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Want facts and want them fast? Our Maths in a minute series explores key mathematical concepts in just a few words.
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Was the mathematical modelling projecting the course of the pandemic too pessimistic, or were the projections justified? Matt Keeling tells our colleagues from SBIDER about the COVID models that fed into public policy.
PhD student Daniel Kreuter tells us about his work on the BloodCounts! project, which uses maths to make optimal use of the billions of blood tests performed every year around the globe.
Cited from https://en.wikipedia.org/wiki/Entropy_(information_theory) : "in the view of (Edwin Thompson) Jaynes (1957), thermodynamic entropy, as explained by statistical mechanics, should be seen as an application of Shannon's information theory: the thermodynamic entropy is interpreted as being proportional to the amount of further Shannon information needed to define the detailed microscopic state of the system, that remains uncommunicated by a description solely in terms of the macroscopic variables of classical thermodynamics, with the constant of proportionality being just the Boltzmann constant."
I find this quite appealing. Considering that "bit" in information theory is unitless, it's just number, this hypothesis may be true. And with this model, we may be able to unify physics and computation in the future.
We can view current physical laws as constrains applied to the logical world of "bits". Each law gives a set of more constrains on how the world(particles, wave, or any other physical representations) should behave. Our world may be just one of many possible worlds described by math.