Empirical measures from Kac's particle system converge to the Boltzmann equation solution for very soft potentials, proving propagation of chaos for all kernel classes.
Stopping Times and Tightness
3 Pith papers cite this work. Polarity classification is still indexing.
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Fragment classification is efficiently learnable by quantum neural networks under suitable conditions but resists known classical dequantization techniques.
Numerical tests on the first 500000 Fibonacci numbers suggest the concatenated constant is normal at tested scales, with any obstruction likely in the asymptotic interior digits of large terms.
citing papers explorer
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Propagation of chaos for the Boltzmann equation with very soft potentials
Empirical measures from Kac's particle system converge to the Boltzmann equation solution for very soft potentials, proving propagation of chaos for all kernel classes.
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Fragmentation is Efficiently Learnable by Quantum Neural Networks
Fragment classification is efficiently learnable by quantum neural networks under suitable conditions but resists known classical dequantization techniques.
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On the normality of the concatenated Fibonacci constant
Numerical tests on the first 500000 Fibonacci numbers suggest the concatenated constant is normal at tested scales, with any obstruction likely in the asymptotic interior digits of large terms.