We present frequency tuning mechanisms for dielectric resonators, which undergo "super-mode" interactions as they tune. The tunable schemes are based on dielectric materials strategically placed inside traditional cylindrical resonant cavities, necessarily operating in Transverse Magnetic modes for use in axion haloscopes. The first technique is based on multiple dielectric disks with radii smaller than that of the cavity. The second scheme relies on hollow dielectric cylinders similar to a Bragg resonator, but of different location and dimension. In particular we engineer a significant increase in form factor for the TM030 mode utilising a variation of a Distributed Bragg Reflector Resonator. Additionally, we demonstrate application of traditional Distributed Bragg Reflectors in TM modes, which may be applied to a haloscope. This is the first demonstration of Bragg resonators applied to TM modes, as well as the first application of super-modes to tune Bragg resonators, or haloscope resonators. Theory and experimental results are presented showing an increase in Q-factor and tunability due to the super-mode effect. The TM030 ring resonator mode offers between 1 and 2orders-of-magnitude improvement in axion sensitivity over current conventional cavity systems and will be employed in the forthcoming ORGAN experiment.
Sample multiplexing is often used to reduce cost and limit batch effects in single-cell RNA (scRNA-seq) sequencing experiments. A commonly used multiplexing technique involves tagging cells prior to pooling with a hashtag oligo (HTO) that can be sequenced along with the cells' RNA to determine their sample of origin. Several tools have been developed to demultiplex HTO sequencing data and assign cells to samples. In this study, we critically assess the performance of six HTO demultiplexing tools: hashedDrops, HTODemux, GMM-Demux, demuxmix, deMULTIplex and BFF. The comparison uses data sets where each sample has also been demultiplexed using genetic variants from the RNA, enabling comparison of HTO demultiplexing techniques against complementary data from the genetic "ground truth". We find that all methods perform similarly where HTO labelling is of high quality, but methods that assume a bimodal counts distribution perform poorly on lower quality data. We also provide heuristic approaches for assessing the quality of HTO counts in a scRNA-seq experiment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.