25,131 research outputs found
Decoupling structure of the principal sigma model-Maxwell interactions
The principal sigma model and Abelian gauge fields coupling is studied. By
expressing the first-order formulation of the gauge field equations an implicit
on-shell scalar-gauge field decoupling structure is revealed. It is also shown
that due to this decoupling structure the scalars of the theory belong to the
pure sigma model and the gauge fields sector consists of a number of coupled
Maxwell theories with currents partially induced by the scalars.Comment: 13 page
Non-linear Realisation of the N=2, D=6 Supergravity
We have applied the method of dualisation to construct the coset realisation
of the bosonic sector of the N=2, D=6 supergravity which is coupled to a tensor
multiplet. The bosonic field equations are regained through the Cartan-Maurer
equation which the Cartan form satisfies. The first-order formulation of the
theory is also obtained as a twisted self-duality condition within the
non-linear coset construction.Comment: 11 page
Algebraic Integration of Sigma Model Field Equations
We prove that the dualization algebra of the symmetric space coset sigma
model is a Lie algebra and we show that it generates an appropriate adjoint
representation which enables the local integration of the field equations
yielding the first-order ones.Comment: 27p
Symmetric Space Sigma-model Dynamics: Internal Metric Formalism
For the symmetric space sigma model in the internal metric formalism we
explicitly construct the lagrangian in terms of the axions and the dilatons of
the solvable Lie algebra gauge and then we exactly derive the axion-dilaton
field equations.Comment: 10 page
Using hardware performance counters for fault localization
In this work, we leverage hardware performance counters-collected data as abstraction mechanisms for program executions and use these abstractions to identify likely causes of failures. Our approach can be summarized as follows: Hardware counters-based data is collected from both successful and failed executions, the data collected from the successful executions is used to create normal behavior models of programs, and deviations from these models observed in failed executions are scored and reported as likely causes of failures. The results of our experiments conducted on three open source projects suggest that the proposed approach can effectively prioritize the space of likely causes of failures, which can in turn improve the turn around time for defect fixes
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