Optics
Meniscope: A Low-Cost Fluid Interface Visualizer
Daniel M. Harris
In this work, we describe the development and application of a low-cost fluid interface visualizer referred to as the “Meniscope.” The device works using a color-based surface gradient detector method that maps the gradient of an air-water interface to a specific color on a target pattern below using a converging lens. Sample experiments are outlined that showcase the working principle and functional versatility of the device. The device and assembly instructions were piloted in a hands-on workshop, with pertinent feedback reviewed herein. The Meniscope is a low-cost device that is capable of producing striking visualizations of static and dynamic free-surface deformations while introducing users to free-surface measurement techniques in an accessible and hands-on manner.
Read the full abstract ▾
Data Analysis and Statistics
GNN For Muon Particle Momentum estimation
Vishak K Bhat, Eric A. F. Reinhardt and Sergei Gleyzer
Due to a high rate of overall data generation relative to data generation of interest, the CMS experiment at the Large
Hadron Collider uses a combination of hardware- and software-based triggers to select data for capture. Accurate momentum calculation is crucial for improving the efficiency of the CMS trigger systems, enabling better classification of low- and high- momentum particles and reducing false triggers. This paper explores the use of Graph Neural Networks (GNNs) for the momentum estimation task. We present two graph construction methods and apply a GNN model to leverage the inherent graph structure of the data. In this paper firstly, we show that the GNN outperforms traditional models like TabNet in terms of Mean Absolute Error (MAE), demonstrating its effectiveness in capturing complex dependencies within the data. Secondly we show that the dimension of the node feature is crucial for the efficiency of GNN.
Read the full abstract ▾
Classical Physics
Universal Displacements in Linear Strain-Gradient Elasticity
Dimitris Sfyris and Arash Yavari
We study universal displacement fields in three-dimensional linear strain-gradient elasticity within the Toupin-Mindlin first strain-gradient theory. Building on the approach of Yavari (2020), we derive, for each material
symmetry class, the universality PDEs obtained by requiring the
equilibrium equations (in the absence of body forces) to hold for any material in that class, and we determine the complete set of universal displacements. Using the full
symmetry classification together with compact
matrix representations of the elasticity tensors, we provide explicit characterizations for all 48 strain-gradient
symmetry classes, including centrosymmetric and
chiral classes. For several high-
symmetry classes, the strain-gradient universality PDEs impose no additional restrictions beyond the classical ones, so the universal displacement families coincide with those of classical linear elasticity (for example, the isotropic classes SO(3) and O(3)). For lower
symmetry classes, the strain-gradient universality PDEs can be stricter than their classical counterparts, so the universal displacements form proper subsets of the classical universal displacement families due to additional higher-order differential conditions.
Read the full abstract ▾
Instrumentation and Detectors · Cross-listed from astro-ph.IM
SNAPPY CubeSat Control Script Generation and Data File Processing
Edward Bierens, Jonathan Folkerts, Brian Doty et al. (+2 more)
This is a document discussing the creation and usage of a server system dedicated to retrieving, processing, and storing data generated from the
Solar Neutrino and Astro-Particle PhYsics (SNAPPY) CubeSat by the nuSOL (
Neutrino Solar Orbiting Laboratory) Project. On a traditional desktop computer with CERN's ROOT and PostgreSQL software installed, and with a file system on two mirrored drives, it is possible to automatically process and organize incoming data, along with keeping a database to record each incoming file along with a command record. In addition to this, an application was created to provide a Graphical User Interface to assist with creating commands to communicate with the CubeSat. With that said, there are still plenty of plans to improve the software, mainly providing an automatic emailing system to notify team members when they are not around the server.
Read the full abstract ▾
All authors Edward Bierens, Jonathan Folkerts, Brian Doty, Holger Meyer, Nickolas Solomey
Atomic Physics
Full-dimensional quantum scattering calculations of rovibrationally excited HD+HD collisions
Bikramaditya Mandal, Hubert Jóźwiak, Piotr Wcisło et al. (+1 more)
Full-dimensional
quantum scattering calculations are reported for ro-vibrational transitions in HD+HD collisions using a highly accurate interaction potential for the H$_2$-H$_2$ system. Several near-resonant ro-vibrational transitions are identified that conserve the overall rotational angular momentum and nearly conserve the internal energy of the collision partners. Key anisotropic terms that drive the rotational transitions and angular momentum partial waves that contribute to low energy resonant features in the energy dependence of the cross sections are identified. The computed results are in agreement with total cross sections reported in previous experimental results, including resonant features in the energy dependence of the cross section. In particular, low-energy cross sections show a strong resonant feature associated with an $l=3$ partial wave in the incident channel. Rate coefficients for several inelastic rotational and ro-vibrational transitions are reported for temperatures ranging from $0.1$ K to $200$ K and they display a maximum between $1$ K-$10$ K reflecting the important contributions from the $l=3$ shape resonance that occurs around 2.5 K.
Read the full abstract ▾
All authors Bikramaditya Mandal, Hubert Jóźwiak, Piotr Wcisło, Naduvalath Balakrishnan
Physics and Society · Cross-listed from cs.AI
Capability Thresholds and Manufacturing Topology: How Embodied Intelligence Triggers Phase Transitions in Economic Geography
Xinmin Fang, Lingfeng Tao and Zhengxiong Li
The fundamental
topology of manufacturing has not undergone a paradigm-level transformation since Henry Ford's moving assembly line in 1913. Every major innovation of the past century, from the Toyota Production System to Industry 4.0, has optimized within the Fordist paradigm without altering its structural logic: centralized mega-factories, located near labor pools, producing at scale. We argue that
embodied intelligence is poised to break this century-long stasis, not by making existing factories more efficient, but by triggering phase transitions in manufacturing economic geography itself. When
embodied AI capabilities cross critical thresholds in dexterity, generalization, reliability, and tactile-
vision fusion, the consequences extend far beyond cost reduction: they restructure where factories are built, how supply chains are organized, and what constitutes viable production scale. We formalize this by defining a Capability Space C = (d, g, r, t) and showing that the site-selection objective function undergoes topological reorganization when capability vectors cross critical surfaces. Through three pathways, weight inversion, batch collapse, and human-infrastructure decoupling, we show that
embodied intelligence enables demand-proximal micro-manufacturing, eliminates "manufacturing deserts," and reverses geographic concentration driven by labor arbitrage. We further introduce Machine
Climate Advantage: once human workers are removed, optimal factory locations are determined by machine-optimal conditions (low humidity, high irradiance, thermal stability), factors orthogonal to traditional siting logic, creating a production geography with no historical precedent. This paper establishes
Embodied Intelligence Economics, the study of how physical AI capability thresholds reshape the spatial and structural logic of production.
Read the full abstract ▾
Plasma Physics
Cavitons Associated with Ion-Acoustic-Like Waves in Foreshock Transients
Runyi Liu, Terry Liu, Xin An et al. (+2 more)
Foreshock transients upstream of the Earth's bow shock, such as foreshock bubbles and hot flow anomalies, are often characterized by reduced-density cores and strong
plasma fluctuations. These conditions provide environments where electrostatic wave activity and localized density structures can coexist. Using high-time-resolution measurements from the Magnetospheric Multiscale (MMS) mission, we investigate the relationship between bursty electrostatic wave activity and localized electron density depletions within foreshock transients. A representative case study reveals a clear scaling between wave activity and density depletion, and a statistical analysis across multiple events shows that this scaling persists when the wave activity, with characteristics consistent with ion-acoustic-like waves, is represented in terms of electrostatic potential fluctuations normalized by electron temperature. In contrast, representations based on electric field amplitude, even when similarly normalized, exhibit substantial event-to-event variability. These results provide observational evidence for a causal relationship between ion-acoustic-like electrostatic wave activity and cavitons in foreshock
plasmas.
Read the full abstract ▾
All authors Runyi Liu, Terry Liu, Xin An, Vassilis Angelopoulos, Xiaofei Shi
Chemical Physics
Absolute Primary Nanothermometry Using Individual Stark Sublevels of Rare-Earth-doped Crystals
Allison R. Pessoa, Thomas Possmayer, Jefferson A. O. Galindo et al. (+4 more)
We present two independent optical methods for absolute primary thermometry using rare-earth-doped nanoparticles. Both approaches rely exclusively on the internal energy levels and population dynamics of the dopant ions, eliminating the need for external temperature references. We experimentally demonstrate the concepts by using Y$_2$O$_3$: Yb$^{3+}$/Er$^{3+}$ nanoparticles, exploiting Boltzmann distribution between individual Stark sublevels of the Er$^{3+}$ ions, emitting in the green spectral region ($\sim$550 nm) and in the near-infrared spectral region ($\sim$1600 nm). Our strategy establishes rare-earth-based luminescence thermometers as genuine absolute primary probes, conceptually comparable to Johnson noise and acoustic gas thermometers, but with the fundamental advantage of possibly being employed at the nanoscale, potentially down to the single-ion limit, with optical readout and over wide temperature ranges.
Read the full abstract ▾
All authors Allison R. Pessoa, Thomas Possmayer, Jefferson A. O. Galindo, Luiz F. dos Santos, Rogéria R. Gonçalves, Leonardo de S. Menezes, Anderson M. Amaral
Instrumentation and Detectors · Cross-listed from hep-ex
Enhancing Angular Sensitivity of Segmented Antineutrino Detectors for Reactor Monitoring
Brian C. Crow, Max A. A. Dornfest, John G. Learned et al. (+4 more)
We present a potential improvement over the standard method developed to determine antineutrino directionality in inverse-beta-decay detectors. The previously developed method for quantifying directionality in monolithic and segmented detectors may be ambiguous in methodology. In this paper, we present a directionality
algorithm and include error analysis. We have developed an
algorithm based on a measure of “distance” between two
matrices. We report findings for our research in reactor-antineutrino directionality, and emphasize that the
algorithm has broad applications whenever one desires computationally efficient 2D pattern-matching. We treat data from Lithium-6-doped detector segments in the form of a
matrix. The validation of our
algorithm boils down to comparing a Monte Carlo generated “empirical” data set to a simulated data set. The empirical data set is generated for a particular orientation of the
neutrino beam. We identify an optimal
segmentation scale in the low-count regime. We also discuss the shortcomings of the conventional method and how this knowledge can be applied to segmented detectors, hybrid designs, and generalized validation, agnostic to the physics of detector design.
Read the full abstract ▾
All authors Brian C. Crow, Max A. A. Dornfest, John G. Learned, Jackson D. Seligman, Nathan S. Sibert, Jeffrey G. Yepez, Viacheslav A. Li
Optics
Finite-Size Effects in Nonlocal Metasurfaces
Tom Hoekstra, Sander A. Mann and Jorik van de Groep
Metasurfaces leveraging nonlocal resonances enable narrowband spectral control and strong near-fields, with applications spanning augmented reality, biosensing, and nonlinear optics. However, the large spa- tial extent of these modes also poses new challenges: finite-size effects often deteriorate the performance of practical, footprint-limited devices. Here, we develop a spatiotemporal coupled-mode theory model that intuitively and quantitatively captures how finite size affects the scattering response of nonlocal metasurfaces. This reveals that, when the modal propagation length becomes constrained by the phys- ical interaction length, the scattered field shows strong interference fringes and linewidth broadening. We derive an expression for the quality factor that incorporates an additional edge-loss channel, demon- strating that the stored energy and effective lifetime scale exponentially with the interaction length. We validate these predictions experimentally using position- and momentum-resolved spectroscopy on a 30-micron-wide metasurface. Overall, this work formalizes the impact of finite size on the scattering re- sponse of nonlocal photonic systems, and provides handles on how to minimize the impact of finite-size effects in metasurface design.
Read the full abstract ▾
Biological Physics
Learning functional groups in complex microbiomes
Matthew S Schmitt, Kiseok Lee, Freddy Bunbury et al. (+3 more)
From soil to the gut, communities composed of thousands of microbes perform functions such as carbon sequestration and immune system regulation. Here, we introduce a data-driven approach that explains how community function can be traced to just a few groups of microbes or genes. In gut communities, our neural-network based clustering
algorithm correctly recovers known functional groups. In the ocean metagenome, it distills ~500 gene modules down to three sparse groups highlighting survival strategies at different depths. In soils, it distills ~4400 bacterial species into two groups that enter a mathematical model of nitrate metabolism. By combining interpretable ML with strain isolation and sequencing experiments, we connect the metabolic specialization of each group to community-wide responses to perturbations. This integrated approach yields simple structure-function maps of microbiomes, allowing the discovery of molecular mechanisms underlying human and environmental health. More broadly, we illustrate how to do function-informed dimensionality reduction in biology.
Read the full abstract ▾
All authors Matthew S Schmitt, Kiseok Lee, Freddy Bunbury, Joseph A Landsittel, Vincenzo Vitelli, Seppe Kuehn
Optics · Cross-listed from gr-qc
Analogue Hawking radiation in nonlinear quantum optics
Isaac Bernal, Miguel A. Cortés-Ortiz and David Bermudez
The Hawking effect can be understood as a broad kinematic phenomenon associated with mode behavior near a horizon. While astrophysical black holes produce one specific realization of this radiation, this perspective inspires extensive theoretical and experimental efforts to create event horizons in diverse physical systems to observe the resulting analogue Hawking emission. One of the most successful realizations is the fiber-optical analogue, based on nonlinear
quantum optics. In these notes, we introduce and motivate this system while outlining the theoretical concepts underlying the gravitational analogy. Finally, we review key experiments and discuss their impact on the field.
Read the full abstract ▾
Data Analysis and Statistics · Cross-listed from cond-mat.dis-nn
q-Gaussian Crossover in Overlap Spectra towards 3D Edwards-Anderson Criticality
Yaprak Onder, Abbas Ali Saberi and Roderich Moessner
We introduce a spectral approach to characterizing the three-dimensional Edwards-Anderson
spin glass. By analyzing the
eigenvalue statistics of overlap
matrices constructed from two-dimensional cross-sections, we identify a crossover from the Wigner semicircle law at high temperatures towards a Gaussian distribution, which is consistently attained near the
spin-glass critical point. Visible for different distributions of the random coupling, the Gaussian distribution can potentially serve as a robust spectral indicator of criticality. Remarkably, the spectral density is well-described by Tsallis statistics, with the entropic index $q$ evolving from $q = -1$ (semicircle, $T=\infty$) to $q = 1$ (Gaussian) at $T_c$, revealing a statistical structure inside the paramagnetic phase. We find $q\le 1$ within numerical precision. While the local level statistics remain consistent with GOE statistics, reflecting standard level repulsion, the temperature dependence appears mainly in the global spectral density. Our results present spectral statistics as a computationally efficient complement to multi-replica correlator methods and provide a new perspective on cooperative and critical phenomena in disordered systems.
Read the full abstract ▾
Chemical Physics · Cross-listed from cs.LG
Orbital Transformers for Predicting Wavefunctions in Time-Dependent Density Functional Theory
Xuan Zhang, Haiyang Yu, Chengdong Wang et al. (+3 more)
We aim to learn wavefunctions simulated by time-dependent density functional theory (TDDFT), which can be efficiently represented as linear combination coefficients of atomic orbitals. In real-time TDDFT, the electronic wavefunctions of a molecule evolve over time in response to an external excitation, enabling first-principles predictions of physical properties such as optical absorption, electron dynamics, and high-order response. However, conventional real-time TDDFT relies on time-consuming propagation of all occupied states with fine time steps. In this work, we propose OrbEvo, which is based on an equivariant graph
transformer architecture and learns to evolve the full electronic wavefunction coefficients across time steps. First, to account for external field, we design an equivariant conditioning to encode both strength and direction of external electric field and break the
symmetry from SO(3) to SO(2). Furthermore, we design two OrbEvo models, OrbEvo-WF and OrbEvo-DM, using wavefunction pooling and density
matrix as interaction method, respectively. Motivated by the central role of the density functional in TDDFT, OrbEvo-DM encodes the density
matrix aggregated from all occupied electronic states into feature vectors via tensor contraction, providing a more intuitive approach to learn the time
evolution operator. We adopt a training strategy specifically tailored to limit the error accumulation of time-dependent wavefunctions over autoregressive rollout. To evaluate our approach, we generate TDDFT
datasets consisting of 5,000 different molecules in the QM9
dataset and 1,500 molecular configurations of the malonaldehyde molecule in the MD17
dataset. Results show that our OrbEvo model accurately captures
quantum dynamics of excited states under external field, including time-dependent wavefunctions, time-dependent dipole moment, and optical absorption spectra.
Read the full abstract ▾
All authors Xuan Zhang, Haiyang Yu, Chengdong Wang, Jacob Helwig, Shuiwang Ji, Xiaofeng Qian
Fluid Dynamics
Shock propagation through a local constriction
Raz Heppner, Hemanth Chandravamsi, Yoav Gichon et al. (+2 more)
The interaction of a shock wave with a localized constriction in a straight conduit is investigated by systematically varying the blockage ratio in the range 0.35-0.75, the normalized constriction length in the range 0.25-2, and the incident Mach numbers of 1.4 and 1.8. Abrupt rectangular constrictions and smoothly contoured sinusoidal constrictions are considered, as they provide two limiting configurations. Validated Large-eddy simulations resolve both the transient start-up dynamics and the subsequent propagation of reflected and transmitted shock waves. The results show that, for rectangular constrictions, the reflected shock strength depends primarily on the blockage ratio and is largely independent of length, whereas the transmitted shock exhibits measurable sensitivity to constriction length. In contrast, sinusoidal constrictions display a strong coupling between blockage and length, with the reflection process governed by the local contour slope and evolving reflection
topology. The start-up process within the constriction occurs over time scales one to two orders of magnitude longer than the shock passage time and is characterized by a sequence of reflection, separation, and flow reorganization events that determine the eventual steady shock configuration. At later times, the reflected shock Mach number scales linearly with blockage ratio, while the transmitted shock strength decreases monotonically with increasing blockage. Based on these trends, semi-empirical models are developed to predict the strengths of both reflected and transmitted shocks across the parameter space considered. These results provide a unified framework for understanding and predicting shock propagation in conduits with localized
geometric variations, with direct relevance to compressible internal flows in engineering and natural systems.
Read the full abstract ▾
All authors Raz Heppner, Hemanth Chandravamsi, Yoav Gichon, Steven H. Frankel, Omri Ram
Atmospheric and Oceanic Physics
Near-surface Extreme Wind Events and Their Responses to Climate Forcings in a Hierarchy of Global Climate Models
G. Zhang, M. Rao, I. Simpson et al. (+4 more)
Near-surface extreme winds profoundly affect human society, yet process-based understanding of their changes under
climate forcings remains limited. This study systematically investigates the responses of high (HWE) and low (LWE) wind extremes (10-meter) to
climate forcings using a hierarchy of
climate model experiments from multiple general circulation models that participated in the Cloud Feedback Model Intercomparison Project. We analyze idealized atmosphere-only aquaplanet (Aqua) simulations and more realistic land-atmosphere (AMIP) simulations to identify robust responses to
climate forcings and trace the sources of structural uncertainty. In Aqua simulations, tropical LWE changes exhibit large inter-model spread, which can be traced to dynamically distinct representations of low-pressure systems between models. In contrast, extratropical HWE intensify robustly with surface warming, linked to the strengthening of high-latitude extratropical cyclones. The AMIP simulations confirm the robust intensification of extratropical HWE. The more realistic boundary conditions in AMIP simulations act as a constraint, reducing inter-model spread in tropical zonal means compared to Aqua simulations. A comparison of uniform and patterned 4-K warming experiments suggests that the global magnitude of warming, rather than the specific warming pattern, dominates the large-scale responses of wind extremes. However, regional projections of extreme wind changes, especially over land, remain highly uncertain due to divergences in model physics. Case studies reveal that major disagreements in HWE changes can stem from fundamental differences in representing the type and seasonality of extreme-producing weather systems. Our results underscore that reducing uncertainty in regional wind projections requires constraining the physical representation of weather systems in
climate models.
Read the full abstract ▾
All authors G. Zhang, M. Rao, I. Simpson, K. A. Reed, B. Medeiros, H.-H. Chou, T. Shaw
Space Physics · Cross-listed from eess.SY
Multidisciplinary Design Optimization of a Low-Thrust Asteroid Orbit Insertion Using Electric Propulsion
Yacob Medhin, Tushar Sial and Simone Servadio
Low-thrust electric propulsion missions are often designed under simplifying assumptions such as constant thrust or fixed specific impulse, neglecting the strong coupling between trajectory dynamics, spacecraft power availability, and propulsion performance. In deep-space environments with reduced
solar irradiance, these assumptions can lead to suboptimal or infeasible designs, underscoring the need to simultaneously optimize the trajectory and power subsystem. This paper presents a multidisciplinary design optimization (MDO) framework for the simultaneous design of low-thrust trajectories and spacecraft power systems, with explicit coupling to electric propulsion performance. The framework incorporates a high-fidelity variable-specific impulse model of the SPT-140
Hall thruster, in which thrust and efficiency are directly constrained by time-varying
solar power availability and
solar array degradation, rather than treated as fixed parameters. The coupled problem is posed as a time-optimal control problem and addressed using a framework built on top of OpenMDAO and Dymos toolchains, where Dymos employs a collocation-based direct-transcription approach for trajectory optimization. OpenMDAO provides accurate analytic partial derivatives, enabling efficient gradient-based optimization. A Fast
Fourier Series shape-based method is used to generate dynamically feasible initial guess trajectories, and the resulting nonlinear programming problem is solved using IPOPT. The proposed framework is demonstrated through a low-thrust orbit insertion scenario around asteroid 16-Psyche, a regime in which reduced
solar irradiance makes power-aware trajectory design particularly critical. Simulation results demonstrate the framework's ability to capture key power-propulsion-trajectory trade-offs, highlighting the importance of integrated power optimization for realistic electric propulsion mission design.
Read the full abstract ▾
History and Philosophy of Physics
A dimensional analysis path to $h$ and the Bohr atom structure
Kostas Glampedakis
Traditionally, the Planck constant $h$ makes its debut appearance in
quantum physics textbooks in the context of the blackbody radiation law and subsequently as a fundamental ingredient of the physics of the photoelectric effect and the Bohr atom. In this paper we consider an alternative timeline path (which could have taken place several years before the proposal of the Bohr atom) where a classical physics hydrogen atom is studied with dimensional analysis techniques in combination with empirical laws of blackbody radiation. The outcome of this “classical physicist's” approach is the identification of the correct fundamental Planck constant and the reconstruction of the energy and size scales of the Bohr atom.
Read the full abstract ▾
Optics
Cubic-in-magnetization contributions to the magneto-optic Kerr effect investigated for Ni(001) and Ni(111) thin films
Robin Silber, Maik Gaerner, Kamil Postava et al. (+2 more)
*The abstract of this article is too long to be included in the arXiv metadata; please see the paper for the full abstract.* ...In this paper, we introduce the detailed theory of cubic-in-magnetization magneto-optic Kerr effect (CMOKE) by deriving the magneto-optic tensor of third order in magnetization, denoted as $\bm{H}$, and comparing the strength of CMOKE for different
crystal orientations theoretically and experimentally. In
crystals with cubic
symmetry, the tensor $\bm{H}$ is described by two independent parameters $H_{123}$ and $H_{125}$. Together with the linear magneto-optic tensor $\bm{K}$ and quadratic magento-optic tensor $\bm{G}$, the permittivity tensor is described up to third order in magnetization. We analytically describe equations of the MOKE including the contribution of QMOKE and CMOKE itself for (001)- and (111)-oriented cubic
crystal structures. Those are compared to experimental measurements of two samples with an (001)- and (111)-oriented fcc Ni layer, respectively. Further, we use Yeh's 4$\times$4 transfer
matrix calculus to simulate and describe the experimental measurements phenomenologically from the permittivity tensor up to third order in $\bm{M}$. We find that the MOKE anisotropy that stems from the magneto-optic tensor $\bm{H}$ described as $\Delta H = H_{123}-3H_{125}$, is much more pronounced for the (111)-oriented cubic
crystal structure, for which it manifests as three-fold in-plane angular dependencies of MOKE with longitudinal and also with transversal magnetization direction, respectively.
Read the full abstract ▾
All authors Robin Silber, Maik Gaerner, Kamil Postava, Jaroslav Hamrle, Timo Kuschel
Biological Physics · Cross-listed from cond-mat.soft
The Integration Host Factor is a pH-responsive protein that switches from DNA bending to DNA bridging in acidic biofilm-like conditions
Dinesh Parthasarathy, Saminathan Ramakrishnan, Georgia Tsang et al. (+9 more)
The Integration Host Factor (IHF) is a nucleoid-associated
protein critical for both DNA compaction and biofilm stability. While its role in DNA packaging within the
cell is well understood, its structural role in scaffolding biofilms is more puzzling and difficult to reconcile with its known DNA bending activity. Here, we investigated how IHF-DNA interactions are modulated across a pH spectrum mimicking the acidic microenvironments of bacterial biofilms. By performing all-atom calculations we discovered that low pHs lead to a change in protonation of IHF residues, which in turn exposes positively charged patches. We then conjectured that these positively charged residues could lead to intermolecular DNA bridging and tested this hypothesis through single-molecule and bulk assays. We discovered that while at physiological pH IHF mostly bends DNA, at pH < 5 there is clear evidence of IHF-mediated intermolecular crosslinking. Our results demonstrate that pH significantly modulates IHF-DNA interactions and explains the structural role played by IHF in supporting biofilm mechanics through intermolecular crosslinking.
Read the full abstract ▾
All authors Dinesh Parthasarathy, Saminathan Ramakrishnan, Georgia Tsang, Auro Varat Patnaik, Sabrina M.C. Hardy, Willem Vanderlinden, Jamieson Howard, Braden Bylett, James R. Law, Mark C. Leake, Agnes Noy, Davide Michieletto
Instrumentation and Detectors
Automatic calibration of gamma-ray detectors deployed in uncontrolled environments
Marco Salathe, Nicolas Abgrall, Mark S. Bandstra et al. (+3 more)
Radiation detectors deployed as part of a large urban network or for homeland security monitoring must maintain reliable energy calibration even when subjected to substantial variations in temperature and ambient background radiation. Traditional calibration methods often rely on power-intensive temperature stabilization or peak-locking
algorithms that are susceptible to environmental changes. This publication presents a novel software-based calibration method that eliminates the need for active temperature control by utilizing full-spectrum analysis. The method continuously updates the calibration parameters by fitting the spectral data with a series of background radiation contributions (K, U, Th series, radon progeny and cosmics) combined with a Monte-Carlo-based physical detector model that incorporates light yield non-proportionality and photomultiplier tube saturation. Performance was validated using simulated data, measurements in an environmental chamber across a wide temperature range (-25C to +50C), and data from a multi-day outdoor field deployment. Results demonstrate that the method successfully maintains stable energy calibration despite significant ambient temperature variations and precipitation events. The technique effectively decouples instrumental drift from spectral changes caused by environmental background fluctuations. This approach provides a robust, automated, and low-power alternative to conventional calibration techniques, enabling the practical deployment of large-scale, unattended networked detector systems.
Read the full abstract ▾
All authors Marco Salathe, Nicolas Abgrall, Mark S. Bandstra, Tenzing H. Y. Joshi, Brian J. Quiter, Reynold J. Cooper
Atmospheric and Oceanic Physics
The Rise and Fall of ENSO in a Warming World: Insights from a Lag-Linear Model
PJ Tuckman and Da Yang
The El Niño-Southern Oscillation (ENSO) is a fluctuation in sea surface temperature and pressure across the equatorial Pacific Ocean with a period of 2-7 years. As the largest mode of interannual variability on Earth, ENSO shapes global weather and
climate patterns ranging from monsoons in southern Asia to hurricanes in the Atlantic and droughts in South America. Predicting and understanding ENSO's response to greenhouse warming is essential for mitigating the impacts of
climate change, yet model ensemble projections are expensive to generate across emission scenarios and remain incompletely understood. Here, we use a hierarchy of models to explain the transient rise and subsequent fall of ENSO strength under greenhouse warming, then develop an efficient and accurate method for predicting ENSO variability in any emissions scenario. Beginning with an East Pacific energy budget, we quantitatively show how enhanced upper-ocean stratification strengthens ENSO and how a slowing Walker circulation and stronger surface flux damping eventually weaken it. This leads to a linear model that predicts the
evolution of ENSO variability from only East Pacific temperature and stratification. We further show that subsurface warming, and therefore stratification, is connected to surface warming with a lag, enabling us to create a lag-linear model that explains $\sim$90% of simulated changes in ENSO variability from only global mean surface temperature and its history. Once calibrated, this efficient predictor can project ENSO strength without running a full
climate model, and allows an analytic solution for the timing and magnitude of peak ENSO variability. We find that the ratio of an ocean subsurface adjustment timescale to the warming timescale strongly alters peak ENSO amplitude, meaning that faster emissions lead to larger ENSO variability even with identical total emissions.
Read the full abstract ▾
Applied Physics · Cross-listed from quant-ph
Photonic hyperentanglement in polarisation and frequency via joint spectrum shaping
Tommaso Faleo, Fabian Steinhauser, Gregor Weihs et al. (+2 more)
Hyperentanglement offers enhanced capacity for
quantum information processing and communication protocols, especially in combination with robust high-dimensional degrees of freedom such as frequency-bin encoding. Here, we present a single-pass, unfiltered, down-conversion source of hyperentangled
photon pairs in polarisation and frequency-bin degrees of freedom with dynamically tunable state dimension and composition at telecom wavelengths. We achieve this by optimal tailoring of the
photons' joint spectral amplitude via pump and nonlinearity shaping. Using polarisation-resolved time-of-flight spectrometry and Hong-Ou-Mandel interference, we characterise the hyperentangled states and demonstrate for the polarisation component fidelities exceeding 99% averaged over frequency bins and concurrences above 98%. The degree of spectral
entanglement, quantified by the Hong-Ou-Mandel visibility, is measured as 90%, well in line with numerical simulations. This approach provides a scalable route toward high-dimensional
quantum states for
quantum communication and computing applications.
Read the full abstract ▾
All authors Tommaso Faleo, Fabian Steinhauser, Gregor Weihs, Stefan Frick, Robert Keil
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Quantum Theory of Functionally Graded Materials
Michael J. Landry, Ryotaro Okabe, Chuliang Fu et al. (+1 more)
Functionally graded materials (FGMs) are composites whose composition or microstructure varies continuously in space, producing position-dependent mechanical and functional properties. In recent years, FGMs have gained significant
attention due to advances in additive manufacturing, which enable precise spatial control of composition and orientation. However, their graded, aperiodic structure breaks the assumptions of Bloch's
theorem, making first-principles electronic and electromagnetic calculations challenging. Here we develop an ab initio
quantum theoretical framework for the electromagnetic properties of FGMs. Using a non-interacting electron model, we formulate a theory of modulated Bloch states, derive effective field equations, and solve them by proposing a generalized WKB (GWKB) method, an effective mass approximation, the Boltzmann equation, and numerical approaches. Our GWKB solution is not semiclassical but remains valid in the fully
quantum regime. We show that effective observables such as conductivity,
magnetic permeability, and electric permittivity generally do not admit a tensorial description in graded media, and that engineered orientational gradients enable precise control of Landau quantization. As a device example, we further develop a theory of graded p-n junctions with enhanced electronic tunability. This framework lays the
quantum foundation for predictive design of graded composite materials, enabling AI-accelerated discovery of next-generation functional architectures.
Read the full abstract ▾
All authors Michael J. Landry, Ryotaro Okabe, Chuliang Fu, Mingda Li
Geophysics
How oil slicks floating on the ocean affect SST?
Liu Kejing
Oil slicks are widely distributed in the ocean today, as a kind of coverage on sea surface, they became a part of ocean environment and affect their surroundings. A
stochastic-dynamic theoretical model proposed in this work to illustrate how oil slicks affect global
climate from micro scale relation between a piece of oil slick and sea surface temperature (SST) of its surrounding unit area, for SST is an important index of global
climate. The model indicate that oil slicks make the sea surface warmer in the future, and the temperature series of the sea surface covered by oil slicks will have greater variance and fatter tails for its distribution and reduce SST predictability from a microcosmic perspective. Thus, more oil infused into the ocean makes the air-sea system more uncertain. These findings indicate that the present air-sea coupled models may lack of sufficient
attention to oil slicks floating on the sea surface.
Read the full abstract ▾
Data Analysis and Statistics
Structured generalized sliced Wasserstein distance for keV X-ray polarization analysis with Gas Pixel Detector
Pengcheng Ai, Hongtao Qin, Xiangming Sun et al. (+3 more)
Because of the special angular distribution of excited electrons by the photoelectric effect, the Gas Pixel Detector (GPD) is effective in measuring keV X-ray polarization of astrophysical events (e.g. gamma-ray bursts), by capturing ionization tracks of excited electrons as polarized images. Traditionally, the emission angles of photoelectrons are extracted from polarized images first, and statistics are then performed on these angles to infer the polarization direction and intensity. However, observation with the wide field of view requires the incident angle of X-rays not directly attainable through the traditional analysis process. In this paper, we propose using the generalized sliced Wasserstein (GSW) distance, projected by neural networks with random weights, as a completely data-driven approach to analyze X-ray polarization based on two-dimensional polarized images. We find the structures of the randomized neural networks matter when focusing on different aspects of the polarized images, and take advantage of the discrimination abilities by different neural network structures. The proposed method, named the structured GSW distance, successfully distinguishes polarized images with different configurations of incident angles and polarization directions. Furthermore, we build a simplified statistical model based on the von Mises distribution and the circular Wasserstein distance and compare the model against the proposed method, showing their high consistency. The computational method reported in this paper may benefit GPD-based polarimetry in astroparticle experiments and also pattern analysis on raw data from pixel detectors.
Read the full abstract ▾
All authors Pengcheng Ai, Hongtao Qin, Xiangming Sun, Dong Wang, Huanbo Feng, Hongbang Liu
Instrumentation and Detectors
Improvement and assessment of the radiopurity of Micromegas readout planes
Juan Castel, Susana Cebrian, Theopisti Dafni et al. (+17 more)
Micromesh Gas Structures (Micromegas) as readout of gaseous Time Projection Chambers (TPCs) are being considered in experiments investigating rare phenomena, like the
nuclear double beta decay,
solar axion detection and low-mass dark matter interactions, due to their good performance on spatial and energy resolution and operation stability. In addition, as they are potentially made mainly of radiopure materials like copper and kapton, they are appropriate for ultra-low background conditions. After a promising first study of the radiopurity of Micromegas readout planes, here results after dedicated development at CERN obtained from new radioassays, performed at the Canfranc Underground Laboratory combining different techniques, are presented. Activity of the isotopes in the lower parts of the 238U and 232Th natural chains has been constrained by analyzing the BiPo sequences using the BiPo-3 detector to be <0.064 and <0.016 muBq/cm2 respectively, while a lowest 40K content of 0.102+-0.030 muBq/cm2 has been determined by gamma spectroscopy using a HPGe detector; the latter value implies a reduction of a factor 34 with respect to the 40K activity quantified in the first analyzed sample. These results confirm the suitability of the use of Micromegas as extremely radiopure readouts for rare event searches.
Read the full abstract ▾
All authors Juan Castel, Susana Cebrian, Theopisti Dafni, David Diez-Ibanez, Alvaro Ezquerro, Juan Antonio Garcia, Hector Gomez, Igor G. Irastorza, Gloria Luzon, Cristina Margalejo, Hector Mirallas, Luis Obis, Rui de Oliveira, Alfonso Ortiz de Solorzano, Oscar Perez, Jorge Porron, Maria J. Puyuelo, Ana Quintana, Maria Rodriguez, Laura Segui