Showing 1–50 of 359 results for author: Smith, A

Degree correlations in graphs with clique clustering

Authors: Peter Mann, V. Anne Smith, John B. O. Mitchell, Simon Dobson

Abstract: Correlations among the degrees of vertices in random graphs often occur when clustering is present. In this paper we define a joint-degree correlation function for vertices in the giant component of clustered configuration model networks which are composed of clique subgraphs. We use this model to investigate, in detail, the organization among nearest-neighbor subgraphs for random graphs as a func… ▽ More Correlations among the degrees of vertices in random graphs often occur when clustering is present. In this paper we define a joint-degree correlation function for vertices in the giant component of clustered configuration model networks which are composed of clique subgraphs. We use this model to investigate, in detail, the organization among nearest-neighbor subgraphs for random graphs as a function of subgraph topology as well as clustering. We find an expression for the average joint degree of a neighbor in the giant component at the critical point for these networks. Finally, we introduce a novel edge-disjoint clique decomposition algorithm and investigate the correlations between the subgraphs of empirical networks. △ Less

Submitted 16 July, 2026; originally announced July 2026.

Comments: 17 pages, 9 figures

Journal ref: Phys. Rev. E 105, 044314 - Published 20 April, 2022

An exact N-strain epidemic model using bond percolation

Authors: Peter Mann, V. Anne Smith, John B. O. Mitchell, Simon Dobson

Abstract: In this paper we examine the emergent structures of random networks that have undergone bond percolation an arbitrary, but finite, number of times. We define two types of sequential branching processes: a competitive branching process - in which each iteration performs bond percolation on the residual graph (RG) resulting from previous generations; and, a collaborative branching process - where pe… ▽ More In this paper we examine the emergent structures of random networks that have undergone bond percolation an arbitrary, but finite, number of times. We define two types of sequential branching processes: a competitive branching process - in which each iteration performs bond percolation on the residual graph (RG) resulting from previous generations; and, a collaborative branching process - where percolation is performed on the giant connected component (GCC) instead. We investigate the behaviour of these models, including the expected size of the GCC for a given generation, the critical percolation probability and other topological properties of the resulting graph structures using the analytically exact method of generating functions. We explore this model for Erdos-Renyi and scale free random graphs. This model can be interpreted as a seasonal N-strain model of disease spreading. △ Less

Submitted 16 July, 2026; originally announced July 2026.

Comments: 23 pages, 13 figures

Journal ref: Phys. Rev. E 106, 014304 - Published 20 July, 2022

Chip-scale nanostructured chaotic billiards for broadband speckle spectrometry

Authors: Matthew R. Wilson, Benoit Guilhabert, Jack A. Smith, Michael J. Strain, Xavier Porte

Abstract: Computational on-chip spectrometers are emerging as a powerful platform for portable spectral analysis, combining photonic integration with advanced signal processing to enable a wide range of in-situ sensing applications. We propose a broadband reconstructive spectrometer based on wave chaos in a stadium microresonator with a nanostructured scattering layer for full-area speckle readout. Waveleng… ▽ More Computational on-chip spectrometers are emerging as a powerful platform for portable spectral analysis, combining photonic integration with advanced signal processing to enable a wide range of in-situ sensing applications. We propose a broadband reconstructive spectrometer based on wave chaos in a stadium microresonator with a nanostructured scattering layer for full-area speckle readout. Wavelength dependent interference within the chaotic microresonator encodes the spectral information into a spatial intensity pattern that can be computationally inverted to reconstruct the input spectra. The optimal fabrication parameters of the SU-8 polymer nanostructured layer yield a surface roughness of 176nm and a root mean square thickness of ~2um. We experimentally validate our spectrometer at visible and infrared wavelengths, with resolutions of 43pm at 630nm and 8.2pm at 1550nm. The spectral reconstruction is demonstrated for single and multiple narrowline sources as well as for a broadband (~1nm) pulsed laser source. The broad experimental validation and compact footprint (0.05mm2) establishes our chaotic microresonator-based speckle spectrometer as a robust and versatile platform for high-resolution, on-chip spectral sensing. △ Less

Submitted 8 July, 2026; originally announced July 2026.

Understanding Non-Gaussian Chorus Wave Statistics via the Benjamin-Feir Index

Authors: D. J. Ratliff, O. Allanson, D. Rasinskaite, J. Stawarz, C. E. J. Watt, S. Chakraborty, A. W. Smith

Abstract: We derive an extended wave action model for equatorial chorus waves, identifying a wave activity index (a version of the Benjamin-Feir index, BFI) which indicates non-Gaussian frequency spectra emerge when BFI$>$0.5. Global maps of this index indicate the night and dawn sectors ($0<{\rm MLT}<9)$ of the magnetosphere as the primary region for non-Gaussian wave statistics to emerge. Comparisons with… ▽ More We derive an extended wave action model for equatorial chorus waves, identifying a wave activity index (a version of the Benjamin-Feir index, BFI) which indicates non-Gaussian frequency spectra emerge when BFI$>$0.5. Global maps of this index indicate the night and dawn sectors ($0<{\rm MLT}<9)$ of the magnetosphere as the primary region for non-Gaussian wave statistics to emerge. Comparisons with events measured by the Van Allen probe A demonstrate good qualitative agreement whilst identifying key aspects for model refinement. A key strength of our model that our work highlights is its ability to account for the asymmetric frequency spectra characteristic of non-Gaussian chorus. This work ultimately establishes the first wave activity index that distinguishes Gaussian and non-Gaussian wave scenarios from first principles, providing the groundwork for a threshold-based quantification for use in space weather modelling. △ Less

Submitted 3 July, 2026; v1 submitted 1 July, 2026; originally announced July 2026.

Comments: 14 pages, 3 figures

Closed-Loop Molecular Design with Calibrated Deference

Authors: Newman Cheng, Gordon Broadbent IV, Jason Dong, Syed Mohammed Ali Hussaini, Farman Ullah, Morris Sharp, Gabrielle Barnes, Nanlin Guo, Deyu Zou, Karin Strauss, William Chappell, David G. Kwabi, Bichlien H. Nguyen, Jake A. Smith

Abstract: We present Cognitive Loop via In-Situ Optimization (CLIO), an agent that couples a continuously-updated belief-state graph with a recursive plan-then-act loop. The result is a reasoning agent that can contribute something qualitatively different, which we term \emph{calibrated deference}: the capacity to recognize when its own tools or assumptions are failing, to adapt its strategy in response, an… ▽ More We present Cognitive Loop via In-Situ Optimization (CLIO), an agent that couples a continuously-updated belief-state graph with a recursive plan-then-act loop. The result is a reasoning agent that can contribute something qualitatively different, which we term \emph{calibrated deference}: the capacity to recognize when its own tools or assumptions are failing, to adapt its strategy in response, and to generate mechanistic hypotheses that guide experimental revision. We tested CLIO in a closed-loop human-AI campaign to design an aqueous organic redox flow battery (AORFB) negolyte, with CLIO leading proposal and interpretation in close partnership with chemists who synthesized, characterized, and weighed in on design choices. Across 17 candidates over three rounds, CLIO converged on a top phosphonate candidate; characterization confirmed a 130~mV improvement in redox potential over the literature baseline. Characterization then revealed unexpectedly poor electrochemical reversibility -- a regression no property predictor had flagged. CLIO generated competing mechanistic hypotheses, prioritized discriminating diagnostics, traced the failure to phosphonate-potassium ion pairing, and prescribed a sulfonate replacement. The resulting compound showed substantially improved electrochemical reversibility and maintained a 90~mV improvement in redox potential, closing the design-make-test-redesign loop. △ Less

Submitted 27 May, 2026; originally announced June 2026.

Commissioning of the large-scale lead tungstate scintillating calorimeter

Authors: A. Somov, V. V. Berdnikov, L. Gan, P. V. Laveen, A. Smith, S. Taylor, H. Voskanyan

Abstract: This article reports on the installation and initial commissioning of a large-scale lead tungstate (PbWO4) scintillating crystal calorimeter developed for high-rate photon detection and precise energy measurement. The calorimeter comprises 1,596 high-granularity, high-resolution scintillating crystals optimized for electromagnetic-shower detection over a wide energy range. Scintillation light from… ▽ More This article reports on the installation and initial commissioning of a large-scale lead tungstate (PbWO4) scintillating crystal calorimeter developed for high-rate photon detection and precise energy measurement. The calorimeter comprises 1,596 high-granularity, high-resolution scintillating crystals optimized for electromagnetic-shower detection over a wide energy range. Scintillation light from each crystal is read out by Hamamatsu R4125 photomultiplier tubes equipped with a custom voltage divider and front-end amplifier to ensure stable gain at high rates. All calorimeter modules were fabricated and characterized using an LED-based optical test system prior to installation to verify uniformity and photodetector performance. After installation, the ECAL was fully integrated into the experiment data acquisition and energy-based trigger systems. The optical response of the modules was equalized using the light-monitoring system, cosmic-ray muons, and photons from Compton-scattering events. Commissioning results demonstrate a reliably calibrated optical response and stable detector performance during the first run. These results validate the calorimeter design and commissioning methodology for large-scale scintillator-based photonic instrumentation. △ Less

Submitted 24 May, 2026; originally announced May 2026.

Comments: 14 pages, 14 figures, Published in SPIE journal Optical Engineering

Journal ref: Opt. Eng. 65(5), 054107 (2026)

36Cl Concentrations from Polar Ice Cores Set New Constraints on the Carrington Event

Authors: F. Mekhaldi, C. I. Paleari, A. M. Smith, A. Aldahan, J. Beer, M. Christl, C. Vockenhuber, H. Hayakawa, M. Curran, T. Erhardt, C. Plummer, K. Simon, K. Wilcken, M. Zheng, R. Muscheler

Abstract: The Carrington event of 1859 CE is considered as one of the largest geomagnetic storms of the observational era, and often used as a benchmark for a worst-case scenario. Yet, there exists no robust evidence of an associated solar energetic particle event of a significant magnitude, based on measurements of cosmogenic radionuclides 10Be and 14C from ice cores and tree rings, respectively. In this s… ▽ More The Carrington event of 1859 CE is considered as one of the largest geomagnetic storms of the observational era, and often used as a benchmark for a worst-case scenario. Yet, there exists no robust evidence of an associated solar energetic particle event of a significant magnitude, based on measurements of cosmogenic radionuclides 10Be and 14C from ice cores and tree rings, respectively. In this study, we present two 36Cl records from Greenland with 2-year and 4-year resolution from the EGRIP and NGRIP ice-core sites, together with semi-annual 10Be data from EGRIP, as well as annual 10Be and 36Cl concentrations from the Dome Summit Site, Law Dome, East Antarctica. We observe no significant 36Cl concentration increase around 1859 CE in the three records. This allows us to rule out an extreme solar energetic particle event hitting Earth associated with the Carrington event in terms of fluence above 30 MeV. Based on these ice core 36Cl measurements, we can suggest two scenarios: i) a soft SEP event with a maximum fluence above 30 MeV up to three times larger than any Space Age event or, ii) the possibility that there was no Earth-bound SEP event. △ Less

Submitted 29 April, 2026; originally announced April 2026.

Comments: 16 pages, 2 figures, and 2 tables

Journal ref: Philosophical Transactions of the Royal Society A, 2026

Readout and PID using AIML for SoLID High Background Cherenkov Detectors

Authors: Zhiwen Zhao, Bishnu Karki, Bo Yu, Andrew Smith, Gary Swift, Simon Gorbaty, Jingyi Zhou, Haiyan Gao, Benjamin Raydo, Alexandre Camsonne, Kishansingh Rajput, Marco Contalbrigo, Roberto Malaguti

Abstract: We present the development of readout electronics and artificial-intelligence-based particle-identification methods for the SoLID Cherenkov detectors at Jefferson Lab. To operate in the high-rate, high-background SoLID environment, we designed a MAROC sum readout system for multianode photomultiplier tubes that provides simultaneous pixel, quadrant-sum, and total-sum signals. Bench studies show th… ▽ More We present the development of readout electronics and artificial-intelligence-based particle-identification methods for the SoLID Cherenkov detectors at Jefferson Lab. To operate in the high-rate, high-background SoLID environment, we designed a MAROC sum readout system for multianode photomultiplier tubes that provides simultaneous pixel, quadrant-sum, and total-sum signals. Bench studies show that the system can sustain rates at or above those expected for SoLID while maintaining acceptable pedestal behavior and signal linearity. Using realistic Geant4 simulations for the heavy-gas Cherenkov detector, we then investigate $π/K$ separation with beam-related background. A simple photoelectron-counting cut is insufficient under these conditions, whereas multilayer perceptron models trained on PMT, quad, and pixel readout data perform substantially better. The quad and pixel readout schemes achieve pion and kaon efficiencies above 90\% and clearly outperform PMT-only readout. These results demonstrate that the combination of high-rate MAROC sum electronics and AIML-based pattern recognition provides a practical path toward robust SoLID Cherenkov PID. △ Less

Submitted 25 April, 2026; originally announced April 2026.

Skillful Global Ocean Emulation and the Role of Correlation-Aware Loss

Authors: Niraj Agarwal, Timothy A. Smith, Sergey Frolov, Laura C. Slivinski

Abstract: Machine learning emulators have shown extraordinary skill in forecasting atmospheric states, and their application to global ocean dynamics offers similar promise. Here, we adapt the GraphCast architecture into a dedicated ocean-only emulator, driven by prescribed atmospheric conditions, for medium-range predictions. The emulator is trained on NOAA's UFS-Replay dataset. Using a 24 hour time step,… ▽ More Machine learning emulators have shown extraordinary skill in forecasting atmospheric states, and their application to global ocean dynamics offers similar promise. Here, we adapt the GraphCast architecture into a dedicated ocean-only emulator, driven by prescribed atmospheric conditions, for medium-range predictions. The emulator is trained on NOAA's UFS-Replay dataset. Using a 24 hour time step, single initial condition, and without using autoregressive training, we produce an emulator that provides skillful forecasts for 10-15 day lead times. We further demonstrate the use of Mahalanobis distance as loss that improves the forecast skill compared to the Mean Squared Error loss by explicitly accounting for the correlations between tendencies of the target variables. Using spatial correlation analysis of the forecasted fields, we also show that the proposed correlation-aware loss acts as a statistical-dynamical regularizer for the slow, correlated dynamics of the global oceans, offering a better background forecast for downstream tasks like data assimilation. △ Less

Submitted 20 April, 2026; originally announced April 2026.

Comments: 13 pages, 4 figures

Solar Wind Classifications at Mars using Machine Learning Techniques

Authors: Catherine E. Regan, Silvia Ferro, Austin M. Smith, Alvin J. G. Angeles, Nicholas A. Gross, Farzad Kamalabadi, Marco Velli, Jasper S. Halekas

Abstract: Understanding solar wind variability throughout the heliosphere is essential for fundamental space physics and future exploration of the Moon and Mars. The Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft has provided upstream solar wind measurements at Mars spanning Solar Cycles 24 and 25, enabling a statistical investigation of solar wind regimes at this heliocentric distance. In this w… ▽ More Understanding solar wind variability throughout the heliosphere is essential for fundamental space physics and future exploration of the Moon and Mars. The Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft has provided upstream solar wind measurements at Mars spanning Solar Cycles 24 and 25, enabling a statistical investigation of solar wind regimes at this heliocentric distance. In this work, we apply an unsupervised machine-learning framework combining Principal Component Analysis and K-Means clustering to a normalized, multi-dimensional solar wind dataset to identify recurrent solar wind regimes in a physically interpretable, data-driven manner. The resulting classification reveals distinct slow, fast, intermediate, and compressed solar wind regimes whose relative occurrence and temporal organization are strongly modulated by solar activity. This manuscript is part of the Heliophysics Summer School Machine Learning Special Collection. △ Less

Submitted 9 April, 2026; originally announced April 2026.

Comments: Submitted to Solar Physics

Measuring impurity-induced shifts in Coulomb crystallization

Authors: Mingyao Xu, Aaron A. Smith, Leonid Prokhorov, Vera Guarrera, Giovanni Barontini

Abstract: We report a laboratory measurement of how impurities shift Coulomb crystallization in a strongly interacting ionic system. This is achieved by using laser cooled Ca$^+$ crystals doped with a controlled number of Xe$^{12+}$ highly charged ions. We find that the crystallization threshold is unchanged at low impurity concentration, but shows a clear crossover once the impurity content becomes suffici… ▽ More We report a laboratory measurement of how impurities shift Coulomb crystallization in a strongly interacting ionic system. This is achieved by using laser cooled Ca$^+$ crystals doped with a controlled number of Xe$^{12+}$ highly charged ions. We find that the crystallization threshold is unchanged at low impurity concentration, but shows a clear crossover once the impurity content becomes sufficiently large, after which the shift grows approximately linearly. Complementary measurements reveal that this global effect originates from a local pinning of the crystal around the impurities. We further show how the measured shift could impact standard models of crystallization in white dwarfs and neutron stars. Our results provide an experimental route to incorporating impurity effects into models of multicomponent Coulomb matter, relevant to stellar crystallization and strongly coupled plasmas. △ Less

Submitted 16 March, 2026; originally announced March 2026.

Exceptional Optical Phonon Coherence in Enriched Cubic Boron Arsenide via Suppression of Three-Phonon Scattering

Authors: Tong Lin, Fengjiao Pan, Gaihua Ye, Sanjna Sukumaran, Cynthia Nnokwe, Ange Benise Niyikiza, William A. Smith, Stephen B. Bayne, Rui He, Zhifeng Ren, Hanyu Zhu

Abstract: Cubic boron arsenide (BAs) is a promising semiconductor for next-generation electronics due to its outstanding ambipolar mobility and thermal conductivity, the latter of which is attributed to the suppression of three-phonon scattering. However, precisely accounting for different high-order anharmonic scattering processes is challenging from both theory and experiment, so that questions remain ope… ▽ More Cubic boron arsenide (BAs) is a promising semiconductor for next-generation electronics due to its outstanding ambipolar mobility and thermal conductivity, the latter of which is attributed to the suppression of three-phonon scattering. However, precisely accounting for different high-order anharmonic scattering processes is challenging from both theory and experiment, so that questions remain open regarding the ultimate limit of phonon lifetime and thermal conductivity in BAs. Here we show that this gap nearly eliminates three-phonon scattering for zone-center optical phonons in a wide temperature range, leading to a record-high, isotope purity-limited phonon coherence with a quality factor above $3.7\times 10^3$ for >98% enriched $^{11}$BAs below 100 K. We discriminate three decoherence mechanisms by their temperature-dependent contribution to the damping rate using high-resolution Raman and Fourier transform infrared spectroscopy. For the as-synthesized crystals, we find that defect scattering has negligible contributions to the linewidth of optical phonons in comparison to isotope scattering. These results provide critical insights into the intrinsic and extrinsic scattering mechanisms of optical phonons in BAs, motivating further studies to quantify anharmonic effects and realize superior phonon transport. △ Less

Submitted 11 March, 2026; originally announced March 2026.

Journal ref: Phys. Rev. Lett. 136, 116903 (2026)

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

Authors: Julia Gonski, Jenni Ott, Shiva Abbaszadeh, Sagar Addepalli, Matteo Cremonesi, Jennet Dickinson, Giuseppe Di Guglielmo, Erdem Yigit Ertorer, Lindsey Gray, Ryan Herbst, Christian Herwig, Tae Min Hong, Benedikt Maier, Maryam Bayat Makou, David Miller, Mark S. Neubauer, Cristián Peña, Dylan Rankin, Seon-Hee, Seo, Giordon Stark, Alexander Tapper, Audrey Corbeil Therrien, Ioannis Xiotidis, Keisuke Yoshihara , et al. (99 additional authors not shown)

Abstract: The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilitie… ▽ More The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML), silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science. △ Less

Submitted 24 July, 2026; v1 submitted 24 February, 2026; originally announced February 2026.

Comments: 123 pages, 53 figures

Rethinking Balance Sheets: A Poisson-Nernst-Planck Based Approach for Modeling Concentration and Flux Profiles Inside an Electrochemical Cell

Authors: Grace Origer, Ritu R. Raj, Nathan Jarvey, P. N. Romero Zavala, Wilson A. Smith, Ankur Gupta

Abstract: Electrochemical cells serve as a building block for producing and storing electrical energy from chemical reactions. The analysis of ion transport in these systems forms the foundation for understanding more complex electrochemical systems that are becoming increasingly present in the broader societal energy infrastructure. From a pedagogical perspective, the ``balance sheets" introduced in Chapte… ▽ More Electrochemical cells serve as a building block for producing and storing electrical energy from chemical reactions. The analysis of ion transport in these systems forms the foundation for understanding more complex electrochemical systems that are becoming increasingly present in the broader societal energy infrastructure. From a pedagogical perspective, the ``balance sheets" introduced in Chapter 4 of Electrochemical Methods: Fundamentals and Applications by Alan J. Bard, Larry R. Faulkner and Henry S. White (hereafter referred to as BFW) provides a first-pass approach to analyze ion transport in electrochemical cells. However, the balance sheet approach lacks first-principles justifications from the underlying equations that describe the transport processes in electrochemical cells. In this work, we compare a first-principles approach via the Poisson-Nernst-Planck equations to describe ion transport in electrochemical cells to that of the balance sheet approach. By re-working the examples presented in BFW, we illustrate that the balance sheet approach is only valid in limited scenarios. Furthermore, we show that the PNP equations provide a more physical route to analyze ion transport in electrochemical systems. We hope the approach outlined here will be adopted by electrochemical engineering researchers and instructors. △ Less

Submitted 3 February, 2026; originally announced February 2026.

A Bridge Between Climate Science and Economics: OPTiMEM and the Heat Conjecture for Estimation of Social Cost of Greenhouse Gases

Authors: Brian Hanley, Pieter Tans, Edward A. G. Schuur, Geoffrey Gardiner, Steve Keen, Adam Smith

Abstract: We present an entirely new physics founded approach to estimating the social cost of carbon (SCC). For this, we developed our Ocean-Heat-Content Physics and Time Macro Economic Model (OPTiMEM) to estimate future heat content. The heat conjecture assumes that weather damages curves are stochastically proportional to ocean heat increase. We model carbon combustion, validate to datasets for greenhous… ▽ More We present an entirely new physics founded approach to estimating the social cost of carbon (SCC). For this, we developed our Ocean-Heat-Content Physics and Time Macro Economic Model (OPTiMEM) to estimate future heat content. The heat conjecture assumes that weather damages curves are stochastically proportional to ocean heat increase. We model carbon combustion, validate to datasets for greenhouse gas (GHG), temperature, and ocean heat content (OHC). We show that the social cost of 4 GHGs: CO2, CH4, N2O and halogenated hydrocarbons, cannot be single values, but must be represented by a kind of economic phase space. We propose very long-term carbon bonds to implement real discounting. This obviates the Gordian knot of the descriptivist versus prescriptivist discount disagreement that is unsolvable. Implementing these bonds leads to a new monitoring metric: real-dollar spending and bond discount rates compared to SC-GHG cost with variation on the discount scale, where the discount has no relationship to the pure rate of time preference (PRTP). This heat conjecture is based on OPTiMEM. OPTiMEM initiates from a fossil fuel consumption function to produce CO2, with 18 scenarios implemented to provide the uncertainty range. We provide 1:N year loss risk models (1:10, 1:100, 1:1000) that government, engineers, and actuaries should find useful. A scenario implementing DICE family of models carbon and growth assumptions shows +18° C is breached by 2210 CE, and +110° C by 2300 CE -- both of which outcomes are obviously not compatible with the fairly rosy conclusions of DICE models. Concerns are raised about having enough low-cost fossil fuel for conversion to minimal CO$_2$ maximal energy return on energy invested (EROEI) power if nations wait too long, and low EROEI power is questioned because monetary value is dependent on energy. △ Less

Submitted 23 July, 2026; v1 submitted 2 February, 2026; originally announced February 2026.

Comments: 43 pages, 30 pages of text, 8 figures, 2 tables, 16 equations

Automatic skull-template alignment without a guidance image

Authors: Oscar Bates, Carlos Cueto, Ciaran Coleman, Cameron A. B. Smith, Lluis Guasch, Oscar Calderon Agudo

Abstract: Transcranial ultrasound must overcome the significant challenge of the human skull, limiting both imaging and therapeutic applications. While high-fidelity numerical simulations can compensate for skull-induced distortions, they require precise skull templates (typically derived from Computed Tomography, CT) and spatial alignment to the patient's anatomy. Current alignment relies on concurrent Mag… ▽ More Transcranial ultrasound must overcome the significant challenge of the human skull, limiting both imaging and therapeutic applications. While high-fidelity numerical simulations can compensate for skull-induced distortions, they require precise skull templates (typically derived from Computed Tomography, CT) and spatial alignment to the patient's anatomy. Current alignment relies on concurrent Magnetic Resonance Imaging (MRI) for registration, introducing financial, logistical, and throughput barriers. To overcome these challenges, we present Manifold Optimisation for Full-Waveform Inversion (MOFI), a method to register skull templates without using a guidance image. Our method aligns the skull template by minimising the difference between simulated and observed radio-frequency acoustic data. We demonstrate that MOFI accurately recovers the position of skull templates in silico and in vitro, offering an alternative to MRI guidance-based registration. These results indicate that MOFI has the potential to be a practical alternative to MRI-guided approaches, reducing the barriers to wider clinical adoption of transcranial ultrasound. △ Less

Submitted 20 January, 2026; originally announced January 2026.

Social Cost of Greenhouse Gases -- OPTiMEM and the Heat Conjecture(s)

Authors: Brian P. Hanley, Pieter Tans, Edward A. G. Schuur, Geoffrey Gardiner, Adam Smith

Abstract: Despite well-meaning scenarios that propose global CO2 emissions will decline presented in every IPCC report since 1988, the trend of global CO2 increase continues without significant change. Even if any individual nation manages to flatten its emissions, what matters is the trajectory of the globe. Together the gulf between climate science and climate economics, plus the urgent need for alternati… ▽ More Despite well-meaning scenarios that propose global CO2 emissions will decline presented in every IPCC report since 1988, the trend of global CO2 increase continues without significant change. Even if any individual nation manages to flatten its emissions, what matters is the trajectory of the globe. Together the gulf between climate science and climate economics, plus the urgent need for alternative methods of estimation, provided the incentives for development of our Ocean-Heat-Content (OHC) Physics and Time Macro Economic Model (OPTiMEM) system. To link NOAA damages to climate required creating a carbon consumption model to drive a physics model of climate. How fast could carbon be burned and how much coal, oil and natural gas was reasonably available? A carbon model driving climate meant burning the carbon, and modelling how the earth heated up. We developed this using the most recent best greenhouse gas equations and production models for CO2, CH4, N2O, and halogenated gases. This developed an ocean heat content model for the globe. Each step is validated against Known carbon consumption, CO2, temperature, and ocean heat content. This allows a physics founded model of climate costs to be projected. △ Less

Submitted 12 June, 2026; v1 submitted 30 December, 2025; originally announced January 2026.

Comments: 115 pages, 268 references, 59 figures, 32 tables, 46 equations

Robust Physical Encryption and Unclonable Object Identification in Classical Optical Networks using Standard Integrated Photonic Components

Authors: Jack A. Smith, Michael J. Strain

Abstract: Spectral complexity is a useful resource in physical device identification, disorder-enhanced spectroscopy, and machine learning, but is often achieved in chip-scale devices at the expense of propagation loss, scalability, or reconfigurability. In this work, we demonstrate that device specific spectral complexity can be achieved using completely standardized photonic building blocks. Using a waveg… ▽ More Spectral complexity is a useful resource in physical device identification, disorder-enhanced spectroscopy, and machine learning, but is often achieved in chip-scale devices at the expense of propagation loss, scalability, or reconfigurability. In this work, we demonstrate that device specific spectral complexity can be achieved using completely standardized photonic building blocks. Using a waveguide Mach-Zehnder interferometer internally loaded with two sets of non-concentric dual ring resonators, we demonstrate the generation of unclonable keys for one-time pad encryption which can be reconfigured on the fly by applying small voltages to on-chip thermo-optic elements. With this method, we access a keyspace larger than 12 Tb for a single device with simple, single-mode waveguide input and output coupling. Using two devices at either end of a communication channel, we show that an eavesdropper tapping the channel fibre link would be unable to recover the same spectrum measured at either end of the link, providing physical encryption for key distribution. Furthermore, being purely classical, this form of secure communications does not require quantum photonic sources or detectors, and can therefore be easily integrated into pre-existing telecommunication architectures. △ Less

Submitted 30 December, 2025; originally announced December 2025.

Comments: 15 pages, 13 figures

Variational quantum eigensolver for chemical molecules

Authors: Luca Ion, Adam Smith

Abstract: Solving interacting multi-particle systems is a central challenge in quantum chemistry and condensed matter physics. In this work, we investigate the computation of ground states and ground-state energies for the He-H+ and H2O molecules using quantum computing techniques. We employ the variational quantum eigensolver (VQE), implemented both on a quantum computer simulator and on an IBM quantum dev… ▽ More Solving interacting multi-particle systems is a central challenge in quantum chemistry and condensed matter physics. In this work, we investigate the computation of ground states and ground-state energies for the He-H+ and H2O molecules using quantum computing techniques. We employ the variational quantum eigensolver (VQE), implemented both on a quantum computer simulator and on an IBM quantum device. The resulting energies are benchmarked against exact ground-state energies obtained via classical methods. Simulations of the H2O molecule were performed on Nottingham's High Performance Computing (HPC) facilities. △ Less

Submitted 7 January, 2026; v1 submitted 27 December, 2025; originally announced December 2025.

Coulomb crystallization of xenon highly charged ions in a laser-cooled Ca+ matrix

Authors: Leonid Prokhorov, Aaron A. Smith, Mingyao Xu, Kostas Georgiou, Vera Guarrera, Lakshmi P. Kozhiparambil Sajith, Elwin A. Dijck, Christian Warnecke, Malte Wehrheim, Alexander Wilzewski, Laura Blackburn, Matthias Keller, Vincent Boyer, Thomas Pfeifer, Ullrich Schwanke, Cigdem Issever, Steven Worm, Piet O. Schmidt, José R. Crespo Lopez-Urrutia, Giovanni Barontini

Abstract: We report on the sympathetic cooling and Coulomb crystallization of xenon highly charged ions (HCIs) with laser-cooled Ca$^+$ ions. The HCIs are produced in a compact electron beam ion trap, then charge selected, decelerated, and finally injected into a cryogenic linear Paul trap. There, they are captured into $^{40}$Ca$^+$ Coulomb crystals, and co-crystallized within them, causing dark voids in t… ▽ More We report on the sympathetic cooling and Coulomb crystallization of xenon highly charged ions (HCIs) with laser-cooled Ca$^+$ ions. The HCIs are produced in a compact electron beam ion trap, then charge selected, decelerated, and finally injected into a cryogenic linear Paul trap. There, they are captured into $^{40}$Ca$^+$ Coulomb crystals, and co-crystallized within them, causing dark voids in their fluorescence images. Fine control over the number of trapped ions and HCIs allows us to realize mixed-species crystals with arbitrary ordering patterns. By investigating Xe$^{q+}$--Ca$^+$ strings, we confirm the HCI charge states, measure their lifetime and characterize the mixed-species motional modes. Our system effectively combines the established quantum control toolbox for Ca$^+$ with the rich set of atomic properties of Xe highly charged ions, providing a resourceful platform for optical frequency metrology, searches for signatures of new physics, and quantum information science. △ Less

Submitted 11 June, 2026; v1 submitted 13 December, 2025; originally announced December 2025.

Journal ref: Phys. Rev. A 113, L041102 (2026)

UK White Paper on Magnetic Reconnection

Authors: Alexander J. B. Russell, James A. McLaughlin, Philippa Browning, Jennifer Carter, Luca Franci, Heli Hietala, Andrew Hillier, Gunnar Hornig, David MacTaggart, Sarah Matthews, James McKevitt, Eric Priest, Jack Reid, Ben Snow, Julia Stawarz, Anthony Yeates, Jeffersson Andres Agudelo Rueda, William Bate, Giulio Del Zanna, Jonathan Eastwood, Lucie Green, Anshu Kumari, Mike Lockwood, Thomas Neukirch, David Pontin , et al. (3 additional authors not shown)

Abstract: Magnetic reconnection powers explosive releases of magnetic energy, heating and particle acceleration throughout the plasma universe. Knowledge of this universal process is vital to understanding the Heliosphere, as it plays a key role in solar flares, coronal mass ejections, coronal heating, solar wind acceleration, geomagnetic storms, and interactions between the solar wind and planetary magneto… ▽ More Magnetic reconnection powers explosive releases of magnetic energy, heating and particle acceleration throughout the plasma universe. Knowledge of this universal process is vital to understanding the Heliosphere, as it plays a key role in solar flares, coronal mass ejections, coronal heating, solar wind acceleration, geomagnetic storms, and interactions between the solar wind and planetary magnetospheres. As such, reconnection underpins multiple science objectives of multiple future space missions. The UK plays a leading role in this international field, through a combination of in situ measurements from Earth's magnetosphere and the solar wind, observations of the solar corona and chromosphere, and world-class numerical simulations and theory. This white paper identifies: Nine priority science objectives for reconnection research in the next decade; Recommendations to guide investment in theory, simulations and infrastructure; Mission priorities and required measurements to ensure the UK maintains and improves its world-class credentials in reconnection science. △ Less

Submitted 12 December, 2025; originally announced December 2025.

Comments: White paper submitted to UK Space Frontiers 2035 on 28 November 2025. A full list of signatories is appended at the end. 6 pages plus title page, list of authors and signatories, and references

Mapping vacancy and bonding electron distributions around aluminium nanovoids

Authors: Philip N. H. Nakashima, Yu-Tsun Shao, Zezhong Zhang, Andrew E. Smith, Tianyu Liu, Nikhil V. Medhekar, Joanne Etheridge, Laure Bourgeois, Jian-Min Zuo

Abstract: All materials have defects and many contain nanostructures, both of which disrupt chemical bonding - the basis of materials properties. No experimental measurements of bonding electron distributions associated with defects and nanostructures have ever been possible. We present a method enabling such measurements and interrogate nanovoids surrounded by vacancies - the most fundamental of nanostruct… ▽ More All materials have defects and many contain nanostructures, both of which disrupt chemical bonding - the basis of materials properties. No experimental measurements of bonding electron distributions associated with defects and nanostructures have ever been possible. We present a method enabling such measurements and interrogate nanovoids surrounded by vacancies - the most fundamental of nanostructures and defects - in aluminium. We measure the volume of a vacancy with 3% uncertainty and map vacancy concentrations surrounding nanovoids with nanometre resolution in three dimensions where previously only two-dimensional mapping was possible. We discover that radiation-damaged voids can "heal". Our bonding measurements are depth-resolved, vacancy-sensitive, and agree with density functional theory. This work opens bonding electron density measurements to inhomogeneous nanostructured multi-phased materials so that the electronic origins of phenomena such as strengthening, weakening, interface functionality, solute diffusion and phase transformations within them may be revealed. △ Less

Submitted 4 December, 2025; originally announced December 2025.

Comments: 69 pages, 4 main figures, 11 extended data figures, 9 supplementary figures, 1 main table, 1 supplementary table, 96 references

Manganese-based macrocyclic chelates as novel MRI contrast agents: In vivo imaging in a porcine model

Authors: Pål B. Marthinsen, Tuva R. Hope, Wibeke Nordhøy, Deirdre B. Cassidy, Adrian P. L. Smith, Paul M. Evans, Atle Bjørnerud

Abstract: Objectives: Mn-based MRI contrast agents (MBCAs) have recently been proposed as alternatives to the currently used class of Gd-chelates. Unlike Gd, Mn is an endogenous paramagnetic metal with known biochemical pathways in the human body for excretion and metal regulation, which may alleviate the raised concerns about the safety of existing GBCAs. The aim of this study was to investigate the distri… ▽ More Objectives: Mn-based MRI contrast agents (MBCAs) have recently been proposed as alternatives to the currently used class of Gd-chelates. Unlike Gd, Mn is an endogenous paramagnetic metal with known biochemical pathways in the human body for excretion and metal regulation, which may alleviate the raised concerns about the safety of existing GBCAs. The aim of this study was to investigate the distribution, kinetics and image enhancement properties of a class of novel Mn-based macrocyclic chelates in a porcine model. Methods: Macrocyclic MBCAs, AH114608, GEH300017 and GEH200486, were tested and compared to gadoterate meglumine. Twelve female adult pigs were divided into four groups (n=3 for each CA). At 3 T MRI, T1 relaxometry analysis were measured longitudinally in multiple organs at five timepoints 30 minutes apart. CA kinetics was estimated from analysis of plasma CA concentrations by ICP-OES. Results: All four CAs exhibited T1-enhancing properties in the blood pool with GEH200486 having the largest increase in T1 relaxation rate (R1), GEH300017 and gadoterate meglumine having similar R1 increase and AH114608 a lower peak R1 change. A persistent increase in liver, kidney and myocardium R1 was observed with AH114608. To a lesser extent, a persistent increase of liver enhancement was also observed in T1-weighted images for GEH300017 and GEH200486 compared to gadoterate meglumine. All four CAs had similar bi-exponential plasma kinetics characterized by a rapid distribution phase and a slower elimination phase. Discussion: We have identified MBCA candidates with predominantly renal clearance and comparable efficacy in terms of vascular T1 relaxation, and comparable to the reference GBCA. The T1-enhancing properties of these novel Mn macrocyclic CAs can be used with routine clinical protocols and could be potentially utilised as an alternative to GBCAs for contrast-enhanced MRI procedures. △ Less

Submitted 25 November, 2025; originally announced November 2025.

Comments: 15 pages, 8 figures and 3 tables

Photonic-integrated quantum sensor array for microscale magnetic localisation

Authors: Hao-Cheng Weng, John G. Rarity, Krishna C. Balram, Joe A. Smith

Abstract: Nitrogen-vacancy centres (NVs) are promising solid-state nanoscale quantum sensors for applications ranging from material science to biotechnology. Using multiple sensors simultaneously offers advantages for probing spatiotemporal correlations of fluctuating fields or the dynamics of point defects. In this work, by integrating NVs with foundry silicon-nitride photonic integrated circuits, we reali… ▽ More Nitrogen-vacancy centres (NVs) are promising solid-state nanoscale quantum sensors for applications ranging from material science to biotechnology. Using multiple sensors simultaneously offers advantages for probing spatiotemporal correlations of fluctuating fields or the dynamics of point defects. In this work, by integrating NVs with foundry silicon-nitride photonic integrated circuits, we realise the scalable operation of eight localised NV sensors in an array, with simultaneous, distinct readout of the individual sensors. Using the eight NV sensors and machine-learning methods for multi-point magnetic field reconstruction, we demonstrate microscale magnetic localisation of a 30 $μ$m-sized needle tip. Experimentally, the needle tip can be localised with an error below its dimension and tracked dynamically with high fidelity. We further simulate the feasibility of our platform for monitoring the position and orientation of magnetic microrobots designed for biological and clinical purposes. Without the complexity of bulk optics, our photonic-integrated multi-sensor platform presents a step towards real-life biomedical applications under out-of-the-lab conditions. △ Less

Submitted 14 November, 2025; originally announced November 2025.

Comments: 13 pages, 5 figures

RSstitcher -- Merging 2D diffraction frames for Wide Range Reciprocal Space Maps with absorption correction and integration functions

Authors: Xiaodong Wang, Michael W. M. Jones, Adam Smith

Abstract: Wide Range Reciprocal Space Mapping (WRRSM) is a technique that allows visualisation of the geometric relationships among multiple hkl spots in a whole reciprocal space map. However, commercial softwares for WRRSMs generation are associated with several issues or limitations, which are overcome by the currently reporting open-source python program RSstitcher (Reciprocal Space Stitcher). RSstitcher… ▽ More Wide Range Reciprocal Space Mapping (WRRSM) is a technique that allows visualisation of the geometric relationships among multiple hkl spots in a whole reciprocal space map. However, commercial softwares for WRRSMs generation are associated with several issues or limitations, which are overcome by the currently reporting open-source python program RSstitcher (Reciprocal Space Stitcher). RSstitcher merges 2D scan frames formats supported by FabIO and enables WRRSM function on most laboratory X-ray diffractometers equipped with a goniometer cradle and a 2D detector of any sensor size. It is so far the only WRRSMs generation tool that applies diffraction intensity correction due to sample self-absorption, which enables quantitative analyses for WRRSMs including texture measurement and 1D data integration. The conversion equations used in the python program is explained geometrically, including novel WRRSM measurements in ω-φ compensated Side Inclination Grazing Incident Diffraction mode for thin film samples. The applications of RSstitcher for bulk and thin film samples are demonstrated using two common 2D X-ray diffraction systems. △ Less

Submitted 6 August, 2026; v1 submitted 11 November, 2025; originally announced November 2025.

Comments: 31 pages, 12 figures. Submitted to the Journal of Applied Crystallography for consideration

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

Authors: Benjamin Hawks, Jason Weitz, Dmitri Demler, Karla Tame-Narvaez, Dennis Plotnikov, Mohammad Mehdi Rahimifar, Hamza Ezzaoui Rahali, Audrey C. Therrien, Donovan Sproule, Elham E Khoda, Keegan A. Smith, Russell Marroquin, Giuseppe Di Guglielmo, Nhan Tran, Javier Duarte, Vladimir Loncar

Abstract: As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as… ▽ More As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multiple efforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680,000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset. △ Less

Submitted 6 November, 2025; originally announced November 2025.

Comments: 30 pages, 18 figures

Report number: FERMILAB-PUB-25-0359-CSAID

Journal ref: Wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation. ACM Trans. Reconfigurable Technol. Syst. 19, 2, Article 20 (June 2026), 29 pages

Diversity in emergent cell locomotion from the coupling cytosolic and cortical Marangoni flows with reaction-diffusion dynamics

Authors: Blaž Ivšić, Igor Weber, Piotr Nowakowski, Ana-Sunčana Smith

Abstract: Cell migration is a fundamental process underlying the survival and function of both unicellular and multicellular organisms. Crawling motility in eukaryotic cells arises from cyclic protrusion and retraction driven by the cytoskeleton, whose organization is regulated by reaction-diffusion (RD) dynamics of Rho GTPases between the cytosol and the cortex. These dynamics generate spatial membrane pat… ▽ More Cell migration is a fundamental process underlying the survival and function of both unicellular and multicellular organisms. Crawling motility in eukaryotic cells arises from cyclic protrusion and retraction driven by the cytoskeleton, whose organization is regulated by reaction-diffusion (RD) dynamics of Rho GTPases between the cytosol and the cortex. These dynamics generate spatial membrane patterning and establish front-rear polarity through the coupling of biochemical signalling and mechanical feedback. We develop a cross-scale mean-field framework that integrates RD signalling with cytosolic and cortical hydrodynamics to capture emergent cellular locomotion. Our model reproduces diverse experimentally observed shape and motility phenotypes with small parameter changes, indicating that these behaviours correspond to self-organized limit cycles. Phase-space analysis reveals that coupling to both cytosolic flow and spatially varying surface tension is essential to recover the full spectrum of motility modes, providing a theoretical foundation for understanding amoeboid migration. △ Less

Submitted 1 November, 2025; originally announced November 2025.

Comments: 23 pages, 6 figures

Light Monitoring System for the Lead Tungstate Calorimeter in Hall D at Jefferson Lab

Authors: A. Somov, V. V. Berdnikov, H. Voskanyan, A. Asaturyan, L. Gan, S. Taylor, F. Barbosa, C. Stanislav, V. Popov, I. Somov, I. Jaegle, A. Smith, H. Egiyan, B. Bunton

Abstract: A new electromagnetic calorimeter composed of 1596 lead tungstate (PbWO$_4$) scintillating crystals has been constructed for the GlueX detector in Hall D at Jefferson Lab. The calorimeter is equipped with a light monitoring system that uses light-emitting diodes. The light monitoring system was fabricated, installed, and integrated into the GlueX trigger system. It was successfully operated during… ▽ More A new electromagnetic calorimeter composed of 1596 lead tungstate (PbWO$_4$) scintillating crystals has been constructed for the GlueX detector in Hall D at Jefferson Lab. The calorimeter is equipped with a light monitoring system that uses light-emitting diodes. The light monitoring system was fabricated, installed, and integrated into the GlueX trigger system. It was successfully operated during detector commissioning and data collection. The paper describes the design, installation, and performance of the light monitoring system. △ Less

Submitted 31 October, 2025; originally announced November 2025.

Comments: 7 pages, 13 figures, submitted to Elsevier

Report number: JLAB-PHY-25-4587

Exceptional Antimodes in Multi-Drive Cavity Magnonics

Authors: Mawgan A. Smith, Ryan D. McKenzie, Alban Joseph, Robert L. Stamps, Rair Macêdo

Abstract: Driven-dissipative systems provide a natural setting for the emergence of exceptional points -- i.e. non-Hermitian degeneracies where eigenmodes coalesce. These points are important for applications such as sensing, where enhanced sensitivity is required, and exhibit interesting and useful phenomena that can be controlled with experimentally accessible parameters. In this regard a four-port, three… ▽ More Driven-dissipative systems provide a natural setting for the emergence of exceptional points -- i.e. non-Hermitian degeneracies where eigenmodes coalesce. These points are important for applications such as sensing, where enhanced sensitivity is required, and exhibit interesting and useful phenomena that can be controlled with experimentally accessible parameters. In this regard a four-port, three-mode, cavity-magnonics platform is demonstrated in which two microwave excitations can be precisely phase shifted and/or attenuated relative to one another. Destructive interference between the hybridised cavity-magnon modes is shown to give rise to antimodes (antiresonances) in the transmission spectrum, enabling coherent perfect extinction of the outgoing signals at selected ports. This interference can be used to actively tune the position and properties of exceptional points, without the fine tuning conventionally required to obtain exceptional points. Such controllable, interference-based engineering of exceptional points provides a practical and flexible pathway toward next-generation, high-sensitivity sensing devices operating at microwave frequencies. △ Less

Submitted 17 October, 2025; originally announced October 2025.

SimPoly: Simulation of Polymers with Machine Learning Force Fields Derived from First Principles

Authors: Gregor N. C. Simm, Jean Hélie, Hannes Schulz, Yicheng Chen, Guillem Simeon, Anna Kuzina, Ernesto Martinez-Baez, Piero Gasparotto, Gabriele Tocci, Chi Chen, Yatao Li, Lixue Cheng, Zun Wang, Bichlien H. Nguyen, Jake A. Smith, Lixin Sun

Abstract: Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses significant modeling challenges. Conventional force fields often lack the accuracy and transferability required to capture the intricate interactions governing polymer behavior. Conversely, quantum-chemical m… ▽ More Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses significant modeling challenges. Conventional force fields often lack the accuracy and transferability required to capture the intricate interactions governing polymer behavior. Conversely, quantum-chemical methods are computationally prohibitive for the large systems and long timescales required to simulate relevant polymer phenomena. Here, we overcome these limitations with a machine learning force field (MLFF) approach. We demonstrate that macroscopic properties for a broad range of polymers can be predicted ab initio, without fitting to experimental data. Specifically, we develop a fast and scalable MLFF to accurately predict polymer densities, outperforming established classical force fields. Our MLFF also captures second-order phase transitions, enabling the prediction of glass transition temperatures. To accelerate progress in this domain, we introduce a benchmark of experimental bulk properties for 130 polymers and an accompanying quantum-chemical dataset. This work lays the foundation for a fully in silico design pipeline for next-generation polymeric materials. △ Less

Submitted 15 October, 2025; originally announced October 2025.

Detecting milli-Hz gravitational waves with optical resonators

Authors: G. Barontini, X. Calmet, V. Guarrera, A. Smith, A. Vecchio

Abstract: We propose a gravitational wave detector based on ultrastable optical cavities enabling the detection of gravitational wave signals in the mostly unexplored $10^{-5}-1$ Hz frequency band. We illustrate the working principle of the detector and discuss that several classes of gravitational wave sources, both of astrophysical and cosmological origin, may be within the detection range of this instrum… ▽ More We propose a gravitational wave detector based on ultrastable optical cavities enabling the detection of gravitational wave signals in the mostly unexplored $10^{-5}-1$ Hz frequency band. We illustrate the working principle of the detector and discuss that several classes of gravitational wave sources, both of astrophysical and cosmological origin, may be within the detection range of this instrument. Our work suggests that terrestrial gravitational wave detection in the milli-Hz frequency range is potentially within reach with current technology. △ Less

Submitted 3 October, 2025; v1 submitted 19 September, 2025; originally announced September 2025.

Journal ref: Class. Quantum Grav. 42 20LT01 (2025)

Low-Cost and Detunable Wireless Resonator Glasses for Enhanced Eye MRI with Concurrent High-Quality Whole Brain MRI

Authors: Ming Lu, Xiaoyue Yang, Jason Moore, Pingping Li, Adam W. Anderson, John C. Gore, Seth A. Smith, Xinqiang Yan

Abstract: Purpose: To develop and evaluate a wearable wireless resonator glasses design that enhances eye MRI signal-to-noise ratio (SNR) without compromising whole-brain image quality at 7 T. Methods: The device integrates two detunable LC loop resonators into a lightweight, 3D-printed frame positioned near the eyes. The resonators passively couple to a standard 2Tx/32Rx head coil without hardware modifi… ▽ More Purpose: To develop and evaluate a wearable wireless resonator glasses design that enhances eye MRI signal-to-noise ratio (SNR) without compromising whole-brain image quality at 7 T. Methods: The device integrates two detunable LC loop resonators into a lightweight, 3D-printed frame positioned near the eyes. The resonators passively couple to a standard 2Tx/32Rx head coil without hardware modifications. Bench tests assessed tuning, isolation, and detuning performance. B1$^+$ maps were measured in a head/shoulder phantom, and SNR maps were obtained in both phantom and in vivo experiments. Results: Bench measurements confirmed accurate tuning, strong inter-element isolation, and effective passive detuning. Phantom B1$^+$ mapping showed negligible differences between configurations with and without the resonators. Phantom and in vivo imaging demonstrated up to about a 3-fold SNR gain in the eye region, with no measurable SNR loss in the brain. Conclusion: The wireless resonator glasses provide a low-cost, easy-to-use solution that improves ocular SNR while preserving whole-brain image quality, enabling both dedicated eye MRI and simultaneous eye-brain imaging at ultrahigh field. △ Less

Submitted 10 September, 2025; originally announced September 2025.

Journal ref: Magn Reson Med. 2026;96(1):499-507

On-chip wave chaos for photonic extreme learning

Authors: Matthew R. Wilson, Jack A. Smith, Michael J. Strain, Xavier Porte

Abstract: The increase in demand for scalable and energy efficient artificial neural networks has put the focus on novel hardware solutions. Integrated photonics offers a compact, parallel and ultra-fast information processing platform, specially suited for extreme learning machine (ELM) architectures. Here we experimentally demonstrate a chip-scale photonic ELM based on wave chaos interference in a stadium… ▽ More The increase in demand for scalable and energy efficient artificial neural networks has put the focus on novel hardware solutions. Integrated photonics offers a compact, parallel and ultra-fast information processing platform, specially suited for extreme learning machine (ELM) architectures. Here we experimentally demonstrate a chip-scale photonic ELM based on wave chaos interference in a stadium microcavity. By encoding the input information in the wavelength of an external single-frequency tunable laser source, we leverage the high sensitivity to wavelength of injection in such photonic resonators. We fabricate the microcavity with direct laser writing of SU-8 polymer on glass. A scattering wall surrounding the stadium operates as readout layer, collecting the light associated with the cavity's leaky modes. We report uncorrelated and aperiodic behavior in the speckles of the scattering barrier from a high resolution scan of the input wavelength. Finally, we characterize the system's performance at classification in four qualitatively different benchmark tasks. As we can control the number of output nodes of our ELM by measuring different parts of the scattering barrier, we demonstrate the capability to optimize our photonic ELM's readout size to the performance required for each task. △ Less

Submitted 27 August, 2025; originally announced August 2025.

HRRRCast: a data-driven emulator for regional weather forecasting at convection allowing scales

Authors: Daniel Abdi, Isidora Jankov, Paul Madden, Vanderlei Vargas, Timothy A. Smith, Sergey Frolov, Montgomery Flora, Corey Potvin

Abstract: The High-Resolution Rapid Refresh (HRRR) model is a convection-allowing model used in operational weather forecasting across the contiguous United States (CONUS). To provide a computationally efficient alternative, we introduce HRRRCast, a data-driven emulator built with advanced machine learning techniques. HRRRCast includes two architectures: a ResNet-based model (ResHRRR) and a Graph Neural Net… ▽ More The High-Resolution Rapid Refresh (HRRR) model is a convection-allowing model used in operational weather forecasting across the contiguous United States (CONUS). To provide a computationally efficient alternative, we introduce HRRRCast, a data-driven emulator built with advanced machine learning techniques. HRRRCast includes two architectures: a ResNet-based model (ResHRRR) and a Graph Neural Network-based model (GraphHRRR). ResHRRR uses convolutional neural networks enhanced with squeeze-and-excitation blocks and Feature-wise Linear Modulation, and supports probabilistic forecasting via the Denoising Diffusion Implicit Model (DDIM). To better handle longer lead times, we train a single model to predict multiple lead times (1h, 3h, and 6h), then use a greedy rollout strategy during inference. When evaluated on composite reflectivity over the full CONUS domain using ensembles of 3 to 10 members, ResHRRR outperforms HRRR forecast at light rainfall threshold (20 dBZ) and achieves competitive performance at moderate thresholds (30 dBZ). Our work advances the StormCast model of Pathak et al. [21] by: a) training on the full CONUS domain, b) using multiple lead times to improve long-range skill, c) training on analysis data instead of the +1h post-analysis data inadvertently used in StormCast, and d) incorporating future GFS states as inputs, enabling downscaling that improves long-lead accuracy. Grid-, neighborhood-, and object-based metrics confirm better storm placement, lower frequency bias, and higher success ratios than HRRR. HRRRCast ensemble forecasts also maintain sharper spatial detail, with power spectra more closely matching HRRR analysis. While GraphHRRR underperforms in its current form, it lays groundwork for future graph-based forecasting. HRRRCast represents a step toward efficient, data-driven regional weather prediction with competitive accuracy and ensemble capability. △ Less

Submitted 8 July, 2025; originally announced July 2025.

Journal ref: Artificial Intelligence for the Earth Systems, Vol. 5, No. 2, 2026, Article 250061

Benchmarking Quantum Heuristics: Non-Variational QWOA for Weighted Maxcut

Authors: Tavis Bennett, Aidan Smith, Edric Matwiejew, Jingbo Wang

Abstract: We present benchmarking results for the non-variational Quantum Walk Optimisation Algorithm (non-variational QWOA) applied to the weighted maxcut problem, using classical simulations for problem sizes up to $n = 31$. The amplified quantum state, prepared using a quadratic number of alternating unitaries, achieves a constant average-case measurement probability for globally optimal solutions across… ▽ More We present benchmarking results for the non-variational Quantum Walk Optimisation Algorithm (non-variational QWOA) applied to the weighted maxcut problem, using classical simulations for problem sizes up to $n = 31$. The amplified quantum state, prepared using a quadratic number of alternating unitaries, achieves a constant average-case measurement probability for globally optimal solutions across these problem sizes. This behaviour contrasts with that of classical heuristics, which, for NP-hard optimisation problems, typically exhibit solve probabilities that decay as problem size increases. Performance comparisons with two local-search heuristics on the same benchmark instances suggest that the non-variational QWOA may offer a meaningful advantage by scaling more favourably with problem size. These results provide supporting evidence for the potential of this quantum heuristic to achieve quantum advantage, though further work is needed to assess whether the observed performance scaling persists at larger problem sizes, and to confirm whether similar performance trends are observed for the other problem classes to which the non-variational QWOA is designed to generalise. △ Less

Submitted 30 May, 2025; originally announced May 2025.

Comments: 14 pages, 6 figures

A Blue Start: A large-scale pairwise and higher-order social network dataset

Authors: Alyssa Smith, Ilya Amburg, Sagar Kumar, Brooke Foucault Welles, Nicholas W. Landry

Abstract: Large-scale networks have been instrumental in shaping how we think about social systems, and have undergirded many foundational results in mathematical epidemiology, computational social science, and biology. However, many of the social systems through which diseases spread, information disseminates, and individuals interact are inherently mediated through groups, known as higher-order interactio… ▽ More Large-scale networks have been instrumental in shaping how we think about social systems, and have undergirded many foundational results in mathematical epidemiology, computational social science, and biology. However, many of the social systems through which diseases spread, information disseminates, and individuals interact are inherently mediated through groups, known as higher-order interactions. A gap exists between higher-order models of group formation and spreading processes and the data necessary to validate these mechanisms. Similarly, few datasets bridge the gap between pairwise and higher-order network data. The Bluesky social media platform is an ideal laboratory for observing social ties at scale through its open API. Not only does Bluesky contain pairwise following relationships, but it also contains higher-order social ties known as "starter packs" which are user-curated lists designed to promote social network growth. We introduce "A Blue Start", a large-scale network dataset comprising 39.7M user accounts, 2.4B pairwise following relationships, and 365.8K groups representing starter packs. This dataset will be an essential resource for the study of higher-order networks. △ Less

Submitted 30 January, 2026; v1 submitted 16 May, 2025; originally announced May 2025.

Comments: 18 pages, 8 figures

Determining the utility of ultrafast nonlinear contrast enhanced and super resolution ultrasound for imaging microcirculation in the human small intestine

Authors: Clotilde Vié, Martina Tashkova, James Burn, Matthieu Toulemonde, Jipeng Yan, Jingwen Zhu, Cameron A. B. Smith, Biao Huang, Su Yan, Kevin G. Murphy, Gary Frost, Meng-Xing Tang

Abstract: The regulation of intestinal blood flow is critical to gastrointestinal function. Imaging the intestinal mucosal micro-circulation in vivo has the potential to provide new insight into the gut physiology and pathophysiology. We aimed to determine whether ultrafast contrast enhanced ultrasound (CEUS) and super-resolution ultrasound localisation microscopy (SRUS/ULM) could be a useful tool for imagi… ▽ More The regulation of intestinal blood flow is critical to gastrointestinal function. Imaging the intestinal mucosal micro-circulation in vivo has the potential to provide new insight into the gut physiology and pathophysiology. We aimed to determine whether ultrafast contrast enhanced ultrasound (CEUS) and super-resolution ultrasound localisation microscopy (SRUS/ULM) could be a useful tool for imaging the small intestine microcirculation in vivo non-invasively and for detecting changes in blood flow in the duodenum. Ultrafast CEUS and SRUS/ULM were used to image the small intestinal microcirculation in a cohort of 20 healthy volunteers (BMI<25). Participants were imaged while conscious and either having been fasted, or following ingestion of a liquid meal or water control, or under acute stress. For the first time we have performed ultrafast CEUS and ULM on the human small intestine, providing unprecedented resolution images of the intestinal microcirculation. We evaluated flow speed inside small vessels in healthy volunteers (2.78 +/- 0.05 mm/s, mean +/- SEM) and quantified changes in the perfusion of this microcirculation in response to nutrient ingestion. Perfusion of the microvasculature of the intestinal mucosa significantly increased post-prandially (36.2% +/- 12.2%, mean +/- SEM, p<0.05). The feasibility of 3D SRUS/ULM was also demonstrated. This study demonstrates the potential utility of ultrafast CEUS for assessing perfusion and detecting changes in blood flow in the duodenum. SRUS/ULM also proved a useful tool to image the microvascular blood flow in vivo non-invasively and to evaluate blood speed inside the microvasculature of the human small intestine. △ Less

Submitted 16 May, 2025; originally announced May 2025.

Highly squeezed nanophotonic quantum microcombs with broadband frequency tunability

Authors: Yichen Shen, Ping-Yen Hsieh, Dhruv Srinivasan, Antoine Henry, Gregory Moille, Sashank Kaushik Sridhar, Alessandro Restelli, You-Chia Chang, Kartik Srinivasan, Thomas A. Smith, Avik Dutt

Abstract: Squeezed light offers genuine quantum advantage in enhanced sensing and quantum computation; yet the level of squeezing or quantum noise reduction generated from nanophotonic chips has been limited. In addition to strong quantum noise reduction, key desiderata for such a nanophotonic squeezer include frequency agility or tunability over a broad frequency range, and simultaneous operation in many d… ▽ More Squeezed light offers genuine quantum advantage in enhanced sensing and quantum computation; yet the level of squeezing or quantum noise reduction generated from nanophotonic chips has been limited. In addition to strong quantum noise reduction, key desiderata for such a nanophotonic squeezer include frequency agility or tunability over a broad frequency range, and simultaneous operation in many distinct, well-defined quantum modes (qumodes). Here we present a strongly overcoupled silicon nitride squeezer based on a below-threshold optical parametric amplifier (OPA) that produces directly detected squeezing of 5.6 dB $\pm$ 0.2 dB, surpassing previous demonstrations in both continuous-wave and pulsed regimes. We introduce a seed-assisted detection technique into such nanophotonic squeezers that reveals a quantum frequency comb (QFC) of 16 qumodes, with a separation of 11~THz between the furthest qumode pair, while maintaining a strong squeezing. Additionally, we report spectral tuning of a qumode comb pair over one free-spectral range of the OPA, thus bridging the spacing between the discrete modes of the QFC. Our results significantly advance both the generation and detection of nanophotonic squeezed light in a broadband and multimode platform, establishing a scalable, chip-integrated path for compact quantum sensors and continuous-variable quantum information processing systems. △ Less

Submitted 6 May, 2025; originally announced May 2025.

Microring resonator-based photonic circuit for faithfully heralding NOON states

Authors: Ryan Scott, Peter L. Kaulfuss, A. Matthew Smith, Paul M. Alsing, Wren Sanders, Gregory A. Howland, Edwin E. Hach III

Abstract: We have designed a Micro-Ring Resonator (MRR) based device that allows for the post-selection of high order NOON states via heralding. NOON states higher than $N=2$ cannot be generated deterministically. By tuning the coupling parameters of the device we can minimize the amplitudes of the 'accidental' states to maximize the probability of obtaining the NOON state upon a successful heralding event.… ▽ More We have designed a Micro-Ring Resonator (MRR) based device that allows for the post-selection of high order NOON states via heralding. NOON states higher than $N=2$ cannot be generated deterministically. By tuning the coupling parameters of the device we can minimize the amplitudes of the 'accidental' states to maximize the probability of obtaining the NOON state upon a successful heralding event. Our device can produce a 3-photon NOON state output with 100% certainty upon a successful heralding detection, which occurs with probability $\frac{8}{27}$ for optimal tunable device parameters. A successful heralding event allows for non-destructive time of flight tracking of the NOON state thus establishing a significantly enhanced level of engineering control for integration of the NOON state into scalable systems for quantum sensing and metrology. We further discuss extensions of our technique to even higher NOON states having $N=4,5$. △ Less

Submitted 31 March, 2025; originally announced April 2025.

Comments: 6 pages, 2 figures

Measurement of Trace Elements in Volcanic Materials: Consequences for the Cretaceous-Tertiary Mass Extinction, Geoneutrinos and the Origin of the Hawaii's Archipelago

Authors: Pedro V. Guillaumon, Iuda D. Goldman, Eric B. Norman, Keenan J. Thomas, Paulo R. Pascholati, Ross E. Meyer, Jordan L. Sabella, Alan R. Smith

Abstract: Seventeen representative samples of volcanic origin were collected from Ecuador (Pichincha Volcano), Iceland (Eyjafjallajökull Volcano), India (Deccan Traps), Hawaii, Kilimanjaro, Mt. Etna, Rwanda (Virunga Mountains), and Uganda (Virunga Mountains). Neutron activation analysis (NAA) was performed to determine the concentration of 33 chemical elements, including 21 trace elements, 20 heavy metals,… ▽ More Seventeen representative samples of volcanic origin were collected from Ecuador (Pichincha Volcano), Iceland (Eyjafjallajökull Volcano), India (Deccan Traps), Hawaii, Kilimanjaro, Mt. Etna, Rwanda (Virunga Mountains), and Uganda (Virunga Mountains). Neutron activation analysis (NAA) was performed to determine the concentration of 33 chemical elements, including 21 trace elements, 20 heavy metals, and 9 rare earth elements: Al, As, Ba, Ca, Ce, Cl, Co, Cr, Cs, Dy, Eu, Fe, Hf, K, La, Lu, Mg, Mn, Na, Nd, Rb, Sb, Sc, Sm, Sr, Ta, Tb, Th, Ti, U, Yb, Zn, and Zr. Correlation analysis of the abundance of samples from different islands in the Hawaii archipelago (Kauai, Kilauea, Mauna Loa, and Haleakala) confirmed that the islands were likely formed by two different lava sources. Additionally, the upper limit of iridium was determined in 11 of these samples using Bayesian analysis, which does not support the hypothesis that volcanic activity caused the extinction of the dinosaurs. We also discuss how the abundance of thorium and uranium in lava from different geological formations and depths can contribute to building a better map of natural radioisotope occurrences on Earth, which is important for geoneutrino experiments. A high abundance of rare elements was reported in some of the analyzed locations, indicating potential commercial interest and the possibility of exploring volcanoes as sources of chemical elements used in electronic devices. △ Less

Submitted 11 March, 2025; originally announced March 2025.

Highly Uniform Thermally Undercut Silicon Photonic Devices in a 300 mm CMOS Foundry Process

Authors: Robert Parsons, Kaylx Jang, Yuyang Wang, Asher Novick, A. Matthew Smith, Christopher C. Tison, Yonas Gebregiorgis, Venkatesh Deenadayalan, Matthew van Niekerk, Lewis Carpenter, Tat Ngai, Gerald Leake, Daniel Coleman, Xiang Meng, Stefan Preble, Michael L. Fanto, Keren Bergman, Anthony Rizzo

Abstract: Silicon photonic devices fundamental to high-density wavelength-division multiplexed (DWDM) optical links and photonic switching networks, such as resonant modulators and Mach-Zehnder interferometers (MZIs), are highly sensitive to fabrication variations and operational temperature swings. However, thermal tuning to compensate for fabrication and operational temperature variations can result in pr… ▽ More Silicon photonic devices fundamental to high-density wavelength-division multiplexed (DWDM) optical links and photonic switching networks, such as resonant modulators and Mach-Zehnder interferometers (MZIs), are highly sensitive to fabrication variations and operational temperature swings. However, thermal tuning to compensate for fabrication and operational temperature variations can result in prohibitive power consumption, challenging the scalability of energy-efficient photonic integrated circuits (PICs). In this work, we develop and demonstrate a wafer-scale thermal undercut process in a 300 mm complementary metal oxide semiconductor (CMOS) foundry that dramatically improves the thermal isolation of thermo-optic devices by selectively removing substrate material beneath the waveguides and resonators. This approach significantly reduces the power required for thermal tuning across multiple device architectures, achieving almost a 5$\times$ improvement in tuning efficiency in a state-of-the-art 4.5 $μ$m radius microdisk modulator and a 40$\times$ improvement in efficiency for a MZI phase shifter. To the best of the authors' knowledge, we demonstrate the first wafer-scale comparison of non-undercut and undercut silicon photonic devices using comprehensive wafer-scale measurements across 64 reticles of a 300 mm silicon-on-insulator (SOI) wafer. Further, we demonstrate a comprehensive wafer-scale analysis of the influence of undercut trench opening geometry on device tuning efficiency. Notably, we observe highly uniform performance across the full 300 mm wafer for multiple device types, emphasizing that our process can be scaled to large-scale photonic circuits with high yield. These results open new opportunities for large-scale integrated photonic circuits using thermo-optic devices, paving the way for scalable, low-power silicon photonic systems. △ Less

Submitted 6 June, 2025; v1 submitted 11 March, 2025; originally announced March 2025.

Comments: 11 pages, 6 figures

Topological descriptors for the electron density of inorganic solids

Authors: Nathan J. Szymanski, Alexander Smith, Prodromos Daoutidis, Christopher J. Bartel

Abstract: Descriptors play an important role in data-driven materials design. While most descriptors of crystalline materials emphasize structure and composition, they often neglect the electron density - a complex yet fundamental quantity that governs material properties. Here, we introduce Betti curves as topological descriptors that compress electron densities into compact representations. Derived from p… ▽ More Descriptors play an important role in data-driven materials design. While most descriptors of crystalline materials emphasize structure and composition, they often neglect the electron density - a complex yet fundamental quantity that governs material properties. Here, we introduce Betti curves as topological descriptors that compress electron densities into compact representations. Derived from persistent homology, Betti curves capture bonding characteristics by encoding components, cycles, and voids across varied electron density thresholds. Machine learning models trained on Betti curves outperform those trained on raw electron densities by an average of 33 percentage points in classifying structure prototypes, predicting thermodynamic stability, and distinguishing metals from non-metals. Shannon entropy calculations reveal that Betti curves retain comparable information content to electron density while requiring two orders of magnitude less data. By combining expressive power with compact representation, Betti curves highlight the potential of topological data analysis to advance materials design. △ Less

Submitted 17 June, 2025; v1 submitted 22 February, 2025; originally announced February 2025.

Journal ref: ACS Materials Lett. 2025, 7, 6, 2158-2164

Frequency auto-homogenization using group-velocity-matched downconversion

Authors: Dylan Heberle, Christopher C. Tison, James Schneeloch, A. Matthew Smith, Paul M. Alsing, Jeffrey Moses, Michael L. Fanto

Abstract: With the stability of integrated photonics at network nodes and the advantages of photons as flying qubits, photonic quantum information processing (PQIP) makes quantum networks increasingly scalable. However, scaling up PQIP requires the preparation of many identical single photons which is limited by the spectral distinguishability of integrated single-photon sources due to variations in fabrica… ▽ More With the stability of integrated photonics at network nodes and the advantages of photons as flying qubits, photonic quantum information processing (PQIP) makes quantum networks increasingly scalable. However, scaling up PQIP requires the preparation of many identical single photons which is limited by the spectral distinguishability of integrated single-photon sources due to variations in fabrication or local environment. To address this, we introduce frequency auto-homogenization via group-velocity-matched downconversion to remove spectral distinguishability in varying quantum emitters. We present our theory using $χ^{(2)}$ quantum frequency conversion and show proof-of-principle data in a free-space optical setup. △ Less

Submitted 4 February, 2025; originally announced February 2025.

Comments: 24 pages, 7 figures

Assimilating Observed Surface Pressure into ML Weather Prediction Models

Authors: Laura C. Slivinski, Jeffrey S. Whitaker, Sergey Frolov, Timothy A. Smith, Niraj Agarwal

Abstract: There has been a recent surge in development of accurate machine learning (ML) weather prediction models, but evaluation of these models has mainly been focused on medium-range forecasts, not their performance in cycling data assimilation (DA) systems. Cycling DA provides a statistically optimal estimate of model initial conditions, given observations and previous model forecasts. Here, real surfa… ▽ More There has been a recent surge in development of accurate machine learning (ML) weather prediction models, but evaluation of these models has mainly been focused on medium-range forecasts, not their performance in cycling data assimilation (DA) systems. Cycling DA provides a statistically optimal estimate of model initial conditions, given observations and previous model forecasts. Here, real surface pressure observations are assimilated into several popular ML models using an ensemble Kalman filter, where accurate ensemble covariance estimation is essential to constrain unobserved state variables from sparse observations. In this cycling DA system, deterministic ML models accumulate small-scale noise until they diverge. Mitigating this noise with a spectral filter can stabilize the system, but with larger errors than traditional models. Perturbation experiments illustrate that these models do not accurately represent short-term error growth, leading to poor estimation of cross-variable covariances. △ Less

Submitted 23 December, 2024; originally announced December 2024.

Verification of single-photon path entanglement using a nitrogen vacancy center

Authors: A. I. Smith, C. M. Steenkamp, M. S. Tame

Abstract: Path entanglement is an essential resource for photonic quantum information processing, including in quantum computing, quantum communication and quantum sensing. In this work, we experimentally study the generation and verification of bipartite path-entangled states using single photons produced by a nitrogen-vacancy center within a nanodiamond. We perform a range of measurements to characterize… ▽ More Path entanglement is an essential resource for photonic quantum information processing, including in quantum computing, quantum communication and quantum sensing. In this work, we experimentally study the generation and verification of bipartite path-entangled states using single photons produced by a nitrogen-vacancy center within a nanodiamond. We perform a range of measurements to characterize the photons being generated and verify the presence of path entanglement. The experiment is performed using continuous-wave laser excitation and a novel state generation 'time-window' method. This approach to path entanglement verification is different to previous work as it does not make use of a pulsed laser excitation source. △ Less

Submitted 10 July, 2025; v1 submitted 12 December, 2024; originally announced December 2024.

Comments: 12 pages, 9 figures, appendix

Journal ref: Appl. Opt. 64, C41-C52 (2025)

Relativistic Electron Acceleration and the 'Ankle' Spectral Feature in Earth's Magnetotail Reconnection

Authors: Weijie Sun, Mitsuo Oka, Marit Øieroset, Drew L. Turner, Tai Phan, Ian J. Cohen, Xiaocan Li, Jia Huang, Andy Smith, James A. Slavin, Gangkai Poh, Kevin J. Genestreti, Dan Gershman, Kyunghwan. Dokgo, Guan Le, Rumi Nakamura, James L. Burch

Abstract: Electrons are accelerated to high, non-thermal energies during explosive energy-release events in space, such as magnetic reconnection. However, the properties and acceleration mechanisms of relativistic electrons directly associated with reconnection X-line are not well understood. This study utilizes Magnetospheric Multiscale (MMS) measurements to analyze the flux and spectral features of sub-re… ▽ More Electrons are accelerated to high, non-thermal energies during explosive energy-release events in space, such as magnetic reconnection. However, the properties and acceleration mechanisms of relativistic electrons directly associated with reconnection X-line are not well understood. This study utilizes Magnetospheric Multiscale (MMS) measurements to analyze the flux and spectral features of sub-relativistic to relativistic (~ 80 to 560 keV) electrons during a magnetic reconnection event in Earth's magnetotail. This event provided a unique opportunity to measure the electrons directly energized by X-line as MMS stayed in the separatrix layer, where the magnetic field directly connects to the X-line, for approximately half of the observation period. Our analysis revealed that the fluxes of relativistic electrons were clearly enhanced within the separatrix layer, and the highest flux was directed away from the X-line, which suggested that these electrons originated directly from the X-line. Spectral analysis showed that these relativistic electrons deviated from the main plasma sheet population and exhibited an "ankle" feature similar to that observed in galactic cosmic rays. The contribution of "ankle" electrons to the total electron energy density increased from 0.1% to 1% in the separatrix layer, though the spectral slopes did not exhibit clear variations. Further analysis indicated that while these relativistic electrons originated from the X-line, they experienced a non-negligible degree of scattering during transport. These findings provide clear evidence that magnetic reconnection in Earth's magnetotail can efficiently energize relativistic electrons directly at the X-line, providing new insights into the complex processes governing electron dynamics during magnetic reconnection. △ Less

Submitted 8 December, 2024; originally announced December 2024.

Comments: 23 pages, 5 figures

Towards a new generation of solid total-energy detectors for neutron-capture time-of-flight experiments with intense neutron beams

Authors: J. Balibrea-Correa, V. Babiano-Suarez, J. Lerendegui-Marco, C. Domingo-Pardo, I. Ladarescu, A. Tarifeño-Saldivia, G. de la Fuente-Rosales, B. Gameiro, N. Zaitseva, V. Alcayne, D. Cano-Ott, E. González-Romero, T. Martínez, E. Mendoza, A. Pérez de Rada, J. Plaza del Olmo, A. Sánchez-Caballero, A. Casanovas, F. Calviño, S. Valenta, O. Aberle, S. Altieri, S. Amaducci, J. Andrzejewski, M. Bacak , et al. (112 additional authors not shown)

Abstract: Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $γ$-flash, and offer the highest possible detection sensitivity. In this paper, we… ▽ More Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $γ$-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps toward such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n\_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C$_{6}$D$_{6}$ detectors, and one LaCl$_{3}$(Ce) detector. The performance of these detection systems is compared using $^{93}$Nb($n$,$γ$) data. We also developed a detailed \textsc{Geant4} Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a $γ$ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigaged experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability. △ Less

Submitted 28 November, 2024; originally announced November 2024.

Diamine Surface Passivation and Post-Annealing Enhance Performance of Silicon-Perovskite Tandem Solar Cells

Authors: Margherita Taddei, Hannah Contreras, Hai-Nam Doan, Declan P. McCarthy, Seongrok Seo, Robert J. E. Westbrook, Daniel J. Graham, Kunal Datta, Perrine Carroy, Delfina Muñoz, Juan-Pablo Correa-Baena, Stephen Barlow, Seth R. Marder, Joel A. Smith, Henry J. Snaith, David S. Ginger

Abstract: We show that the use of 1,3-diaminopropane (DAP) as a chemical modifier at the perovskite/electron-transport layer (ETL) interface enhances the power conversion efficiency (PCE) of 1.7 eV bandgap FACs mixed-halide perovskite single-junction cells, primarily by boosting the open-circuit voltage (VOC) from 1.06 V to 1.15 V. Adding a post-processing annealing step after C60 evaporation, further impro… ▽ More We show that the use of 1,3-diaminopropane (DAP) as a chemical modifier at the perovskite/electron-transport layer (ETL) interface enhances the power conversion efficiency (PCE) of 1.7 eV bandgap FACs mixed-halide perovskite single-junction cells, primarily by boosting the open-circuit voltage (VOC) from 1.06 V to 1.15 V. Adding a post-processing annealing step after C60 evaporation, further improves the fill factor (FF) by 20% from the control to the DAP + post-annealing devices. Using hyperspectral photoluminescence microscopy, we demonstrate that annealing helps improve compositional homogeneity at the top and bottom interfaces of the solar cell, which prevents detrimental bandgap pinning in the devices and improves C60 adhesion. Using time-of-flight secondary ion mass spectrometry, we show that DAP reacts with formamidinium present near the surface of the perovskite lattice to form a larger molecular cation, 1,4,5,6-tetrahydropyrimidinium (THP) that remains at the interface. Combining the use of DAP and the annealing of C60 interface, we fabricate Si-perovskite tandems with PCE of 25.29%, compared to 23.26% for control devices. Our study underscores the critical role of chemical reactivity and thermal post-processing of the C60/Lewis-base passivator interface in minimizing device losses and advancing solar-cell performance of wide-bandgap mixed-cation mixed-halide perovskite for tandem application. △ Less

Submitted 4 December, 2024; v1 submitted 27 November, 2024; originally announced November 2024.

In-situ observations of resident space objects with the CHEOPS space telescope

Authors: Nicolas Billot, Stephan Hellmich, Willy Benz, Andrea Fortier, David Ehrenreich, Christopher Broeg, Alexis Heitzmann, Anja Bekkelien, Alexis Brandeker, Yann Alibert, Roi Alonso, Tamas Bárczy, David Barrado Navascues, Susana C. C. Barros, Wolfgang Baumjohann, Federico Biondi, Luca Borsato, Andrew Collier Cameron, Carlos Corral van Damme, Alexandre C. M. Correia, Szilard Csizmadia, Patricio E. Cubillos, Melvyn B. Davies, Magali Deleuil, Adrien Deline , et al. (58 additional authors not shown)

Abstract: The CHaracterising ExOPlanet Satellite (CHEOPS) is a partnership between the European Space Agency and Switzerland with important contributions by 10 additional ESA member States. It is the first S-class mission in the ESA Science Programme. CHEOPS has been flying on a Sun-synchronous low Earth orbit since December 2019, collecting millions of short-exposure images in the visible domain to study e… ▽ More The CHaracterising ExOPlanet Satellite (CHEOPS) is a partnership between the European Space Agency and Switzerland with important contributions by 10 additional ESA member States. It is the first S-class mission in the ESA Science Programme. CHEOPS has been flying on a Sun-synchronous low Earth orbit since December 2019, collecting millions of short-exposure images in the visible domain to study exoplanet properties. A small yet increasing fraction of CHEOPS images show linear trails caused by resident space objects crossing the instrument field of view. To characterize the population of satellites and orbital debris observed by CHEOPS, all and every science images acquired over the past 3 years have been scanned with a Hough transform algorithm to identify the characteristic linear features that these objects cause on the images. Thousands of trails have been detected. This statistically significant sample shows interesting trends and features such as an increased occurrence rate over the past years as well as the fingerprint of the Starlink constellation. The cross-matching of individual trails with catalogued objects is underway as we aim to measure their distance at the time of observation and deduce the apparent magnitude of the detected objects. As space agencies and private companies are developing new space-based surveillance and tracking activities to catalogue and characterize the distribution of small debris, the CHEOPS experience is timely and relevant. With the first CHEOPS mission extension currently running until the end of 2026, and a possible second extension until the end of 2029, the longer time coverage will make our dataset even more valuable to the community, especially for characterizing objects with recurrent crossings. △ Less

Submitted 27 November, 2024; originally announced November 2024.

Comments: 9 pages, 8 figures, Special Issue of the Journal of Space Safety Engineering

Journal ref: Journal of Space Safety Engineering, Volume 11, Issue 3, September 2024, Pages 498-506

Strong nanophotonic quantum squeezing exceeding 3.5 dB in a foundry-compatible Kerr microresonator

Authors: Yichen Shen, Ping-Yen Hsieh, Sashank Kaushik Sridhar, Samantha Feldman, You-Chia Chang, Thomas A. Smith, Avik Dutt

Abstract: Squeezed light, with its quantum noise reduction capabilities, has emerged as a powerful resource in quantum information processing and precision metrology. To reach noise reduction levels such that a quantum advantage is achieved, off-chip squeezers are typically used. The development of on-chip squeezed light sources, particularly in nanophotonic platforms, has been challenging. We report 3.7… ▽ More Squeezed light, with its quantum noise reduction capabilities, has emerged as a powerful resource in quantum information processing and precision metrology. To reach noise reduction levels such that a quantum advantage is achieved, off-chip squeezers are typically used. The development of on-chip squeezed light sources, particularly in nanophotonic platforms, has been challenging. We report 3.7 $\pm$ 0.2 dB of directly detected nanophotonic quantum squeezing using foundry-fabricated silicon nitride (Si$_3$N$_4$) microrings with an inferred squeezing level of 10.7 dB on-chip. The squeezing level is robust across multiple devices and pump detunings, and is consistent with the overcoupling degree without noticeable degradation from excess classical noise. We also offer insights to mitigate thermally-induced excess noise, that typically degrades squeezing, by using small-radius rings with a larger free spectral range (450 GHz) and consequently lower parametric oscillation thresholds. Our results demonstrate that Si$_3$N$_4$ is a viable platform for strong quantum noise reduction in a CMOS-compatible, scalable architecture. △ Less

Submitted 18 November, 2024; originally announced November 2024.

Journal ref: Optica 12 (3), pp. 302-308 (2025)