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L. Santana

Publications and source records attributed to L. Santana.

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Stochastic Optical Variability and an rms-flux Relation in the Intermediate Polar EP240309a

Magnetic cataclysmic variables provide a natural laboratory for studying how accretion interacts with compact-object magnetospheres and generates stochastic variability. We present an optical variability study of the intermediate-polar candidate EP240309a, an Einstein Probe X-ray transient, using BOOTES photometry, high-cadence TESS light curves, and a SOAR/Goodman optical spectrum. Previous studies found a white-dwarf spin period of 3.97 min (Pspin ~ 238 s) and an orbital period of Porb = 3.7614(4) h. Power spectral densities from the BOOTES data are consistent with single power laws with slopes alpha ~ 1.2-1.8, with no statistically significant evidence for a bend across the sampled frequency range. Using red-noise simulations and injection-recovery tests, we place one-sided constraints on any putative break frequency, which translate, under standard dynamical identifications, into an upper limit on the magnetospheric radius of Rm <= few x 10^10 cm for MWD = 0.8 Msun. In the TESS data, we detect a linear rms-flux relation on hour timescales in three high-cadence sectors, while two other sectors do not show a robust detection, indicating epoch-dependent rms-flux behavior. The SOAR spectrum shows Balmer and He II emission lines with FWHM about 1000-1600 km s^-1; under a Keplerian interpretation, these imply characteristic radii of r about (0.9-3.4) x 10^10 cm, broadly comparable to the timing-based constraints. Overall, the data provide conservative, order-of-magnitude radius constraints consistent with accretion onto a magnetic white dwarf, but they do not establish the detailed accretion geometry or exclude stream-fed or mixed accretion scenarios.

astro-ph.SR

Testing for the Pareto type I distribution: A comparative study

Pareto distributions are widely used models in economics, finance and actuarial sciences. As a result, a number of goodness-of-fit tests have been proposed for these distributions in the literature. We provide an overview of the existing tests for the Pareto distribution, focussing specifically on the Pareto type I distribution. To date, only a single overview paper on goodness-of-fit testing for Pareto distributions has been published. However, the mentioned paper has a much wider scope than is the case for the current paper as it covers multiple types of Pareto distributions. The current paper differs in a number of respects. First, the narrower focus on the Pareto type I distribution allows a larger number of tests to be included. Second, the current paper is concerned with composite hypotheses compared to the simple hypotheses (specifying the parameters of the Pareto distribution in question) considered in the mentioned overview. Third, the sample sizes considered in the two papers differ substantially. In addition, we consider two different methods of fitting the Pareto Type I distribution; the method of maximum likelihood and a method closely related to moment matching. It is demonstrated that the method of estimation has a profound effect, not only on the powers achieved by the various tests, but also on the way in which numerical critical values are calculated. We show that, when using maximum likelihood, the resulting critical values are shape invariant and can be obtained using a Monte Carlo procedure. This is not the case when moment matching is employed. The paper includes an extensive Monte Carlo power study. Based on the results obtained, we recommend the use of a test based on the phi divergence together with maximum likelihood estimation.

stat.ME