Recently, bootstrap methods from conformal field theory have been adapted for studying the energy spectrum of various quantum mechanical systems. In this paper, we consider application these in obtaining Schr\"odinger equation with periodic potentials, paying particular attention to Kronig-Penney model a particle one-dimensional lattice. With an appropriate choice operator basis involving posit...

Gravitational interferometers and cosmological observations of the cosmic microwave background offer us prospect to probe laws gravity in primordial universe. To study interpret these datasets we need know possible graviton non-Gaussianities. this end, derive most general tree-level three-point functions (bispectra) for a massless all orders derivatives, assuming scale invariance. Instead worki...

Abstract Recently, a novel bootstrap method for numerical calculations in matrix models and quantum mechanical systems was proposed. We apply the to certain derived from some well-known local toric Calabi–Yau geometries, where exact quantization conditions have been conjecturally related topological string theory. find that provides promising alternative precision of energy eigenvalues. An impr...

This paper introduces the confidence interval estimate for measuring the bullwhip effect, which has been observed across most industries. Calculating a confidence interval usually needs the assumption about the underlying distribution. Bootstrapping is a non-parametric, but computer intensive, estimation method. In this paper, a simulation study on the behavior of the 95% bootstrap confidence i...

Children face ve central diiculties when learning the vocabulary of their native language: learning from multi-word utterances, bootstrapping from an empty mental lexicon, referential uncertainty, noise, and homonymy. These diiculties are modeled formally via a simpliied lexical acquisition task called the mapping problem. Algorithms for solving this mapping problem are developed, based on the ...

This paper introduces the confidence interval estimate for measuring the bullwhip effect, which has been observed across most industries. Calculating a confidence interval usually needs the assumption about the underlying distribution. Bootstrapping is a non-parametric, but computer intensive, estimation method. In this paper, a simulation study on the behavior of the 95% bootstrap confidence i...

Bootstrapping a classifier from a small set of seed rules can be viewed as the propagation of labels between examples via features shared between them. This paper introduces a novel variant of the Yarowsky algorithm based on this view. It is a bootstrapping learning method which uses a graph propagation algorithm with a well defined objective function. The experimental results show that our pro...