16,341 research outputs found
Convergence of symmetric diffusions on Wiener spaces
We prove convergence of symmetric diffusions on Wiener spaces by using
stopping times arguments and capacity techniques. The drifts of the diffusions
can be singular, we require the densities of the processes to be neither
bounded from above nor away from zero
Market ecology of active and passive investors
We study the role of active and passive investors in an investment market
with uncertainties. Active investors concentrate on a single or a few stocks
with a given probability of determining the quality of them. Passive investors
spread their investment uniformly, resembling buying the market index. In this
toy market stocks are introduced as good and bad. If a stock receives
sufficient investment it will survive, otherwise die. Active players exert a
selective pressure since they can determine to an extent the investment
quality. We show that the active players provide the driving force whereas the
passive ones act as free riders. While their gains do not differ too much, we
show that the active players enjoy an edge. Their presence also provides better
gains to the passive players and stocks themselves.Comment: 16 pages, 4 figure
What do we know about carbon taxes? an inquiry into their impacts on competitiveness and distribution of income
The Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC) has set legally binding emissions targets for a basket of six greenhouse gases and timetables for industrialised countries. It has also incorporated three international flexibility mechanisms. However, the Articles defining the flexibility mechanisms carry wording that their use must be supplemental to domestic actions. This has led to the open debates on interpretations of these supplementarity provisions. Such debates ended at the resumed sixth Conference of the Parties (COP) to the UNFCCC, held in Bonn, July 2001, and at the subsequent COP-7 in Marrakesh, November 2001. The final wording in the Bonn Agreement, reaffirmed in the Marrakesh Accords, at least indicates that domestic policies will have an important role to play in meeting Annex B countries’ emissions commitments. Carbon taxes have long been advocated because of their cost-effectiveness in achieving a given emissions reduction. In this paper, the main economic impacts of carbon taxes are assessed. Based on a review of empirical studies on existing carbon/energy taxes, it is concluded that competitive losses and distributive impacts are generally not significant and definitely less than often perceived. However, given the ultimate objective of the Framework Convention, future carbon taxes could have higher rates than those already imposed and thus the resulting economic impacts could be more acute. In this context, it has been shown that how to use the generated fiscal revenues will be of fundamental importance in determining the final economic impacts of carbon taxes. Finally, we briefly discuss carbon taxes in combination with other domestic and international instruments.Border tax adjustments; carbon taxes; distribution of income; double dividend; emissions trading; energy taxes; international competitiveness
New BPS Wilson loops in circular quiver Chern-Simons-matter theories
We construct new families of 1/4 BPS Wilson loops in circular quiver
superconformal Chern-Simons-matter (SCSM) theories in three
dimensions. They are defined as the holonomy of superconnections that contain
non-trivial couplings to scalar and fermions, and cannot be reduced to
block-diagonal matrices. Consequently, the new operators cannot be written in
terms of double-node Wilson loops, as the ones considered so far in the
literature. For particular values of the couplings the superconnection becomes
block-diagonal and we recover the known fermionic 1/4 and 1/2 BPS Wilson loops.
The new operators are cohomologically equivalent to bosonic 1/4 BPS Wilson
loops and are then amenable of exact evaluation via localization techniques.
Moreover, in the case of orbifold ABJM theory we identify the corresponding
gravity duals for some of the 1/4 and 1/2 BPS Wilson loops.Comment: 32 pages; v2: minor improvements, general classification of BPS WLs
added; v3: comments added, typos fixed, JHEP published versio
Deep Learning for Real Time Crime Forecasting
Accurate real time crime prediction is a fundamental issue for public safety,
but remains a challenging problem for the scientific community. Crime
occurrences depend on many complex factors. Compared to many predictable
events, crime is sparse. At different spatio-temporal scales, crime
distributions display dramatically different patterns. These distributions are
of very low regularity in both space and time. In this work, we adapt the
state-of-the-art deep learning spatio-temporal predictor, ST-ResNet [Zhang et
al, AAAI, 2017], to collectively predict crime distribution over the Los
Angeles area. Our models are two staged. First, we preprocess the raw crime
data. This includes regularization in both space and time to enhance
predictable signals. Second, we adapt hierarchical structures of residual
convolutional units to train multi-factor crime prediction models. Experiments
over a half year period in Los Angeles reveal highly accurate predictive power
of our models.Comment: 4 pages, 6 figures, NOLTA, 201
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