Meta-learning Control Variates: Variance Reduction with Limited Data

Control variates can be a powerful tool to reduce the variance of Monte Carlo estimators, but constructing effective control variates can be challenging when the number of samples is small. In this paper, we show that when a large number of related integrals need to be computed, it is possible to leverage the similarity between these integration tasks to improve performance even when the number of samples per task is very small. Our approach, called meta learning CVs (Meta-CVs), can be used for up to hundreds or thousands of tasks. Our empirical assessment indicates that Meta-CVs can lead to significant variance reduction in such settings, and our theoretical analysis establishes general conditions under which Meta-CVs can be successfully trained

Polymeric pH nanosensor with extended measurement range bearing octaarginine as cell penetrating peptide

A synthetic peptide octaarginine which mimics human immunodeficiency virus‐1, Tat protein is used as cell penetrating moiety for new pH nanosensors which demonstrate enhanced cellular uptake and expanded measurement range from pH 3.9 to pH 7.3 by simultaneously incorporating two complemental pH‐sensitive fluorophores in a same nanoparticle. The authors believe that this triple fluorescent pH sensor provides a new tool to pH measurements that can have application in cellular uptake mechanism study and new nanomedicine design

Room temperature control of valley coherence in bilayer WS2 exciton polaritons

We demonstrate robust retention of valley coherence and its control via polariton pseudospin precession through the optical TE-TM splitting in bilayer WS2 microcavity exciton polaritons at room temperature