11,307+ open-access research outputs.
Semiconductor-based plasmonic nanostructures support localized surface plasmon modes in the infrared region. Unlike metallic nanostructures, they support both free electrons and holes, requiring a two…
Biological neurons perform arithmetic computations - including additive integration and divisive gain modulation - through synaptic conductance changes and shunting inhibition, enabling context-depend…
To construct dispersion relations for diffusion or oscillation processes on random networks, it is necessary to obtain effective length scales for the eigenvectors of a graph Laplacian matrix, whose e…
Momentum-space nonsymmorphic symmetries have recently attracted significant interest in both artificial and condensed-matter crystals, whereas real-space nonsymmorphic symmetries have long played an i…
Natural materials achieve adaptive behavior through hierarchical organization and coupled mechanisms across scales. Their translation into engineering, however, remains largely heuristic. What is miss…
First-principles atomistic simulations are essential for understanding complex material phenomena but are fundamentally limited by their computational cost. While Machine Learning Interatomic Potentia…
If dark matter consists of ultralight bosons, on galactic scales it can be effectively described as a coherent classical field experiencing oscillations. Such a field could perturb the dynamics of cel…
The measurement of polarization serves as an important probe to investigate the production mechanism of quarkonia, the bound state of heavy quark anti-quark (charm or bottom) pairs, in hadronic collis…
Entropic uncertainty relations are universal quantifiers of fundamental uncertainties of quantum measurements and are widely discussed in the quantum metrology literature. Quantum memory is a phenomen…
Deciphering the complicated interplay between collective and separate behaviors lies at the heart of first-order metal-insulator transition (MIT) in correlated electron systems, enabling the rational …
Artificial intelligent language-model based coding agents have significantly changed the way we interact with computers in our day-to-day, as it is common to use them to create, improve, and run progr…
Image classification is a core task of intelligent sensing, conventionally follows a sequential imaging then processing pipeline. However, redundant high-dimensional image reconstruction is inherently…
Synthetic materials are obtained by assembling atoms or artificial atoms into regular arrays, thereby forming artificial crystals that offer powerful platforms to emulate and explore condensed-matter …
Accurate and real-time sensing of targets in three-dimensional (3D) environments is essential for modern machine vision, underpinning emerging technologies such as autonomous systems, robotic manipula…
We study the early post-bounce neutrino signal of the published Garching $15\,M_\odot$ rotating core-collapse supernova (CCSN) sequence consisting of non-rotating (NR), slowly rotating (SR, $\Omega_0=…
Quantum neural networks generalize classical artificial neural networks into the quantum domain. They are formulated as parameterized quantum circuits which are optimized by measuring and minimizing a…
Material properties are fundamentally dictated by multiscale phenomena, which often reach mesoscale in size. The {\mu}m mesoscale is also the size which can be observed directly under an optical micro…
We study how stochastic resetting affects first-passage processes in systems of many interacting particles. While resetting is well understood for single-particle dynamics, its consequences for collec…
In artificial spin ice (ASI), magnetic interactions between nanomagnets determine both the stable states and the switching pathways under an applied field. Here, first-order reversal curve (FORC) meas…
Superfluorescence is a collective emission from several quantum emitters that initially have random phases and are then synchronized through vacuum field interactions. Despite its fascinating prospect…
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