Time in a Sparse-Information Universe

Einstein once famously complained, “Since the mathematicians have invaded the theory of relativity, I do not understand it myself anymore.” Einstein meant Hermann Minkowski, his former math instructor, who in 1908 translated Einstein’s clocks-and-rulers version of special relativity into a smooth, four-dimensional mathematical continuum that required no material objects. Einstein’s reasons for this dramatic switch were twofold: Regret after Minkowski’s untimely 1909 death that he had not paid more attention to his work, and the realization that generalizing special relativity required an ability to curve space and time in complex ways.

Einstein’s earlier clocks-and-rulers methods had culminated in his extraordinary 1911 prediction of the Twins’ Paradox — an idea so far ahead of its time that six decades passed before Joseph Hafele and Richard Keating verified his prediction. However, the cost of the prediction was high since Einstein had to develop an inelegant set of procedures that, to modern eyes, read more like a computer program than a mathematical continuum. His procedure included, for example, the need to build, spread, and synchronize clouds of carefully synchronized clocks to make the space and time metrics of an inertial frame meaningful. This approach places strong limits on the density (sparsity) of the time and space information available when modeling physical phenomena.

In this talk, Terry will look at what might have happened had Einstein stuck with his original strategy of defining time and space solely in terms of sparsely scattered information associated directly with matter and energy. Quantum uncertainty, in particular, emerges easily in this model.

Speaker:

Terry Bollinger is a computer scientist with a BS, MS, and Professional Degrees from the Missouri University of Science and Technology. He views physics as a debugging problem in which failures to resolve a problem often indicate not a lack of creative thinking but reliance on some subtly false assumption from papers far in the past. Folks know him best for keeping the US Department of Defense from banning open-source software, which would have seriously undermined national defense and the open-source software industry. He has also helped find and insert new technologies into the federal government and define and obtain federal fundinding for robotics and AI research.