Browsing by Author "Wang, Zhen"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    A Generalized Trust Region Algorithm for Equality Constrained Optimization
    (2003-12) Wang, Zhen
    We introduce and analyze a class of generalized trust region sequential quadratic programming (GTRSQP) algorithms for equality constrained optimization. Unlike in standard trust region SQP (TRSQP) algorithms, the optimization subproblems arising in our GTRSQP algorithm can be generated from models of the objective and constraint functions that are not necessarily based on Taylor approximations. The need for such generalizations is motivated by optimal control problems for which model problems can be generated using, e.g., different discretizations. Several existing TRSQP algorithms are special cases of our GTRSQP algorithm. Our first order global convergence result for the GTRSQP algorithm applied to TRSQP allows one to relax the condition that the so-called tangential step lies in the null-space of the linearized constraints. The application of the GTRSQP algorithm to an optimal control problem governed by Burgers equation is discussed.
  • Thumbnail Image
    Item
    A generalized trust region SQP algorithm for equality constrained optimization
    (2004) Wang, Zhen; Heinkenschloss, Matthias
    We introduce and analyze a class of generalized trust region sequential quadratic programming (GTRSQP) algorithms for equality constrained optimization. Unlike in standard trust region SQP (TRSQP) algorithms, the optimization subproblems arising in our GTRSQP algorithm can be generated from models of the objective and constraint functions that are not necessarily based on Taylor approximations. The need for such generalizations is motivated by optimal control problems for which model problems can be generated using, e.g., different discretizations. Several existing TRSQP algorithms are special cases of our GTRSQP algorithm. Our first order global convergence result for the GTRSQP algorithm applied to TRSQP allows one to relax the condition that the so-called tangential step lies in the null-space of the linearized constraints. The application of the GTRSQP algorithm to an optimal control problem governed by Burgers equation is discussed.
  • Thumbnail Image
    Item
    Heavy fermion quantum criticality at dilute carrier limit in CeNi2−δ(As1−xPx)2
    (Springer Nature, 2019) Chen, Jian; Wang, Zhen; Li, Yupeng; Feng, Chunmu; Dai, Jianhui; Xu, Zhu’an; Si, Qimiao
    We study the quantum phase transitions in the nickel pnctides, CeNi2−δ(As1−xPx)2 (δ ≈ 0.07–0.22) polycrystalline samples. This series displays the distinct heavy fermion behavior in the rarely studied parameter regime of dilute carrier limit. We systematically investigate the magnetization, specific heat and electrical transport down to low temperatures. Upon increasing the P-content, the antiferromagnetic order of the Ce-4f moment is suppressed continuously and vanishes at xc ~ 0.55. At this doping, the temperature dependences of the specific heat and longitudinal resistivity display non-Fermi liquid behavior. Both the residual resistivity ρ0 and the Sommerfeld coefficient γ0 are sharply peaked around xc. When the P-content reaches close to 100%, we observe a clear low-temperature crossover into the Fermi liquid regime. In contrast to what happens in the parent compound x = 0.0 as a function of pressure, we find a surprising result that the non-Fermi liquid behavior persists over a nonzero range of doping concentration, xc < x < 0.9. In this doping range, at the lowest measured temperatures, the temperature dependence of the specific-heat coefficient is logarithmically divergent and that of the electrical resistivity is linear. We discuss the properties of CeNi2−δ(As1−xPx)2 in comparison with those of its 1111 counterpart, CeNi(As1−xPx)O. Our results indicate a non-Fermi liquid phase in the global phase diagram of heavy fermion metals.
  • Thumbnail Image
    Item
    Role of the 245 phase in alkaline iron selenide superconductors revealed by high-pressure studies
    (American Physical Society, 2014) Gao, Peiwen; Yu, Rong; Sun, Liling; Wang, Hangdong; Wang, Zhen; Wu, Qi; Fang, Minghu; Chen, Genfu; Guo, Jing; Zhang, Chao; Gu, Dachun; Tian, Huanfang; Li, Jianqi; Liu, Jing; Li, Yanchun; Li, Xiaodong; Jiang, Sheng; Yang, Ke; Li, Aiguo; Si, Qimiao; Zhao, Zhongxian
    There is considerable interest in uncovering the physics of iron-based superconductivity from the alkaline iron selenides, a materials class containing an insulating phase (245 phase) and a superconducting (SC) phase. Due to the microstructural complexity of these superconductors, the role of the 245 phase in the development of the superconductivity has been a puzzle. Here we demonstrate a comprehensive high-pressure study on the insulating samples with pure 245 phase and biphasic SC samples. We find that the insulating behavior can be completely suppressed by pressure in the insulating samples and also identify an intermediate metallic (M′) state. The Mott insulating (MI) state of the 245 phase and the M′ state coexist over a significant range of pressure up to ∼10 GPa, the same pressure at which the superconductivity of the SC samples vanishes. Our results reveal the M′ state as a pathway that connects the insulating and SC phases of the alkaline iron selenides and indicate that the coexistence and interplay between the MI and M′ states is a necessary condition for superconductivity. Finally, we interpret the M′ state in terms of an orbital selectivity of the correlated 3d electrons.
  • Thumbnail Image
    Item
    Speeding Up Mobile Browsers without Infrastructure Support
    (2012-09-05) Wang, Zhen; Zhong, Lin; Wallach, Dan S.; Ng, T. S. Eugene
    Mobile browsers are known to be slow. We characterize the performance of mobile browsers and find out that resource loading is the bottleneck. Leveraging an unprecedented set of web usage data collected from 24 iPhone users continuously over one year, we examine the three fundamental, orthogonal approaches to improve resource loading without infrastructure support: caching, prefetching, and speculative loading, which is first proposed and studied in this work. Speculative loading predicts and speculatively loads the subresources needed to open a webpage once its URL is given. We show that while caching and prefetching are highly limited for mobile browsing, speculative loading can be significantly more effective. Empirically, we show that client-only solutions can improve the browser speed by 1.4 seconds on average. We also report the design, realization, and evaluation of speculative loading in a WebKit-based browser called Tempo. On average, Tempo can reduce browser delay by 1 second (~20%).