, Yale University
Pages: pp. 9-11
Abstract—Computation bridges analytic theory to experimentation in science. This issue reminds us that it also bridges between disciplines.
Keywords—Data visualization, laboratories, turbulence, crystalline defects. biomedical applications, spectroscopy
Iorganized this special theme issue to illustrate ways in which research in the physical and life sciences is stimulated by computational science, and conversely. The title— Crosstalk—is meant to epitomize such reciprocal exchanges. This magazine was originally created to facilitate this cross-fertilization, as was characterized by George Cybenko , CiSE's first editor in chief. In his introduction to CiSE's inaugural issue, 1 Cybenko framed a beautiful metaphor:
" CiSE is setting up camp at the confluence of two great intellectual rivers—the physical sciences and the computational sciences. This camp will grow into a town and then a city but only if we learn each other's languages and trade in good faith."
In that first editorial, Cybenko pointed out some challenges of this building task, not just for the magazine, but also within the sciences. It's no secret that in physics, early on, computational simulations were niche applications in areas such as accelerator design and orbital mechanics. But planning a career dedicated to creating a wider range of simulation use was considered "crazy thinking" and not worthy of a career's work. Today, the situation is different, as simulations have undisputedly enabled significant progress in condensed matter physics, material science, and astrophysics. On the other hand, computation in the physics curriculum doesn't have the wide footprint it deserves given its demonstrated significance in both scientific research and engineering development. But that is a story waiting to be told on a different day.
In this issue, I wish to present evidence that argues for Cybenko's trading metaphor but extends it into an even broader allegory. I argue that computation is not only a meeting place, but that it's also a medium for research collaboration and exchange of scientific ideas. So, pattern matching of experimental datasets in service of combinatorial mathematics builds an instrument for elucidating the human genome. This three-way collaboration is built upon computation. It's the metalanguage that transcends the argots of computer science, mathematics, and genetics.
This issue's theme articles offer three case studies that illustrate and provide evidence for the intellectual trading that Cybenko envisioned. The first article describes exchanges between computer science (visualization) and medical practice (cardiology and neurology); the second between theoretical spectroscopy (quantum chemistry) and materials engineering (photovoltaics); and the third between materials science (defects in crystals) and fluid dynamics (liquid turbulence).
In "Biomedical Visual Computing: Case Studies and Challenges," Chris R. Johnson lays out cases in which investigations of certain biomedical problems benefited from visualizations that enable one to infer relationships among data. This capability is what makes investigations of many complex systems practical. Although his examples illustrate how visualization "rescued" cardiology and neurology from the throes of complexity, the prospect for its extension to other complex systems seems bright. This is a good example of reciprocal benefits. Complex biomedical problems stimulate computer science to invent/adapt effective visualization techniques, which reflexively inspire applications of visualizations to other scientific research areas.
Next, in "The ETSF: An e-Infrastructure that Bridges Simulations and Experiments," Anne Y. Matsuura and her colleagues describe how the needs of the photovoltaic industry inspired the creation of the European Theoretical Spectroscopy Facility, a shared-use facility that gives industrial materials developers access to the results of quantum chemistry research. Further, the ETSF's approach to designing this facility is a model for other such access-enabling liaisons between theoretical research in some area and its related experimental science.
Finally, in "Is Dislocation Flow Turbulent in Deformed Crystals?" Woosong Choi and his colleagues describe how they uncovered a similarity in the behavior of crystals that seems to bear an analogy to turbulence in liquids. In this case, the discovery might open the door to material scientists borrowing concepts, if not computational tools, developed for turbulence research to apply in the area of defect migration. In a broader sense, this success could stimulate other computational scientists or engineers to look for similarities that might point to shortcuts for their own research by borrowing methods from others.
In the end, it would be good for us to know how well this theme issue has done the job that Cybenko imagined more than a decade ago. I also invite you to tell us how CiSE is doing overall.