Recently, there has been success creating novel nanostructures by encapsulating materials inside carbon nanotubes (CNTs), yet the chirality dependent electronic properties of CNTs make device application difficult. Encapsulation of nanoribbons and atomic chains in boron nitride nanotubes (BNNTs) has proven to yield nanostructures fit for field effect transistors and other electronic applications. In this talk I will discuss the experimental methods of the encapsulation of tellurium atomic chains inside BNNTs.

Neerav Kaushal [Advisor: Elena Giusarma]
NECOLA: Towards a Universal Field-level Cosmological Emulator

The upcoming galaxy surveys such as EUCLID, DESI and WFIRST are expected to improve the constraints on cosmological parameters. These surveys contain the information of the matter distribution in the Universe whose properties in turn contain information about the dark matter, dark energy and the laws of gravity. In order to maximize the information that can be retrieved from these observations, accurate theoretical predictions are needed. A powerful tool to obtain rigorous theoretical predictions is performing a suite of cosmological simulations. However, generating these simulations is very computationally expensive. Here, we present a deep learning model to quickly generate fast and accurate simulations of the Universe. Our model, NECOLA, maps from moderately accurate but fast COLA simulations to accurate but slow N-body simulations. Using several summary statistics, we find that NECOLA can reproduce the results of the full N-body simulations with sub-percent accuracy down to scales of 6.28 𝑀𝑀𝑀𝑀𝑀𝑀 ℎ−1. Furthermore, NECOLA generalizes extremely well on simulations it has never been trained on with very high accuracy. Our work represents a first step towards the development of a fast field-level emulator to sample not only primordial mode amplitudes and phases, but also the parameter space defined by the values of the cosmological parameters. The use of such an approach will be particularly useful to compare theory and predictions, to compute covariance matrices, generating mock galaxy catalogs and optimizing observational strategies in the future.