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Register a new user21st Century Statistical and Computational Challenges in Astrophysics
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Modern astronomy has been rapidly increasing our ability to see deeper into the universe, acquiring enormous samples of cosmic populations. Gaining astrophysical insights from these datasets requires a wide range of sophisticated statistical and machine learning methods. Long-standing problems in cosmology include characterization of galaxy clustering and estimation of galaxy distances from photometric colors. Bayesian inference, central to linking astronomical data to nonlinear astrophysical models, addresses problems in solar physics, properties of star clusters, and exoplanet systems. Likelihood-free methods are growing in importance. Detection of faint signals in complicated noise is needed to find periodic behaviors in stars and detect explosive gravitational wave events. Open issues concern treatment of heteroscedastic measurement errors and understanding probability distributions characterizing astrophysical systems. The field of astrostatistics needs increased collaboration with statisticians in the design and analysis stages of research projects, and to jointly develop new statistical methodologies. Together, they will draw more astrophysical insights into astronomical populations and the cosmos itself.
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Data volumes from multiple sky surveys have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into tens (or hundreds) of petabytes in the next decade. This exponential growth of new data both enables and challenges effective astronomical research, requiring new approaches. Thus far, astronomy has tended to address these challenges in an informal and ad hoc manner, with the necessary special expertise being assigned to e-Science or survey science. However, we see an even wider scope and therefore promote a broader vision of this data-driven revolution in astronomical research. For astronomy to effectively cope with and reap the maximum scientific return from existing and future large sky surveys, facilities, and data-producing projects, we need our own information science specialists. We therefore recommend the formal creation, recognition, and support of a major new discipline, which we call Astroinformatics. Astroinformatics includes a set of naturally-related specialties including data organization, data description, astronomical classification taxonomies, astronomical concept ontologies, data mining, machine learning, visualization, and astrostatistics. By virtue of its new stature, we propose that astronomy now needs to integrate Astroinformatics as a formal sub-discipline within agency funding plans, university departments, research programs, graduate training, and undergraduate education. Now is the time for the recognition of Astroinformatics as an essential methodology of astronomical research. The future of astronomy depends on it.
Classical nova explosions and type I X-ray bursts are the most frequent types of thermonuclear stellar explosions in the Galaxy. Both phenomena arise from thermonuclear ignition in the envelopes of accreting compact objects in close binary star systems. Detailed observations of these events have stimulated numerous studies in theoretical astrophysics and experimental nuclear physics. We discuss observational features of these phenomena and theoretical efforts to better understand the energy production and nucleosynthesis in these explosions. We also examine and summarize studies directed at identifying nuclear physics quantities with uncertainties that significantly affect model predictions.
The answers to fundamental science questions in astrophysics, ranging from the history of the expansion of the universe to the sizes of nearby stars, hinge on our ability to make precise measurements of diverse astronomical objects. As our knowledge of the underlying physics of objects improves along with advances in detectors and instrumentation, the limits on our capability to extract science from measurements is set, not by our lack of understanding of the nature of these objects, but rather by the most mundane of all issues: the precision with which we can calibrate observations in physical units. We stress the need for a program to improve upon and expand the current networks of spectrophotometrically calibrated stars to provide precise calibration with an accuracy of equal to and better than 1% in the ultraviolet, visible and near-infrared portions of the spectrum, with excellent sky coverage and large dynamic range.
The traditional university science curriculum was designed to train specialists in specific disciplines. However, in universities all over the world, science students are going into increasingly diverse careers and the current model does not fit their needs. Advances in technology also make certain modes of learning obsolete. In the last 10 years, the Faculty of Science of the University of Hong Kong has undertaken major curriculum reforms. A sequence of science foundation courses required of all incoming science students are designed to teach science in an integrated manner, and to emphasize the concepts and utilities, not computational techniques, of mathematics. A number of non-discipline specific common core courses have been developed to broaden students awareness of the relevance of science to society and the interdisciplinary nature of science. By putting the emphasis on the scientific process rather than the outcome, students are taught how to identify, formulate, and solve diverse problems.
As the oldest science common to all human cultures, astronomy has a unique connection to indigenous knowledge (IK) and the long history of indigenous scientific contributions. Many STEM disciplines, agencies and institutions have begun to do the work of recruiting and retaining underrepresented minorities, including indigenous, Native American and Native Hawaiian professionals. However, with the expansion of telescope facilities on sacred tribal or indigenous lands in recent decades, and the current urgency of global crises related to climate, food/water sovereignty and the future of humanity, science and astronomy have the opportunity more than ever to partner with indigenous communities and respect the wealth of sustainable practices and solutions inherently present in IK. We share a number of highly successful current initiatives that point the way to a successful model of collaboration with integrity between western and indigenous scholars. Such models deserve serious consideration for sustained funding at local and institutional levels. We also share six key recommendations for funding agencies that we believe will be important first steps for nonindigenous institutions to fully dialog and partner with indigenous communities and IK to build together towards a more inclusive, sustainable and empowering scientific enterprise.
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