Landau-Zener-Stuckelberg-Majorana interferometry of a single hole

We perform Landau-Zener-Stuckelberg-Majorana (LZSM) spectroscopy on a system with strong spin-orbit interaction (SOI), realized as a single hole confined in a gated double quantum dot. In analogy to the electron systems, at magnetic field B=0 and high modulation frequencies we observe the photon-assisted tunneling (PAT) between dots, which smoothly evolves into the typical LZSM funnel-shaped interference pattern as the frequency is decreased. In contrast to electrons, the SOI enables an additional, efficient spin-flipping interdot tunneling channel, introducing a distinct interference pattern at finite B. Magneto-transport spectra at low-frequency LZSM driving show the two channels to be equally coherent. High-frequency LZSM driving reveals complex photon-assisted tunneling pathways, both spin-conserving and spin-flipping, which form closed loops at critical magnetic fields. In one such loop an arbitrary hole spin state is inverted, opening the way toward its all-electrical manipulation.Comment: 6 pages, 4 figures, and supplementary materia

Vermont Restaurant Owner & Manager Perspectives on Creating Heart-Healthy Kids Meals

Introduction: The prevalence of sugar sweetened beverages and fried foods combined with a lack of healthy children’s menu options has contributed to the obesity epidemic among young Americans. Recent legislation in New York City and San Francisco instituted strict nutritional requirements on children’s menu items. We performed a cross-sectional study that focused on independently owned restaurants with printed children’s menus in Vermont. We investigated the nutritional content of children’s menu items, restaurant owner and manager perspectives on customer ordering habits, and barriers that restaurants would face if they made children’s menu items healthier.https://scholarworks.uvm.edu/comphp_gallery/1220/thumbnail.jp

Graph Encoding and Neural Network Approaches for Volleyball Analytics: From Game Outcome to Individual Play Predictions

This research aims to improve the accuracy of complex volleyball predictions and provide more meaningful insights to coaches and players. We introduce a specialized graph encoding technique to add additional contact-by-contact volleyball context to an already available volleyball dataset without any additional data gathering. We demonstrate the potential benefits of using graph neural networks (GNNs) on this enriched dataset for three different volleyball prediction tasks: rally outcome prediction, set location prediction, and hit type prediction. We compare the performance of our graph-based models to baseline models and analyze the results to better understand the underlying relationships in a volleyball rally. Our results show that the use of GNNs with our graph encoding yields a much more advanced analysis of the data, which noticeably improves prediction results overall. We also show that these baseline tasks can be significantly improved with simple adjustments, such as removing blocked hits. Lastly, we demonstrate the importance of choosing a model architecture that will better extract the important information for a certain task. Overall, our study showcases the potential strengths and weaknesses of using graph encodings in sports data analytics and hopefully will inspire future improvements in machine learning strategies across sports and applications by using graphbased encodings.Comment: This paper is an extended version of the one accepted at the KDD 2023 Workshop on Data Science and AI for Sports (DSAI4Sports), entitled 'RallyGraph: Specialized Graph Encoding for Enhanced Volleyball

Gift Contagion in Online Groups: Evidence From WeChat Red Packets

Gifts are important instruments for forming bonds in interpersonal relationships. Our study analyzes the phenomenon of gift contagion in online groups. Gift contagion encourages social bonds of prompting further gifts; it may also promote group interaction and solidarity. Using data on 36 million online red packet gifts on China's social site WeChat, we leverage a natural experimental design to identify the social contagion of gift giving in online groups. Our natural experiment is enabled by the randomization of the gift amount allocation algorithm on WeChat, which addresses the common challenge of causal identifications in observational data. Our study provides evidence of gift contagion: on average, receiving one additional dollar causes a recipient to send 18 cents back to the group within the subsequent 24 hours. Decomposing this effect, we find that it is mainly driven by the extensive margin -- more recipients are triggered to send red packets. Moreover, we find that this effect is stronger for "luckiest draw" recipients, suggesting the presence of a group norm regarding the next red packet sender. Finally, we investigate the moderating effects of group- and individual-level social network characteristics on gift contagion as well as the causal impact of receiving gifts on group network structure. Our study has implications for promoting group dynamics and designing marketing strategies for product adoption.Comment: 33 page

Senior Recital

Program listing performers and works performe

Bird nests as botanical time capsules: DNA barcoding identifies the contents of contemporary and historical nests

Bird nests in natural history collections are an abundant yet vastly underutilized source of genetic information. We sequenced the nuclear ribosomal internal transcribed spacer to identify plant species used as nest material in two contemporary (2003 and 2018) and two historical (both 1915) nest specimens constructed by Song Sparrows (Melospiza melodia) and Savannah Sparrows (Passerculus sandwichensis). A total of 13 (22%) samples yielded single, strong bands that could be identified using GenBank resources: six plants (Angiospermae), six green algae (Chlorophyta), and one ciliate (Ciliophora). Two native plant species identified in the nests included Festuca microstachys, which was introduced to the nest collection site by restoration practitioners, and Rosa californica, identified in a nest collected from a lost habitat that existed about 100 years ago. Successful sequencing was correlated with higher sample mass and DNA quality, suggesting future studies should select larger pieces of contiguous material from nests and materials that appear to have been fresh when incorporated into the nest. This molecular approach was used to distinguish plant species that were not visually identifiable, and did not require disassembling the nest specimens as is a traditional practice with nest material studies. The many thousands of nest specimens in natural history collections hold great promise as sources of genetic information to address myriad ecological questions

Energy-Ecient Physically Tagged Caches for Embedded Processors with Virtual Memory

ABSTRACT In this paper we present a low-power tag organization for physically tagged caches in embedded processor