Solving the kilo-second QPO problem of the intermediate polar GK Persei

We detect the likely optical counterpart to previously reported X-ray QPOs in spectrophotometry of the intermediate polar GK Persei during the 1996 dwarf nova outburst. The characteristic timescales range between 4000--6000 s. Although the QPOs are an order of magnitude longer than those detected in the other dwarf novae we show that a new QPO model is not required to explain the long timescale observed. We demonstrate that the observations are consistent with oscillations being the result of normal-timescale QPOs beating with the spin period of the white dwarf. We determine the spectral class of the companion to be consistent with its quiescent classification and find no significant evidence for irradiation over its inner face. We detect the white dwarf spin period in line fluxes, V/R ratios and Doppler-broadened emission profiles.Comment: 14 pages, 11 figures. Accepted for publication in MNRA

Demystifying Kepler Data: A Primer for Systematic Artifact Mitigation

The Kepler spacecraft has collected data of high photometric precision and cadence almost continuously since operations began on 2009 May 2. Primarily designed to detect planetary transits and asteroseismological signals from solar-like stars, Kepler has provided high quality data for many areas of investigation. Unconditioned simple aperture time-series photometry are however affected by systematic structure. Examples of these systematics are differential velocity aberration, thermal gradients across the spacecraft, and pointing variations. While exhibiting some impact on Kepler's primary science, these systematics can critically handicap potentially ground-breaking scientific gains in other astrophysical areas, especially over long timescales greater than 10 days. As the data archive grows to provide light curves for $10^5$ stars of many years in length, Kepler will only fulfill its broad potential for stellar astrophysics if these systematics are understood and mitigated. Post-launch developments in the Kepler archive, data reduction pipeline and open source data analysis software have occurred to remove or reduce systematic artifacts. This paper provides a conceptual primer for users of the Kepler data archive to understand and recognize systematic artifacts within light curves and some methods for their removal. Specific examples of artifact mitigation are provided using data available within the archive. Through the methods defined here, the Kepler community will find a road map to maximizing the quality and employment of the Kepler legacy archive.Comment: Accepted to PASP, 27 pages, 21 figure

Arkansas Soybean Performance Tests 2012

Soybean variety and strain performance tests are conducted each year in Arkansas by the University of Arkansas System Division of Agriculture Arkansas Crop Variety Improvement Program. The tests provide information to companies developing varieties and/or marketing seed within the state, and aid the Arkansas Cooperative Extension Service in formulating variety recommendations for soybean producers

Mapping quasi-periodic oscillations from the outbursting intermediate polar GK Persei

We present time-resolved spectrophotometry of GK Per taken on the rise to outburst maximum, in which we detect 5000 s QPOs in the optical emission lines. We use this opportunity to provide a kinematically-resolved analysis of the phenomenon. Observations are consistent with reprocessing off blobs of gas orbiting within the inner accretion disc, and evidence is found for the migration of the QPO source towards the compact star over orbital timescales.Comment: 4 pages, uuencoded postscript (194kb), MNRAS in press, also available at http://star-www.st-and.ac.uk/~mds1/gkper-abs.htm

Imaging starspot evolution on Kepler target KIC 5110407 using light curve inversion

The Kepler target KIC 5110407, a K-type star, shows strong quasi-periodic light curve fluctuations likely arising from the formation and decay of spots on the stellar surface rotating with a period of 3.4693 days. Using an established light-curve inversion algorithm, we study the evolution of the surface features based on Kepler space telescope light curves over a period of two years (with a gap of .25 years). At virtually all epochs, we detect at least one large spot group on the surface causing a 1-10% flux modulation in the Kepler passband. By identifying and tracking spot groups over a range of inferred latitudes, we measured the surface differential rotation to be much smaller than that found for the Sun. We also searched for a correlation between the seventeen stellar flares that occurred during our observations and the orientation of the dominant surface spot at the time of each flare. No statistically-significant correlation was found except perhaps for the very brightest flares, suggesting most flares are associated with regions devoid of spots or spots too small to be clearly discerned using our reconstruction technique. While we may see hints of long-term changes in the spot characteristics and flare statistics within our current dataset, a longer baseline of observation will be needed to detect the existence of a magnetic cycle in KIC 5110407.Comment: 32 pages, 15 figures, accepted to Ap

Information theoretic approach to interactive learning

The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.Comment: 6 page