297+ open-access research outputs.
Low-cost FPGA platforms can broaden access to neuromorphic systems research, but current spiking neural network (SNN) workflows remain divided between hardware-first implementations, which are difficu…
Heat waste is a bottleneck in the development of green information technologies and much effort has been devoted to suppress the heating effect in both electronic and spintronic devices. Here we take …
The field of attosecond physics has expanded significantly in recent years, yet experimental facilities supporting attosecond pump attosecond probe spectroscopy remain rare. Here, we present a newly c…
This paper presents the design and implementation of an asynchronous delta modulator as a spike encoder for event-driven neural recording in a 65nm CMOS process. The proposed neuromorphic front-end co…
Nonlinear processes, mediated by multiphoton interactions rather than single-photon response, drive numerous fundamental phenomena and momentous applications in modern physics. Among these processes, …
A 64-spin all-to-all current-mode coupling Ising machine is implemented in 65 nm CMOS. The design supports 31 coefficient levels in 0.943 mm2 and achieves Energy-to-Solution (ETS) of 2.28 nJ/edge-bit.…
Femtosecond laser micromachining (FLM) fabricated waveguides inherently form elliptical cores due to differences in focal spot size and the Rayleigh range of the microscope objective. Consequently, it…
We report on extensive experimental investigation of novel barium chalcogenides (BaGa4Se7, BaGa2GeSe6 and BaGa2GeS6) for generation of a strong narrowband terahertz (THz) radiation. The Ba-containing …
Droplet microlasers, as promising tools for biophotonics and biomedical sciences, have witnessed rapid advances due to their flexible reconfigurability, high sensitivity to stimuli, and label-free bio…
Topological active materials have emerged as powerful paradigm bridging the discovery of exotic topological phases of matter with the development of functional topological devices. The recent extensio…
We present an implementation of edge AI to compress data on an in-memory analog content-addressable memory (ACAM) device. A variational autoencoder is trained on a simulated sample of energy measureme…
We report a high-energy, bidirectional, dissipative soliton mode-locked fiber laser operating in the 1550 nm normal-dispersion regime. By leveraging intracavity dispersion management and a Lyot filter…
Motivation: mtDNA distance matrices are standard inputs for distance-based phylogeny, but computing all pairwise alignments is costly. Missing entries can degrade inferred topology and branch lengths,…
Reinforcement learning (RL) is a core technology enabling the transition of artificial intelligence (AI) from perception to decision-making, but its deployment on conventional electronic hardware suff…
X-ray calorimetric sample platforms combining specific heat and synchrotron x-ray measurements provide a powerful means to investigate fundamental material properties. Calorimeter cell designs featuri…
Demand for lower computing power has rapidly increased. In this context, brain-inspired neuromorphic computing, which integrate data storage and processing, has attracted significant attention. Here, …
AI tools are increasingly suggested as solutions to assist public agencies with heavy workloads. In public defense, where a constitutional right to counsel meets the complexities of law, overwhelming …
Multiphase fluid flows comprising of mesoscale solid particles, liquid droplets, or gas bubbles are common in both natural and man-made systems, but quantifying the energy transfer is challenging due …
Spectrally engineered multifrequency nanolasers are highly desirable for on-chip photonics, multiplexed biosensing, and display technologies; yet, achieving them within a single compact platform remai…
Scaling femtosecond terahertz (THz) and ultraviolet (UV) sources to high repetition rates is essential for high-throughput ultrafast spectroscopy and imaging applications. Yet, their efficient generat…
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