NLS approximation of the Euler-Poisson system for a cold ion-acoustic plasma
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作者:
Liu, Huimin
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Shanxi Univ Finance & Econ, Fac Appl Math, Taiyuan 030006, Peoples R ChinaShanxi Univ Finance & Econ, Fac Appl Math, Taiyuan 030006, Peoples R China
Liu, Huimin
[1
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Bian, Dongfen
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Beijing Inst Technol, Sch Math & Stat, Beijing 100081, Peoples R ChinaShanxi Univ Finance & Econ, Fac Appl Math, Taiyuan 030006, Peoples R China
Bian, Dongfen
[2
]
Pu, Xueke
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Guangzhou Univ, Sch Math & Informat Sci, Guangzhou 510006, Peoples R ChinaShanxi Univ Finance & Econ, Fac Appl Math, Taiyuan 030006, Peoples R China
Pu, Xueke
[3
]
机构:
[1] Shanxi Univ Finance & Econ, Fac Appl Math, Taiyuan 030006, Peoples R China
[2] Beijing Inst Technol, Sch Math & Stat, Beijing 100081, Peoples R China
[3] Guangzhou Univ, Sch Math & Informat Sci, Guangzhou 510006, Peoples R China
In the previous paper Liu and Pu (2019) [17], we proved the nonlinear Schrodinger (NLS) approximation for the Euler-Poisson system for a hot ion-acoustic plasma, where the appearance of resonances and the loss of derivatives of quadratic terms are the main difficulties. Note that when the ion-acoustic plasma is hot, the Euler-Poisson system is Friedrich symmetrizable, and the linear term can provide a derivative to compensate the loss of derivative induced by quadratic terms after diagonalizing the linearized system. When the ion-acoustic plasma is cold, as considered in the present paper, the situation is very different from that in the previous paper. The Euler-Poisson system becomes a pressureless system, so the linear operator has no regularity, and the quadratic terms still lose a derivative in the diagonalized system. This fact makes it more difficult to prove the NLS approximation of Euler-Poisson system for a cold ion-acoustic plasma. In this paper, we take advantage of the special structure of the pressureless Euler-Poisson system and the normal-form transformation to deal with the difficulties caused by resonances, especially the difficulties caused by derivative loss, in order to prove the NLS approximation. (c) 2023 Elsevier Inc. All rights reserved.
机构:
Guangzhou Univ, Sch Math & Informat Sci, Guangzhou 510006, Peoples R ChinaGuangzhou Univ, Sch Math & Informat Sci, Guangzhou 510006, Peoples R China
Pu, Xueke
Zhou, Wenli
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机构:
Guangxi Normal Univ, Sch Math & Stat, Guilin 541006, Peoples R ChinaGuangzhou Univ, Sch Math & Informat Sci, Guangzhou 510006, Peoples R China
Zhou, Wenli
Bian, Dongfen
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机构:
Beijing Inst Technol, Sch Math & Stat, Beijing 100081, Peoples R ChinaGuangzhou Univ, Sch Math & Informat Sci, Guangzhou 510006, Peoples R China
机构:
Korea Adv Inst Sci & Technol, Dept Math Sci, 291 Daehak Ro, Daejeon 34141, South Korea
Korea Inst Adv Study, 85 Hoegiro, Seoul 02455, South KoreaKorea Adv Inst Sci & Technol, Dept Math Sci, 291 Daehak Ro, Daejeon 34141, South Korea
Bae, Myoungjean
Park, Hyangdong
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Yonsei Univ, Ctr Math Anal & Computat CMAC, 50 Yonsei Ro, Seoul 03722, South KoreaKorea Adv Inst Sci & Technol, Dept Math Sci, 291 Daehak Ro, Daejeon 34141, South Korea