawa, H., Kojima, Y., Kokeyama, K., Komori, K., Kong, A. K. H., Kotake, K., Kozu, R., Kumar, R., Kuo, H-S., Kuroyanagi, S., Lee, H. K., Lee, H. M., Lee, H. W., Leonardi, M., Lin, C-Y., Lin, F-L., Liu, G. C., Liu, Y., Majorana, E., Mano, S., Marchio, M., Matsui, T., Matsushima, F., Michimura, Y., Mio, N., Miyakawa, O., Miyamoto, A., Miyamoto, T., Miyo, K., Miyoki, S., Morii, W., Morisaki, S., Moriwaki, Y., Morozumi, T., Musha, M., Nagano, K., Nagano, S., Nakamura, K., Nakamura, T., Nakano, H., Nakano, M., Nakao, K., Narikawa, T., Naticchioni, L., Quynh, L. Nguyen, Ni, W. -T., Nishizawa, A., Ochi, T., Oh, J. J., Oh, S. H., Ohashi, M., Ohishi, N., Ohkawa, M., Okutomi, K., Ono, K., Oohara, K., Ooi, C. P., Pan, S-S., Park, J., Arellano, F. E. Peña, Pinto, I., Sago, N., Saijo, M., Saito, Y., Sakai, K., Sakai, Y., Sasai, M., Sasaki, M., Sasaki, Y., Sato, S., Sato, T., Sekiguchi, Y., Seto, N., Shibata, M., Shimoda, T., Shinkai, H., Shishido, T., Shoda, A., Somiya, K., Son, E. J., Suemasa, A., Suzuki, T., Tagoshi, H., Tahara, H., Takahashi, H., Takahashi, R., Takamori, A., Takeda, H., Tanaka, H., Tanaka, K., Tanaka, T., Tanioka, S., Martin, E. N. Tapia San, Tatsumi, D., Tomaru, T., Tomura, T., Travasso, F., Tsubono, K., Tsuchida, S., Uchikata, N., Uchiyama, T., Uehara, T., Ueki, S., Ueno, K., Ushiba, T., van Putten, M. H. P. M., Vocca, H., Wada, S., Wakamatsu, T., Watanabe, Y., Xu, W-R., Yamada, T., Yamamoto, A., Yamamoto, K., Yamamoto, S., Yamamoto, T., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoon, T. H., Yoshioka, T., Yuzurihara, H., Zeidler, S., and Zhu, Z. -H.

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors
Abstract

The recent detections of gravitational waves (GWs) reported by LIGO/Virgo collaborations have made significant impact on physics and astronomy. A global network of GW detectors will play a key role to solve the unknown nature of the sources in coordinated observations with astronomical telescopes and detectors. Here we introduce KAGRA (former name LCGT; Large-scale Cryogenic Gravitational wave Telescope), a new GW detector with two 3-km baseline arms arranged in the shape of an "L", located inside the Mt. Ikenoyama, Kamioka, Gifu, Japan. KAGRA's design is similar to those of the second generations such as Advanced LIGO/Virgo, but it will be operating at the cryogenic temperature with sapphire mirrors. This low temperature feature is advantageous for improving the sensitivity around 100 Hz and is considered as an important feature for the third generation GW detector concept (e.g. Einstein Telescope of Europe or Cosmic Explorer of USA). Hence, KAGRA is often called as a 2.5 generation GW detector based on laser interferometry. The installation and commissioning of KAGRA is underway and its cryogenic systems have been successfully tested in May, 2018. KAGRA's first observation run is scheduled in late 2019, aiming to join the third observation run (O3) of the advanced LIGO/Virgo network. In this work, we describe a brief history of KAGRA and highlights of main feature. We also discuss the prospects of GW observation with KAGRA in the era of O3. When operating along with the existing GW detectors, KAGRA will be helpful to locate a GW source more accurately and to determine the source parameters with higher precision, providing information for follow-up observations of a GW trigger candidate., Comment: 6 pages, 3 figures (quality of some figures has been reduced)

Published
2018
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19. Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO, Advanced Virgo and KAGRA

Author

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abbott, B. P., Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Allen, G., Allocca, A., Aloy, M. A., Altin, P. A., Amato, A., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Angelova, S. V., Antier, S., Appert, S., Arai, K., Arai, Koya, Arai, Y., Araki, S., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arun, K. G., Ascenzi, S., Ashton, G., Aso, Y., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Avila-Alvarez, A., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S. W., Bae, Y. B., Baiotti, L., Bajpai, R., Baker, P. T., Baldaccini, F., Ballardin, G., Ballmer, S. W., Banagiri, S., Barayoga, J. C., Barclay, S. E., Barish, B. C., Barker, D., Barkett, K., Barnum, S., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Berger, B. K., Bergmann, G., Bernuzzi, S., Bero, J. J., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bidler, J., Bilenko, I. A., Bilgili, S. A., Billingsley, G., Birch, J., Birney, R., Birnholtz, O., Biscans, S., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bloemen, S., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Booth, C. D., Bork, R., Boschi, V., Bose, S., Bossie, K., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Briant, T., Briggs, J. 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L., Willke, B., Wimmer, M. H., Winkler, W., Wipf, C. C., Wittel, H., Woan, G., Woehler, J., Wofford, J. K., Worden, J., Wright, J. L., Wu, C. M., Wu, D. S., Wu, H. C., Wu, S. R., Wysocki, D. M., Xiao, L., Xu, W. R., Yamada, T., Yamamoto, H., Yamamoto, Kazuhiro, Yamamoto, Kohei, Yamamoto, T., Yancey, C. C., Yang, L., Yap, M. J., Yazback, M., Yeeles, D. W., Yokogawa, K., Yokoyama, J., Yokozawa, T., Yoshioka, T., Yu, Hang, Yu, Haocun, Yuen, S. H. R., Yuzurihara, H., Yvert, M., Zadrożny, A. K., Zanolin, M., Zeidler, S., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, T., Zhao, C., Zhao, Y., Zhou, M., Zhou, Z., Zhu, X. J., Zhu, Z. H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.

Subjects
General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present our current best estimate of the plausible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next several years, with the intention of providing information to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals for the third (O3), fourth (O4) and fifth observing (O5) runs, including the planned upgrades of the Advanced LIGO and Advanced Virgo detectors. We study the capability of the network to determine the sky location of the source for gravitational-wave signals from the inspiral of binary systems of compact objects, that is BNS, NSBH, and BBH systems. The ability to localize the sources is given as a sky-area probability, luminosity distance, and comoving volume. The median sky localization area (90\% credible region) is expected to be a few hundreds of square degrees for all types of binary systems during O3 with the Advanced LIGO and Virgo (HLV) network. The median sky localization area will improve to a few tens of square degrees during O4 with the Advanced LIGO, Virgo, and KAGRA (HLVK) network. We evaluate sensitivity and localization expectations for unmodeled signal searches, including the search for intermediate mass black hole binary mergers., Comment: 52 pages, 9 figures, 5 tables. We have updated the detector sensitivities (including the A+ and AdV+ upgrade); added expectations for binary black-holes, neutron-star black-holes, and intermediate-mass black holes; and added 3D volume localization expectations. This update is to change some numbers in Table 5 based on refinements to the simulations. Three authors were added

Published
2013
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20. Unconventional superconductivity in Cr-based compound Pr3Cr10−xN11.

Author

Chen, C. S., Wu, Q., Zou, M. Y., Zhu, Z. H., Yang, Y. X., Tan, C., Hillier, A. D., Chang, J., Luo, J. L., Wu, W., and Shu, L.

Subjects
SUPERCONDUCTIVITY, MUON spin rotation, SUPERCONDUCTING transitions, IRON-based superconductors, SPECIFIC heat, SUPERFLUIDITY
Abstract

We report results of specific heat and muon spin relaxation (μSR) measurements on a polycrystalline sample of Pr3Cr10−xN11, which shows superconducting state below Tc = 5.25 K, a large upper critical field Hc2 ~ 20 T and a residual Sommerfeld coefficient γ0. The field dependence of γ0(H) resembles γ of the U-based superconductors UTe2 and URhGe at low temperatures. The temperature-dependent superfluid density measured by transverse-field μSR experiments is consistent with a p-wave pairing symmetry. ZF-μSR experiment suggests a time-reversal symmetry broken superconducting transition, and temperature-independent spin fluctuations at low temperatures are revealed by LF-μSR experiments. These results indicate that Pr3Cr10−xN11 is a candidate of p-wave superconductor which breaks time-reversal symmetry. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Leptogenesis in the extension of the Zee-Babu model

Author

Chen, C. S., Geng, C. Q., and Zhuridov, D. V.

Subjects
High Energy Physics - Phenomenology
Abstract

We demonstrate that the extension of the Zee-Babu model can generate not only the small neutrino masses but also the baryon number asymmetry in the universe. In particular, we show that the scale of the singlet scalar responsible for the leptogenesis can be of order 1 TeV, that can be tested at the LHC and ILC. We also considered the possible minimal extension of this model to generate the dark matter., Comment: 10 pages, 3 figures. The model has been revised by including a singlet scalar. The leptogenesis is due to the three-body decay of the scalar

Published
2008

24. Searching for doubly charged Higgs bosons in M\'{o}ller scattering by resonance effects at linear $e^-e^-$ collider

Author

Chen, C. S., Geng, C. Q., and Zhuridov, D. V.

Subjects
High Energy Physics - Phenomenology
Abstract

We discuss the parity-violating left-right asymmetries (LRAs) in M\"{o}ller scattering at the International Linear Collider (ILC) induced by doubly charged Higgs bosons in models with $SU(2)_L$ triplet and singlet scalar bosons, which couple to the left- and right-handed charged leptons, respectively. These bosons are important in the scenarios for the generation of the neutrino mass. We demonstrate that the contributions to the LRAs from the triplet and singlet bosons are opposite to each other. In particular, we show that the doubly charged Higgs boson from the singlet scalar can be tested at the ILC by using the resonance effect., Comment: 12 pages, 5 figures; version published in Eur.Phys.J.C60:119-124,2009

Published
2008
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25. Generalized Study with Isospin-phased Topological Approach on the $B \to K\pi$ Puzzle

Author

Chang, D., Chen, C. S., Hatanaka, H., and Kim, C. S.

Subjects
High Energy Physics - Phenomenology
Abstract

We study the decay processes $B \to K \pi$ by using generalized decay amplitudes with both the final state re-scattering strong phases and the topological quark diagrammatic strong phases included together as part of fitting parameters. Using a generalized approach, so called ``isospin phased topological approach'', for all the currently available data of $B \to K \pi$ decays, we determine the allowed values of the relevant theoretical parameters, corresponding to the electroweak penguin, the color-suppressed tree contribution, strong phase differences, etc. In order to find the most likely values of the parameters in a statistically reliable way, we use the $\chi^2$ minimization technique. We find that the long distance final state re-scattering, when taken at proper value, can provide a reasonable fit to the standard model with the perturbative QCD estimated values, and therefore, it is premature to conclude that it requires new physics to explain the CP violating $B \to K\pi$ data., Comment: 21 pages, 4 tables Talk given at the third International Conference on Flavor Physics (ICFP 2005), National Central University, Chong-li, Taiwan, R.O.C, 3-8 Oct 2005. A table added. Comments and References added. Notation of formulas modified

Published
2005

26. Orbit Feedback System for the Storage Ring of SRRC

Author

Kuo, C. H., Chen, Jenny, Wang, C. J., Hu, K. H., Chen, C. S., and Hsu, K. T.

Subjects
Physics - Instrumentation and Detectors
Abstract

Orbit feedback system plays crucial roles for the operation of the 3rd generation light source. There are various issues in orbit feedback system should be addressed to achieve ultimate performance. The orbit feedback system in SRRC is upgraded recently to satisfy the requirement of demanding users. Based upon operational experiences of the last few years, new system was designed with more robustness and flexibility. Performance analysis tools are also developed to monitor system performance. Algorithms for feedback control, data acquisition and analysis are described and measurement is also presented., Comment: Poster Paper for ICALEPCS-2001 (WEAP047), 3 pages, pdf

Published
2001

27. Data Acquisition and Uesr Interface of Beam Instrumentation System at SRRC

Author

Chen, Jenny, Wang, C. J., Kuo, C. H., Hu, K. H., Chen, C. S., and Hsu, K. T.

Subjects
Physics - Instrumentation and Detectors
Abstract

Data acquisition systems for the accelerator complex at SRRC composed various hardware and software components. Beam signals are processed by related processing electronics, and connect to control system by various type of interfaces in data acquisition front-end. These front-end include VME crates, personal computers and instruments bus adapters. Fast Ethernet connected all elements together with control consoles. User interface is running on control console. Real-time data capture; display and alaysis are supported on control console. Analysis tools based on Matlab scripts are adopted. Hardware and software implementation of the system will be presented. User interface supports are also described., Comment: ICALEPCS 2001 poster paper (WEAP035), 3 pages, PDF

Published
2001

28. Fracture in Mode I using a Conserved Phase-Field Model

Author

Eastgate, L. O., Sethna, J. P., Rauscher, M., Cretegny, T., Chen, C. -S., and Myers, C. R.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Soft Condensed Matter
Abstract

We present a continuum phase-field model of crack propagation. It includes a phase-field that is proportional to the mass density and a displacement field that is governed by linear elastic theory. Generic macroscopic crack growth laws emerge naturally from this model. In contrast to classical continuum fracture mechanics simulations, our model avoids numerical front tracking. The added phase-field smoothes the sharp interface, enabling us to use equations of motion for the material (grounded in basic physical principles) rather than for the interface (which often are deduced from complicated theories or empirical observations). The interface dynamics thus emerges naturally. In this paper, we look at stationary solutions of the model, mode I fracture, and also discuss numerical issues. We find that the Griffith's threshold underestimates the critical value at which our system fractures due to long wavelength modes excited by the fracture process., Comment: 10 pages, 5 figures (eps). Added 2 figures and some text. Removed one section (and a figure). To be published in PRE

Published
2001
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29. Prospects for observing and localizing gravitational-wave transients with Advanced LIGO, Advanced Virgo and KAGRA

Author

Abbott, B. P., Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Allen, G., Allocca, A., Aloy, M. A., Altin, P. A., Amato, A., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Angelova, S. V., Antier, S., Appert, S., Arai, K., Arai, Koya, Arai, Y., Araki, S., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arun, K. G., Ascenzi, S., Ashton, G., Aso, Y., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Avila-Alvarez, A., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S. W., Bae, Y. B., Baiotti, L., Bajpai, R., Baker, P. T., Baldaccini, F., Ballardin, G., Ballmer, S. W., Banagiri, S., Barayoga, J. C., Barclay, S. E., Barish, B. C., Barker, D., Barkett, K., Barnum, S., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Berger, B. K., Bergmann, G., Bernuzzi, S., Bero, J. J., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bidler, J., Bilenko, I. A., Bilgili, S. A., Billingsley, G., Birch, J., Birney, R., Birnholtz, O., Biscans, S., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bloemen, S., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Booth, C. D., Bork, R., Boschi, V., Bose, S., Bossie, K., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brisson, V., Brockill, P., Brooks, A. F., Brown, D. A., Brown, D. D., Brunett, S., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Buy, C., Byer, R. L., Cabero, M., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Campbell, W. A., Canepa, M., Cannon, K., Cannon, K. C., Cao, H., Cao, J., Capocasa, E., Carbognani, F., Caride, S., Carney, M. F., Carullo, G., Diaz, J. Casanueva, Casentini, C., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cerretani, G., Cesarini, E., Chaibi, O., Chakravarti, K., Chamberlin, S. J., Chan, M., Chan, M. L., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chaturvedi, M., Chatziioannou, K., Cheeseboro, B. D., Chen, C. S., Chen, H. Y., Chen, K. H., Chen, X., Chen, Y., Chen, Y. R., Cheng, H.-P., Cheong, C. K., Chia, H. Y., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Christensen, N., Chu, H. Y., Chu, Q., Chu, Y. K., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, J. A., Clearwater, P., Cleva, F., Cocchieri, C., Coccia, E., Cohadon, P.-F., Cohen, D., Colgan, R., Colleoni, M., Collette, C. G., Collins, C., Cominsky, L. R., Constancio, Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corley, K. R., Cornish, N., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J.-P., Countryman, S. T., Couvares, P., Covas, P. B., Cowan, E. E., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Cripe, J., Croquette, M., Crowder, S. G., Cullen, T. J., Cumming, A., Cunningham, L., Cuoco, E., Canton, T. Dal, Dálya, G., Danilishin, S. L., D’Antonio, S., Danzmann, K., Dasgupta, A., Da Silva Costa, C. F., Datrier, L. E. H., Dattilo, V., Dave, I., Davier, M., Davis, D., Daw, E. J., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Pozzo, W. Del, DeMarchi, L. M., Demos, N., Dent, T., De Pietri, R., Derby, J., De Rosa, R., De Rossi, C., DeSalvo, R., de Varona, O., Dhurandhar, S., Díaz, M. C., Dietrich, T., Fiore, L. Di, Giovanni, M. Di, Girolamo, T. Di, Lieto, A. Di, Ding, B., Pace, S. Di, Palma, I. Di, Renzo, F. Di, Dmitriev, A., Doctor, Z., Doi, K., Donovan, F., Dooley, K. L., Doravari, S., Dorrington, I., Downes, T. P., Drago, M., Driggers, J. C., Du, Z., Ducoin, J.-G., Dupej, P., Dwyer, S. E., Easter, P. J., Edo, T. B., Edwards, M. C., Effler, A., Eguchi, S., Ehrens, P., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Enomoto, Y., Essick, R. C., Estelles, H., Estevez, D., Etienne, Z. B., Etzel, T., Evans, M., Evans, T. M., Fafone, V., Fair, H., Fairhurst, S., Fan, X., Farinon, S., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favata, M., Fays, M., Fazio, M., Fee, C., Feicht, J., Fejer, M. M., Feng, F., Fernandez-Galiana, A., Ferrante, I., Ferreira, E. C., Ferreira, T. A., Ferrini, F., Fidecaro, F., Fiori, I., Fiorucci, D., Fishbach, M., Fisher, R. P., Fishner, J. M., Fitz-Axen, M., Flaminio, R., Fletcher, M., Flynn, E., Fong, H., Font, J. A., Forsyth, P. W. F., Fournier, J.-D., Frasca, S., Frasconi, F., Frei, Z., Freise, A., Frey, R., Frey, V., Fritschel, P., Frolov, V. V., Fujii, Y., Fukunaga, M., Fukushima, M., Fulda, P., Fyffe, M., Gabbard, H. A., Gadre, B. U., Gaebel, S. M., Gair, J. R., Gammaitoni, L., Ganija, M. R., Gaonkar, S. G., Garcia, A., García-Quirós, C., Garufi, F., Gateley, B., Gaudio, S., Gaur, G., Gayathri, V., Ge, G. G., Gemme, G., Genin, E., Gennai, A., George, D., George, J., Gergely, L., Germain, V., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, S., Giacomazzo, B., Giaime, J. A., Giardina, K. D., Giazotto, A., Gill, K., Giordano, G., Glover, L., Godwin, P., Goetz, E., Goetz, R., Goncharov, B., González, G., Castro, J. M. Gonzalez, Gopakumar, A., Gorodetsky, M. L., Gossan, S. E., Gosselin, M., Gouaty, R., Grado, A., Graef, C., Granata, M., Grant, A., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, E. M., Groot, P., Grote, H., Grunewald, S., Gruning, P., Guidi, G. M., Gulati, H. K., Guo, Y., Gupta, A., Gupta, M. K., Gustafson, E. K., Gustafson, R., Haegel, L., Hagiwara, A., Haino, S., Halim, O., Hall, B. R., Hall, E. D., Hamilton, E. Z., Hammond, G., Haney, M., Hanke, M. M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanson, J., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hasegawa, K., Haster, C.-J., Haughian, K., Hayakawa, H., Hayama, K., Hayes, F. J., Healy, J., Heidmann, A., Heintze, M. C., Heitmann, H., Hello, P., Hemming, G., Hendry, M., Heng, I. S., Hennig, J., Heptonstall, A. W., Heurs, M., Hild, S., Himemoto, Y., Hinderer, T., Hiranuma, Y., Hirata, N., Hirose, E., Hoak, D., Hochheim, S., Hofman, D., Holgado, A. M., Holland, N. A., Holt, K., Holz, D. E., Hong, Z., Hopkins, P., Horst, C., Hough, J., Howell, E. J., Hoy, C. G., Hreibi, A., Hsieh, B. H., Huang, G. Z., Huang, P. W., Huang, Y. J., Huerta, E. A., Huet, D., Hughey, B., Hulko, M., Husa, S., Huttner, S. H., Huynh-Dinh, T., Idzkowski, B., Iess, A., Ikenoue, B., Imam, S., Inayoshi, K., Ingram, C., Inoue, Y., Inta, R., Intini, G., Ioka, K., Irwin, B., Isa, H. N., Isac, J.-M., Isi, M., Itoh, Y., Iyer, B. R., Izumi, K., Jacqmin, T., Jadhav, S. J., Jani, K., Janthalur, N. N., Jaranowski, P., Jenkins, A. C., Jiang, J., Johnson, D. S., Jones, A. W., Jones, D. I., Jones, R., Jonker, R. J. G., Ju, L., Jung, K., Jung, P., Junker, J., Kajita, T., Kalaghatgi, C. V., Kalogera, V., Kamai, B., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G. W., Kanner, J. B., Kapadia, S. J., Karki, S., Karvinen, K. S., Kashyap, R., Kasprzack, M., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaufer, S., Kawabe, K., Kawaguchi, K., Kawai, N., Kawasaki, T., Keerthana, N. V., Kéfélian, F., Keitel, D., Kennedy, R., Key, J. S., Khalili, F. Y., Khan, H., Khan, I., Khan, S., Khan, Z., Khazanov, E. A., Khursheed, M., Kijbunchoo, N., Kim, Chunglee, Kim, C., Kim, J. C., Kim, J., Kim, K., Kim, W., Kim, W. S., Kim, Y.-M., Kimball, C., Kimura, N., King, E. J., King, P. J., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kita, N., Kitazawa, H., Kleybolte, L., Klika, J. H., Klimenko, S., Knowles, T. D., Knyazev, E., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kojima, Y., Kokeyama, K., Koley, S., Komori, K., Kondrashov, V., Kong, A. K. H., Kontos, A., Koper, N., Korobko, M., Korth, W. Z., Kotake, K., Kowalska, I., Kozak, D. B., Kozakai, C., Kozu, R., Kringel, V., Krishnendu, N., Królak, A., Kuehn, G., Kumar, A., Kumar, P., Kumar, Rahul, Kumar, R., Kumar, S., Kume, J., Kuo, C. M., Kuo, H. S., Kuo, L., Kuroyanagi, S., Kusayanagi, K., Kutynia, A., Kwak, K., Kwang, S., Lackey, B. D., Lai, K. H., Lam, T. L., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., Lanza, R. K., Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lecoeuche, Y. K., Lee, C. H., Lee, H. K., Lee, H. M., Lee, H. W., Lee, J., Lee, K., Lee, R. K., Lehmann, J., Lenon, A., Leonardi, M., Leroy, N., Letendre, N., Levin, Y., Li, J., Li, K. J. L., Li, T. G. F., Li, X., Lin, C. Y., Lin, F., Lin, F. L., Lin, L. C. C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, G. C., Liu, J., Liu, X., Lo, R. K. L., Lockerbie, N. A., London, L. T., Longo, A., Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lough, J. D., Lousto, C. O., Lovelace, G., Lower, M. E., Lück, H., Lumaca, D., Lundgren, A. P., Luo, L. W., Lynch, R., Ma, Y., Macas, R., Macfoy, S., MacInnis, M., Macleod, D. M., Macquet, A., Magaña-Sandoval, F., Zertuche, L. Magaña, Magee, R. 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2020
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34. Global Burden of Cardiovascular Diseases and Risks, 1990-2022

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Mensah, G, Fuster, V, Murray, C, Roth, G, Abate, Y, Abbasian, M, Abd-Allah, F, Abdollahi, A, Abdollahi, M, Abdulah, D, Abdullahi, A, Abebe, A, Abedi, A, Abiodun, O, Ali, H, Abu-Gharbieh, E, Abu-Rmeileh, N, Aburuz, S, Abushouk, A, Abu-Zaid, A, Adane, T, Adderley, N, Adebayo, O, Aden, B, Adeyeoluwa, T, Adeyomoye, O, Sakilah Adnani, Q, Afrashteh, F, Afyouni, S, Afzal, S, Agasthi, P, Agodi, A, Aguilera Arriagada, C, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, M, Ahmed, A, Ahmed, H, Ahmed, M, Ahmed, S, Ajami, M, Akinosoglou, K, Ala, M, Ali AL-Ahdal, T, Alalalmeh, S, Al-Aly, Z, Alam, N, Al-amer, R, Alashi, A, Albashtawy, M, Albataineh, M, Alema, H, Alemi, S, Alemu, Y, Saeed Al-Gheethi, A, Alhabib, K, Naji Alhalaiqa, F, Ali, M, Ali, R, Pursuing, P, Shujait Ali, S, Alicandro, G, Alikhani, R, Aljunid, S, Alla, F, Almahmeed, W, Al-Marwani, S, Alonso, J, Al-Raddadi, R, Alvi, F, Alvis-Guzman, N, Alvis-Zakzuk, N, Alwafi, H, Aly, H, Amegbor, P, Amin, T, Amindarolzarbi, A, 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D., Morze J., Mostafavi E., Mostofinejad A., Mougin V., Mousavi P., Mousavi S. E., Mozaffarian D., Msherghi A., Muccioli L., Mueller U. O., Mukherjee S., Munjal K., Murillo-Zamora E., Mustafa G., Muthu S., Mwita J. C., Myung W., Nagarajan A. J., Nagaraju S. P., Naik G. R., Naik G., Nair T. S., Najafi M. S., Ansari N. N., Nangia V., Swamy S. N., Nargus S., Nascimento B. R., Nascimento G. G., Nasoori H., Natto Z. S., Nauman J., Naveed M., Nayak B. P., Nayak V. C., Negash H., Negoi I., Negoi R. I., Shahrokh Abadi R. N., Nejadghaderi S. A., Nejjari C., Nematollahi M. H., Nepal S., Ng N., Nguyen D. H., Nguyen P. T., Nguyen V. T., Niazi R. K., Nijjar S. S., Nizam M. A., Noman E. A., Nomura S., Noreen M., Norrving B., Noubiap J. J., Nri-Ezedi C. A., Ntsekhe M., Nurrika D., Nzoputam C. I., Nzoputam O. J., Obamiro K. O., O'Donnell M. J., Oghenetega O. B., Oguntade A. S., Oguta J. O., Okeke S. R., Okekunle A. P., Okidi L., Okonji O. C., Okwute P. G., Olagunju A. T., Olaiya M. T., Olana M. 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T., Zeng Y., Zhai C., Zhang C., Zhang H., Zhang L., Zhang N., Zhang Y., Zhao H., Zheng P., Zhong C., Zhou S., Zhu B., Zhu L., Zielinska M., Zikarg Y. T., Zmaili M., Zoeckler L. Z., Zou Z., Zumla A., Zweck E., and Zyoud S. H.

Published
2023

35. Physics-Informed with Power-Enhanced Residual Network for Interpolation and Inverse Problems

Author

Noorizadegan, Amir, Young, D. L., Hon, Y. C., Chen, C. S., Noorizadegan, Amir, Young, D. L., Hon, Y. C., and Chen, C. S.

Abstract

This paper introduces a novel neural network structure called the Power-Enhancing residual network, designed to improve interpolation capabilities for both smooth and non-smooth functions in 2D and 3D settings. By adding power terms to residual elements, the architecture boosts the network's expressive power. The study explores network depth, width, and optimization methods, showing the architecture's adaptability and performance advantages. Consistently, the results emphasize the exceptional accuracy of the proposed Power-Enhancing residual network, particularly for non-smooth functions. Real-world examples also confirm its superiority over plain neural network in terms of accuracy, convergence, and efficiency. The study also looks at the impact of deeper network. Moreover, the proposed architecture is also applied to solving the inverse Burgers' equation, demonstrating superior performance. In conclusion, the Power-Enhancing residual network offers a versatile solution that significantly enhances neural network capabilities. The codes implemented are available at: \url{https://github.com/CMMAi/ResNet_for_PINN}.

Published
2023

37. Introduction

Author

Chen, Wen, Fu, Zhuo-Jia, Chen, C. S., Chen, Wen, Fu, Zhuo-Jia, and Chen, C.S.

Published
2014
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