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Creators/Authors contains: "Laginja, Iva"

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  1. TheβPictoris system is the closest known stellar system with directly detected gas giant planets, an edge-on circumstellar disc, and evidence of falling sublimating bodies and transiting exocomets. The inner planet,βPictoris c, has also been indirectly detected with radial velocity (RV) measurements. The star is a knownδScuti pulsator, and the long-term stability of these pulsations opens up the possibility of indirectly detecting the gas giant planets through time delays of the pulsations due to a varying light travel time. We search for phase shifts in theδScuti pulsations consistent with the known planetsβPictoris b and c and carry out an analysis of the stellar pulsations ofβPictoris over a multi-year timescale. We used photometric data collected by the BRITE-Constellation, bRing, ASTEP, and TESS to derive a list of the strongest and most significantδScuti pulsations. We carried out an analysis with the open-source python package maelstrom to study the stability of the pulsation modes ofβPictoris in order to determine the long-term trends in the observed pulsations. We did not detect the expected signal forβPictoris b orβPictoris c. The expected time delay is 6 s forβPictoris c and 24 s forβPictoris b. With simulations, we determined that the photometric noise in all the combined data sets cannot reach the sensitivity needed to detect the expected timing drifts. An analysis of the pulsational modes ofβPictoris using maelstrom showed that the modes themselves drift on the timescale of a year, fundamentally limiting our ability to detect exoplanets aroundβPictoris via pulsation timing. 
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  2. Software is a critical part of modern research, and yet there are insufficient mechanisms in the scholarly ecosystem to acknowledge, cite, and measure the impact of research software. The majority of academic fields rely on a one-dimensional credit model whereby academic articles (and their associated citations) are the dominant factor in the success of a researcher's career. In the petabyte era of astronomical science, citing software and measuring its impact enables academia to retain and reward researchers that make significant software contributions. These highly skilled researchers must be retained to maximize the scientific return from petabyte-scale datasets. Evolving beyond the one-dimensional credit model requires overcoming several key challenges, including the current scholarly ecosystem and scientific culture issues. This white paper will present these challenges and suggest practical solutions for elevating the role of software as a product of the research enterprise. 
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