Recent experiments demonstrating large spin-transfer torques in topological-insulator (TI)-ferromagnetic-metal (FM) bilayers have generated a great deal of excitement due to their potential applications in spintronics. The source of the observed spin-transfer torque, however, remains unclear. This is because the large charge transfer from the FM to the TI layer would prevent the Dirac cone at the interface from being anywhere near the Fermi level to contribute to the observed spin-transfer torque.

After decades of progress and effort, obtaining a phase diagram for a strongly correlated topological system still remains a challenge. Although in principle one could turn to Wilson loops and long-range entanglement, evaluating these nonlocal observables at many points in phase space can be prohibitively costly. With growing excitement over topological quantum computation comes the need for an efficient approach for obtaining topological phase diagrams. Here we turn to machine learning using quantum loop topography (QLT), a notion we have recently introduced.

We investigated the influence of metal coating on the optical characteristics of Si nanopillar (NP) arrays with and without thin metal layers coated on the sample surface. The reflection dips of the metal-coated arrays were much broader and more pronounced than those of the bare arrays. The coated metal layers consisted of two parts—the metal disks on the Si NP top and the holey metal backreflectors on the Si substrate.

We propose a strategy to achieve an unconventional superconductor in a heterostructure: use a quantum paramagnet (QPM) as a substrate for heterostructure growth of metallic films to design exotic superconductors. The proposed setup allows us to "customize" electron-electron interaction imprinted on the metallic layer. The QPM material of our choice is quantum spin ice. Assuming the metallic layer forms a single isotropic Fermi pocket, we predict its coupling to spin fluctuations in quantum spin ice will drive topological odd-parity pairing.

We address the nature of spin-orbit torques at the magnetic surfaces of topological insulators using the linear-response theory. We find that the so-called Dirac torques in such systems possess a different symmetry compared to their Rashba counterpart, as well as a high anisotropy as a function of the magnetization direction. In particular, the damping torque vanishes when the magnetization lies in the plane of the topological-insulator surface. We also show that the Onsager reciprocal of the spin-orbit torque, the charge pumping, induces an enhanced anisotropic damping.

Despite rapidly growing interest in harnessing machine learning in the study of quantum many-body systems, training neural networks to identify quantum phases is a nontrivial challenge. The key challenge is in efficiently extracting essential information from the many-body Hamiltonian or wave function and turning the information into an image that can be fed into a neural network. When targeting topological phases, this task becomes particularly challenging as topological phases are defined in terms of nonlocal properties.

Theoretically, it has been known that breaking spin degeneracy and effectively realizing spinless fermions is a promising path to topological superconductors. Yet, topological superconductors are rare to date. Here we propose to realize spinless fermions by splitting the spin degeneracy in momentum space. Specifically, we identify monolayer hole-doped transition metal dichalcogenide (TMD)s as candidates for topological superconductors out of such momentum-space-split spinless fermions.

Half-filled Landau levels form a zoo of strongly correlated phases. These include non-Fermi-liquids (NFLs), fractional quantum Hall (FQH) states, nematic phases, and FQH nematic phases. This diversity begs the following question: what keeps the balance between the seemingly unrelated phases? The answer is elusive because the Halperin-Lee-Read description that offers a natural departure point is inherently strongly coupled. However, the observed nematic phases suggest that nematic fluctuations play an important role.

There has been growing research interest in realizing optoelectronic devices based on the two-dimensional atomically thin semiconductor MoS2 owing to its distinct physical properties that set it apart from conventional semiconductors. However, there is little optical absorption in these extremely thin MoS2 layers, which presents an obstacle toward applying them for use in high-efficiency light-absorbing devices. We synthesized trilayers of MoS2 directly on SiO2/Si nanocone (NC) arrays using chemical vapor deposition and investigated their photodetection characteristics.

Upconversion is a unique optical property that is driven by a sequential photon pumping and generation of higher energy photons in a consecutive manner. The efficiency improvement in photovoltaic devices can be achieved when upconverters are integrated since upconverters contribute to the generation of extra photons. Despite numerous experimental studies confirming the relationship, fundamental explanations for a real contribution of upconversion to photovoltaic efficiency are still in demand.