51 citations · 88 across the 13 of their papers we have counts for
15 papers
Vision-Language Agents for Active Perception in Optics Laboratories
Ryan Lopez, Sachin Vaidya, Seou Choi +2
Vision-language models (VLMs) are increasingly being used in scientific workflows, but their ability as agents to directly control laboratory experiments from visual feedback remai…
A Programmable Optics Cloud Laboratory
Sachin Vaidya, Caio Silva, Seou Choi +2
Laboratory automation can improve experimental throughput, accessibility, and reproducibility, but many robotic laboratory systems remain difficult to reconfigure. This challenge i…
Nanophotonic control of spatial information in scintillation detectors
Joshua Chen, Simo Pajovic, Seou Choi +9
X-rays enable non-invasive imaging across medicine, security, materials science, and beyond, yet modern systems remain constrained by the need to resolve finer structures at lower…
Vacuum Fluctuation-Induced State Switching in Degenerate Optical Parametric Oscillators
Yihao Huang, Seou Choi, Rom Simovitch +5
Bistable driven-dissipative systems near bifurcations can exhibit noise-activated switching between steady states. Here, we investigate how quantum vacuum fluctuations induce such…
A Framework for Closed-Loop Robotic Assembly, Alignment and Self-Recovery of Precision Optical Systems
Seou Choi, Sachin Vaidya, Caio Silva +4
Robotic automation has transformed scientific workflows in domains such as chemistry and materials science, yet free-space optics, which is a high precision domain, remains largely…
Wavefront Engineering for Scintillation-Based Imaging
Joshua Chen, Sachin Vaidya, Simo Pajovic +7
Recent research in nanophotonics for scintillation-based imaging has demonstrated promising improvements in scintillator performance. In parallel, advances in nanophotonics have en…
Nanophotonic thermal management in X-ray tubes
Simo Pajovic, Charles Roques-Carmes, Seou Choi +5
In X-ray tubes, more than 99% of the kilowatts of power supplied to generate X-rays via bremsstrahlung are lost in the form of heat generation in the anode. Therefore, thermal mana…
Probing intensity noise in ultrafast pulses using the dispersive Fourier transform augmented by quantum sensitivity analysis
Shiekh Zia Uddin, Sahil Pontula, Jiaxin Liu +4
To reach the next frontier in multimode nonlinear optics, it is crucial to better understand the classical and quantum phenomena of systems with many interacting degrees of freedom…
Quantum sensitivity of parametric oscillators
Alex Gu, Jamison Sloan, Charles Roques-Carmes +6
Many quantum systems exhibit high sensitivity to their initial conditions, where microscopic quantum fluctuations can significantly influence macroscopic observables. Understanding…
Observing the dynamics of quantum states generated inside nonlinear optical cavities
Seou Choi, Yannick Salamin, Charles Roques-Carmes +3
Quantum states at optical frequencies are often generated inside cavities to facilitate strong nonlinear interactions. However, measuring these quantum states with traditional homo…
Large-scale self-assembled nanophotonic scintillators for X-ray imaging
Louis Martin-Monier, Simo Pajovic, Muluneh G. Abebe +9
Scintillators are essential for converting X-ray energy into visible light in imaging technologies. Their widespread application in imaging technologies has been enabled by scalabl…
End-to-end design of multicolor scintillators for enhanced energy resolution in X-ray imaging
Seokhwan Min, Seou Choi, Simo Pajovic +5
Scintillators have been widely used in X-ray imaging due to their ability to convert high-energy radiation into visible light, making them essential for applications such as medica…
Stochastic logic in biased coupled photonic probabilistic bits
Michael Horodynski, Charles Roques-Carmes, Yannick Salamin +4
Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. A…
Photonic probabilistic machine learning using quantum vacuum noise
Seou Choi, Yannick Salamin, Charles Roques-Carmes +7
Probabilistic machine learning utilizes controllable sources of randomness to encode uncertainty and enable statistical modeling. Harnessing the pure randomness of quantum vacuum n…
Biasing the quantum vacuum to control macroscopic probability distributions
Charles Roques-Carmes, Yannick Salamin, Jamison Sloan +7
One of the most important insights of quantum field theory is that electromagnetic fields must fluctuate. Even in the vacuum state, the electric and magnetic fields have a nonzero…