Medical Physics
Contactless Monitoring of Muscle Vibrations During Exercise with a Chaos-Inspired Radar
Jiangyifei Zhu, Yuzhe Wang, Tao Qiang et al. (+6 more)
In this paper, our goal is to enable quantitative feedback on muscle fatigue during exercise to optimize exercise effectiveness while minimizing injury risk. We seek to capture fatigue by monitoring surface vibrations that muscle exertion induces. Muscle vibrations are unique as they arise from the asynchronous firing of motor units, producing surface micro-displacements that are broadband, nonlinear, and seemingly
stochastic. Accurately sensing these noise-like signals requires new algorithmic strategies that can uncover their underlying structure. We present GigaFlex the first contactless system that measures muscle vibrations using mmWave radar to infer muscle force and detect fatigue. GigaFlex draws on algorithmic foundations from Chaos theory to model the deterministic patterns of muscle vibrations and extend them to the radar domain. Specifically, we design a radar processing architecture that systematically infuses principles from Chaos theory and nonlinear dynamics throughout the sensing pipeline, spanning localization,
segmentation, and learning, to estimate muscle forces during static and dynamic weight-bearing exercises. Across a 23-participant study, GigaFlex estimates maximum voluntary isometric contraction (MVIC) root mean square error (RMSE) of 5.9%, and detects one to three Repetitions in Reserve (RIR), a key quantitative muscle fatigue metric, with an AUC of 0.83 to 0.86, performing comparably to a contact-based IMU baseline. Our system can enable timely feedback that can help prevent fatigue-induced injury, and opens new opportunities for physiological sensing of complex, non-periodic biosignals.
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All authors Jiangyifei Zhu, Yuzhe Wang, Tao Qiang, Vu Phan, Zhixiong Li, Evy Meinders, Eni Halilaj, Justin Chan, Swarun Kumar
Biological Physics
Rapid Design and Fabrication of Body Conformable Surfaces with Kirigami Cutting and Machine Learning
Jyotshna Bali, Jinyang Li, Jie Chen et al. (+1 more)
By integrating the principles of kirigami cutting and data-driven modeling, this study aims to develop a personalized, rapid, and low-cost design and fabrication pipeline for creating body-conformable surfaces around the knee joint. The process begins with 3D scanning of the anterior knee surface of human subjects, followed by extracting the corresponding skin deformation between two joint angles in terms of longitudinal strain and Poisson's ratio. In parallel, a machine learning model is constructed using extensive simulation data from experimentally calibrated finite element analysis. This model employs Gaussian Process (GP) regression to relate kirigami cut lengths to the resulting longitudinal strain and Poisson's ratio. With an R2 score of 0.996, GP regression outperforms other models in predicting kirigami's large deformations. Finally, an inverse design approach based on the Covariance
Matrix Adaptation
Evolution Strategy (CMA-ES) is used to generate kirigami patch designs that replicate the in-plane skin deformation observed from the knee scans. This pipeline was applied to three human subjects, and the resulting kirigami knee patches were fabricated using rapid
laser cutting, requiring only a business day from knee scanning to kirigami patch delivery. The low-cost, personalized kirigami patches successfully conformed to over 75 percent of the skin area across all subjects, establishing a foundation for a wide range of wearable devices. The study demonstrates this potential through an impact-resistant kirigami foam patch, which not only conforms to dynamic knee motion but also provides joint protection against impact. Finally, the proposed design and fabrication framework is generalizable and can be extended to other deforming body surfaces, enabling the creation of personalized wearables such as protective gear, breathable adhesives, and body-conformable electronics.
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All authors Jyotshna Bali, Jinyang Li, Jie Chen, Suyi Li
Chemical Physics
Interaction of Polymer of Intrinsic Microporosity PIM-1 with explosive analytes at the molecular level: Combined experiment and computational modelling
Salam Mohammed, Edward B. Ogugu, Ramakant Sharma et al. (+7 more)
This work investigates the molecular-level interactions of a fluorescent microporous
polymer (PIM-1) with nitroaromatic explosives, in the context of thin film explosive sensors. Thin films of the PIM-1 were exposed to 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT), and their steady-state absorption and emission spectra measured. For comparison, the response of PIM-1 to non-explosive molecules such as benzene (BN) was also explored. Complementary electronic-structure calculations were used to predict absorption and emission spectra and to determine binding energies for the PIM-1-analyte complexes. The calculations agree well with experiment and reveal that association of nitroaromatic analyte molecules with PIM-1 alters the energy levels and the arrangements of frontier orbitals, indicating significant molecular interactions. Calculations show that the electronic properties and photo-excited electron transfer can be described by interaction with a single repeat unit of the
polymer. The molecular binding, however, involves interaction with at least three repeat units, with the DNT or TNT molecule binding into a pocket in the contorted structure of the microporous
polymer. Together, the experimental and theoretical results demonstrate that PIM-1 is a promising platform for selective nitroaromatic detection and provide molecular design principles that could improve sensitivity and selectivity in future sensor materials.
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All authors Salam Mohammed, Edward B. Ogugu, Ramakant Sharma, Dominic Taylor, Graeme Cooke, Neil McKeown, Glib Baryshnikov, Hans Ågren, Ifor D.W. Samuel, Graham A. Turnbull
Physics and Society · Cross-listed from cs.LG
Complex-Weighted Convolutional Networks: Provable Expressiveness via Complex Diffusion
Cristina López Amado, Tassilo Schwarz, Yu Tian et al. (+1 more)
Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain limited by oversmoothing and poor performance on heterophilic graphs. To address these challenges, we introduce a novel framework that equips graphs with a complex-weighted structure, assigning each edge a complex number to drive a
diffusion process that extends random walks into the complex domain. We prove that this
diffusion is highly expressive: with appropriately chosen complex weights, any node-classification task can be solved in the steady state of a complex random walk. Building on this insight, we propose the Complex-Weighted Convolutional Network (CWCN), which learns suitable complex-weighted structures directly from data while enriching
diffusion with learnable
matrices and nonlinear activations. CWCN is simple to implement, requires no additional hyperparameters beyond those of standard GNNs, and achieves competitive performance on
benchmark datasets. Our results demonstrate that complex-weighted
diffusion provides a principled and general mechanism for enhancing GNN expressiveness, opening new avenues for models that are both theoretically grounded and practically effective.
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All authors Cristina López Amado, Tassilo Schwarz, Yu Tian, Renaud Lambiotte
Optics
Charge reservoir as a design concept for plasmonic antennas
Rostislav Řepa, Michal Horák, Tomáš Šikola et al. (+1 more)
Plasmonic
antennas exploit localized surface plasmons to shape, confine, and enhance electromagnetic fields with subwavelength resolution. The field enhancement is contributed to by various effects, such as the inherent surface localization of plasmons or the plasmonic lightning-rod effect. Inspired by nanofocusing observed for propagating plasmons, we test the hypothesis that plasmonic
antennas with a large cross-section represent a large charge reservoir, enabling large induced charge and field enhancement. Our study reveals that a large charge reservoir is accompanied by large radiative losses, which are the dominant factor, resulting in a low field enhancement.
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All authors Rostislav Řepa, Michal Horák, Tomáš Šikola, Vlastimil Křápek
Computational Physics · Cross-listed from cond-mat.soft
Dynamical behavior of compound vesicles in wall-bounded shear flow
A. Lamura
We report a numerical study addressing the dynamics of compound vesicles confined in a channel under shear flow. The system comprises a smaller vesicle embedded within a larger one and can be used to mimic, for example, leukocytes or nucleate
cells. A two-dimensional model, which combines molecular dynamics and mesoscopic hydrodynamics including thermal fluctuations, is adopted to perform an extended investigation. We are able to vary independently the swelling degree and the relative size of vesicles, the viscosities of fluids internal and external to vesicles, and the Capillary number, so to observe a rich dynamical phenomenology which goes well beyond what observed for single vesicles, matching quantitatively with experimental findings. Tank-treading, tumbling, and trembling motions are enriched by dynamical states where inner and outer vesicles can perform different motions. We show that thermal fluctuations are crucial during trembling and swinging dynamics, as observed in experiments. Undulating motion of the external vesicle, characterized by periodic oscillation of the inclination and buckling of the membrane, is observed at high filling fractions. This latter state exhibits features that are shown to depend on the relative size, the swelling degree of both vesicles as well as on thermal noise lacking in previous analytical and numerical studies.
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Classical Physics
On Universal Deformations and Material Preferred Directions in Anisotropic Cauchy Elasticity
Seyedemad Motaghian and Arash Yavari
In this paper we study universal deformations in anisotropic Cauchy elasticity. We show that the universality constraints of hyperelasticity and Cauchy elasticity for transversely isotropic, orthotropic, and monoclinic solids are equivalent. This implies that for each of these
symmetry classes the universal deformations and the corresponding universal material preferred directions of hyperelastic and Cauchy elastic solids are identical. This is consistent with previous findings for isotropic solids. Universal deformations and material preferred directions are therefore independent of the existence or absence of a strain energy function.
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Classical Physics · Cross-listed from quant-ph
Michael Rose and David A. Mazziotti
We introduce the correlation-efficient time-
evolution (CETE)
algorithm for simulating
quantum many-body dynamics. CETE recasts each step of time
evolution as a time-independent correlation problem: the ansatz begins from a mean-field single Slater determinant and is then correlated to capture the true time-evolved state. We derive this exact ansatz from a contraction of the time-dependent Schrödinger equation onto the space of two electrons. Unlike conventional
evolution by sequential short-time propagators, which must both correlate and decorrelate the state as the degree of correlation fluctuates in time, CETE correlates only once. This substantially reduces
circuit depth, extending accessible simulation times on near-term
quantum devices. We demonstrate the approach by simulating the time
evolution of the hydrogen molecule's electronic wavefunction, highlighting the potential for the CETE
algorithm to simulate strongly correlated systems on near-term devices.
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Plasma Physics · Cross-listed from astro-ph.SR
Dual Origins of Rapid Flare Ribbon Downflows in an X9-class Solar Flare
Ryan J. French, William H. Ashfield IV, Cole A. Tamburri et al. (+4 more)
We detect rapid downflows of 150-217 km/s in IRIS Si IV 1402.77 nm measurements of an X9-class
solar flare on 2024 October 3rd. The fast
redshift values persist for over 15 minutes from
flare onset, and can be split into two distinct stages of behavior, suggesting that multiple mechanisms are responsible for the downwards acceleration of
flare ribbon
plasma. The first stage of rapid downflows are synchronized with peaks in emission from the Advanced Space-based
Solar Observatory Hard X-ray Imager (ASO-S/HXI) and Large Yield Radiometer (LYRA) Lyman-alpha measurements, indicative that the chromospheric downflows (with a maximum
redshift of 176 km/s) result from chromospheric condensations associated with impulsive energy release in the
solar flare. Later in the event, strong Si IV
flare ribbon downflows persist (to a maximum value of 217 km/s), despite the
magnetic flux rate falling to zero, and high-energy HXR and Lyman-alpha measurements returning to background levels. This is reflective of downflows in the
flare ribbon footpoints of
flare-induced coronal rain. Hard X-ray spectral analysis supports this scenario, revealing strong non-thermal emission during the initial downflow stage, falling near background levels by the second stage. Despite these distinct and contrasting stages of ribbon behavior, Si IV Doppler velocities exhibit quasi-periodic pulsations with a constant ~50 s period across the 15-minute
flare evolution (independently of loop length). We deduce that these pulsations are likely caused by MHD oscillations in the
magnetic arcade. Finally, we utilize machine learning K-means clustering methods to quantify line profile variations during the stages of rapid downflows.
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All authors Ryan J. French, William H. Ashfield IV, Cole A. Tamburri, Maria D. Kazachenko, Marie Dominique, Marcel Corchado Albelo, Amir Caspi
Optics
Quantum Metamorphosis: Programmable Emergence and the Breakdown of Bulk-Edge Dichotomy in Multiscale Systems
Mahmoud Jalali Mehrabad, Alireza Parhizkar, Lida Xu et al. (+6 more)
Multiscale synergy – the interplay of a system's distinct characteristic length, time, and energy scales – is becoming a unifying thread across many contemporary branches of science. Ranging from moiré and super-moiré materials and cold atoms to DNA-templated superlattices and nested photonic networks, multiscale synergy produces behaviors not obtainable at any single scale alone. Yet a general framework that programs cross-scale interplay to steer spectra, transport, and
topology has been missing. Here, we elevate multiscale synergy from a byproduct to a general design principle for emergent phenomena. Specifically, we introduce a scale-programmable framework for hierarchically nested
lattices (HNLs) that can host
quantum metamorphosis (QuMorph) – a continuous
evolution between system-dependent features governed by a dimensionless tunable parameter $\alpha$ (the relative hopping). To exemplify, we show an HNL, in which as $\alpha$ changes, the spectrum metamorphoses from integer
quantum Hall-like to anomalous
quantum Hall-like, passing through a cocoon regime with proliferating mini-gaps. This multiscale mixing yields multiple novel phenomena, including hybrid edge-bulk states, scale-dependent
topology, topologically embedded flat bands, and isolated edge bands. We propose a feasible photonic implementation using commercially available coupled-resonator arrays, outline spatial-spectral signatures to map QuMorph, and explore applications for multi-timescale nonlinear optics. Our work establishes a scalable and programmable paradigm for engineering multiscale emergent phenomena.
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All authors Mahmoud Jalali Mehrabad, Alireza Parhizkar, Lida Xu, Gregory Moille, Avik Dutt, Dirk Englund, Kartik Srinivasan, Daniel Leykam, Mohammad Hafezi
Optics
In-Situ Growth of Halide Perovskite Single Crystals and Thin Films on Optical Fiber End Facets
Yang Yu, Kanak Kanti Bhowmik, Ruan Li et al. (+4 more)
Halide perovskites exhibit significant advantages for active optical components such as light emitting diodes,
solar cells and photodetectors due to their excellent optoelectronic properties. Their nonlinear optical effects and other characteristics also make them suitable for integration into waveguide components, such as optical fibers, for applications like optical modulation. Although some efforts have been made to integrate perovskite nanomaterials with optical fibers, technological challenges have hindered reliable in-situ preparation methods. Herein, we propose an area-selective wetting strategy for optical fibers, which utilizes hydrophobic sidewalls and hydrophilic end facets to reliably hold small precursor droplets. By introducing a space confinement strategy to suppress the kinetics of solvent evaporation, Methylammonium lead bromide (MAPbBr3) perovskite single
crystals were successfully grown in-situ on the fiber end facet. The versatility of this in-situ growth method for single
crystals on fiber end facets of various sizes has also been verified. In a separate approach, the controllable in-situ preparation of CsPbBr3 polycrystalline thin films was achieved through
vacuum-assisted rapid crystallization. Our strategy provides a controllable platform for the integration of perovskite materials and optical fibers, enabling further development in optical applications.
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All authors Yang Yu, Kanak Kanti Bhowmik, Ruan Li, Kexin Li, Lin Zhu, Hai Xiao, Lianfeng Zhao
Space Physics
The Role of Gyrating Ions in Reformation of a Quasi-parallel Supercritical Shock
Hadi Madanian and Terry Z. Liu
Collisionless shocks in space and astrophysical
plasmas mediate energy exchange between charged particles and fields in two or more
plasma flows. In this study we analyze the
evolution of ion distributions around a reformation cycle of a quasi-parallel shock. We use multi-point in-situ observations in the foreshock region of the Earths bow shock of a transient foreshock structure as it generates a shock. We find that backstreaming ions in the foreshock create a density and
magnetic field depletion known as caviton which locally changes the shock geometry. Gyrating suprathermal ions that emerge within the caviton and reach the upstream edge of the core create a cross-field current imbalance that results in the nonlinear growth of a new shock layer. The new shock forms from the background foreshock fields over a distance of ~6 ion inertial lengths ($l_i$) and within 4.5 to 11.2 $l_i$ from the main bow shock. We find that
plasma compression at the new thin shock layer is due to compactification of the cold upstream ion beam by high amplitude
magnetic field-aligned electrostatic fields. At later stages, the
plasma compression expands to form a new sheath.
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Optics
Molecular Engineering for Enhanced Second-Order Nonlinear Response in Spontaneously-Oriented Evaporated Organic Films
Pierre-Luc Thériault, Heorhii V. Humeniuk, Zhechang He et al. (+4 more)
Materials with large second-order nonlinearities are crucial for next-generation integrated photonics. Spontaneously oriented organic thin films prepared by physical vapor deposition offer a promising poling-free and scalable approach. This study investigates molecular engineering strategies to enhance the second-order nonlinear response of derivatives based on the donor-acceptor molecule 2-(4'-diphenylaminobiphenyl-4-yl)quinoxaline-6,7-dicarbonitrile (TPA-QCN). Four derivatives incorporating modifications designed to increase molecular hyperpolarizability ($\beta$) or promote favorable orientation were synthesized and characterized. The most successful modification, intramolecular bridge-locking, simultaneously increases hyperpolarizability and enhances spontaneous orientation by reducing detrimental electrostatic interactions during deposition. It leads to a significant enhancement of the second-order nonlinear response, achieving off-resonance $\chi^{(2)}_{31} \approx 16$ pm V$^{-1}$ and $\chi^{(2)}_{33} \approx 18$ pm V$^{-1}$ at 1550 nm, a twofold improvement over the parent TPA-QCN. Analysis combining nonlinear optical measurements, surface potential measurement, optical anisotropy, and density functional theory calculations indicates that improved molecular orientation, rather than increased $\beta$ alone, is the primary driver for the enhanced performance in the leading derivatives. These findings demonstrate the effectiveness of targeting molecular orientation via structural design and position spontaneously oriented organic films as compelling poling-free candidates for integrated nonlinear photonic applications where the increased electrode-induced optical losses, fabrication complexity and footprint are a critical limitation.
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All authors Pierre-Luc Thériault, Heorhii V. Humeniuk, Zhechang He, Gabriel Juteau, Alexandre Malinge, Dmytro F. Perepichka, Stéphane Kéna-Cohen
Chemical Physics
Open-shell frozen natural orbital approach for quantum eigensolvers
Angela F. Harper, Xiaobing Liu, Scott N. Genin et al. (+1 more)
We present an open-shell frozen natural orbital (FNO) approach, which utilizes the second-order Z-averaged perturbation theory (ZAPT2), to reduce the restricted opten-shell Hartree-Fock virtual space size with controllable accuracy. Our ZAPT2 frozen natural orbital (ZAPT-FNO) selection scheme significantly outperforms the canonical molecular orbital virtual space truncation scheme based on Hartree-Fock orbital energies, especially when using large multiple-polarized and augmented basis sets. We demonstrate that the ZAPT-FNO-selected virtual orbitals lead to a systematic convergence of the correlation energies, but more importantly to the singlet-triplet T$_1$-S$_ 0$ energy gaps with respect to the complete active space (CAS) [occupied + virtual] size. We confirm our findings by simulating T$_1$-S$_ 0$ gaps in H$_2$O$_2$ and O$_2$ molecules using the traditional complete active space configuration interaction (CASCI) approach, as well as in stretched CH$_2$, for which we also employed the iterative
qubit coupled cluster (iQCC) method as a
quantum eigensolver. Finally, we applied the iQCC method with ZAPT-FNO-selected active space to the phosphorescent Ir(ppy)$_3$ complex with 260 electrons, where extended basis sets are required to achieve chemical (ca. 1 m$E_h$) accuracy. In this case, CASCI results are not available; however, the iQCC-computed T$_1$-S$_ 0$ gaps show robust convergence with enlarging basis set and CAS size, approaching the experimental value. Thus, the ZAPT-FNO method is very promising for improving the accuracy of
quantum chemical modelling in a resource-efficient manner, and opens the door to simulating open-shell states of large materials within realistic active space sizes and without compromising on basis-set quality.
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All authors Angela F. Harper, Xiaobing Liu, Scott N. Genin, Ilya G. Ryabinkin
Data Analysis and Statistics · Cross-listed from cs.LG
Scientific Data Compression and Super-Resolution Sampling
Minh Vu and Andrey Lokhov
Modern scientific simulations, observations, and large-scale experiments generate data at volumes that often exceed the limits of storage, processing, and analysis. This challenge drives the development of data reduction methods that efficiently manage massive
datasets while preserving essential physical features and quantities of interest. In many scientific workflows, it is also crucial to enable data recovery from compressed representations - a task known as super-resolution - with guarantees on the preservation of key physical characteristics. A notable example is checkpointing and restarting, which is essential for long-running simulations to recover from failures, resume after interruptions, or examine intermediate results. In this work, we introduce a novel framework for scientific data compression and super-resolution, grounded in recent advances in learning exponential families. Our method preserves and quantifies uncertainty in physical quantities of interest and supports flexible trade-offs between compression ratio and reconstruction fidelity.
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Applied Physics · Cross-listed from cond-mat.mes-hall
High-Efficiency Three-Stroke Quantum Isochoric Heat Engine: From Infinite Potential Wells to Magic Angle Twisted Bilayer Graphene
Hadi Mohammed Soufy and Colin Benjamin
We introduce a three-stroke
quantum isochoric cycle that functions as a heat engine operating between two thermal reservoirs. Implemented for a particle confined in a one-dimensional infinite potential well, the cycle's performance is benchmarked against the classical three-stroke triangular and isochoric engines. We find that the
quantum isochoric cycle achieves a higher efficiency than both classical counterparts and also surpasses the efficiency of the recently proposed three-stroke
quantum isoenergetic cycle. Owing to its reduced number of strokes, the design substantially lowers control complexity in nanoscale thermodynamic devices, offering a more feasible route to experimental realization compared to conventional four-stroke architectures. We further evaluate the cycle in
graphene-based systems under an external
magnetic field, including monolayer
graphene (MLG), AB-stacked
bilayer graphene (BLG), and twisted
bilayer graphene (TBG) at both magic and non-magic twist angles. Among these platforms, magic-angle twisted
bilayer graphene (MATBG) attains the highest efficiency at fixed work output, highlighting its promise for
quantum thermodynamic applications.
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Applied Physics
Ultrafast propagation of magnon-polaritons
Ondřej Wojewoda, Miela J. Gross, Jan Klíma et al. (+11 more)
The manipulation of magnetization lies at the heart of spintronic and magnonic technologies, with the ultimate performance of such systems limited by the velocity at which
magnetic excitations can propagate. Here, we demonstrate ultrafast propagation of
magnon-polaritons-hybrid quasiparticles arising from the coupling between
spin waves and electromagnetic fields in thin pure, bismuth-, and gallium substituted yttrium iron garnet (YIG, Bi:YIG and Ga:YIG) films. Using time- and phase-resolved Brillouin light scattering microscopy and time-resolved scanning transmission microscopy, we show that
magnon-polaritons can propagate faster than 100 km/s, nearly three orders of magnitude more than conventional
spin waves, and can be observed at distances exceeding 40 micrometers in 20 nm thick films. Analytical modeling based on retarded Maxwell equations and Polder tensor formalism confirms the hybridized nature of the excitations and captures the nontrivial dispersion and attenuation profiles. Notably, the
magnon-polaritons maintain high initial magnetization amplitudes and long decay lengths, enabling ultrafast manipulation of the magnetization far away from the excitation source. We show, that they can move domain walls or stabilize nonlinear magnetization processes. The unprecedentedly high propagation velocities make
magnon-polaritons promising candidates for high-speed information transfer in future
spin-based computing architectures, potentially overcoming long-standing group delay bottlenecks in magnonic logic
circuits.
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All authors Ondřej Wojewoda, Miela J. Gross, Jan Klíma, Jaganandha Panda, Jakub Krčma, Jakub Holobrádek, Kristýna Davídková, Andrii V. Chumak, Philipp Pirro, Roman Verba, Sebastian Wintz, Qi Wang, Caroline A. Ross, Michal Urbánek
Instrumentation and Detectors
Exploring the production of Terbium-161 in the Brazilian Multipurpose Reactor
Fernando Cozim Melges, Jhonatha Ricardo Santos, Luiz Paulo de Oliveira et al. (+6 more)
The Brazilian Multipurpose Reactor (RMB) was conceived to meet national needs for radioisotope production, materials irradiation testing, and
neutron beam applications. In addition to its 30~MW pool-type reactor, the RMB complex will include additional facilities for radioisotope production and related applications. $^{161}Tb$ is a promising radionuclide for radiopharmaceutical therapy, offering decay properties similar to $^{177}Lu$ but with additional conversion and Auger electrons that enhance dose delivery to cancer
cells. In light of this emerging radioisotope, this study explores the potential production of $^{161}Tb$ in the RMB through
neutron irradiation of enriched $Gd_{2}O_{3}$ targets. Monte Carlo (MCNP) simulations provided detailed
neutron flux distributions, which were used as input for ORIGEN calculations of isotope buildup. Assuming 10 mg targets enriched to 97.5% in $^{160}Gd$, a 40-day irradiation, and a thermal flux of $2 \cdot 10^{14}$ $n/cm^{2}s$, the results indicate that $^{161}Tb$ activity reaches approximately 4.5 GBq after 14 days ($\approx 450 GBq/g$), in agreement with data from other research reactors. Building on prior studies that demonstrated the RMB's capability to irradiate larger targets, terabecquerel-scale yields appear feasible. These findings highlight the RMB's potential to support domestic production of emerging therapeutic radionuclides such as $^{161}Tb$. The potential for isotopic enrichment of $^{160}Gd$ using the AVLIS method is also discussed.
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All authors Fernando Cozim Melges, Jhonatha Ricardo Santos, Luiz Paulo de Oliveira, Alexandre Pinho dos Santos Souza, Carlos Gabriel Santos da Silva, Iberê Souza Ribeiro Júnior, Barbara Perez Gonçalves Silva, Marco Antonio Stanojev Pereira, Frederico Antonio Genezini
Medical Physics · Cross-listed from eess.IV
Smooth Total variation Regularization for Interference Detection and Elimination (STRIDE) for MRI
Alexander Mertens, Diego Martinez, Amgad Louka et al. (+3 more)
MRI is increasingly desired to function near electronic devices that emit potentially dynamic electromagnetic interference (EMI). To accommodate for this, we propose the STRIDE method, which improves on previous external-sensor-based EMI removal methods by exploiting inherent MR image smoothness in its total variation. STRIDE measures data from both EMI detectors and primary MR imaging coils, transforms this data into the image domain, and for each column of the resulting image array, combines and subtracts data from the EMI detectors in a way that optimizes for total-variation smoothness. Performance was tested on phantom and in-vivo
datasets with a 0.5T scanner. STRIDE resulted in visually better EMI removal, higher temporal SNR, larger EMI removal percentage, and lower RMSE than standard implementations. STRIDE is a robust technique that leverages inherent MR image properties to provide improved EMI removal performance over standard
algorithms, particularly for time-varying noise sources.
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All authors Alexander Mertens, Diego Martinez, Amgad Louka, Ying Yang, Chad Harris, Ian Connell
Optics · Cross-listed from quant-ph
Modeling Quantum Noise in Nanolasers using Markov Chains
Matias Bundgaard-Nielsen, Gian Luca Lippi and Jesper Mørk
The random nature of spontaneous emission leads to unavoidable fluctuations in a
laser's output. This is often included through random Langevin forces in
laser rate equations, but this approach falls short for nanolasers. In this paper, we show that the
laser quantum noise can be quantitatively computed for a very broad class of
lasers by starting from simple and intuitive rate equations and merely assuming that the number of
photons and excited electrons only takes discrete values. While the approach has seen previous success, we here derive it rigorously from an open
quantum system master equation, whereas it was previously introduced only on phenomenological grounds. We further show that in the many-
photon limit, the model simplifies to Langevin equations. We perform an extensive comparison of different approaches for computing
quantum noise in
lasers, identifying the best approach for different system sizes, ranging from nanolasers to macroscopic
lasers, and different levels of excitation, i.e., cavity
photon number. In particular, we show that below the
laser threshold,
stochastic fluctuations in the numerical solution to the Langevin equations can drive populations to unphysical negative values, requiring the introduction of population bounds, which in turn skew the noise statistics, leading to inaccuracies. The
Laser Markov Chain model, on the other hand, is accurate for all pump values and
laser sizes when collective emitter effects are excluded.
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Instrumentation and Detectors
Variable-temperature attenuator calibration method for on-wafer microwave noise characterization of low-noise amplifiers
Anthony J. Ardizzi, Jiayin Zhang, Akim A. Babenko et al. (+2 more)
Low-noise cryogenic microwave amplifiers are widely used in applications such as
radio astronomy and
quantum computing. On-wafer noise characterization of cryogenic low-noise transistors is desirable because it facilitates more rapid characterization of devices prior to packaging, but obtaining accurate noise measurements is difficult due to the uncertainty arising from the input loss and temperature gradients prior to the device-under-test (DUT). Here, we report a calibration method that enables the simultaneous determination of the backend noise temperature and effective-noise-ratio at the input plane of the DUT. The method is based on measuring the S-parameters and noise power of a series of attenuators at two or more distinct physical temperatures. We validate our method by measuring the noise temperature of InP HEMTs in 4-8 GHz. The calibration method can be generalized to measure the microwave noise temperature of any two-port device so long as a series of attenuators can be measured at two or more distinct physical temperatures.
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All authors Anthony J. Ardizzi, Jiayin Zhang, Akim A. Babenko, Kieran A. Cleary, Austin J. Minnich
Optics · Cross-listed from quant-ph
Long-range entanglement and quantum correlations in a multi-frequency comb system
Sahil Pontula, Debasmita Banerjee, Marin Soljacic et al. (+1 more)
Frequency combs are multimode photonic systems that underlie countless precision sensing and metrology applications. Since their invention over two decades ago, numerous efforts have pushed frequency combs to broader bandwidths and more stable operation. More recently,
quantum squeezing and
entanglement have been explored in single frequency comb systems for
quantum advantages in sensing and signal multiplexing. However, the production of
quantum light across multiple frequency combs remains unexplored. In this work, we theoretically explore a mechanism that generates a series of nonlinearly coupled frequency combs through cascaded three-wave upconversion and downconversion processes mediated by a single idler comb. We show how this system generates inter- and intracomb two-mode squeezing and
entanglement spanning a very large spectral range, from ultraviolet to mid-IR frequencies. Finally, we show how this system can be engineered to produce on-demand multimode
quantum light through covariance
matrix optimization. Our findings could enable tunable broadband ghost spectroscopy protocols, squeezing-enhanced pump-probe measurements, and broadband
entanglement between spectrally-multiplexed quanta of information.
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All authors Sahil Pontula, Debasmita Banerjee, Marin Soljacic, Yannick Salamin
Instrumentation and Detectors
Development of a Low-Cost, Autonomous Pulse Amplitude Modulated (PAM) Chlorophyll Fluorometer for In-Situ Monitoring of Photosystem II Efficiency
Samaneh Baghbani, Uygar Akkoc, Clara Stock et al. (+2 more)
The
quantum yield efficiency of photosystem II (PhiPSII) is an important parameter for assessing the photosynthetic performance and stress status of plants. Commercial PAM fluorometers can measure this parameter, but they are often expensive, bulky, or lack autonomous operation. This work presents the development of an autonomous PAM fluorometer designed to address these limitations and enable large-scale deployment. It supports high spatio-temporal monitoring of PhiPSII in forest canopies under a wide range of ambient light conditions. The prototype costs approximately 150 EUR, has dimensions of 3 cm x 6 cm x 2 cm, and weighs about 50 g. In side-by-side tests across three plant species, it achieved measurement accuracy comparable to state-of-the-art commercial sensors, with a correlation factor of R^2 = 0.95.
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All authors Samaneh Baghbani, Uygar Akkoc, Clara Stock, Christiane Werner, Stefan J. Rupitsch
Optics
Calibration of Microscope-coupled Fourier Transform Infrared Spectrometers for CW and Modulated Light Emission Measurements
Maxime Brazeau, Mathieu Giroux, Nada Boubrik et al. (+1 more)
Measurement of low power infrared light emission spectra from microstructures can be challenging, but is of key importance in several research fields.
Fourier transform infrared spectrometers (FTIR) can be used for characterizing such weak light emitters, but this requires additional custom user calibration compared to traditional FTIR measurements of, e.g., transmission or reflection. These calibration techniques are well documented for standalone FTIR instruments but not for microscope coupled-FTIRs, even though such an architecture greatly simplifies collection of light from micro and nano scale structures. We propose and demonstrate a calibration method for microsope-FTIRs based on the well-known emissivity of doped silicon at high temperature. With this method, we measure responsivity and noise floor of a recently installed microscope-FTIR instrument (Bruker\textsuperscript{\textcopyright} Invenio\textsuperscript{\textregistered} R coupled with a Hyperion II microscope), which is found to be within theoretically predicted values. The method is demonstrated for two different detectors (Mercury Cadmium Telluride and Indium Antimonide), in both continuous wave (CW) and modulated (step-scan) emission measurements mode.
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All authors Maxime Brazeau, Mathieu Giroux, Nada Boubrik, Raphael St-Gelais
Chemical Physics
Electron Correlation by Exchange Mapping in Electronic Structure Calculations
Jerry L. Whitten
A method for increasing the accuracy of configuration interaction (CI) calculations of molecules and other electronic systems is proposed. The energy defect of a given calculation is associated with the electron pair origin of configurations not yet generated and this defect is mapped onto the exchange interaction for the corresponding pair of spatial molecular orbitals. The orbitals can be of opposite
spin and thus the contribution includes the self-energy and differs from
fermion exchange due to antisymmetry. A single parameter multiplying the exchange integral, is determined from the exact thermodynamic energy of a few reference molecules. The value of the parameter depends on the basis and level of configuration interaction but is the same for all molecules. Calculated energies are compared with experimental thermodynamic data for a set of forty mainly organic molecules representing a wide range of bonding environments. Results are reported for two types of multi- reference CI calculations: 1) a triple-
zeta basis plus d-type functions for C, N, O and F and an s, p basis for H, and 2) a severely truncated virtual space in which higher spherical harmonic basis functions are removed. The error of the initial CI calculations is large, however, including the exchange-based contribution brings calculated CI energies into much closer agreement with exact values.
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Fluid Dynamics
Identification of triadic phase coupling in wall-bounded turbulence using the bispectrum
Clayton P. Byers and Subrahmanyam Duvvuri
The direction and magnitude of energy transfer between
turbulence scale brought about by external forcing on a turbulent boundary layer are uncovered through the bispectrum, bicoherence, and biphase. The bispectrum is a third-order, complex-valued spectrum of the streamwise velocity that preserves the phase information between triadically consistent scales. Normalized bispectrum is the bicoherence, a measure of the relative amount of energy at a higher frequency that results from quadratic phase coupling of two lower frequencies. The phase of the bispectrum, the biphase, measures the phase lag between the high frequency and two lower frequencies that add to it, unveiling whether a triadic interaction produces a forward or reverse cascade of energy. Summing the bispectrum over triadically consistent frequencies allows a spectral decomposition of the velocity skewness and asymmetry, unveiling the triadically active scales in the energy transfer processes. An average sense of energy transfer is inferred from the phase of this skewness spectrum, which shows that scales smaller than the boundary layer thickness contribute to a forward cascade on average, while those larger than the boundary layer thickness have a mix of forward and reverse events. These measures show that the forced scales in the perturbed boundary layer have a mixture of forward and reverse energy transfer processes for different sets of triadic scales and wall-normal locations, providing a method of quantifying the effects of external perturbations on turbulent flows without any need for artificial filtering.
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Computational Physics · Cross-listed from q-bio.BM
MDIntrinsicDimension: Dimensionality-Based Analysis of Collective Motions in Macromolecules from Molecular Dynamics Trajectories
Irene Cazzaniga and Toni Giorgino
Molecular dynamics (MD) simulations provide atomistic insights into the structure, dynamics, and function of biomolecules by generating time-resolved, high-dimensional trajectories. Analyzing such data benefits from estimating the minimal number of variables required to describe the explored conformational
manifold, known as the intrinsic dimension (ID). We present MDIntrinsicDimension, an open-source Python package that estimates ID directly from MD trajectories by combining rotation- and translation-invariant molecular projections (e.g., backbone dihedrals and inter-residue distances) with state-of-the-art
estimators. The package provides three complementary analysis modes: whole-molecule ID; sliding windows along the sequence; and per-secondary-structure elements. It computes both overall ID (a single summary value) and instantaneous, time-resolved ID that can reveal transitions and heterogeneity over time. We illustrate the approach on fast folding-unfolding trajectories from the DESRES
dataset, demonstrating that ID complements conventional
geometric descriptors by highlighting spatially localized flexibility and differences across structural segments.
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Physics and Society
The Influence of Neighborhood Design on the Sustainability of US Suburbs
Arianna Salazar-Miranda
The growth of suburbs in the US has led to significant sustainability challenges; yet, it remains unclear whether these challenges stem from the remoteness of suburbs from city centers or the specific designs used to develop them. This paper examines how Garden City Design (GCD) – one of the most influential suburban design paradigms since the early 20th century – impacts the social and environmental outcomes of neighborhoods. I first introduce a composite measure of GCD, derived from street layouts and block configurations, to quantify its nationwide adoption. I use this measure combined with mobility and emissions data to estimate the impact of GCD on neighborhood outcomes using complementary identification strategies, including ordinary least squares (OLS), matching
estimators, and an instrumental variables (IV) approach that exploits historical variation in GCD adoption. Results show that GCD leads to worse sustainability outcomes, including increased greenhouse gas emissions, greater social isolation, and higher sedentary behavior. The prevalence of GCD accounts for 27-38% of the adverse effects associated with suburbanization, underscoring the crucial role that neighborhood design plays in shaping urban sustainability.
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Applied Physics
In-memory phononic learning toward cognitive mechanical intelligence
Yuning Zhang and K. W. Wang
Modern autonomous systems are driving the critical need for next-generation adaptive materials and structures with
embodied intelligence, i.e., the embodiment of
memory, perception, learning, and decision-making within the mechanical domain. A fundamental challenge is the seamless and efficient integration of
memory with information processing in a physically interpretable way that enables cognitive learning and decision-making under uncertainty. Prevailing paradigms, from intricate logic cascades to black-box morphological computing or physical neural networks, are seriously limited by trade-offs among efficiency, scalability, interpretability, transparency, and reliance on additional electronics. Here, we introduce in-
memory phononic learning, a paradigm-shifting framework that unifies nonvolatile mechanical
memory with wave-based perception within a phononic metastructure. Our system encodes spatial information into stable structural states as mechanical
memory that directly programs its elastic wave-propagation landscape. This
memory/wave-dynamics coupling enables effective sensory perception, decomposing complex patterns into informative
geometric features through frequency-selective wave localization. Learning is created by optimizing input waveforms to selectively probe these features for
memory-pattern classification, with decisions inferred directly from the output wave energy, thereby completing the entire information loop mechanically through an efficient and physically transparent mechanism without hidden architectures or electronics. This work transcends the paradigm of 'materials that compute' to cognitive matter capable of interpreting dynamic environments, paving the way for future intelligent structural-material systems with low power consumption, more direct interaction with surroundings, and enhanced cybersecurity and resilience in harsh conditions.
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Chemical Physics
Formation of HNC and HCN isomers in molecular plasmas revealed by frequency comb and quantum cascade laser spectroscopy
Ibrahim Sadiek, Simona Di Bernardo, Uwe Macherius et al. (+1 more)
Hydrogen cyanide (HCN) is a well-known product in combustion, astrophysical, and
plasma environments, but its isomer, hydrogen isocyanide (HNC), remains unexplored in molecular
plasmas. Here, we report on the detection and quantification of both HNC and HCN isomers in low-temperature
plasmas generated from N$_2$/H$_2$/CH$_4$ mixtures using
quantum cascade
laser and frequency comb absorption spectroscopy. The identification of HNC is confirmed by comparison with molecular spectroscopic databases. The observed [HNC]/[HCN] abundance ratio of $\sim 10^{-4}$ is far lower than reported values in interstellar media, where ratios can reach unity. We attribute this stark difference to fundamentally different kinetics, dominated by an interplay between formation of vibrationally 'hot' intermediates (HCN* and HNC*) and their subsequent stabilization and destruction. This mechanism contrasts with cold interstellar environments, where dissociative recombination reactions dominate and the formed HNC persists and accumulates over astrochemical timescales. Our results highlight the overlooked role of HNC in
plasma chemistry containing carbon, nitrogen and hydrogen, with implications for
plasma-assisted HCN synthesis and nitrogen-carbon
plasma processes in surface modification and material treatments.
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All authors Ibrahim Sadiek, Simona Di Bernardo, Uwe Macherius, Jean-Pierre H. van Helden