The paper “Holonomy and vortex structures in quantum hydrodynamics“, co-authored by Michael Foskett and Cesare Tronci, has been accepted for publication in the MSRI Proceedings. This is the proceedings of the programme at MSRI on Hamiltonian Systems that ran in Autumn 2018, and Michael and Cesare participated in. A link to the arXiv version of […]
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Anna Kostianko is giving a virtual seminar today (Thursday 16th July) to the Chair for Analysis and Modeling at the Mathematics Department in the University of Stuttgart, Germany. The title of the talk is “Validity of the hyperbolic Whitham modulation equations in Sobolev spaces“. It is based a paper of the same title (arxiv link here). A link to the seminar […]
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The paper “Boost generator in AdS-3 integrable superstrings for general braiding“, co-authored by Juan Miguel Nieto Garcia, Alessandro Torrielli, and Leander Wyss, has been accepted for publication in the Journal of High Energy Physics. A link to the final form preprint at the arXiv is here. The abstract is shown below.
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The paper “Analyticity of the affinity dimension for planar iterated function systems with matrices which preserve a cone“, co-authored by Natalia Jurga and Ian Morris, has been published in Nonlinearity (journal link here and arXiv link here). They prove that when the linear parts of the affinities which define the IFS are 2×2 matrices, which […]
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Cesare Tronci has been appointed Adjunct Professor, in the Department of Physics, School of Science and Engineering, at Tulane University, in New Orleans, Louisiana. The appointment commenced on 1st June 2020 and runs for three years. The position involves collaboration with the group of Professor Denys Bondar. A link to the department is here. The […]
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The paper “Ensemble-based method for the inverse Frobenius–Perron operator problem: Data-driven global analysis from spatiotemporal “Movie” data“, co-authored by Naratip Santitissadeekorn and Erik Bollt (Clarkson University), has been published in Physica D (link here). It appears in a special issue on “Machine Learning and Dynamical Systems”. The paper’s ensemble-based approach improves the parameter inferences from […]
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