Hasil untuk "q-fin.PM"

Yu Chen, Guobao Jiang, Shuqing Chen et al.

Black phosphorus (BP), an emerging narrow direct band-gap two-dimensional (2D) layered material that can fill the gap between the semi-metallic graphene and the wide-bandgap transition metal dichalcogenides (TMDs), had been experimentally found to exhibit the saturation of optical absorption if under strong light illumination. By taking advantage of this saturable absorption property, we could fabricate a new type of optical saturable absorber (SA) based on mechanically exfoliated BPs, and further demonstrate the applications for ultra-fast laser photonics. Based on the balanced synchronous twin-detector measurement method, we have characterized the saturable absorption property of the fabricated BP-SAs at the telecommunication band. By incorporating the BP-based SAs device into the all-fiber Erbium-doped fiber laser cavities, we are able to obtain either the passive Q-switching (with maximum pulse energy of 94.3 nJ) or the passive mode-locking operation (with pulse duration down to 946 fs). Our results show that BP could also be developed as an effective SA for pulsed fiber or solid-state lasers.

M. Walter, E. Warren, J. Mckone et al.

Energy harvested directly from sunlight offers a desirable approach toward fulfilling, with minimal environmental impact, the need for clean energy. Solar energy is a decentralized and inexhaustible natural resource, with the magnitude of the available solar power striking the earth’s surface at any one instant equal to 130 million 500 MW power plants.1 However, several important goals need to be met to fully utilize solar energy for the global energy demand. First, the means for solar energy conversion, storage, and distribution should be environmentally benign, i.e. protecting ecosystems instead of steadily weakening them. The next important goal is to provide a stable, constant energy flux. Due to the daily and seasonal variability in renewable energy sources such as sunlight, energy harvested from the sun needs to be efficiently converted into chemical fuel that can be stored, transported, and used upon demand. The biggest challenge is whether or not these goals can be met in a costeffective way on the terawatt scale.2

Viorica Marian, Henrike K. Blumenfeld, Margarita Kaushanskaya

F. Hayashi

Q. Du, V. Faber, M. Gunzburger

John D. Storey

D. Tuch

R. Stulz

J. Zhou, R. Adrian, S. Balachandar et al.

Kee H. Chung, Stephen W. Pruitt

C. Watkins, P. Dayan

J. Q. Candela, C. Rasmussen

Yixin Xu, Guangjie Li, Tiberiu Harko et al.

We propose an extension of the symmetric teleparallel gravity, in which the gravitational action L is given by an arbitrary function f of the non-metricity Q and of the trace of the matter-energy-momentum tensor T, so that L=f(Q,T)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L=f(Q,T)$$\end{document}. The field equations of the theory are obtained by varying the gravitational action with respect to both metric and connection. The covariant divergence of the field equations is obtained, with the geometry–matter coupling leading to the nonconservation of the energy-momentum tensor. We investigate the cosmological implications of the theory, and we obtain the cosmological evolution equations for a flat, homogeneous and isotropic geometry, which generalize the Friedmann equations of general relativity. We consider several cosmological models by imposing some simple functional forms of the function f(Q, T), corresponding to additive expressions of f(Q, T) of the form f(Q,T)=αQ+βT\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f(Q,T)=\alpha Q+\beta T$$\end{document}, f(Q,T)=αQn+1+βT\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f(Q,T)=\alpha Q^{n+1}+\beta T$$\end{document}, and f(Q,T)=-αQ-βT2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f(Q,T)=-\alpha Q-\beta T^2$$\end{document}. The Hubble function, the deceleration parameter, and the matter-energy density are obtained as a function of the redshift by using analytical and numerical techniques. For all considered cases the Universe experiences an accelerating expansion, ending with a de Sitter type evolution. The theoretical predictions are also compared with the results of the standard Λ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Lambda $$\end{document}CDM model.

Peide Liu, Junlin Liu

In the real multi‐attribute group decision making (MAGDM), there will be a mutual relationship between different attributes. As we all know, the Bonferroni mean (BM) operator has the advantage of considering interrelationships between parameters. In addition, in describing uncertain information, the eminent characteristic of q‐rung orthopair fuzzy sets (q‐ROFs) is that the sum of the qth power of the membership degree and the qth power of the degrees of non‐membership is equal to or less than 1, so the space of uncertain information they can describe is broader. In this paper, we combine the BM operator with q‐rung orthopair fuzzy numbers (q‐ROFNs) to propose the q‐rung orthopair fuzzy BM (q‐ROFBM) operator, the q‐rung orthopair fuzzy weighted BM (q‐ROFWBM) operator, the q‐rung orthopair fuzzy geometric BM (q‐ROFGBM) operator, and the q‐rung orthopair fuzzy weighted geometric BM (q‐ROFWGBM) operator, then the MAGDM methods are developed based on these operators. Finally, we use an example to illustrate the MAGDM process of the proposed methods. The proposed methods based on q‐ROFWBM and q‐ROFWGBM operators are very useful to deal with MAGDM problems.

Aiora Zabala, C. Sandbrook, Nibedita Mukherjee

Understanding human perspectives is critical in a range of conservation contexts, for example, in overcoming conflicts or developing projects that are acceptable to relevant stakeholders. The Q methodology is a unique semiquantitative technique used to explore human perspectives. It has been applied for decades in other disciplines and recently gained traction in conservation. This paper helps researchers assess when Q is useful for a given conservation question and what its use involves. To do so, we explained the steps necessary to conduct a Q study, from the research design to the interpretation of results. We provided recommendations to minimize biases in conducting a Q study, which can affect mostly when designing the study and collecting the data. We conducted a structured literature review of 52 studies to examine in what empirical conservation contexts Q has been used. Most studies were subnational or national cases, but some also address multinational or global questions. We found that Q has been applied to 4 broad types of conservation goals: addressing conflict, devising management alternatives, understanding policy acceptability, and critically reflecting on the values that implicitly influence research and practice. Through these applications, researchers found hidden views, understood opinions in depth and discovered points of consensus that facilitated unlocking difficult disagreements. The Q methodology has a clear procedure but is also flexible, allowing researchers explore long‐term views, or views about items other than statements, such as landscape images. We also found some inconsistencies in applying and, mainly, in reporting Q studies, whereby it was not possible to fully understand how the research was conducted or why some atypical research decisions had been taken in some studies. Accordingly, we suggest a reporting checklist.

Kewei Hou, Haitao Mo, Chen Xue et al.

In the investment theory, firms with high expected investment growth earn higher expected returns than firms with low expected investment growth, holding investment and expected profitability constant. Building on cross-sectional growth forecasts with Tobin’s q, operating cash flows, and change in return on equity as predictors, an expected growth factor earns an average premium of 0.84% per month (t = 10.27) in the 1967–2018 sample. The q5 model, which augments the Hou–Xue–Zhang (2015, Rev. Finan. Stud., 28, 650–705) q-factor model with the expected growth factor, shows strong explanatory power in the cross-section and outperforms the Fama–French (2018, J. Finan. Econom., 128, 234–252) six-factor model.

M. Aguilar, L. Ali Cavasonza, B. Alpat et al.

A precision measurement by AMS of the antiproton flux and the antiproton-to-proton flux ratio in primary cosmic rays in the absolute rigidity range from 1 to 450 GV is presented based on 3.49×10^{5} antiproton events and 2.42×10^{9} proton events. The fluxes and flux ratios of charged elementary particles in cosmic rays are also presented. In the absolute rigidity range ∼60 to ∼500  GV, the antiproton p[over ¯], proton p, and positron e^{+} fluxes are found to have nearly identical rigidity dependence and the electron e^{-} flux exhibits a different rigidity dependence. Below 60 GV, the (p[over ¯]/p), (p[over ¯]/e^{+}), and (p/e^{+}) flux ratios each reaches a maximum. From ∼60 to ∼500  GV, the (p[over ¯]/p), (p[over ¯]/e^{+}), and (p/e^{+}) flux ratios show no rigidity dependence. These are new observations of the properties of elementary particles in the cosmos.

G. Pintilie, Kaiming Zhang, Z. Su et al.

Cryogenic electron microscopy (cryo-EM) maps are now at the point where resolvability of individual atoms can be achieved. However, resolvability is not necessarily uniform throughout the map. We introduce a quantitative parameter to characterize the resolvability of individual atoms in cryo-EM maps, the map Q -score. Q -scores can be calculated for atoms in proteins, nucleic acids, water, ligands and other solvent atoms, using models fitted to or derived from cryo-EM maps. Q -scores can also be averaged to represent larger features such as entire residues and nucleotides. Averaged over entire models, Q -scores correlate very well with the estimated resolution of cryo-EM maps for both protein and RNA. Assuming the models they are calculated from are well fitted to the map, Q -scores can be used as a measure of resolvability in cryo-EM maps at various scales, from entire macromolecules down to individual atoms. Q -score analysis of multiple cryo-EM maps of the same proteins derived from different laboratories confirms the reproducibility of structural features from side chains down to water and ion atoms. Q -scores provide a quantitative metric for resolvability in cryo-EM maps, and can be used at the atom, residue or macromolecule scale.

S. Gu, T. Lillicrap, Zoubin Ghahramani et al.

© ICLR 2019 - Conference Track Proceedings. All rights reserved. Model-free deep reinforcement learning (RL) methods have been successful in a wide variety of simulated domains. However, a major obstacle facing deep RL in the real world is their high sample complexity. Batch policy gradient methods offer stable learning, but at the cost of high variance, which often requires large batches. TD-style methods, such as off-policy actor-critic and Q-learning, are more sample-efficient but biased, and often require costly hyperparameter sweeps to stabilize. In this work, we aim to develop methods that combine the stability of policy gradients with the efficiency of off-policy RL. We present Q-Prop, a policy gradient method that uses a Taylor expansion of the off-policy critic as a control variate. Q-Prop is both sample efficient and stable, and effectively combines the benefits of on-policy and off-policy methods. We analyze the connection between Q-Prop and existing model-free algorithms, and use control variate theory to derive two variants of Q-Prop with conservative and aggressive adaptation. We show that conservative Q-Prop provides substantial gains in sample efficiency over trust region policy optimization (TRPO) with generalized advantage estimation (GAE), and improves stability over deep deterministic policy gradient (DDPG), the state-of-the-art on-policy and off-policy methods, on OpenAI Gym's MuJoCo continuous control environments.

Jiafei Lyu, Xiaoteng Ma, Xiu Li et al.

Offline reinforcement learning (RL) defines the task of learning from a static logged dataset without continually interacting with the environment. The distribution shift between the learned policy and the behavior policy makes it necessary for the value function to stay conservative such that out-of-distribution (OOD) actions will not be severely overestimated. However, existing approaches, penalizing the unseen actions or regularizing with the behavior policy, are too pessimistic, which suppresses the generalization of the value function and hinders the performance improvement. This paper explores mild but enough conservatism for offline learning while not harming generalization. We propose Mildly Conservative Q-learning (MCQ), where OOD actions are actively trained by assigning them proper pseudo Q values. We theoretically show that MCQ induces a policy that behaves at least as well as the behavior policy and no erroneous overestimation will occur for OOD actions. Experimental results on the D4RL benchmarks demonstrate that MCQ achieves remarkable performance compared with prior work. Furthermore, MCQ shows superior generalization ability when transferring from offline to online, and significantly outperforms baselines. Our code is publicly available at https://github.com/dmksjfl/MCQ.