Search results for "density [dark matter]"

Explaining the Formation Rates of Post-Communist Interest Organizations: Density Dependence and Political Opportunity Structure

2020

This article presents an analysis of the formation of organized interest groups in the post-communist context and organizational populations over time. We test two theories that shed doubt on whether vital rates of interest groups are explained by individual incentives, namely, the political opportunity structure and population ecology theory. Based on an analysis of the energy policy and higher education policy organizations active at the national level in Hungary, Poland, and Slovenia, we find that while the period of democratic and economic transition indeed opened up the opportunity structure for organizational formations, it by no means presented a clean slate. Communist-era successor…

Electronic Properties, Band Structure, and Fermi Surface Instabilities ofNi1+/Ni2+NickelateLa3Ni2O6, Isoelectronic with Superconducting Cuprates

2009

Electronic structure calculations were performed for the mixed-valent Ni(1+)/Ni(2+) nickelate La3Ni2O6, which exhibits electronic instabilities of the Fermi surface similar to that of the isostructural superconducting La2CaCu2O6 cuprate. La3Ni2O6 shows activated hopping, which fits to Mott's variable-range-hopping model with localized states near the Fermi level. However, a simple local spin density approximation calculation leads to a metallic ground state. The calculations including local density approximation+Hubbard U and hybrid functionals indicate a multiply degenerate magnetic ground state. For electron-doped La2ZrNi2O6, which is isoelectronic with La2CaCu2O6, an antiferromagnetic in…

Applications of Kernel Methods

2009

In this chapter, we give a survey of applications of the kernel methods introduced in the previous chapter. We focus on different application domains that are particularly active in both direct application of well-known kernel methods, and in new algorithmic developments suited to a particular problem. In particular, we consider the following application fields: biomedical engineering (comprising both biological signal processing and bioinformatics), communications, signal, speech and image processing.

Learning non-linear time-scales with kernel -filters

2009

A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…

Annihilators of tensor density modules

2007

Abstract We describe the two-sided ideals in the universal enveloping algebras of the Lie algebras of vector fields on the line and the circle which annihilate the tensor density modules. Both of these Lie algebras contain the projective subalgebra, a copy of sl 2 . The restrictions of the tensor density modules to this subalgebra are duals of Verma modules (of sl 2 ) for Vec ( R ) and principal series modules (of sl 2 ) for Vec ( S 1 ) . Thus our results are related to the well-known theorem of Duflo describing the annihilating ideals of Verma modules of reductive Lie algebras. We find that, in general, the annihilator of a tensor density module of Vec ( R ) or Vec ( S 1 ) is generated by …

Event generation and statistical sampling for physics with deep generative models and a density information buffer

2021

Simulating nature and in particular processes in particle physics require expensive computations and sometimes would take much longer than scientists can afford. Here, we explore ways to a solution for this problem by investigating recent advances in generative modeling and present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but to also ensure that these events occur with the correct frequencies. We investigate the feasibility of learning the event generation and the frequency of occurrence with several generative machine learning models to produce events l…

Parametrizations of density matrices

2011

This article gives a brief overview of some recent progress in the characterization and parametrization of density matrices of finite dimensional systems. We discuss in some detail the Bloch-vector and Jarlskog parametrizations and mention briefly the coset parametrization. As applications of the Bloch parametrization we discuss the trace invariants for the case of time dependent Hamiltonians and in some detail the dynamics of three-level systems. Furthermore, the Bloch vector of two-qubit systems as well as the use of the polarization operator basis is indicated. As the main application of the Jarlskog parametrization we construct density matrices for composite systems. In addition, some r…

Proportional Small Sample Bias in Pricing Kernel Estimations

2014

Numerous empirical studies find pricing kernels that are not-monotonically decreasing; the findings are at odds with the pricing kernel being marginal utility of a risk-averse, so-called representative agent. We study in detail the common procedure which estimates the pricing kernel as the ratio of two separate density estimations. In a first step, we analyze theoretically the functional dependence for the ratio of a density to its estimated density; this cautions the reader of potential computational issues coupled with statistical techniques. In a second step, we study this quantitatively; we show that small sample biases shape the estimated pricing kernel, and that estimated pricing kern…

Traffic fundamentals for A22 Brenner freeway by microsimulation models.

La tesi di dottorato ha avuto come tema lo studio e l’applicazione di un modello di micro-simulazione del traffico in ambito autostradale. Essa si compone di quattro capitoli, con ognuno dei quali si è voluto sintetizzare e descrivere il lavoro di studio e ricerca svolto durante il suddetto corso di Dottorato di Ricerca. L’obiettivo principale del presente lavoro di tesi è stato quello di mettere a punto una metodologia finalizzata all’ottenimento delle relazioni fondamentali di deflusso in ambito autostradale attraverso il software di microsimulazione del traffico Aimsun. Come risulta infatti noto dalla letteratura scientifica, le relazioni fondamentali del deflusso sono utilizzate nel cam…

Stark ionization of atoms and molecules within density functional resonance theory

2013

We show that the energetics and lifetimes of resonances of finite systems under an external electric field can be captured by Kohn–Sham density functional theory (DFT) within the formalism of uniform complex scaling. Properties of resonances are calculated self-consistently in terms of complex densities, potentials, and wave functions using adapted versions of the known algorithms from DFT. We illustrate this new formalism by calculating ionization rates using the complex-scaled local density approximation and exact exchange. We consider a variety of atoms (H, He, Li, and Be) as well as the H2 molecule. Extensions are briefly discussed.