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At least 199 records · Page 11

Resonant metasurface‐enabled quantum light sources for single‐photon emission and entangled photon‐pair generation

Light encodes information in multiple degrees of freedom (e.g., frequency, amplitude, and phase), enabling high‐speed, high‐bandwidth communication through fiber optics. Unlike classical light, quantum light (single or entangled photons) can transmit quantum states over long distances without loss of coherence, thereby coherently interconnecting quantum nodes for distributed quantum entanglement. Quantum light sources are critical for developing scalable quantum networks aimed at distributed quantum computing, quantum teleportation, and secure quantum communications. However, existing quantum light sources suffer from limited integrability, insufficient spectral and spatial tunability, and inefficiencies in achieving mass‐produced, deterministic, on‐demand quantum light generation. These limitations significantly hinder progress toward direct, on‐chip integration with quantum processing units and detectors – an essential step toward scalable quantum networks. Resonant metasurfaces that leverage photonic modes – such as Mie resonances, guided‐mode resonances, or symmetry‐protected bound states in the continuum – offer strong spatial and temporal confinement of electromagnetic fields, characterized by high quality factors and small mode volumes. These metasurfaces greatly enhance linear and nonlinear light‐matter interactions, making them ideal for efficient on‐chip quantum light generation and manipulation. Here, we describe recent advances in nanoscale quantum light sources and quantum photonic state manipulation enabled by resonant metasurfaces. We also provide an outlook on next‐generation miniaturized quantum light sources achievable through materials innovations in quantum emitters, the co‐design of resonant metasurfaces, and ultimately, the heterogeneous integration of emerging layered van der Waals materials with resonant metasurfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗

Terahertz Spectroscopy of Gas Mixtures with Dual Quantum Cascade Laser Frequency Combs

Terahertz laser frequency combs based on quantum cascade lasers provide coherent, broadband, electrically pumped, THz radiation sources for use in future spectroscopic applications. In this work, we explore the feasibility of such lasers in a dual-comb spectroscopy configuration for the detection of multiple molecular samples in the gas phase. The lasers span approximately 180 GHz of optical bandwidth, centered at 3.4 THz, with submilliwatt total optical power. One of the main advantages of dual-comb spectroscopy is its high speed, which opens up the possibility for direct observations of chemical reaction dynamics in the terahertz spectral region. As a proof-of-concept, we recorded continuously evolving spectra from gas mixtures with 1 ms temporal resolution.

42 ENGINEERING↗

Refined interpretation of electron temperature response to neutral beam injection at DIII-D

Accurate particle and power deposition profiles of neutral beam injection (NBI) are essential to transport studies, and that information is usually acquired through Monte Carlo simulations with a given collisional model. The deposition process of the energetic beam particles leads to the informative electron temperature (T e ) evolution trajectory, which can be captured by electron cyclotron emission (ECE) system due to its good spatial and temporal resolution. Previously, some work has been done to interpret the T e responses to the pulsed NBI as a linear heating source with Fourier-based techniques, although that approach fell short when the fast ion slowing-down time becomes significant (~100 ms). It has been observed in DIII-D that the modulated NBI pulses (10–50 Hz) reduce local core T e values ~0.1 keV through cold electron dilution in high-T e (>2 keV) plasmas alongside accumulative heating. Here, a novel approach to interpret the T e response to NBI was developed by linearizing and modeling the detailed T e evolution trajectory using coherently averaged ECE data based on the different time scales of the terms in the local power and particle balance equations. The technique does not require absolute calibrations of ECE and is independent of collisional models. The resulting beam deposition profiles show good consistency and reasonable agreement with Monte Carlo calculations based on the atomic data from the Atomic Data and Analysis Structure (ADAS). Local electron density response measured by Thomson scattering (TS) also suggests the same features when the beam pulse is large enough for that diagnostic to resolve. The remaining discrepancies are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-resolution in-situ characterization of laser powder bed fusion via transmission X-ray microscopy at X-ray free electron lasers

In this work, we describe the instrumentation used to perform the first operando transmission X-ray microscopy (TXM) and simultaneous X-ray diffraction of laser melting simulating laser powder bed fusion on the XCS instrument at the Linac Coherent Light Source (LCLS) X-ray free-electron laser (XFEL). Our TXM with 40× magnification in the X-ray regime at 11 keV gave spatial resolutions down to 940 nm per line pair, with effective pixel sizes down to 206 nm, image integration times of <100 fs, and frame rates tunable between 2.1 and 119 ns for two probe frames (0.48 GHz to 8.4 MHz). Images were recorded on Zyla and Icarus (UXI) detectors to trade off between spatial resolution and time dynamics. A 1 kW CW IR laser was coupled into the interaction point to conduct pump–probe studies of laser melting and solidification dynamics. Our temporal and spatial resolution with attenuation-based contrast exceeds that currently possible with synchrotron-based high-speed radiography. This system was sensitive to feature velocities of 10–12000 m s −1 but we did not observe any motion in this range in the laser melting of Al6061 alloy. Shockwaves were not observed and hot cracking proceeded at velocities below the detection limits. Pore accumulation was observed between successive shots, indicating that bubble escape mechanisms were not active. With proper experimental design, the spatial resolution, contrast and field of view could be further improved or modified. The increased brightness and narrower bandwidth of the XFEL allowed for this imaging technique and it lays the groundwork for a wide range of operando techniques to study additive manufacturing.

47 OTHER INSTRUMENTATION↗

Vibronic exciton model for low bandgap donor–acceptor polymers

In this study, a vibronic exciton model is introduced to describe the excited state band structure and associated absorption spectra of low bandgap donor–acceptor conjugated polymers. The Hamiltonian is represented in a diabatic basis consisting of Frenkel-like donor and acceptor fragment excitations as well as charge-transfer (CT) excitations between neighboring fragments. States are coupled to each other through electron and hole transfer as well as Coulombically, through interacting fragment transition dipole moments. Local vibronic coupling involving the prominent aromatic-quinoidal vibrational mode, which is responsible for pronounced vibronic progressions in most conjugated oligomers and polymers, is also included. The DAD repeat unit is shown to behave like a J-aggregate trimer, driven by both the sizable in-phase electron and hole transfer integrals between donor and acceptor fragments as well as negative Coulomb coupling between donor and acceptor fragment excitations. The J-aggregate behavior is enhanced in the polymer limit through inter-repeat unit coupling, with the 0–0 vibronic peak significantly enhanced in the lowest-energy near-IR band. In addition, the radiative rate is enhanced by the number of coherently connected repeat units. The near-IR band is shown to possess roughly equal admixtures of CT and Frenkel-like excitations. Applications are made to the polymer PffBT4T-2DT, with the simulated absorption spectrum quantitatively capturing the salient features of the measured spectrum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resonant propagation of extreme-ultraviolet pulses through strongly driven high-density media

We show that by combining strong-field dressing and resonant propagation of XUV pulses, the transition of absorption lines from their natural Lorentzian profiles through Fano and complex multipeak shapes all the way back to broadened near-Lorentzian profiles can be achieved, in the limit of optically thick samples. The final stage of this spectral modification can be understood in terms of a significant temporal stretching and delay of the resonant XUV pulse as it propagates through the dense gas, which alters the ultrafast absorption that is modified by the time-synchronized few-femtosecond laser pulse. We first demonstrate this concept in numerical calculations, both using a model system and through a fully coupled solution of the time-dependent Schrödinger equation and the Maxwell wave equation. The applicability and generality of the underlying mechanism is then illustrated in proof-of-principle attosecond transient absorption measurements in a helium gas with a widely varying atomic density. These results provide insights into the interaction of ultrashort laser pulses with dense media and its coherent control. Published by the American Physical Society 2025

He, Yu (ORCID:0000000152120176)↗

High resolution density pedestal measurements during edge localized modes by short-pulse reflectometry in the TCV tokamak

This publication presents high spatio-temporal resolution (mm/μs) density profile measurements of the pedestal top during type I, III, and small edge localized mode (ELM) H-mode plasmas in the Tokamak à Configuration Variable (TCV). These measurements were performed using a novel short-pulse reflectometer. Average inter-ELM density profiles are obtained via conditional averaging using the Dα trace as ELM indicator. Changes to the pedestal density profile gradients prior to type-III ELMs reveal unique pedestal dynamics leading to the ELM crash which can provide important experimental data for validation of non-linear MHD ELM simulations. The small-ELM scenario is found to feature a ∼25-35 kHz quasi-coherent density fluctuation near the separatrix rho_psi ∼0.993-1.05 not observed during a similar type-I ELM discharge. This oscillation is also found in low-field-side magnetic pick- up probes displaying a ballooning character and n=+1 toroidal mode number. This oscillation could help explain the markedly different pedestal dynamics observed in the small-ELM regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Seeking Repeating Anthropogenic Seismic Sources: Implications for Seismic Velocity Monitoring at Fault Zones

Abstract Seismic velocities in rocks are highly sensitive to changes in permanent deformation and fluid content. The temporal variation of seismic velocity during the preparation phase of earthquakes has been well documented in laboratories but rarely observed in nature. It has been recently found that some anthropogenic, high‐frequency (>1 Hz) seismic sources are powerful enough to generate body waves that travel down to a few kilometers and can be used to monitor fault zones at seismogenic depth. Anthropogenic seismic sources typically have fixed spatial distribution and provide new perspectives for velocity monitoring. In this work, we propose a systematic workflow to seek such powerful seismic sources in a rapid and straightforward manner. We tackle the problem from a statistical point of view, considering that persistent, powerful seismic sources yield highly coherent correlation functions (CFs) between pairs of seismic sensors. The algorithm is tested in California and Japan. Multiple sites close to fault zones show high‐frequency CFs stable for an extended period of time. These findings have great potential for monitoring fault zones, including the San Jacinto Fault and the Ridgecrest area in Southern California, Napa in Northern California, and faults in central Japan. However, extra steps, such as beamforming or polarization analysis, are required to determine the dominant seismic sources and study the source characteristics, which are crucial to interpreting the velocity monitoring results. Train tremors identified by the present approach have been successfully used for seismic velocity monitoring of the San Jacinto Fault in previous studies.

58 GEOSCIENCES↗

High resolution density pedestal measurements during edge localized modes by short-pulse reflectometry in the TCV tokamak

Here, this publication presents high spatio-temporal resolution (mm µs -1 ) density profile measurements of the pedestal top during type I, III, and small edge localized mode (ELM) H-mode plasmas in the tokamak à configuration variable (TCV). These measurements were performed using a novel short-pulse reflectometer. Average inter-ELM density profiles are obtained via conditional averaging using the D α trace as ELM indicator. Changes to the pedestal density profile gradients prior to type-III ELMs reveal unique pedestal dynamics leading to the ELM crash which can provide important experimental data for validation of non-linear MHD ELM simulations. The small-ELM scenario is found to feature a ~25–35 kHz quasi-coherent density fluctuation near the separatrix ρ ψ 0.993–1.05 not observed during a similar type-I ELM discharge. This oscillation is also found in low-field-side magnetic pick-up probes displaying a ballooning character and n = +1 toroidal mode number. This oscillation could help explain the markedly different pedestal dynamics observed in the small-ELM regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Kinetic effects of self-organization in low-temperature magnetized plasmas (Final Report for DE-SC0019045: 9/1/2018-8/31/2019)

The research goal of this Early Career Research Program project is to advance the science of low temperature magnetized plasmas using first-principles kinetic, e.g., solving the Boltzmann equation, models. A better understanding of the plasma transport properties, such as electrical resistivity and thermal conductivity must be obtained to better control and design magnetized plasma sources. A key physical phenomenon in low-temperature magnetized plasmas is the self-organization of plasma flows, e.g., coherent plasma structures and transition between different discharge modes. Understanding the physics of coherent plasma structures has been identified as one of the four important frontier topics in a recent workshop by the Office of Fusion Energy Science. These self-emerging plasma patterns results from the nonlinear coupling between plasma constituents (ions, electrons, and neutral atoms), electromagnetic fields, and materials. The physics of low-temperature magnetized plasmas is particularly complex because (i) the collisionless instabilities affect collisional phenomena (ionization, transport, etc.) and vice versa and (ii) the presence of materials (sheath, electron injection, etc.) influences the bulk plasma properties in low-temperature plasma (LTP) devices. Computational models of these plasma flows remain challenging because the plasma density can vary several orders of magnitudes, a wide range of temporal and spatial scales must be resolved, the phenomena are inherently three-dimensional, and various physical processes, such as wall interaction, instabilities, inelastic collisions, etc., must be simultaneously and self-consistently taken into account. Understanding the fundamental transport mechanisms in cross-field configurations enables additional controllability of plasma properties and electron energy distribution functions (EEDFs).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of K + Force Fields on Ionic Conductivity and Charge Dynamics of KOH in Ethylene Glycol

Predicting ionic conductivity is crucial for developing efficient electrolytes for energy storage and conversion and other electrochemical applications. An accurate estimate of ionic conductivity requires understanding complex ion–ion and ion–solvent interactions governing the charge transport at the molecular level. Molecular simulations can provide key insights into the spatial and temporal behavior of electrolyte constituents. However, such insights depend on the ability of force fields to describe the underlying phenomena. In this work, molecular dynamics simulations were leveraged to delineate the impact of force field parameters on ionic conductivity predictions of potassium hydroxide (KOH) in ethylene glycol (EG). Four different force fields were used to represent the K + ion. Diffusion-based Nernst–Einstein and correlation-based Einstein approaches were implemented to estimate the ionic conductivity, and the predicted values were compared with experimental measurements. The physical aspects, including ion-aggregation, charge distribution, cluster correlation, and cluster dynamics, were also examined. A force field was identified that provides reasonably accurate Einstein conductivity values and a physically coherent representation of the electrolyte at the molecular level.

25 ENERGY STORAGE↗

Non-linear enhancement of ultrafast X-ray diffraction through transient resonances

Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale.

47 OTHER INSTRUMENTATION↗

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗

Strong-Field Bloch Electron Interferometry for Band-Structure Retrieval

When Bloch electrons in a solid are exposed to a strong optical field, they are coherently driven in their respective bands where they acquire a quantum phase as the imprint of the band shape. If an electron approaches an avoided crossing formed by two bands, it may be split by undergoing a Landau-Zener transition. We here employ subsequent Landau-Zener transitions to realize strong-field Bloch electron interferometry (SFBEI), allowing us to reveal band structure information. In particular, we measure the Fermi velocity (band slope) of graphene in the vicinity of the K points as 1.07±0.04 nm fs –1 . As a result, we expect SFBEI for band structure retrieval to apply to a wide range of material systems and experimental conditions, making it suitable for studying transient changes in band structure with femtosecond temporal resolution at ambient conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multi-qubit nanoscale sensing with entanglement as a resource

Nitrogen vacancy (NV) centres in diamond are widely deployed as local magnetic sensors, using single-qubit control to measure both time-averaged fields and noise with nanoscale spatial resolution. Moving beyond single qubits to multi-qubit control enables new sensing modalities such as measuring nonlocal spatiotemporal correlators or using entangled states to enhance measurement sensitivity. Here, in this work, we describe protocols for using optically unresolved NV centre pairs and nuclear spins as multi-qubit sensors for measuring correlated noise at nanometre length scales. For noninteracting NV centres, we implement a phase-cycling protocol that disambiguates magnetic correlations from variance fluctuations, leveraging the presence of a third qubit, a 13 C nucleus, to effect coherent single-NV spin flips and enable phase cycling even for co-aligned NV centres that are spectrally unresolved. For length scales around 10 nm, we create maximally entangled Bell states through dipole–dipole coupling between two NV centres and use these entangled states to directly read out the magnetic field correlation, rather than reconstructing it from independent measurements of unentangled NV centres. Importantly, this changes the scaling of sensitivity with readout noise from quadratic to linear. For conventional off-resonant readout of the NV centre spin state (for which the readout noise is roughly 30 times the quantum projection limit), this results in more than an order of magnitude improvement in sensitivity. Finally, we demonstrate methods for detecting high spatial- and temporal-resolution correlators with pairs of strongly interacting NV centres.

condensed-matter physics↗

A Multi-Branch Decoder Network Approach to Adaptive Temporal Data Selection and Reconstruction for Big Scientific Simulation Data

A key challenge in scientific simulation is that the simulation outputs often require intensive I/O and storage space to store the results for effective post hoc analysis. This article focuses on a quality-aware adaptive temporal data selection and reconstruction problem where the goal is to adaptively select simulation data samples at certain key timesteps in situ and reconstruct the discarded samples with quality assurance during post hoc analysis. This problem is motivated by the limitation of current solutions that a significant amount of simulation data samples are either discarded or aggregated during the sampling process, leading to inaccurate modeling of the simulated phenomena. Two unique challenges exist: 1) the sampling decisions have to be made in situ and adapted to the dynamics of the complex scientific simulation data; 2) the reconstruction error must be strictly bounded to meet the application requirement. To address the above challenges, we develop DeepSample , an error-controlled convolutional neural network framework, that jointly integrates a set of coherent multi-branch deep decoders to effectively reconstruct the simulation data with rigorous quality assurance. The results on two real-world scientific simulation applications show that DeepSample significantly outperforms other state-of-the-art methods on both sampling efficiency and reconstructed simulation data quality.

Zhang, Yang↗

Magnetic Field Sensing via Optically Detected Magnetic Resonance and Spin Relaxometry Using Nitrogen Vacancies in Nanodiamonds

Quantum sensing is broadly defined as the use of quantum materials, quantum coherence, and/or quantum entanglement to measure physical quantities and/or to enhance the sensitivity of classical analytical measurements. Certain materials exhibit interesting quantum properties that have the potential to be utilized in quantum sensing applications. One such quantum property is electronic spin, which is utilized in this work. Here, we built a custom apparatus capable of conducting both optically detected magnetic resonance (ODMR) and spin relaxometry. The quantum material investigated was an ensemble of nitrogen vacancies (NV) in nanodiamonds. We have characterized the system and measured ODMR spectra for different strengths of the applied DC magnetic field and clearly observed the expected splitting of the resonances due to Zeeman splitting. We also have measured the spin relaxation times for two different powers of the applied AC magnetic field. The lower power dataset exhibited expected exponential temporal dependence of the relaxation of a modified spin state, whereas the higher power dataset exhibited stretched exponential dependence of the evolution of the modified spin state, indicating the presence of high-power phenomena that emerge that retard the relaxation of the spin state.

Lander, Gary↗