46,677 research outputs found
Continuous-time statistics and generalized relaxation equations
Using two simple examples, the continuous-time random walk as well as a two
state Markov chain, the relation between generalized anomalous relaxation
equations and semi-Markov processes is illustrated. This relation is then used
to discuss continuous-time random statistics in a general setting, for
statistics of convolution-type. Two examples are presented in some detail: the
sum statistic and the maximum statistic.Comment: 12 pages, submitted to EPJ
Continuous-time statistics and generalized relaxation equations
Using two simple examples, the continuous-time random walk as well as a two state Markov chain, the relation between generalized anomalous relaxation equations and semi-Markov processes is illustrated. This relation is then used to discuss continuous-time random statistics in a general setting, for statistics of convolution-type. Two examples are presented in some detail: the sum statistic and the maximum statistic
Quartic Graphs with Minimum Spectral Gap
Aldous and Fill conjectured that the maximum relaxation time for the random
walk on a connected regular graph with vertices is . This conjecture can be rephrased in terms of the spectral
gap as follows: the spectral gap (algebraic connectivity) of a connected
-regular graph on vertices is at least ,
and the bound is attained for at least one value of . We determine the
structure of connected quartic graphs on vertices with minimum spectral gap
which enable us to show that the minimum spectral gap of connected quartic
graph on vertices is . From this result, the
Aldous--Fill conjecture follows for .Comment: 28 pages. arXiv admin note: text overlap with arXiv:1907.0373
A Nanoflare Distribution Generated by Repeated Relaxations Triggered by Kink Instability
Context: It is thought likely that vast numbers of nanoflares are responsible
for the corona having a temperature of millions of degrees. Current
observational technologies lack the resolving power to confirm the nanoflare
hypothesis. An alternative approach is to construct a magnetohydrodynamic
coronal loop model that has the ability to predict nanoflare energy
distributions.
Aims: This paper presents the initial results generated by such a model. It
predicts heating events with a range of sizes, depending on where the
instability threshold for linear kink modes is encountered. The aims are to
calculate the distribution of event energies and to investigate whether kink
instability can be predicted from a single parameter.
Methods: The loop is represented as a straight line-tied cylinder. The
twisting caused by random photospheric motions is captured by two parameters,
representing the ratio of current density to field strength for specific
regions of the loop. Dissipation of the loop's magnetic energy begins during
the nonlinear stage of the instability, which develops as a consequence of
current sheet reconnection. After flaring, the loop evolves to the state of
lowest energy where, in accordance with relaxation theory, the ratio of current
to field is constant throughout the loop and helicity is conserved.
Results: The results suggest that instability cannot be predicted by any
simple twist-derived property reaching a critical value. The model is applied
such that the loop undergoes repeated episodes of instability followed by
energy-releasing relaxation. Hence, an energy distribution of the nanoflares
produced is collated.
Conclusions: The final energy distribution features two nanoflare populations
that follow different power laws. The power law index for the higher energy
population is more than sufficient for coronal heating.Comment: 13 pages, 18 figure
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