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9,494 results on '"Yi Bin"'

55. High-Precision Autonomous Navigation Method for Deep Space Probe Cruise Phase Under Uncertain Conditions with Q-Learning Filter

Author

Zhou, Xuanying, Wang, Jiongqi, Yi, Bin, Hou, Bowen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Jia, Yingmin, editor, Zhang, Weicun, editor, Fu, Yongling, editor, and Yang, Huihua, editor

Published
2024
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62. Measurable residual disease and posttransplantation gilteritinib maintenance for patients with FLT3-ITD–mutated AML

Author

Levis, Mark J., Hamadani, Mehdi, Logan, Brent R., Jones, Richard J., Singh, Anurag K., Litzow, Mark R., Wingard, John R., Papadopoulos, Esperanza B., Perl, Alexander E., Soiffer, Robert J., Ustun, Celalettin, Oshima, Masumi Ueda, Uy, Geoffrey L., Waller, Edmund K., Vasu, Sumithira, Solh, Melhem, Mishra, Asmita, Muffly, Lori S., Kim, Hee-Je, Stelljes, Matthias, Najima, Yuho, Onozawa, Masahiro, Thomson, Kirsty, Nagler, Arnon, Wei, Andrew H., Marcucci, Guido, Chen, Caroline, Hasabou, Nahla, Rosales, Matt, Hill, Jason, Gill, Stanley C., Nuthethi, Rishita, King, Denise, Mendizabel, Adam, Devine, Steven M., Horowitz, Mary M., and Chen, Yi-Bin

Published
2025
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64. Variational determination of arbitrarily many eigenpairs in one quantum circuit

Author

Xu, Guanglei, Guo, Yi-Bin, Li, Xuan, Zhou, Zong-Sheng, Liao, Hai-Jun, and Xiang, T.

Subjects
Quantum Physics
Abstract

The state-of-the-art quantum computing hardware has entered the noisy intermediate-scale quantum (NISQ) era. Having been constrained by the limited number of qubits and shallow circuit depth, NISQ devices have nevertheless demonstrated the potential of applications on various subjects. One example is the variational quantum eigensolver (VQE) that was first introduced for computing ground states. Although VQE has now been extended to the study of excited states, the algorithms previously proposed involve a recursive optimization scheme which requires many extra operations with significantly deeper quantum circuits to ensure the orthogonality of different trial states. Here we propose a new algorithm to determine many low energy eigenstates simultaneously. By introducing ancillary qubits to purify the trial states so that they keep orthogonal to each other throughout the whole optimization process, our algorithm allows these states to be efficiently computed in one quantum circuit. Our algorithm reduces significantly the complexity of circuits and the readout errors, and enables flexible post-processing on the eigen-subspace from which the eigenpairs can be accurately determined. We demonstrate this algorithm by applying it to the transverse Ising model. By comparing the results obtained using this variational algorithm with the exact ones, we find that the eigenvalues of the Hamiltonian converge quickly with the increase of the circuit depth. The accuracies of the converged eigenvalues are of the same order, which implies that the difference between any two eigenvalues can be more accurately determined than the eigenvalues themselves., Comment: 9 pages, 4 figures

Published
2022

75. Structural transitions in liquid semiconductor alloys: A molecular dynamics study with a neural network potential.

Author

Fang, Yi-Bin, Shang, Cheng, Liu, Zhi-Pan, and Gong, Xin-Gao

Subjects
*CONDENSED matter physics, *LIQUID alloys, *MOLECULAR dynamics, *MELTING points, *ROCK salt
Abstract

Liquid–liquid phase transitions hold a unique and profound significance within condensed matter physics. These transitions, while conceptually intriguing, often pose formidable computational challenges. However, recent advances in neural network (NN) potentials offer a promising avenue to effectively address these challenges. In this paper, we delve into the structural transitions of liquid CdTe, CdS, and their alloy systems using molecular dynamics simulations, harnessing the power of an NN potential named LaspNN. Our investigations encompass both pressure and temperature effects. Through our simulations, we uncover three primary liquid structures around melting points that emerge as pressure increases: tetrahedral, rock salt, and close-packed structures, which greatly resemble those of solid states. In the high-temperature regime, we observe the formation of Te chains and S dimers, providing a deeper understanding of the liquid's atomic arrangements. When examining CdSxTe1−x alloys, our findings indicate that a small substitution of S by Te atoms for S-rich alloys (x > 0.5) exhibits a structural transition much different from CdS, while a large substitution of Te by S atoms for Te-rich alloys (x < 0.5) barely exhibits a structural transition similar to CdTe. We construct a schematic diagram for liquid alloys that considers both temperature and pressure, providing a comprehensive overview of the alloy system's behavior. The local aggregation of Te atoms demonstrates a linear relationship with alloy composition x, whereas that of S atoms exhibits a nonlinear one, shedding light on the composition-dependent structural changes. [ABSTRACT FROM AUTHOR]

Published
2024
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76. Quantum Liang Information Flow as Causation Quantifier

Author

Yi, Bin and Bose, Sougato

Subjects
Quantum Physics
Abstract

Liang information flow is a quantity widely used in classical network theory to quantify causation, and has been applied widely, for example, to finance and climate. The most striking aspect here is to freeze/subtract a certain node of the network to ascertain its causal influence to other nodes of the network. Such an approach is yet to be applied to quantum network dynamics. Here we generalize Liang information flow to the quantum domain using the von-Neumann entropy. Using that we propose to assess the relative importance of various nodes of a network to causally influence a target node. We exemplify the application by using small quantum networks.

Published
2022
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77. A new class of differential quasivariational inequalities with an application to a quasistatic viscoelastic frictional contact problem

Author

Chu, Xu, Chen, Tao, Huang, Nan-jing, and Xiao, Yi-bin

Subjects
Mathematics - Optimization and Control
Abstract

The overarching goal of this paper is to introduce and investigate a new nonlinear system driven by a nonlinear differential equation, a history-dependent quasivariational inequality, and a parabolic variational inequality in Banach spaces. Such a system can be used to model quasistatic frictional contact problems for viscoelastic materials with long memory, damage and wear. By using the Banach fixed point theorem, we prove an existence and uniqueness theorem of solution for such a system under some mild conditions. As a novel application, we obtain a unique solvability of a quasistatic viscoelastic frictional contact problem with long memory, damage and wear.

Published
2021

82. Health-related quality of life with gilteritinib vs placebo posttransplant for FLT3-ITD+ acute myeloid leukemia

Author

Hamilton, Betty K., Pandya, Bhavik J., Ivanescu, Cristina, Elsouda, Dina, Hamadani, Mehdi, Chen, Yi-Bin, Levis, Mark J., Ueda Oshima, Masumi, Litzow, Mark R., Soiffer, Robert J., Ustun, Celalettin, Perl, Alexander E., Singh, Anurag K., Geller, Nancy, Hasabou, Nahla, Rosales, Matt, Cella, David, Corredoira, Laura, Pestana, Carolina, Horowitz, Mary M., and Logan, Brent

Published
2024
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87. Phase 1 study of CAR-37 T cells in patients with relapsed or refractory CD37+ lymphoid malignancies

Author

Frigault, Matthew J., Graham, Charlotte E., Berger, Trisha R., Ritchey, Julie, Horick, Nora K., El-Jawahri, Areej, Scarfò, Irene, Schmidts, Andrea, Haradhvala, Nicholas J., Wehrli, Marc, Lee, Won-Ho, Parker, Aiyana L., Wiggin, Hadley R., Bouffard, Amanda, Dey, Aonkon, Leick, Mark B., Katsis, Katelin, Elder, Eva L., Dolaher, Maria A., Cook, Daniella T., Chekmasova, Alena A., Huang, Lu, Nikiforow, Sarah, Daley, Heather, Ritz, Jerome, Armant, Myriam, Preffer, Fred, DiPersio, John F., Nardi, Valentina, Chen, Yi-Bin, Gallagher, Kathleen M. E., and Maus, Marcela V.

Published
2024
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