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Reference Terms
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Scientific visualization

Scientific and Information visualization are branches of computer graphics and user interface design that are concerned with presenting data to users, by means of images. The goal of this area is usually to improve understanding of the data being presented. For example, scientists interpret potentially huge quantities of laboratory or simulation data or the results from sensors out in the field to aid reasoning, hypothesis building and cognition. The field of data mining offers many abstract visualizations related to these visualization types. They are active research areas, drawing on theory in information graphics, computer graphics, human-computer interaction and cognitive science. Desktop programs capable of presenting interactive models of molecules and microbiological entities are becoming relatively common (Molecular graphics). The field of Bioinformatics and the field of Cheminformatics make a heavy use of these visualization engines for interpreting lab data and for training purposes.

Medical imaging is a huge application domain for scientific visualization with an emphasis on enhancing imaging results graphically, e.g. using pseudo-coloring or overlaying of plots. Real-time visualization can serve to simultaneously image analysis results within or beside an analyzed (e.g. segmented) scan.

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June 22, 2026

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A clever nanoscale redesign may have solved one of superconductivity’s biggest problems. Researchers in Sweden discovered that by subtly sculpting the surface beneath an ultrathin superconducting material, they could make it stay superconducting ...
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Scientists at the University of Hong Kong have created a remarkable new type of brain-inspired chip that can function just above absolute zero, one of the coldest environments imaginable. By using a ...
Scientists at RIKEN have proposed a new way to make quantum systems synchronize in only one direction—like a one-way street for sound particles known as phonons. The breakthrough combines two quantum effects to create a form of one-way quantum ...
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Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need for expensive simulations. Yet the approach can backfire when AI relies too heavily on familiar patterns, potentially missing ...
Researchers gave top AI models a classic attention test used in psychology and found a major flaw. While the models could correctly name colors in short lists, their performance deteriorated sharply as the task became longer and more complex. Some ...

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