2,935 research outputs found
How to Determine whether Regional Markets are Integrated? Theory and Evidence from European Electricity Markets
Prices may di er between regional markets if transport capacities are limited. We develop a new approach to determine to which extent such di erences stem from limited participation in cross-border trader rather than from bottlenecks. We derive a theoretical integration benchmark for the typical case where transportation markets clear before the product markets, using Grossman's (1976) notion of a rational expectations equilibrium. We compare the benchmark to data from European electricity markets. The data reject the integration hypothesis: Capacity prices contain too little information about spot price di erential; this indicates that well informed traders do not engage in cross-border trade
From Frazier-Jawerth characterizations of Besov spaces to Wavelets and Decomposition spaces
This article describes how the ideas promoted by the fundamental papers
published by M. Frazier and B. Jawerth in the eighties have influenced
subsequent developments related to the theory of atomic decompositions and
Banach frames for function spaces such as the modulation spaces and
Besov-Triebel-Lizorkin spaces.
Both of these classes of spaces arise as special cases of two different,
general constructions of function spaces: coorbit spaces and decomposition
spaces. Coorbit spaces are defined by imposing certain decay conditions on the
so-called voice transform of the function/distribution under consideration. As
a concrete example, one might think of the wavelet transform, leading to the
theory of Besov-Triebel-Lizorkin spaces.
Decomposition spaces, on the other hand, are defined using certain
decompositions in the Fourier domain. For Besov-Triebel-Lizorkin spaces, one
uses a dyadic decomposition, while a uniform decomposition yields modulation
spaces.
Only recently, the second author has established a fruitful connection
between modern variants of wavelet theory with respect to general dilation
groups (which can be treated in the context of coorbit theory) and a particular
family of decomposition spaces. In this way, optimal inclusion results and
invariance properties for a variety of smoothness spaces can be established. We
will present an outline of these connections and comment on the basic results
arising in this context
How to Determine whether Regional Markets are Integrated? Theory and Evidence from European Electricity Markets
Prices may di er between regional markets if transport capacities are limited. We develop a new approach to determine to which extent such di erences stem from limited participation in cross-border trader rather than from bottlenecks. We derive a theoretical integration benchmark for the typical case where transportation markets clear before the product markets, using Grossman's (1976) notion of a rational expectations equilibrium. We compare the benchmark to data from European electricity markets. The data reject the integration hypothesis: Capacity prices contain too little information about spot price di erential; this indicates that well informed traders do not engage in cross-border trade.Market integration; electricity markets; interconnector;competition policy; rational expectations equilibrium
Consistent Probabilistic Social Choice
Two fundamental axioms in social choice theory are consistency with respect
to a variable electorate and consistency with respect to components of similar
alternatives. In the context of traditional non-probabilistic social choice,
these axioms are incompatible with each other. We show that in the context of
probabilistic social choice, these axioms uniquely characterize a function
proposed by Fishburn (Rev. Econ. Stud., 51(4), 683--692, 1984). Fishburn's
function returns so-called maximal lotteries, i.e., lotteries that correspond
to optimal mixed strategies of the underlying plurality game. Maximal lotteries
are guaranteed to exist due to von Neumann's Minimax Theorem, are almost always
unique, and can be efficiently computed using linear programming
Analytic Performance Modeling and Analysis of Detailed Neuron Simulations
Big science initiatives are trying to reconstruct and model the brain by
attempting to simulate brain tissue at larger scales and with increasingly more
biological detail than previously thought possible. The exponential growth of
parallel computer performance has been supporting these developments, and at
the same time maintainers of neuroscientific simulation code have strived to
optimally and efficiently exploit new hardware features. Current state of the
art software for the simulation of biological networks has so far been
developed using performance engineering practices, but a thorough analysis and
modeling of the computational and performance characteristics, especially in
the case of morphologically detailed neuron simulations, is lacking. Other
computational sciences have successfully used analytic performance engineering
and modeling methods to gain insight on the computational properties of
simulation kernels, aid developers in performance optimizations and eventually
drive co-design efforts, but to our knowledge a model-based performance
analysis of neuron simulations has not yet been conducted.
We present a detailed study of the shared-memory performance of
morphologically detailed neuron simulations based on the Execution-Cache-Memory
(ECM) performance model. We demonstrate that this model can deliver accurate
predictions of the runtime of almost all the kernels that constitute the neuron
models under investigation. The gained insight is used to identify the main
governing mechanisms underlying performance bottlenecks in the simulation. The
implications of this analysis on the optimization of neural simulation software
and eventually co-design of future hardware architectures are discussed. In
this sense, our work represents a valuable conceptual and quantitative
contribution to understanding the performance properties of biological networks
simulations.Comment: 18 pages, 6 figures, 15 table
Screened exchange corrections to the random phase approximation from many-body perturbation theory
The random phase approximation (RPA) systematically overestimates the
magnitude of the correlation energy and generally underestimates cohesive
energies. This originates in part from the complete lack of exchange terms,
which would otherwise cancel Pauli exclusion principle violating (EPV)
contributions. The uncanceled EPV contributions also manifest themselves in
form of an unphysical negative pair density of spin-parallel electrons close to
electron-electron coalescence.
We follow considerations of many-body perturbation theory to propose an
exchange correction that corrects the largest set of EPV contributions while
having the lowest possible computational complexity. The proposed method
exchanges adjacent particle/hole pairs in the RPA diagrams, considerably
improving the pair density of spin-parallel electrons close to coalescence in
the uniform electron gas (UEG). The accuracy of the correlation energy is
comparable to other variants of Second Order Screened Exchange (SOSEX)
corrections although it is slightly more accurate for the spin-polarized UEG.
Its computational complexity scales as or
in orbital space or real space, respectively. Its memory requirement scales as
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