Publications
Wind information requirements for NextGen applications phase 1: 4D-trajectory based operations (4D-TBO)
Summary
Summary
Accurate wind information is required to support some of the key applications envisioned for future air traffic concepts. A Wind Information Analysis Framework has been developed to assess wind information needs for different applications. The framework is described and then applied in a Four-Dimensional Trajectory Based Operations (4D-TBO) application using...
Nonlinear bleaching, absorption, and scattering of 532-nm-irradiated plasmonic nanoparticles
Summary
Summary
Single-pulse irradiation of Au and Ag suspensions of nanospheres and nanodisks with 532-nm 4-ns pulses has identified complex optical nonlinearities while minimizing material damage. For all materials tested, we observe competition between saturable absorption (SA) and reverse SA (RSA), with RSA behavior dominating for intensities above ~50 MW/cm^2. Due to...
Development of adaptive liquid microlenses and microlens arrays
Summary
Summary
We report on the development of sub-millimeter size adaptive liquid microlenses and microlens arrays using two immiscible liquids to form individual lenses. Microlenses and microlens arrays having aperture diameters as small as 50 microns were fabricated on a planar quartz substrate using patterned hydrophobic/hydrophilic regions. Liquid lenses were formed by...
Measurement of the surface-enhanced coherent anti-Stokes Raman scattering (SECARS) due to the 1574 cm^-1 surface-enhanced Raman scattering (SERS) mode of benzenethiol using low-power (<20 mW) CW diode lasers
Summary
Summary
The surface-enhanced coherent anti-Stokes Raman scattering (SECARS) from a self-assembled monolayer (SAM) of benzenethiol on a silver-coated surface-enhanced Raman scattering (SERS) substrate has been measured for the 1574 cm^-1 SERS mode. A value of 9.6 +- 1.7 x 10^-14 W was determined for the resonant component of the SECARS signal...
Novel graph processor architecture
Summary
Summary
Graph algorithms are increasingly used in applications that exploit large databases. However, conventional processor architectures are hard-pressed to handle the throughput and memory requirements of graph computation. Lincoln Laboratory's graph-processor architecture represents a fundamental rethinking of architectures. It utilizes innovations that include high-bandwidth three-dimensional (3D) communication links, a sparse matrix-based...
Taming biological big data with D4M
Summary
Summary
The supercomputing community has taken up the challenge of "taming the beast" spawned by the massive amount of data available in the bioinformatics domain: How can these data be exploited faster and better? MIT Lincoln Laboratory computer scientists demonstrated how a new Laboratory-developed technology, the Dynamic Distributed Dimensional Data Model...
Detection theory for graphs
Summary
Summary
Graphs are fast emerging as a common data structure used in many scientific and engineering fields. While a wide variety of techniques exist to analyze graph datasets, practitioners currently lack a signal processing theory akin to that of detection and estimation in the classical setting of vector spaces with Gaussian...
Social network analysis with content and graphs
Summary
Summary
Social network analysis has undergone a renaissance with the ubiquity and quantity of content from social media, web pages, and sensors. This content is a rich data source for constructing and analyzing social networks, but its enormity and unstructured nature also present multiple challenges. Work at Lincoln Laboratory is addressing...
Improving quantum gate fidelities by using a qubit to measure microwave pulse distortions
Summary
Summary
We present a new method for determining pulse imperfections and improving the single-gate fidelity in a superconducting qubit. By applying consecutive positive and negative pi pulses, we amplify the qubit evolution due to microwave pulse distortions, which causes the qubit state to rotate around an axis perpendicular to the intended...
Convective initiation forecasts through the use of machine learning methods
Summary
Summary
Storm initiation is a very challenging aspect of nowcasting. Rapidly forming storms that appear in areas of little to no pre-existing convection can pose a danger to aircraft, and have the potential to cause unforeseen delays in the national airspace system (NAS). As such, detection and prediction of the initial...