Synthetic Data
APA
Fish, V. (2014). Synthetic Data. Perimeter Institute. https://pirsa.org/14110111
MLA
Fish, Vincent. Synthetic Data. Perimeter Institute, Nov. 14, 2014, https://pirsa.org/14110111
BibTex
@misc{ pirsa_PIRSA:14110111, doi = {10.48660/14110111}, url = {https://pirsa.org/14110111}, author = {Fish, Vincent}, keywords = {Strong Gravity}, language = {en}, title = {Synthetic Data}, publisher = {Perimeter Institute}, year = {2014}, month = {nov}, note = {PIRSA:14110111 see, \url{https://pirsa.org}} }
Massachusetts Institute of Technology (MIT)
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Abstract
You've just finished running your code, and you're certain that you (and only you) know exactly what the region around a supermassive black hole looks like. You could lie back and wait for the accolades to roll in, but why not take an extra moment to make testable predictions that even the observers can understand? Synthetic data can help.