We report on an experiment in combining the theorem prover Isabelle with automatic first-order arithmetic provers to increase automation on the verification of distributed protocols. As a case study for the experiment we verify several averaging clock synchronization algorithms. We present a formalization of Schneider's generalized clock synchronization protocol [Sch87] in Isabelle/HOL. Then, we verify that the convergence functions used in two clock synchronization algorithms, namely, the Interactive Convergence Algorithm (ICA) of Lamport and Melliar-Smith [LMS85] and the Fault-tolerant Midpoint algorithm of Lundelius-Lynch [LL84], satisfy Schneider's general conditions for correctness. The proofs are completely formalized in Isabelle/HOL. We identify parts of the proofs which are not fully automatically proven by Isabelle built-in tactics and show that these proofs can be handled by automatic first-order provers with support for arithmetics.
We analyze a prospect for predicting gravitational waveforms from compact binaries based on automated machine learning (AutoML) from around a hundred different possible regression models, without having to resort to tedious and manual case-by-case analyses and fine-tuning. The particular study of this article is within the context of the gravitational waves emitted by the collision of two spinless black holes in initial quasi-circular orbit. We find, for example, that approaches such as Gaussian process regression with radial bases as kernels, an approach which is generalizable to multiple dimensions with low computational evaluation cost, do provide a sufficiently accurate solution. The results here presented suggest that AutoML might provide a framework for regression in the field of surrogates for gravitational waveforms. Our study is within the context of surrogates of numerical relativity simulations based on Reduced Basis and the Empirical Interpolation Method, where we find that for the particular case analyzed AutoML can produce surrogates which are essentially indistinguishable from the NR simulations themselves.
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