Heavy quarkonia from classical SU(3) Yang-Mills configurations

A generalized Cho-Faddeev-Niemi ansatz for SU(3) Yang-Mills is investigated. The corresponding classical field equations are solved for its simplest parametrization. From these solutions it is possible to define a confining non-relativistic central potential used to study heavy quarkonia. The associated spectra reproduces the experimental spectra with an error of less than 3% for charmonium and 1% for bottomonium. Moreover, the recently discovered new charmonium states can be accomodate in the spectra, keeping the same level of precision. The leptonic widths show good agreement with the recent measurements. The charmonium and bottomonium E1 electromagnetic transitions widths are computed and compared with the experimental values.     

基于选择性填充的超高非线性纳米纤芯光纤特性

为了改善纳米纤芯光纤的非线性与色散特性,提出利用气孔填充非线性液体的新型纳米纤芯光纤结构来增强现有纳米纤芯光纤的非线性系数,利用选择性填充方法来改进现有纳米纤芯光纤的特性调控能力,实现改善光纤非线性和色散特性目的.分析结果表明采用选择性气孔填充方式和适当的光纤参量有助于实现光纤单模单偏振工作,可以大幅度地提升纳米纤芯光纤的非线性系数和改善光纤色散特性.     

Marginal filtering in large state spaces

Recognising everyday activities including information about the context requires to handle large state spaces. The usage of wearable sensors like six degree of freedom accelerometers increases complexity even more. Common approaches are unable to maintain an accurate belief state within such complex domains. We show how marginal filtering can overcome limitations of standard particle filtering and efficiently infer the context of actions. Symbolic models of human behaviour are used to recognise activities in two different settings with different state space sizes. Based on these scenarios we compare the marginal filter to the standard particle filter. An evaluation shows that the marginal filter performs comparably in small state spaces but outperforms the particle filter in large state spaces.     

Enhancing Tris(pyrazolyl)borate-Based Models of Cysteine/Cysteamine Dioxygenases through Steric Effects: Increased Reactivities,Full Product Characterization and Hints to Initial Superoxide Formation

The design of biomimetic model complexes for the cysteine dioxygenase (CDO) and cysteamine dioxygenase (ADO) is reported, where the 3-His coordination of the iron ion is simulated by three pyrazole donors of a trispyrazolyl borate ligand (Tp) and protected cysteine and cysteamine represent substrate ligands. It is found that the replacement of phenyl groups—attached at the 3-positions of the pyrazole units in a previous model—by mesityl residues has massive consequences, as the latter arrange to a more spacious reaction pocket. Thus, the reaction with O₂ proceeds much faster and afterwards the first structural characterization of an iron(II) η²-O,O-sulfinate product became possible. If one of the three Tp-mesityl groups is placed in the 5-position, an even larger reaction pocket results, which leads to yet faster rates and accumulation of a reaction intermediate at low temperatures, as shown by UV/Vis and Mössbauer spectroscopy. After comparison with the results of investigations on the cobalt analogues this intermediate is tentatively assigned to an iron(III) superoxide species.     

A Predictive Model Towards Site‐Selective Metalations of Functionalized Heterocycles,Arenes, Olefins,and Alkanes using TMPZnCl⋅LiCl

The development of a predictive model towards site‐selective deprotometalation reactions using TMPZnCl?LiCl is reported (TMP=2,2,6,6‐tetramethylpiperidinyl). The pK_a values of functionalized N‐, S‐, and O‐heterocycles, arenes, alkenes, or alkanes were calculated and compared to the experimental deprotonation sites. Large overlap (>80 %) between the calculated and empirical deprotonation sites was observed, showing that thermodynamic factors strongly govern the metalation regioselectivity. In the case of olefins, calculated frozen state energies of the deprotonated substrates allowed a more accurate prediction. Additionally, various new N‐heterocycles were analyzed and the metalation regioselectivities rationalized using the predictive model.     

通过Painlevé分析从低维模型中寻找高维可积模型

将Painlevé方法推广到更一般的形式, 可以从给定的低维可积模型中得到无穷多个新的可积模型. 新的可积模型与原模型相比都是较高维的, 它们保持保角不变性和Painlevé性质. 本文主要以KdV、NLS和KP方程为例, 运用WTC法、截断展开、领头项分析等方法, 给出了(3+1)维可积模型的具体形式.     

Determination of structure parameters in strong-field ionization models of atoms

The Ammosov–Delone–Krainov (ADK) and Perelomov–Popov–Terent’ev (PPT) ionization models were widely used in strong-field physics and attosecond science due to their many attractive advantages such as simpler analytical formula, less computational demands, and satisfied accuracy of ionization rate. Based on the density-functional theory, we systematically determine accurate structure parameters of 25 atoms, 24 positive ions and 13 negative ions and tabulate for future applications. The wave function with correct asymptotic behavior is obtained by solving the time-independent Schrödinger equation with B-spline basis sets and the accurate structure parameters are extracted from this wave function in the asymptotic region. The accuracies of structure parameters are carefully examined by comparing the ionization probabilities (or yields) calculated by PPT and ADK models with those of solving the three-dimensional time-dependent Schrödinger equation and the experimental data.     

Information Network Modeling for U.S. Banking Systemic Risk

In this work we investigate whether information theory measures like mutual information and transfer entropy, extracted from a bank network, Granger cause financial stress indexes like LIBOR-OIS (London Interbank Offered Rate-Overnight Index Swap) spread, STLFSI (St. Louis Fed Financial Stress Index) and USD/CHF (USA Dollar/Swiss Franc) exchange rate. The information theory measures are extracted from a Gaussian Graphical Model constructed from daily stock time series of the top 74 listed US banks. The graphical model is calculated with a recently developed algorithm (LoGo) which provides very fast inference model that allows us to update the graphical model each market day. We therefore can generate daily time series of mutual information and transfer entropy for each bank of the network. The Granger causality between the bank related measures and the financial stress indexes is investigated with both standard Granger-causality and Partial Granger-causality conditioned on control measures representative of the general economy conditions.     

Network Bending: Expressive Manipulation of Generative Models in Multiple Domains

This paper presents the network bending framework, a new approach for manipulating and interacting with deep generative models. We present a comprehensive set of deterministic transformations that can be inserted as distinct layers into the computational graph of a trained generative neural network and applied during inference. In addition, we present a novel algorithm for analysing the deep generative model and clustering features based on their spatial activation maps. This allows features to be grouped together based on spatial similarity in an unsupervised fashion. This results in the meaningful manipulation of sets of features that correspond to the generation of a broad array of semantically significant features of the generated results. We outline this framework, demonstrating our results on deep generative models for both image and audio domains. We show how it allows for the direct manipulation of semantically meaningful aspects of the generative process as well as allowing for a broad range of expressive outcomes.