Publications

Results 4001–4050 of 9,998

Search results

Jump to search filters

Electron Turbulence at Nanoscale Junctions

Nano Letters

Bushong, Neil; Laros, James H.; Di Ventra, Massimiliano

Electron transport through a nanostructure can be characterized in part using concepts from classical fluid dynamics. Hence, it is natural to ask how far the analogy can be taken and whether the electron liquid can exhibit nonlinear dynamical effects such as turbulence. Here we present an ab initio study of the electron dynamics in nanojunctions which reveals that the latter indeed exhibits behavior quite similar to that of a classical fluid. In particular, we find that a transition from laminar to turbulent flow occurs with increasing current, corresponding to increasing Reynolds numbers. These findings reveal unexpected features of electron dynamics and shed new light on our understanding of transport properties of nanoscale systems.

More Details
TYPE Journal Article YEAR 2017
DOIOSTIDOIOSTI

Experimental Demonstration of a Cheap and Accurate Phase Estimation

Physical Review Letters

Rudinger, Kenneth M.; Kimmel, Shelby; Lobser, Daniel L.; Maunz, Peter L.

We demonstrate an experimental implementation of robust phase estimation (RPE) to learn the phase of a single-qubit rotation on a trapped Yb+ ion qubit. We show this phase can be estimated with an uncertainty below 4×10-4 rad using as few as 176 total experimental samples, and our estimates exhibit Heisenberg scaling. Unlike standard phase estimation protocols, RPE neither assumes perfect state preparation and measurement, nor requires access to ancillae. We crossvalidate the results of RPE with the more resource-intensive protocol of gate set tomography.

More Details
TYPE Journal Article YEAR 2017
DOIOSTIScopus

Write-optimized skip lists

Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

Bender, Michael A.; Farach-Colton, Martin; Johnson, Rob; Mauras, Simon; Mayer, Tyler; Phillips, Cynthia A.; Xu, Helen

The skip list is an elegant dictionary data structure that is commonly deployed in RAM. A skip list with N elements supports searches, inserts, and deletes in O (log N) operations with high probability (w.h.p.) and range queries returning K elements in O(log N + K) operations w.h.p. A seemingly natural way to generalize the skip list to external memory with block size B is to "promote" with probability 1/B, rather than 1/2. However, there are practical and theoretical obstacles to getting the skip list to retain its efficient performance, space bounds, and high-probability guarantees. We give an external-memory skip list that achieves write-optimized bounds. That is, for 0 < ϵ < 1, range queries take O(logBϵ N + K/B) I/Os w.h.p. and insertions and deletions take O((logBϵ N)/B1-ϵ) amortized I/Os w.h.p. Our write-optimized skip list inherits the virtue of simplicity from RAM skip lists. Moreover, it matches or beats the asymptotic bounds of prior write-optimized data structures such as Bϵ trees or LSM trees. These data structures are deployed in high-performance databases and file systems. The main technical challenge in proving our bounds comes from the fact that there are so few levels in the skip list, an aspect of the data structure that is essential to getting strong external-memory bounds. We use extremal-graph coloring to show that it is possible to decompose paths in the skip list into uncorrelated groups, regardless of the insertion/deletion pattern. Thus, we achieve our bounds by averaging over these uncorrelated paths rather than by averaging over uncorrelated levels, as in the standard skip list.

More Details
TYPE Conference Poster YEAR 2017
DOIOSTIScopus

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

Moreland, Kenneth D.; Pugmire, David; Rogers, David; Childs, Hank; Ma, Kwan-Liu; Geveci, Berk

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

More Details
TYPE Other Report YEAR 2017
DOIOSTI

USACM Thematic Workshop On Uncertainty Quantification And Data-Driven Modeling

Stewart, James R.

The USACM Thematic Workshop on Uncertainty Quantification and Data-Driven Modeling was held on March 23-24, 2017, in Austin, TX. The organizers of the technical program were James R. Stewart of Sandia National Laboratories and Krishna Garikipati of University of Michigan. The administrative organizer was Ruth Hengst, who serves as Program Coordinator for the USACM. The organization of this workshop was coordinated through the USACM Technical Thrust Area on Uncertainty Quantification and Probabilistic Analysis. The workshop website (http://uqpm2017.usacm.org) includes the presentation agenda as well as links to several of the presentation slides (permission to access the presentations was granted by each of those speakers, respectively). Herein, this final report contains the complete workshop program that includes the presentation agenda, the presentation abstracts, and the list of posters.

More Details
TYPE Other Report YEAR 2017
DOIOSTI
Results 4001–4050 of 9,998
Results 4001–4050 of 9,998