143 citations · 476 across the 8 of their papers we have counts for
6 papers · 1 filter
Maximum Caliber: a general variational principle for dynamical systems
Purushottam D. Dixit, Jason Wagoner, Corey Weistuch +3
We review here {\it Maximum Caliber} (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical tr…
Reply to C. Tsallis' Comment on our "Nonadditive Entropies Yield Probability Distributions with Biases not Warranted by the Data"
Steve Pressé, Kingshuk Ghosh, Julian Lee +1
We reply to Tsallis' Comment on our "Nonadditive Entropies Yield Probability Distributions with Biases not Warranted by the Data" which first appeared in PRL.
Nonadditive Entropies Yield Probability Distributions with Biases not Warranted by the Data
Steve Pressé, Kingshuk Ghosh, Julian Lee +1
Different quantities that go by the name of entropy are used in variational principles to infer probability distributions from limited data. Shore and Johnson showed that maximizin…
Markov processes follow from the principle of Maximum Caliber
Hao Ge, Steve Presse, Kingshuk Ghosh +1
Markov models are widely used to describe processes of stochastic dynamics. Here, we show that Markov models are a natural consequence of the dynamical principle of Maximum Caliber…
Measurement of FLux Fluctuations in Diffusion in the Small-Numbers Limit
Effrosyni Seitaridou, Mandar M. Inamdar, Rob Phillips +2
Using a microfluidics device filled with a colloidal suspension of microspheres, we test the laws of diffusion in the limit of small particle numbers. Our focus is not just on aver…
Teaching the Principles of Statistical Dynamics
Kingshuk Ghosh, Ken Dill, Mandar M. Inamdar +2
We describe a simple framework for teaching the principles that underlie the dynamical laws of transport: Fick's law of diffusion, Fourier's law of heat flow, the Newtonian viscosi…