We propose a new type of generative model of high-dimensional data that learns a manifold geometry of the data, rather than density, and can generate points evenly along this manifold. This is in contrast to existing ...
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The NSF-funded Redshirt in Engineering Consortium was formed in 2016 with the goal of enhancing the ability of academically talented but underprepared students coming from low-income backgrounds to successfully gradua...
The NSF-funded Redshirt in Engineering Consortium was formed in 2016 with the goal of enhancing the ability of academically talented but underprepared students coming from low-income backgrounds to successfully graduate with engineering degrees. The Consortium takes its name from the practice of redshirting in college athletics, with the idea of providing an extra year and support to help promising engineering students complete a bachelor's degree. The Consortium builds on the success of three existing "academic redshirt" programs and expands the model to three new schools. The Existing Redshirt Institutions (ERIs) help mentor and train the new Student Success Partners (SSPs), and SSPs contribute their unique expertise to help ERIs improve existing Redshirt programs. The Redshirt model consists of seven main programmatic components aimed at improving the engagement, retention, and graduation of students underrepresented in engineering. These components include: "intrusive" academic advising and support services, an intensive first-year academic curriculum, community-building (including pre-matriculation summer programs), career awareness and vision, faculty mentorship, NSF S-STEM scholarships, and second-year support. Successful implementation of these activities is intended to produce two main long-term outcomes: a six-year graduation rate of 60%-75% for Redshirt students, and increased rates of enrollment and graduation of Pell-eligible, URM, and women students in engineering at participating universities. In the first year of the grant (AY 16-17), SSPs developed their own Redshirt programs, hired and trained staff, and got their programs off the ground. ERIs implemented faculty mentorship programs and expanded support to Redshirt students into their sophomore year. In the second year (AY 17-18), Redshirt programs were expanded at the ERIs while SSPs welcomed their first cohorts of Redshirt students. This Work in Progress paper describes the Redshirt programs at e
We present a simple metasurface-inspired planar focusing collector for concentrated solar power. Fabrication is achieved using two-photon lithography, and subsequent nanoimprint lithography tests for scalability. Opti...
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The ability to monitor and control distinct states is at the heart of emerging quantum technologies. The valley pseudospin in transition metal dichalcogenide (TMDC) monolayers is a promising degree of freedom for such...
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The ability to monitor and control distinct states is at the heart of emerging quantum technologies. The valley pseudospin in transition metal dichalcogenide (TMDC) monolayers is a promising degree of freedom for such control, with the optical Stark effect allowing for valley-selective manipulation of energy levels in WS2 and WSe2 using ultrafast optical pulses. Despite these advances, understanding of valley-sensitive optical Stark shifts in TMDCs has been limited by reflectance-based detection methods where the signal is small and prone to background effects. More sensitive polarization-based spectroscopy is required to better probe ultrafast Stark shifts for all-optical manipulation of valley energy levels. Here, we show time-resolved Kerr rotation to be a more sensitive probe of the valley-selective optical Stark effect in monolayer TMDCs. Compared to the established time-resolved reflectance methods, Kerr rotation is less sensitive to background effects. Kerr rotation provides a fivefold improvement in the signal-to-noise ratio of the Stark effect optical signal and a more precise estimate of the energy shift. This increased sensitivity allows for observation of an optical Stark shift in monolayer MoS2 that exhibits both valley and energy selectivity, demonstrating the promise of this method for investigating this effect in other layered materials and heterostructures.
Moiré superlattices formed in van der Waals bilayers have enabled the creation and manipulation of new quantum states, as is exemplified by the discovery of superconducting and correlated insulating states in twi...
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Several classification methods assume that the underlying distributions follow tree-structured graphical models. Indeed, trees capture statistical dependencies between pairs of variables, which may be crucial to attai...
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Latent variable models with hidden binary units appear in various applications. Learning such models, in particular in the presence of noise, is a challenging computational problem. In this paper we propose a novel sp...
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In distributed simulation, the purpose of multi-resolution methods is to allow simulation integration getting consis- tent views of different resolutions. In these methods, chal- lenges in the treatment of aggregation...
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