Publications
Γ-VAE: Curvature regularized variational autoencoders for uncovering emergent low dimensional geometric structure in high dimensional data
Natural systems with emergent behaviors often organize along low-dimensional subsets of high-dimensional spaces. For example, despite the tens of thousands of genes in the human genome, the principled study of genomics is fruitful because biological processes rely on coordinated organization that results in lower dimensional phenotypes. To uncover this organization, many nonlinear dimensionality reduction techniques have successfully embedded high-dimensional data into low-dimensional spaces by preserving local similarities between data points.
Cross Layer Design for the Predictive Assessment of Technology-Enabled Architectures
There is great interest in “end-to-end” analysis that captures how innovation at the materials, device, and/or archi-tectural levels will impact figures of merit at the application-level. However, there are numerous combinations of devices and architectures to study, and we must establish systematic ways to accurately explore and cull a vast design space. We aim to capture how innovations at the materials/device-level may ultimately impact figures of merit associated with both existing and emerging technologies that may be employed for either logic and/or memory.
An algorithm for subtraction of doublet emission lines in angle-resolved photoemission spectroscopy
Plasma discharge lamps are widely utilized in the practice of angle-resolved photoemission spectroscopy (ARPES) experiments as narrow-linewidth ultraviolet photon sources. However, many emission lines such as Ar-I, Ne-I, and Ne-II have closely spaced doublet emission lines, which result in superimposed replica on the measured ARPES spectra. Here, we present a simple method for subtracting the contribution of these doublet emission lines from photoemission spectra.
Giant spin Hall effect in AB-stacked MoTe2/WSe2 bilayers
The spin Hall effect (SHE), in which an electrical current generates a transverse spin current, plays an important role in spintronics for the generation and manipulation of spin-polarized electrons. The phenomenon originates from spin–orbit coupling. In general, stronger spin–orbit coupling favours larger SHEs but shorter spin relaxation times and diffusion lengths. However, correlated magnetic materials often do not support large SHEs.
Remote imprinting of moiré lattices
Two-dimensional moiré materials are formed by overlaying two layered crystals with small differences in orientation or/and lattice constant, where their direct coupling generates moiré potentials. Moiré materials have emerged as a platform for the discovery of new physics and device concepts, but while moiré materials are highly tunable, once formed, moiré lattices cannot be easily altered. Here we demonstrate the electrostatic imprinting of moiré lattices onto a target monolayer semiconductor.
ZrNb(CO) RF Superconducting Thin Film with High Critical Temperature in the Theoretical Limit
Superconducting radio-frequency (SRF) resonators are critical components for particle accelerator applications, such as free-electron lasers, and for emerging technologies in quantum computing. Developing advanced materials and their deposition processes to produce RF superconductors that yield nΩ surface resistances is a key metric for the wider adoption of SRF technology. Here, ZrNb(CO) RF superconducting films with high critical temperatures (Tc) achieved for the first time under ambient pressure are reported.
Machine learning reveals features of spinon Fermi surface
With rapid progress in simulation of strongly interacting quantum Hamiltonians, the challenge in characterizing unknown phases becomes a bottleneck for scientific progress. We demonstrate that a Quantum-Classical hybrid approach (QuCl) of mining sampled projective snapshots with interpretable classical machine learning can unveil signatures of seemingly featureless quantum states.
Bragg glass signatures in PdxErTe3 with X-ray diffraction temperature clustering
The Bragg glass phase is a nearly perfect crystal with glassy features predicted to occur in vortex lattices and charge-density-wave systems in the presence of disorder. Detecting it has been challenging, despite its sharp theoretical definition in terms of diverging correlation lengths. Here we present bulk probe evidence supporting a Bragg glass phase in the systematically disordered charge-density-wave material of PdxErTe3. We do this by using comprehensive X-ray data and a machine-learning-based analysis tool called X-ray diffraction temperature clustering (X-TEC).
Anterior forebrain pathway in parrots is necessary for producing learned vocalizations with individual signatures
Parrots have enormous vocal imitation capacities and produce individually unique vocal signatures. Like songbirds, parrots have a nucleated neural song system with distinct anterior (AFP) and posterior forebrain pathways (PFP). To test if song systems of parrots and songbirds, which diverged over 50 million years ago, have a similar functional organization, we first established a neuroscience-compatible call-and-response behavioral paradigm to elicit learned contact calls in budgerigars (Melopsittacus undulatus).
Comparing study features is easy but identifying next steps is hard: Evaluating critical thinking through the Biology Lab Inventory of Critical Thinking in Ecology
Critical thinking, which can be defined as the evidence-based ways in which people decide what to trust and what to do, is an important competency included in many undergraduate science, technology, engineering, and mathematics (STEM) courses. To help instructors effectively measure critical thinking, we developed the Biology Lab Inventory of Critical Thinking in Ecology (Eco-BLIC), a freely available, closed-response assessment of undergraduate students' critical thinking in ecology.