39,750 research outputs found
Hierarchical Structure Formation and Chemical Evolution of Damped Ly alpha Systems
We present a model for chemical evolution of damped Ly alpha systems
considering production of metals by SNe II and infall associated with
hierarchical structure formation. The growth of metallicity in these systems is
a reflection of the competition between astration and infall. The apparent late
turn-on of these systems is due to the late cut-off of infall. The wide range
in [Fe/H] at a given redshift is explained by the range of the times for onset
of star formation and the range of the times for infall cessation in different
systems. The observed lower bound of [Fe/H] = -3 follows from the very rapid
initial rise of [Fe/H] subsequent to onset of star formation. To reach [Fe/H] =
-3 from a metal-free initial state requires only about 30 Myr so that the
probability of observing lower [Fe/H] values is very small.Comment: 4 pages, 2 figures, to appear in ApJ
A Functional Approach to FBSDEs and Its Application in Optimal Portfolios
In Liang et al (2009), the current authors demonstrated that BSDEs can be
reformulated as functional differential equations, and as an application, they
solved BSDEs on general filtered probability spaces. In this paper the authors
continue the study of functional differential equations and demonstrate how
such approach can be used to solve FBSDEs. By this approach the equations can
be solved in one direction altogether rather than in a forward and backward
way. The solutions of FBSDEs are then employed to construct the weak solutions
to a class of BSDE systems (not necessarily scalar) with quadratic growth, by a
nonlinear version of Girsanov's transformation. As the solving procedure is
constructive, the authors not only obtain the existence and uniqueness theorem,
but also really work out the solutions to such class of BSDE systems with
quadratic growth. Finally an optimal portfolio problem in incomplete markets is
solved based on the functional differential equation approach and the nonlinear
Girsanov's transformation.Comment: 26 page
Knowledge Refinement via Rule Selection
In several different applications, including data transformation and entity
resolution, rules are used to capture aspects of knowledge about the
application at hand. Often, a large set of such rules is generated
automatically or semi-automatically, and the challenge is to refine the
encapsulated knowledge by selecting a subset of rules based on the expected
operational behavior of the rules on available data. In this paper, we carry
out a systematic complexity-theoretic investigation of the following rule
selection problem: given a set of rules specified by Horn formulas, and a pair
of an input database and an output database, find a subset of the rules that
minimizes the total error, that is, the number of false positive and false
negative errors arising from the selected rules. We first establish
computational hardness results for the decision problems underlying this
minimization problem, as well as upper and lower bounds for its
approximability. We then investigate a bi-objective optimization version of the
rule selection problem in which both the total error and the size of the
selected rules are taken into account. We show that testing for membership in
the Pareto front of this bi-objective optimization problem is DP-complete.
Finally, we show that a similar DP-completeness result holds for a bi-level
optimization version of the rule selection problem, where one minimizes first
the total error and then the size
A Test of the Balassa-Samuelson Effect Applied to Chinese Regional Data
In this paper, we investigate the relevance of the Balassa-Samuelson effect to the determination of regional inflation in China, for the period 1985 – 2000. To do this, we first construct annual measures of Chinese inflation and industry input on regional and sectoral basis. Then we generalise the Asea and Mendoza (1994) settings to consider asymmetric productivity shocks across sectors. Testing this model on Chinese Regional Data aid of non-stationary panel data techniques, it shows that our extended theoretical model is a good empirical representation of the Chinese data that supports the Balassa-Samuelson effect. Moreover, we are able to test the Asea and Mendoza (1994) version of our general model and find that the restrictions are rejected.Balassa-Samuelson effect, productivity shocks, panel data
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