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7,137 results on '"Wen Jia"'

153. Scaling of the Reduced Energy Spectrum of Random Matrix Ensemble

Author

Rao, Wen-Jia and Chen, M. N.

Subjects
Condensed Matter - Disordered Systems and Neural Networks
Abstract

We study the reduced energy spectrum $\{E_{i}^{(n)}\}$, which is constructed by picking one level from every $n$ levels of the original spectrum $\{E_{i}\}$, in a Gaussian ensemble of random matrix with Dyson index $\beta\in \left( 0,\infty \right) $. It's shown $\{E_{i}^{(n)}\}$ bears the same form of probability distribution as $\{E_{i}\}$ with a rescaled parameter $\gamma =\frac{n(n+1)}{2}\beta +n-1$. Notably, the $n$-th order level spacing and non-overlapping gap ratio in $\{E_{i}\}$ become the lowest-order ones in $\{E_{i}^{(n)}\}$, hence their distributions will rescale in an identical way. Numerical evidences are provided by simulating random spin chain as well as modelling random matrices. Our results establish the higher-order spacing distributions in random matrix ensembles beyond GOE,GUE,GSE, and reveals a hierarchy of structures hidden in the energy spectrum., Comment: 8 pages, 4 figures

Published
2020
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154. Higher-order level spacings in random matrix theory based on Wigner's conjecture

Author

Rao, Wen-Jia

Subjects
Condensed Matter - Disordered Systems and Neural Networks
Abstract

The distribution of higher order level spacings, i.e. the distribution of $\{s_{i}^{(n)}=E_{i+n}-E_{i}\}$ with $n\geq 1$ is derived analytically using a Wigner-like surmise for Gaussian ensembles of random matrix as well as Poisson ensemble. It is found $s^{(n)}$ in Gaussian ensembles follows a generalized Wigner-Dyson distribution with rescaled parameter $\alpha=\nu C_{n+1}^2+n-1$, while that in Poisson ensemble follows a generalized semi-Poisson distribution with index $n$. Numerical evidences are provided through simulations of random spin systems as well as non-trivial zeros of Riemann zeta function. The higher order generalizations of gap ratios are also discussed., Comment: 7 pages, 4 figures

Published
2020
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155. Detection of metastable electronic states by Penning trap mass spectrometry

Author

Schüssler, Rima Xenia, Bekker, Hendrik, Braß, Martin, Cakir, Halil, López-Urrutia, José R. Crespo, Door, Menno, Filianin, Pavel, Harman, Zoltan, Haverkort, Maurits W., Huang, Wen Jia, Indelicato, Paul, Keitel, Christoph Helmut, König, Charlotte Maria, Kromer, Kathrin, Müller, Marius, Novikov, Yuri N., Rischka, Alexander, Schweiger, Christoph, Sturm, Sven, Ulmer, Stefan, Eliseev, Ssergey, and Blaum, Klaus

Subjects
Physics - Atomic Physics
Abstract

State-of-the-art optical clocks achieve fractional precisions of $10^{-18}$ and below using ensembles of atoms in optical lattices or individual ions in radio-frequency traps. Promising candidates for novel clocks are highly charged ions (HCIs) and nuclear transitions, which are largely insensitive to external perturbations and reach wavelengths beyond the optical range, now becoming accessible to frequency combs. However, insufficiently accurate atomic structure calculations still hinder the identification of suitable transitions in HCIs. Here, we report on the discovery of a long-lived metastable electronic state in a HCI by measuring the mass difference of the ground and the excited state in Re, the first non-destructive, direct determination of an electronic excitation energy. This result agrees with our advanced calculations, and we confirmed them with an Os ion with the same electronic configuration. We used the high-precision Penning-trap mass spectrometer PENTATRAP, unique in its synchronous use of five individual traps for simultaneous mass measurements. The cyclotron frequency ratio $R$ of the ion in the ground state to the metastable state could be determined to a precision of $\delta R=1\cdot 10^{-11}$, unprecedented in the heavy atom regime. With a lifetime of about 130 days, the potential soft x-ray frequency reference at $\nu=4.86\cdot 10^{16}\,\text{Hz}$ has a linewidth of only $\Delta \nu\approx 5\cdot 10^{-8}\,\text{Hz}$, and one of the highest electronic quality factor ($Q=\frac{\nu}{\Delta \nu}\approx 10^{24}$) ever seen in an experiment. Our low uncertainty enables searching for more HCI soft x-ray clock transitions, needed for promising precision studies of fundamental physics in a thus far unexplored frontier.

Published
2020
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156. Learning What a Machine Learns in a Many-Body Localization Transition

Author

Kausar, Rubah, Rao, Wen-Jia, and Wan, Xin

Subjects
Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Strongly Correlated Electrons
Abstract

We employ a convolutional neural network to explore the distinct phases in random spin systems with the aim to understand the specific features that the neural network chooses to identify the phases. With the energy spectrum normalized to the bandwidth as the input data, we demonstrate that a network of the smallest nontrivial kernel width selects level spacing as the signature to distinguish the many-body localized phase from the thermal phase. We also study the performance of the neural network with an increased kernel width, based on which we find an alternative diagnostic to detect phases from the raw energy spectrum of such a disordered interacting system.

Published
2020
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162. Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Author

Keshawarz, Amena, Bui, Helena, Joehanes, Roby, Ma, Jiantao, Liu, Chunyu, Huan, Tianxiao, Hwang, Shih-Jen, Tejada, Brandon, Sooda, Meera, Courchesne, Paul, Munson, Peter J., Demirkale, Cumhur Y., Yao, Chen, Heard-Costa, Nancy L., Pitsillides, Achilleas N., Lin, Honghuang, Liu, Ching-Ti, Wang, Yuxuan, Peloso, Gina M., Lundin, Jessica, Haessler, Jeffrey, Du, Zhaohui, Cho, Michael, Hersh, Craig P., Castaldi, Peter, Raffield, Laura M., Wen, Jia, Li, Yun, Reiner, Alexander P., Feolo, Mike, Sharopova, Nataliya, Vasan, Ramachandran S., DeMeo, Dawn L., Carson, April P., Kooperberg, Charles, and Levy, Daniel

Published
2023
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173. Siamese Adaptive Template Update Network for Visual Tracking

Author

Wen, Jia, Ren, Kejun, Xiang, Yang, Tang, Dandan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Premaratne, Prashan, editor, Jin, Baohua, editor, Qu, Boyang, editor, Jo, Kang-Hyun, editor, and Hussain, Abir, editor

Published
2023
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177. Jensen Type Inequalities Involving Homogeneous Polynomials

Author

Zhang Zhi-Hua and Wen Jia-Jin

Subjects
Mathematics, QA1-939
Abstract

By means of algebraic, analytical and majorization theories, and under the proper hypotheses, we establish several Jensen type inequalities involving th homogeneous polynomials as follows: , , and , and display their applications.

Published
2010

186. Rationale and design of a randomized controlled trial: The effect of intensive lipid-lowering therapy with PCSK9 inhibitor on endothelial-coverage of stent strut after percutaneous coronary intervention (PCI) for patients with acute coronary syndrome (ACS): Optical coherence tomography (OCT) study (PIECES-OCT study)

Author

Yin, Zheng, Li, Zhi-Fan, Zhang, Wen-Jia, Zhang, Shuang, Sui, Yong-Gang, Xu, Yan-Lu, Zhang, Hai-Tao, Liu, Xiao-Ning, Qiu, Hong, Zhao, Jing-Lin, Li, Jian-Jun, Dou, Ke-Fei, Qian, Jie, Wu, Yong-Jian, and Wu, Na-Qiong

Published
2023
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193. Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

Author

Wen, Jia, Xie, Munan, Rowland, Bryce, Rosen, Jonathan D, Sun, Quan, Chen, Jiawen, Tapia, Amanda L, Qian, Huijun, Kowalski, Madeline H, Shan, Yue, Young, Kristin L, Graff, Marielisa, Argos, Maria, Avery, Christy L, Bien, Stephanie A, Buyske, Steve, Yin, Jie, Choquet, Hélène, Fornage, Myriam, Hodonsky, Chani J, Jorgenson, Eric, Kooperberg, Charles, Loos, Ruth JF, Liu, Yongmei, Moon, Jee-Young, North, Kari E, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Zhao, Wei, Shang, Lulu, Wang, Tao, Zhou, Xiang, Reiner, Alexander P, Raffield, Laura M, and Li, Yun

Subjects
Biological Sciences, Genetics, Human Genome, Minority Health, Health Disparities, Hematology, Atherosclerosis, 2.1 Biological and endogenous factors, Good Health and Well Being, Black or African American, Blood Cells, Cohort Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Transcriptome, White People, TWAS, non-European populations, ancestry, expression analysis
Abstract

BackgroundThousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed.MethodsTo derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants.ResultsOur results revealed 24 suggestive signals (p < 1 × 10-4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN.ConclusionsThese analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Published
2021

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