Searcharxiv⌕ Search

arXiv subjects

Wei Lin

Publications and source records attributed to Wei Lin.

318 records · Page 18Linked to original sources

Observable Signatures of a Classical Transition

Eternal inflation arising from a potential landscape predicts that our universe is one realization of many possible cosmological histories. One way to access different cosmological histories is via the nucleation of bubble universes from a metastable false vacuum. Another way to sample different cosmological histories is via classical transitions, the creation of pocket universes through the collision between bubbles. Using relativistic numerical simulations, we examine the possibility of observationally determining if our observable universe resulted from a classical transition. We find that classical transitions produce spatially infinite, approximately open Friedman-Robertson-Walker universes. The leading set of observables in the aftermath of a classical transition are negative spatial curvature and a contribution to the Cosmic Microwave Background temperature quadrupole. The level of curvature and magnitude of the quadrupole are dependent on the position of the observer, and we determine the possible range of observables for two classes of single-scalar field models. For the first class, where the inflationary phase has a lower energy than the vacuum preceding the classical transition, the magnitude of the observed quadrupole generally falls to zero with distance from the collision while the spatial curvature grows to a constant. For the second class, where the inflationary phase has a higher energy than the vacuum preceding the classical transition, the magnitude of the observed quadrupole generically falls to zero with distance from the collision while the spatial curvature grows without bound. We find that the magnitude of the quadrupole and curvature grow with increasing centre of mass energy of the collision, and explore variations of the parameters in the scalar field lagrangian.

astro-ph.CO↗

Regularization Methods for High-Dimensional Instrumental Variables Regression With an Application to Genetical Genomics

In genetical genomics studies, it is important to jointly analyze gene expression data and genetic variants in exploring their associations with complex traits, where the dimensionality of gene expressions and genetic variants can both be much larger than the sample size. Motivated by such modern applications, we consider the problem of variable selection and estimation in high-dimensional sparse instrumental variables models. To overcome the difficulty of high dimensionality and unknown optimal instruments, we propose a two-stage regularization framework for identifying and estimating important covariate effects while selecting and estimating optimal instruments. The methodology extends the classical two-stage least squares estimator to high dimensions by exploiting sparsity using sparsity-inducing penalty functions in both stages. The resulting procedure is efficiently implemented by coordinate descent optimization. For the representative $L_1$ regularization and a class of concave regularization methods, we establish estimation, prediction, and model selection properties of the two-stage regularized estimators in the high-dimensional setting where the dimensionality of covariates and instruments are both allowed to grow exponentially with the sample size. The practical performance of the proposed method is evaluated by simulation studies and its usefulness is illustrated by an analysis of mouse obesity data. Supplementary materials for this article are available online.

stat.ME↗

Evaluation on the Financial Competitiveness of Chinese Listed Real Estate Companies Based on Entropy Method

The real estate is a pillar industry of China's national economy. Due to changes in policy and market conditions, the real estate companies are facing greater pressures to survive in a competitive environment. They must improve their financial competitiveness. Based on the conceptual framework of financial competitiveness, this paper presented a financial competitiveness evaluation index system, covering four aspects, including profitability, solvency, sustainable development and operational capacity. Entropy value method is applied to determine the index weight. 105 listed real estate company's financial competitiveness are evaluated, the results show that: high-scoring company has strong profitability, sustainable development and operational capacity; low-scoring company has weak profitability and poor ability of sustainable development; solvency doesn't affect the company's financial competitiveness obviously.

q-fin.GN↗

High-Dimensional Sparse Additive Hazards Regression

High-dimensional sparse modeling with censored survival data is of great practical importance, as exemplified by modern applications in high-throughput genomic data analysis and credit risk analysis. In this article, we propose a class of regularization methods for simultaneous variable selection and estimation in the additive hazards model, by combining the nonconcave penalized likelihood approach and the pseudoscore method. In a high-dimensional setting where the dimensionality can grow fast, polynomially or nonpolynomially, with the sample size, we establish the weak oracle property and oracle property under mild, interpretable conditions, thus providing strong performance guarantees for the proposed methodology. Moreover, we show that the regularity conditions required by the $L_1$ method are substantially relaxed by a certain class of sparsity-inducing concave penalties. As a result, concave penalties such as the smoothly clipped absolute deviation (SCAD), minimax concave penalty (MCP), and smooth integration of counting and absolute deviation (SICA) can significantly improve on the $L_1$ method and yield sparser models with better prediction performance. We present a coordinate descent algorithm for efficient implementation and rigorously investigate its convergence properties. The practical utility and effectiveness of the proposed methods are demonstrated by simulation studies and a real data example.

stat.ME↗

A Dynamical Model Reveals Gene Co-Localizations in Nucleus

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency- or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes.

q-bio.MN↗

Bifurcations of Emergent Bursting in a Neuronal Network

Currently we routinely develop a complex neuronal network to explain observed but often paradoxical phenomena based upon biological recordings. Here we present a general approach to demonstrate how to mathematically tackle such a complex neuronal network so that we can fully understand the underlying mechanism. Using an oxytocin network developed earlier as an example, we show how we can reduce a complex model with many variables to a tractable model with two variables, while retaining all key qualitative features of the model. The approach enables us to uncover how emergent synchronous bursting could arise from a neuronal network which embodies all known biological features. Surprisingly, the discovered mechanisms for bursting are similar to those found in other systems reported in the literature, and illustrate a generic way to exhibit emergent and multi-time scale spikes: at the membrane potential level and the firing rate level.

q-bio.QM↗

A Novel VSWR-Protected and Controllable CMOS Class E Power Amplifier for Bluetooth Applications

This paper describes the design of a differential class-E PA for Bluetooth applications in 0.18um CMOS technology with load mismatch protection and power control features. The breakdown induced by load mismatch can be avoided by attenuating the RF power to the final stage during over voltage conditions. Power control is realized by means of "open loop" techniques to regulate the power supply voltage, and a novel controllable bias network with temperature compensated is proposed, which allows a moderate power control slope (dB/V) to be achieved. Post-layout Simulation results show that the level of output power can be controlled in 2dBm steps; especially the output power in every step is quite insensitive to temperature variations.

cs.OH↗

Measurements of Transit Timing Variations for WASP-5b

We have observed 7 new transits of the `hot Jupiter' WASP-5b using a 61 cm telescope located in New Zealand, in order to search for transit timing variations (TTVs) which can be induced by additional bodies existing in the system. When combined with other available photometric and radial velocity (RV) data, we find that its transit timings do not match a linear ephemeris; the best fit χ^2 values is 32.2 with 9 degrees of freedom which corresponds to a confidence level of 99.982 % or 3.7 σ. This result indicates that excess variations of transit timings has been observed, due either to unknown systematic effects or possibly to real TTVs. The TTV amplitude is as large as 50 s, and if this is real, it cannot be explained by other effects than that due to an additional body or bodies. From the RV data, we put an upper limit on the RV amplitude caused by the possible secondary body (planet) as 21 m s^{-1}, which corresponds to its mass of 22-70 M_{Earth} over the orbital period ratio of the two planets from 0.2 to 5.0. From the TTVs data, using the numerical simulations, we place more stringent limits down to 2 M_{Earth} near 1:2 and 2:1 mean motion resonances (MMRs) with WASP-5b at the 3 σlevel, assuming that the two planets are co-planer. We also put an upper limit on excess of Trojan mass as 43 M_{Earth} (3 σ) using both RV and photometric data. We also find that if the possible secondary planet has non- or a small eccentricity, its orbit would likely be near low-order MMRs. Further follow-up photometric and spectroscopic observations will be required to confirm the reality of the TTV signal, and results such as these will provide important information for the migration mechanisms of planetary systems.

astro-ph.EP↗

The Transmission Property of the Discrete Heisenberg Ferromagnetic Spin Chain

We present a mechanism for displaying the transmission property of the discrete Heisenberg ferromagnetic spin chain (DHF) via a geometric approach. By the aid of a discrete nonlinear Schrödinger-like equation which is the discrete gauge equivalent to the DHF, we show that the determination of transmitting coefficients in the transmission problem is always bistable. Thus a definite algorithm and general stochastic algorithms are presented. A new invariant periodic phenomenon of the non-transmitting behavior for the DHF, with a large probability, is revealed by an adoption of various stochastic algorithms.

nlin.CD↗

Failure of Parameter Identification Based on Adaptive Synchronization Techniques

In the paper, several concrete examples, as well as their numerical simulations, are given to show that parameter identification based on the so-called adaptive synchronization techniques might be failed if those functions with parameters pending for identification in coupled systems are designed to be mutually linearly dependent or approximately linearly dependent on the orbit in the synchronization manifold. This failure might be emergent not only when the synchronized orbit is selected to be some sort of equilibrium or some sort of periodic oscillation, but also when it is taken as some type of chaotic attractor produced by driving system. This result implies that chaotic property of driving signal is not necessary to achievement of parameter identification. The mechanism inducing such a failure, as well as the bounded property of all trajectories generated by coupled systems, is theoretically expatiated. New synchronization techniques are proposed to rigorously realize the complete synchronization and parameter identification in a class of systems where the nonlinearity is not globally Lipschitz. In addition, parameter identification are discussed for systems with time delay.

nlin.AO↗

Polarized networks, diameter, and synchronizability of networks

Previous research claimed or disclaimed the role of a small diameter in the synchronization of a network of coupled dynamical systems. We investigate this connection and show that it is two folds. We first construct two classes of networks, the polarized networks and the random networks with a fixed diameter, which exhibit very different synchronizability. This shows that the diameter itself is insufficient to determine the synchronizability of networks. Secondly, we derive analytic estimates on the synchronizability of networks in terms of the diameter, and find that a larger size of network admits of a more flexible synchronizability. The analysis is confirmed by numerical results.

cond-mat.dis-nn↗

The Very Low Energy Solar Flux of Electron and Heavy-Flavor Neutrinos and Antineutrinos

We calculate the thermal flux of low-energy solar neutrinos and antineutrinos of all flavors arising from a variety of neutrino pair processes: Compton production (including plasmon-pole diagrams), neutral current decay of thermally populated nuclear states, plasmon decay, and electron transitions from free to atomic bound states. The resulting flux density per flavor is significant (10E8-10E9/cm2/sec/MeV) below about 5 keV, and the distributions fill much of the valley between the high-energy edge of the cosmic background neutrino spectrum and the low energy tails of the pp-chain electron neutrino and terrestrial electron antineutrino spectra. Thermal neutrinos carry information on the solar core temperature distribution and on heavy flavor masses in the range of 1 keV. The detection of these neutrinos is a daunting but interesting challenge.

nucl-th↗