arXiv subjects

Seou Choi

Publications and source records attributed to Seou Choi.

15 recordsLinked to original sources

arXiv2026

Nanophotonic control of spatial information in scintillation detectors

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 radiation dose. Scintillators are the dominant materials for detecting X-rays, but face a longstanding compromise: thick scintillators absorb X-rays effectively, whereas optical photons generated throughout their volume spread before detection, degrading spatial information. Existing scintillator architectures largely try to preserve resolution by physically confining light using pixels, columnar crystals, or microstructured channels. Here, we show that high-resolution detection does not require the volumetric confinement of scintillation light. A metalens integrated directly with a bulk scintillator uses nanophotonic wavefront control to preferentially transfer high-spatial-frequency information from volumetrically generated scintillation light to the detector, while retaining the X-ray absorption of a thick scintillator. We experimentally recover fine spatial detail in X-ray images of inorganic and biological specimens. In a detector geometry relevant to computed tomography (CT), the experimentally validated model predicts a fivefold reduction in required X-ray dose and a 25-fold increase in resolution bandwidth relative to a state-of-the-art pixelated scintillator. These results establish wavefront engineering as a route to separating efficient X-ray absorption from optical image formation, with the potential for substantially higher-resolution, lower-dose CT.

physics.optics↗

arXiv2026

Vacuum Fluctuation-Induced State Switching in Degenerate Optical Parametric Oscillators

Bistable driven-dissipative systems near bifurcations can exhibit noise-activated switching between steady states. Here, we investigate how quantum vacuum fluctuations induce such switching in a biased optical parametric oscillator (OPO), a nonlinear system with intrinsic bistability. We show how microscopic quantum fluctuations driving macroscopic transitions can be controlled with an external bias field that reshapes the OPO steady-state metapotential. We derive analytical expressions for the average switching time and validate them through simulations of the OPO field distribution and inter-state probability flow under bias injection. We further examine how switching depends on bias strength, pump gain, and optical nonlinearity. Our findings clarify how quantum noise can shape macroscopic dynamics and provide a foundation for noise-assisted photonic machine learning and probabilistic quantum gates.

quant-ph↗

arXiv2026

Supercollimating photonic crystal scintillators

Scintillators convert X-ray energy into visible or near-visible photons, enabling applications in high-energy particle detection and X-ray imaging. Increasing scintillator thickness improves X-ray absorption but degrades spatial resolution due to diffraction-induced lateral spreading of emitted light, resulting in a fundamental trade-off between detection efficiency and image resolution. Here, we propose a class of three-dimensional photonic crystal scintillators that overcomes this limitation through supercollimation, in which light propagates with suppressed diffraction. We develop a multiscale modeling framework that integrates nanophotonic band-structure simulations with Monte Carlo particle transport to quantitatively evaluate the performance of such scintillators. Our results show that supercollimating photonic crystal scintillators can enhance spatial resolution by up to an order of magnitude relative to conventional bulk scintillators of equal thickness. This improvement leads to a substantial increase in detector quantum efficiency (DQE), particularly at high spatial frequencies, enabling fine features to be preserved at reduced X-ray dose. We further demonstrate that comparable image quality can be achieved with approximately an order-of-magnitude lower X-ray dose. By directly engineering light transport within the bulk of the scintillator, this work establishes a nanophotonic route to simultaneously improving resolution and dose efficiency in X-ray imaging.

physics.optics↗

arXiv2026

Hybrid Nanophotonic Scintillators for Enhanced X-ray Absorption, Emission, and Time Resolution

Scintillators convert ionizing radiation into visible photons, enabling applications from cosmic ray detection to medical imaging. Two independent strategies for improving scintillator performance via nanoscale patterning have recently been demonstrated: engineering material properties to enhance absorption of ionizing radiation and integrating nanophotonic structures to enhance the spontaneous emission rate ("nanophotonic scintillators"). Here, we propose a nanophotonic scintillator that simultaneously enhances both the initial energy conversion and the spontaneous emission rate, by periodically stacking a fast-emitting scintillator and a visible-light-transparent material with strong X-ray attenuation ("stopping layer") to form a one-dimensional (1D) photonic crystal (PhC) scintillator. Photoelectric absorption in the stopping layer increases the number of photoelectrons that deposit energy in neighboring scintillator layers and contribute to scintillation. At the same time, the spontaneous emission rate is enhanced by the nanophotonic structuring itself. We design a 1D PhC comprising an organic scintillator and indium tin oxide (ITO) as the stopping layer and numerically simulate the enhancement in scintillation yield and decay rate. The total detected light output is enhanced by up to a factor of 700 compared to a bulk organic scintillator of equal thickness. We further investigate a 1D PhC structure integrating inorganic and organic scintillators for time-of-flight positron emission tomography (TOF-PET): replacing the non-scintillating stopping layer with an inorganic scintillator further increases the light yield, and the coincidence time resolution (CTR) is enhanced up to 3.5 times compared to a bulk inorganic scintillator of equal thickness. Our work presents a unified approach to improve key scintillation parameters within a single nanophotonic structure.

physics.optics↗

arXiv2026

A Framework for Closed-Loop Robotic Assembly, Alignment and Self-Recovery of Precision Optical Systems

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 manual. Optical systems impose strict spatial and angular tolerances, and their performance is governed by tightly coupled physical parameters, making generalizable automation particularly challenging. In this work, we present a robotics framework for the autonomous construction, alignment, and maintenance of precision optical systems. Our approach integrates hierarchical computer vision systems, optimization routines, and custom-built tools to achieve this functionality. As a representative demonstration, we perform the fully autonomous construction of a tabletop laser cavity from randomly distributed components. The system performs several tasks such as laser beam centering, spatial alignment of multiple beams, resonator alignment, laser mode selection, and self-recovery from induced misalignment and disturbances. By achieving closed-loop autonomy for highly sensitive optical systems, this work establishes a foundation for autonomous optical experiments for applications across technical domains.

cs.RO↗

arXiv2026

Wavefront Engineering for Scintillation-Based Imaging

Recent research in nanophotonics for scintillation-based imaging has demonstrated promising improvements in scintillator performance. In parallel, advances in nanophotonics have enabled wavefront control through metasurfaces, a capability that has transformed fields such as microscopy by allowing tailored control of optical propagation. This naturally raises the following question, which we address in this perspective: can wavefront-control strategies be leveraged to improve scintillation-based imaging? To answer this question, we explore nanophotonic- and metasurface-enabled wavefront control in scintillators to mitigate image blurring arising from their intrinsically diffuse light emission. While depth-of-field extension in scintillation faces fundamental limitations absent in microscopy, this approach reveals promising avenues, including stacked scintillators, selective spatial-frequency enhancement, and X-ray energy-dependent imaging. These results clarify the key distinctions in adapting wavefront engineering to scintillation and its potential to enable tailored detection strategies.

physics.optics↗

arXiv2025

Nanophotonic thermal management in X-ray tubes

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 management is a critical barrier to the development of more powerful X-ray tubes with higher brightness and spatial coherence, which are needed to translate imaging modalities such as phase-contrast imaging to the clinic. In rotating anode X-ray tubes, the most common design, thermal radiation is a bottleneck that prevents efficient cooling of the anode$\unicode{x2014}$the hottest part of the device by far. We predict that nanophotonically patterning the anode of an X-ray tube enhances heat dissipation via thermal radiation, enabling it to operate at higher powers without increasing in temperature. The focal spot size, which is related to the spatial coherence of generated X-rays, can also be made smaller at a constant temperature. A major advantage of our "nanophotonic thermal management" approach is that in principle, it allows for complete control over the spectrum and direction of thermal radiation, which can lead to optimal thermal routing and improved performance.

physics.optics↗

arXiv2025

Probing intensity noise in ultrafast pulses using the dispersive Fourier transform augmented by quantum sensitivity analysis

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 -- both how they emerge and how they can be tailored to emerging applications, from multimode quantum light generation to optical computing. Soliton fission and Raman scattering comprise two such phenomena that are ideal testbeds for exploring multimode nonlinear optics, especially power-dependent physics. To fully capture the complexity of such processes, an experimental measurement technique capable of measuring shot-to-shot pulse variations is necessary. The dispersive Fourier transform (DFT) is the ideal technique to achieve this goal, using chromatic dispersion to temporally stretch an ultrafast pulse and map its spectrum onto a measurable temporal waveform. Here, we apply DFT to explore the power-dependent mean field and noise properties of soliton fission and Raman scattering. To explain quantum noise properties, the traditional approach is to perform several hundred stochastic simulations for computing statistics. In our work, we apply quantum sensitivity analysis (QSA) to compute the noise in any output observable based on fluctuations in the input pulse, all using a single backwards differentiation step. We find that the combination of DFT and QSA provides a powerful framework for understanding the quantum and classical properties of soliton fission and Raman scattering, and can be generalized to other multimode nonlinear phenomena.

physics.optics↗

arXiv2024

Quantum sensitivity of parametric oscillators

Many quantum systems exhibit high sensitivity to their initial conditions, where microscopic quantum fluctuations can significantly influence macroscopic observables. Understanding how quantum states may influence the behavior of nonlinear dynamic systems may open new avenues in controlling light-matter interactions. To explore this issue, we analyze the sensitivity of a fundamental quantum optical process - parametric oscillation - to quantum initializations. Focusing on optical parametric oscillators (OPOs), we demonstrate that the quantum statistics of arbitrary initial states are imprinted in the early-stage dynamics and can persist in the steady-state probabilities. We derive the "quantum sensitivity" of parametric oscillators, linking the initial quantum state to the system's steady-state outcomes, highlighting how losses and parametric gain govern the system's quantum sensitivity. Moreover, we show that these findings extend beyond OPOs to a broader class of nonlinear systems, including Josephson junction based superconducting circuits. Our work opens the way to a new class of experiments that can test the sensitivity of macroscopic systems to quantum initial conditions and offers a pathway for controlling systems with quantum degrees of freedom.

quant-ph↗

arXiv2024

Observing the dynamics of quantum states generated inside nonlinear optical cavities

Quantum states at optical frequencies are often generated inside cavities to facilitate strong nonlinear interactions. However, measuring these quantum states with traditional homodyne techniques poses a challenge, as outcoupling from the cavity disturbs the state's quantum properties. Here, we propose a framework for reconstructing quantum states generated inside nonlinear optical cavities and observing their dynamics. Our approach directly imprints the field distribution of the cavity quantum state onto the statistics of bistable cavity steady-states. We propose a protocol to fully reconstruct the cavity quantum state, visualized in 2D phase-space, by measuring the changes in the steady-state statistics induced by a probe signal injected into the cavity under different condition. We experimentally demonstrate our approach in a degenerate optical parametric oscillator, generating and reconstructing the quasi-probability distribution of different quantum states. As a validation, we reconstruct the Husimi Q function of the cavity squeezed vacuum state. In addition, we observe the evolution of the quantum vacuum state inside the cavity as it undergoes phase-sensitive amplification. By enabling generation and measurement of quantum states in a single nonlinear optical cavity, our method realizes an "end-to-end" approach to intracavity quantum tomography, facilitating studies of quantum optical phenomena in nonlinear driven-dissipative systems.

quant-ph↗

arXiv2024

End-to-end design of multicolor scintillators for enhanced energy resolution in X-ray imaging

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 medical imaging and high-energy physics. Recent advances in the artificial structuring of scintillators offer new opportunities for improving the energy resolution of scintillator-based X-ray detectors. Here, we present a three-bin energy-resolved X-ray imaging framework based on a three-layer multicolor scintillator used in conjunction with a physics-aware image postprocessing algorithm. The multicolor scintillator is able to preserve X-ray energy information through the combination of emission wavelength multiplexing and energy-dependent isolation of X-ray absorption in specific layers. The dominant emission color and the radius of the spot measured by the detector are used to infer the incident X-ray energy based on prior knowledge of the energy-dependent absorption profiles of the scintillator stack. Through ab initio Monte Carlo simulations, we show that our approach can achieve an energy reconstruction accuracy of 49.7%, which is only 2% below the maximum accuracy achievable with realistic scintillators. We apply our framework to medical phantom imaging simulations where we demonstrate that it can effectively differentiate iodine and gadolinium-based contrast agents from bone, muscle, and soft tissue.

physics.ins-det↗

arXiv2024

Large-scale self-assembled nanophotonic scintillators for X-ray imaging

Scintillators are essential for converting X-ray energy into visible light in imaging technologies. Their widespread application in imaging technologies has been enabled by scalable, high-quality, and affordable manufacturing methods. Nanophotonic scintillators, which feature nanostructures at the scale of their emission wavelength, provide a promising approach to enhance emission properties like light yield, decay time, and directionality. However, scalable fabrication of such nanostructured scintillators has been a significant challenge, impeding their widespread adoption. Here, we present a scalable fabrication method for large-area nanophotonic scintillators based on the self-assembly of chalcogenide glass photonic crystals. This technique enables the production of nanophotonic scintillators over wafer-scale areas, achieving a six-fold enhancement in light yield compared to unpatterned scintillators. We demonstrate this approach using a conventional X-ray scintillator material, cerium-doped yttrium aluminum garnet (YAG:Ce). By analyzing the influence of surface nanofabrication disorder, we establish its effect on imaging performance and provide a route towards large-scale scintillation enhancements without decrease in spatial resolution. Finally, we demonstrate the practical applicability of our nanophotonic scintillators through X-ray imaging of biological and inorganic specimens. Our results indicate that this scalable fabrication technique could enable the industrial implementation of a new generation of nanophotonic-enhanced scintillators, with significant implications for advancements in medical imaging, security screening, and nondestructive testing.

physics.optics↗

arXiv2024

Stochastic logic in biased coupled photonic probabilistic bits

Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. An important computing approach that is still missing its corresponding optical hardware is probabilistic computing, used e.g. for solving difficult combinatorial optimization problems. In this study, we propose an experimentally viable photonic approach to solve arbitrary probabilistic computing problems. Our method relies on the insight that coherent Ising machines composed of coupled and biased optical parametric oscillators can emulate stochastic logic. We demonstrate the feasibility of our approach by using numerical simulations equivalent to the full density matrix formulation of coupled optical parametric oscillators.

physics.optics↗

arXiv2024

Photonic probabilistic machine learning using quantum vacuum noise

Probabilistic machine learning utilizes controllable sources of randomness to encode uncertainty and enable statistical modeling. Harnessing the pure randomness of quantum vacuum noise, which stems from fluctuating electromagnetic fields, has shown promise for high speed and energy-efficient stochastic photonic elements. Nevertheless, photonic computing hardware which can control these stochastic elements to program probabilistic machine learning algorithms has been limited. Here, we implement a photonic probabilistic computer consisting of a controllable stochastic photonic element - a photonic probabilistic neuron (PPN). Our PPN is implemented in a bistable optical parametric oscillator (OPO) with vacuum-level injected bias fields. We then program a measurement-and-feedback loop for time-multiplexed PPNs with electronic processors (FPGA or GPU) to solve certain probabilistic machine learning tasks. We showcase probabilistic inference and image generation of MNIST-handwritten digits, which are representative examples of discriminative and generative models. In both implementations, quantum vacuum noise is used as a random seed to encode classification uncertainty or probabilistic generation of samples. In addition, we propose a path towards an all-optical probabilistic computing platform, with an estimated sampling rate of ~ 1 Gbps and energy consumption of ~ 5 fJ/MAC. Our work paves the way for scalable, ultrafast, and energy-efficient probabilistic machine learning hardware.

physics.optics↗

arXiv2023

Biasing the quantum vacuum to control macroscopic probability distributions

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 variance, leading to ubiquitous effects such as spontaneous emission, the Lamb shift, the Casimir effect, and more. These "vacuum fluctuations" have also been harnessed as a source of perfect randomness, for example to generate perfectly random photonic bits. Despite these achievements, many potential applications of quantum randomness in fields such as probabilistic computing rely on controllable probability distributions, which have not yet been realized on photonic platforms. In this work, we show that the injection of vacuum-level "bias" fields into a multi-stable optical system enables a controllable source of "biased" quantum randomness. We demonstrate this concept in an optical parametric oscillator (OPO). Ordinarily, an OPO initiated from the ground state develops a signal field in one of two degenerate phase states (0 and $\pi$) with equal probability. By injecting bias pulses which contain less than one photon on average, we control the probabilities associated with the two output states, leading to the first controllable photonic probabilistic bit (p-bit). We shed light on the physics behind this process, showing quantitative agreement between theory and experiment. Finally, we demonstrate the potential of our approach for sensing sub-photon level fields by showing that our system is sensitive to the temporal shape of bias field pulses far below the single photon level. Our results suggest a new platform for the study of stochastic quantum dynamics in nonlinear driven-dissipative systems, and point toward possible applications in ultrafast photonic probabilistic computing, as well as the sensing of extremely weak fields.

quant-ph↗