Plasma Physics
On magnetic-field consistency in the sideways force calculation of Phys. Plasmas 27, 012508 (2020)
Denis Mironov
We examine the consistency of the
equilibrium magnetic field $\mathbf{B}_0$ used in the analytical calculation of the sideways wall force by A. A. Martynov and S. Yu. Medvedev [Phys.
Plasmas 27, 012508 (2020)] and the subsequent reformulation presented in [Phys.
Plasmas 27, 054702 (2020)]. In these attempts, the current density $\mathbf{j}_0 = \nabla \times \mathbf{B}_0$ must vanish in the
vacuum regions adjacent to the wall, making $\mathbf{B}_0$ curl-free as a complement to the natural $\nabla \cdot \mathbf{B}_0 = 0$. Since the cited works incorporate selected toroidal corrections without explicitly specifying the corresponding differential operators, we test $\mathbf{B}_0$ adopted in these models against Maxwell's equations using both toroidal and quasi-cylindrical formulations. We show that the divergence-free requirement is violated in the toroidal interpretation, while the curl-free condition is not satisfied in the quasi-cylindrical limit. The reformulation likewise fails to define a self-consistent
equilibrium field with toroidal effects because the accompanying field corrections required for consistency with Maxwell's equations are not specified. Since the sideways force calculations are built upon these inconsistent field prescriptions, their analytical derivations are consequently compromised. The resulting arguments therefore cannot serve as a valid basis for revising either the earlier results established by D. V. Mironov and V. D. Pustovitov [Phys.
Plasmas 24, 092508 (2017)] or those obtained within the single-harmonic analysis [Phys.
Plasmas 22, 052502 (2015)].
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Computational Physics
Thermochemically Constrained Multiscale Laplace Neural Operator to Learn Stiff Chemical Kinetics with Conditional Diffusion Model Sampling
Dong Yang, Xiongbo Duan, Min Zhang et al. (+1 more)
Stiff chemical kinetics is a major computational bottleneck in reacting-flow simulations, while data-driven solvers remain sensitive to training-state coverage and chemical dynamics. This work combines conditional
diffusion sampling with a thermochemically constrained multiscale Laplace neural operator (TC-MLNO) for chemistry ODE integration. The
diffusion model learns the equivalence-ratio-conditioned joint distribution of temperature and species from low-dimensional flame data, augmenting the state space without independent perturbations. TC-MLNO represents transient, non-periodic responses through pole-residue Laplace layers and assigns fast, medium, and slow species to separate branches. Thermochemical constraints are imposed through losses for mass and elemental conservation and heat release rate. The framework is evaluated in 1D premixed flames, a 2D developing jet, and a 3D turbulent burner flame. With equal-sized
datasets,
diffusion sampling reduces the 95th-percentile distance to the base flame
manifold by up to 37.5% and the a posteriori full-species macro-average error by up to 92.7% versus random sampling, especially for minor species and radicals. TC-LNO yields smaller errors than the DeepONet baseline for 84.9% of retained modes and reduces the 95th-percentile error for the most attenuated modes from 0.372 to 0.081. In multidimensional flames, TC-MLNO better preserves reaction-zone locations, heat-release structures, and chemically sensitive species than DeepONet. Errors of representative radical and nitrogen-containing species in the 3D flame decrease by 88.0%-88.9%. Compared with direct CVODE integration, TC-MLNO reduces mean chemistry and total solution times by 90.1% and 62.6%, respectively. These results show that distribution-aware sampling and Laplace neural operator learning provide an accurate and efficient alternative for stiff chemical ODE integration.
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All authors Dong Yang, Xiongbo Duan, Min Zhang, Yuqiang Li
Biological Physics · Cross-listed from cond-mat.soft
Biomolecular condensates and their pathologies: A colloidal, interfacial, and transport perspective
Vineeth Godavarti and Vinny Chandran Suja
Biomolecular condensates are micron-scale, membraneless compartments that concentrate
proteins and nucleic acids by
liquid-
liquid phase separation (LLPS). Condensates play critical roles in transcription, mRNA metabolism, stress responses, and signaling across the
cell, with their dysregulation increasingly correlated with several pathologies spanning neurodegeneration, cancer, cardiometabolic disease, and viral infections. The emergent biology of condensates can be cohesively viewed through the framework of colloidal, interfacial, and transport phenomena. Here we review the condensate literature through this joint lens, treating each condensate as a biological colloid whose behavior is captured by four measurable physical quantities: a Flory–Huggins interaction parameter that determines whether the dense phase forms at all, a partition coefficient that dictates the degree of client molecule accumulation, a viscoelastic relaxation time that sets whether the dense phase responds as a
liquid or a solid, and an interfacial tension that governs droplet shape and interfacial dynamics. Each quantity is traced to its physical origin, its measured range in biological condensates, and the techniques that quantify it, for both three-dimensional droplets and two-dimensional membrane-tethered condensates. Interpreting disease as the displacement of these physical quantities from their functional ranges, we reorganize condensate pathologies into a small set of physical failure modes — saturation concentration dysregulation, aberrant aging and
liquid-to-solid transitions, disrupted partitioning, interfacial aggregation, and pathogen hijacking — and show how the same parameters become design variables for condensate-targeted drugs and engineered coacervate delivery vehicles. The review concludes with open questions at the interface of condensate biology and colloidal and interfacial science.
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Plasma Physics
A New Degree of Freedom in Stellarator Coil Design
Sophia A. Henneberg and Annika Zettl
Reversed toroidal field (RTF) coils introduce a new degree of freedom in stellarator coil design. While the total
plasma-linked current is fixed by Ampere's law, compensating RTF currents allow the modular-coil current to exceed this value without altering the net linkage. This redistribution decouples key coil constraints and modifies the external coil geometry without significantly compromising the confining
magnetic field. As a result, the achievable coil-
plasma separation can be increased in the configurations studied, potentially enabling more compact stellarator designs.
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Fluid Dynamics
AI Meets Turbulence Modeling: Complex Systems Perspective
Sharath S. Girimaji
Despite widespread enthusiasm, applying artificial intelligence and machine learning (AI/ML) to
turbulence modeling has yielded only modest progress, primarily due to a lack of situation-aware deployment. Data-driven Reynolds-averaged Navier–Stokes (ML-RANS) closures frequently fail to generalize across diverse flow regimes, while scale-resolving simulations (SRS) remain computationally prohibitive. As a result, ML-RANS is often misapplied outside its domain of validity, and ML-SRS is unnecessarily deployed on flows fully amenable to RANS. To guide optimal AI/ML deployment, we propose a
turbulence taxonomy map parameterized by degrees of freedom ($Re$) and the degree of non-
equilibrium ($SK/\epsilon$). By applying Weaver's well-recognized complexity framework, we classify
turbulence into distinct physical regimes. This categorization identifies where local ML-RANS surrogates can generalize, clarifies where explicit scale resolution is physically mandatory, and highlights where physics-informed neural networks (PINNs) are most effective. Ultimately, this perspective establishes a physics-grounded framework for the flow-aware, successful deployment of AI/ML in
turbulence.
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Applied Physics
Optimization of Active Reconfigurable Surfaces for Spatiotemporal MU-MIMO Wave Routing in Disordered Media: Application to the Cocktail-Party Problem
Frederic J. N. Jorgensen, Florent Dorlot, Constant Bourdeloux et al. (+4 more)
We design an active reconfigurable intelligent surface (RIS) for acoustic multi-user multiple-input multiple-output (MU-
MIMO) communication by solving a large-scale convex optimization problem, so that each emitter's broadband signal focuses in space and time at its intended receivers while crosstalk is suppressed. In acoustic experiments, we show that our approach outperforms existing time-reversal methods by 5.1-7.6 dB in crosstalk suppression, while achieving better temporal focusing.
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All authors Frederic J. N. Jorgensen, Florent Dorlot, Constant Bourdeloux, Mathias Fink, Fabrice Lemoult, Steven G. Johnson, Raphaël Pestourie
Applied Physics · Cross-listed from cond-mat.mtrl-sci
A Solution-Processed Ti/Pt/NiOx/Ag RRAM Device with Multiple Forming-Free Non-Volatile Intermediate States
Abhrajit Roy, Chopali Chanchal Sahu, Rudraksh Sangore et al. (+5 more)
Artificial neural networks (ANN) implemented on crossbar arrays of non-volatile synaptic devices are known to consume much less energy compared to that implemented on conventional computing units. Solution-processed resistive random-access
memory (RRAM) devices based on transition-metal oxides are suitable as such synaptic devices because of their cheap and easy fabrication method, stability, and suitable memristive properties. Here, in NiO-based RRAM devices with Ti/Pt as the bottom electrode and Ag as the top electrode (NiO layer deposited through solution processing), we experimentally report forming-free binary switching between a high resistance state (HRS) and a low resistance state (LRS) as well as forming-free pulse-driven modulation (long-term potentiation (LTP), long-term depression (LTD)) through 30 intermediate synaptic states between HRS and LRS (around 5-bit synaptic weight resolution). Many of these states are measured to be stable at least up to 1000 seconds confirming their non-
volatility and their utility in storage of synaptic weights for ANN crossbar arrays. On the contrary, most prior experimental reports (including reports both on solution-processing-based and sputtering-based RRAM devices) require forming to exhibit non-
volatility. Avoiding forming reduces variability, eliminates the need for high voltage pulses, and makes the crossbar array design simpler. Further, we confirm the presence of oxygen vacancies in our materials stack using X-ray photo-electron spectroscopy (XPS). Finally, we show successful data classification on MNIST and CIFAR-10 data sets using a multi-layer perceptron (MLP) model and a convolution neural network (CNN) model respectively, where the synaptic weight updates of these ANN models are calibrated against the experimentally measured LTP-LTD characteristics of the NiO RRAM devices.
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All authors Abhrajit Roy, Chopali Chanchal Sahu, Rudraksh Sangore, Raman Hissariya, Poulomi Chakrabarty, Harsh Roniyar, Merlyne De Souza, Debanjan Bhowmik
Fluid Dynamics
Finding a reconnection in a vortex-haystack
Abhishek Harikrishnan, Benjamin Musci, Adrien Lopez et al. (+8 more)
Counter-rotating
vortex reconnection is a
topology-transforming event that leads to strong vorticity amplification and is often associated with the most irregular regions of the velocity field. Detecting such events directly in turbulent flows is a major challenge due to the ambiguity inherent in the definition of a
vortex and the rapid proliferation of intense small scale
vortices. We develop a novel methodology by combining two tools. The first is a local in scale, space and time regularity indicator that isolates spatio-temporal regions of interest. The second is a reconnection indicator that exploits a well-known property of
vortex reconnection namely, that the enstrophy (volume integral of the square of vorticity) flows from the
symmetry to the collision plane. To examine the flow of enstrophy in the correct reference frame, a new method inspired by orientational order parameters in
liquid crystals is developed. We then show a proof of concept for our reconnection indicator by comparing it with diagnostic methods available in the literature. The method is validated on experimental
datasets from a turbulent von Kármán flow at two different resolutions, one of which allows us to probe the flow below the Kolmogorov scale, $\eta$. Our findings suggest that counter-rotating
vortex reconnection could be a potential mechanism for the creation of motions at scales below $\eta$.
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All authors Abhishek Harikrishnan, Benjamin Musci, Adrien Lopez, Bartosz Protas, Adam Cheminet, Jean Le Bris, Jean-Marc Foucaut, Jean-Philippe Laval, Christophe Cuvier, Pierre Bragança, Bérengère Dubrulle
Optics
Fast local field calculation in cascaded coupled systems
Isam Ben Soltane, Romain Asso and Matthieu Davy
Computing the field within a sub-unit of cascaded systems is a recurring problem in wave physics. It is central to gradient-based inverse design, in situations where only a region of the system is modified while the rest remains fixed. Standard approaches either resimulate the entire cascade at every change, or require a detailed characterization of every surrounding sub-system. Both become impractical when many design iterations are needed. Here, we introduce a hybrid method combining the $S$-
matrix approach, which propagates fields through cascaded systems, with the Green's function method, which gives the field generated by a source within a characterized system. In this approach, the sub-systems surrounding the region of interest need only be characterized once, after which the local field can be recomputed rapidly for any new configuration. We validate the method on a disordered lossy waveguide, finding excellent agreement with finite-element simulations. We also demonstrate its efficiency on a disordered multimode cavity, where it achieves a fifty-fold speed-up over full-wave simulation and reduces a wideband focusing calculation from eleven hours to ten minutes. This approach opens the way to fast, iterative field calculations in complex systems coupled to their environment, with direct applications to inverse design and wideband wavefront-shaping.
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Physics Education
Characterizing adopters of named active learning methods in physics: An interview study
Ibukunoluwa Bukola, Eric Brewe, Adrienne L. Traxler et al. (+1 more)
Active learning has been shown to be more beneficial for student learning than lecturing. Consequently, researchers have developed named active learning strategies for use in physics instruction. To increase adoption and support implementation of these named methods, it is important to understand the backgrounds and experiences of instructors who use them. In this study, we interviewed 20 introductory physics and astronomy instructors who use one of Student-Centered Active Learning Environment with Upside-Down Pedagogies (SCALE-UP), Investigative Science Learning Environment (ISLE), Tutorials in Introductory Physics and Astronomy, or Peer Instruction to gain insight into their teaching experiences, professional development, pathways to learning about their method, and supports for and difficulties in implementation. We find for our sample that all implementers are involved with the discipline-based education research community, but there is variation in the extent of engagement. While instructors identify a variety of supports for their implementation, such as from the broader education community and departmental administration, the difficulties they experience are representative of both long-standing issues associated with active learning adoption (e.g., timing constraints) and new issues related to emergent technologies (e.g., Artificial Intelligence). Finally, we uncover differences in implementers across the four named methods, particularly related to their training for the method and the supports they received for implementation. Together, these findings underscore the importance of supporting multiple dissemination avenues for named active learning methods, point to a possible need for more training opportunities for SCALE-UP and ISLE in particular, and identify nascent issues in the contemporary active learning classroom that future work may further characterize and address.
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All authors Ibukunoluwa Bukola, Eric Brewe, Adrienne L. Traxler, Meagan Sundstrom
Accelerator Physics
AI Acceleration of Muon Collider R&D: A Report from the AI4MuC Workshop
J. Scott Berg, David Bizzozero, Tulika Bose et al. (+27 more)
A
Muon Collider is one of the most attractive routes to multi-TeV lepton collisions, but it requires the accelerator and detector communities to solve a tightly coupled set of problems that have no close precedent in an operating
collider.
Muons must be produced, captured, cooled, accelerated, and collided before they decay. The detector must then extract clean physics from an environment dominated by decay products from the beamline. Artificial intelligence is not a substitute for accelerator physics, detector design, or engineering validation. It is, however, unusually well matched to several of the central obstacles: high-dimensional design spaces, expensive simulations, coupled subsystem trade-offs, and workflows that are currently too slow or too fragile to support broad design exploration. This report distills the AI4MuC workshop into a summary of AI use cases with the potential to change the pace of
Muon Collider R&D, organized around the following physics bottlenecks:
muon production and capture, ionization cooling, magnet and RF technology, detector design in beam-induced background, background simulation and generation, reconstruction, and software.
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All authors J. Scott Berg, David Bizzozero, Tulika Bose, Lance Cooley, John Dervan, Auralee Edelen, Peter Elmer, Cristiano Fanelli, Tova Holmes, Walter Hopkins, Sergo Jindariani, Michael Kagan, Maira Khan, Young-Kee Kim, Matt LeBlanc, Lawrence Lee, Matthias Liepe, Radha Mastandrea, Patrick Meade, Federico Meloni, Chad Mitchell, Linh Nguyen, Isobel Ojalvo, Ryan Roberts, Nicholas Smith, Jean-Luc Vay, Gordon Watts, Drew Winder, Chenran Xu, Katsuya Yonehara
Optics
Definition of Multi-Parameter Super-Resolution for Optical Telescopes
Peter Menart, Seungman Choi and Zubin Jacob
Super-resolution techniques in microscopy are opening new frontiers in biology, and super-resolution for
telescope imaging may provide similar benefits for astronomy and space domain awareness.
Telescope super-resolution techniques such as multi-plane light conversion and photonic lanterns have been inspired by the ability of mode sorting measurements to extract classical Fisher information closer to the
quantum bound than standard
telescope imaging. Fisher information analyses for super-resolution imaging systems commonly consider the case of imaging point sources, but often only consider estimating a small subset of the parameters. Furthermore, there has been no demonstration of an estimation
algorithm with performance that follows the limit set by the Fisher information when all point source parameters are considered. We provide a framework for defining and analyzing super-resolution using the classical and
quantum Fisher information for the multi-parameter estimation problem and demonstrate an
algorithm that can achieve the classical Fisher information bound for all the parameters simultaneously.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Mn–Cr dopant association in dilute co-doped $\mathrm{ZnAl_2O_4}$ revealed by combined EPR and optical spectroscopy
Apoko S. Omondi, Mátyás M. Rudolf, Nikoletta Jegenyés et al. (+5 more)
Efficient and durable phosphors made from abundant elements underpin energy-saving solid-state lighting, near-infrared light sources for sensing, and X-ray and biomedical imaging. Co-doping is a standard route to brighter phosphors, yet the fate of the co-dopants is rarely established. We combine quantitative electron paramagnetic resonance (EPR)
spin counting with photoluminescence, photoluminescence excitation, and X-ray-excited spectroscopy across two dilute Mn/Cr co-doping series of hydrothermally grown $\mathrm{ZnAl_2O_4}$ nanoparticles and show that the two ions can form an exchange-coupled, edge-sharing Cr–Mn defect complex, with $\mathrm{Mn^{2+/4+}}$ entering an octahedral site next to $\mathrm{Cr^{3+}}$. The octahedral Mn lifts the inversion
symmetry of the $\mathrm{Cr^{3+}}$ site and strengthens its parity-forbidden absorption, enhancing the $\mathrm{Cr^{3+}}$ emission without energy transfer. The population of the defect complex follows the law of mass action, and above a threshold Mn concentration, Mn re-partitions into EPR-silent octahedral configurations that quench both emissions. Concentration optima in co-doped phosphors can thus reflect defect speciation, not only energy-transfer efficiency, which opens a structural design handle for brighter emitters.
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All authors Apoko S. Omondi, Mátyás M. Rudolf, Nikoletta Jegenyés, Árpád Jakab, Gábor Bortel, Bence G. Márkus, Adam Gali, Dávid Beke
Chemical Physics
UGME: A python package for non-Markovian protein folding dynamics
Anthony J. Dominic III, Bertram Cham and Andrés Montoya-Castillo
Biomolecular processes, including
protein folding,
protein-
protein association, and
protein-DNA recognition, often occur on timescales beyond what individual atomistic molecular dynamics (MD) simulations can reach. To access these longer-timescale dynamics, practitioners commonly combine many parallelized, short trajectories into reduced kinetic models, such as Markov state models (MSMs), that describe how the biomolecules interconvert between a handful of biomolecular configurations (e.g., folded and unfolded states of a
protein). Central to MSM construction is the assumption that, at sufficiently long time lags, these projected dynamics become memoryless, such that the future
evolution of the system depends only on its current state. Yet, projecting high-dimensional biomolecular dynamics onto a small set of states necessarily discards information about unresolved degrees of freedom, including solvent reorganization, side-chain rearrangements, and intermediate configurations. Because these unresolved motions can continue to influence subsequent dynamics, the resulting dynamics retain
memory that is absent from a Markovian description. Here, we present ugme, a modular, open-source Python package for constructing and validating generalized master equations (GME) models that explicitly account for these non-Markovian (
memory) effects.
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Medical Physics
Separating active irradiation from passive outcome learning in radiotherapy: a finite-model computational benchmark
Yuntao Wang
Apparent gains from informative irradiation may reflect treatment reoptimization or better use of outcomes from static treatment. We tested whether changing irradiation adds value beyond optimized static treatment, passive outcome learning, and data-dependent stopping. Three synthetic three-dimensional geometries supplied 51 parent fluences. Four known response scenarios generated Bernoulli risks from normalized organ-dose contrasts at uncalibrated slopes of 0, 4, 16, and 64; one unknown scenario applied to all 2,816 hypothetical uses. Loss included acquisition and deployment. We compared fixed passive and locally selected fixed active sampling, passive optimal stopping, and a restricted one-checkpoint, one-switch active policy with a shared terminal menu. Fixed active sampling improved on fixed passive sampling in three of nine nonzero-slope conditions, but never on passive stopping. One-switch adaptation added at most 4.00625e-5 expected model events avoided. With the policies held fixed, two of four increments above the numerical reporting threshold reversed sign under alternative integration; all four became negative at some allowed prior weighting. Adding three generated probes changed none of 72 paired policy values, and none was used on a positive-probability path. The tested probes did not demonstrate stable incremental value beyond optimized passive stopping. Treatment opportunities, stopping permissions, acquisition costs, and input sensitivity must be separated when attributing benefits to active irradiation. These are restricted finite-model results, not evidence about unrestricted active learning or clinical safety and effectiveness.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Precursor stoichiometry controls dopant structure, defect chemistry, and valence in Mn-doped ZnGa$_2$O$_4$ nanocrystals
Mátyás M. Rudolf, Gábor Bortel, Nikoletta Jegenyés et al. (+5 more)
The luminescence of doped nanocrystals is usually optimised through the activator; here we show that the host cation ratio is an equally decisive, and largely overlooked, design variable. Mn-doped ZnGa$_2$O$_4$ nanocrystals (Mn:Zn = $4\times10^{-4}$) were grown hydrothermally at nominal Zn/Ga ratios between 0.30 and 0.75 (stoichiometric: 0.50) and post-annealed at 400–1100$^\circ$C, and the resulting composition–temperature
matrix was mapped by X-ray- and UV-excited luminescence, EPR, Rietveld-refined X-ray diffraction, Raman spectroscopy and SEM. The as-grown
crystals are phase-pure spinel at every composition and accommodate their off-stoichiometry internally as a point-defect inventory, reflected in a 0.4% variation of the
lattice parameter; on annealing, the excess gallium is exsolved as $\beta$-Ga$_2$O$_3$ in amounts set by the solution composition. The Mn$^{2+}$ emission separates into two optima, near-stoichiometric
crystals annealed at 400–600$^\circ$C and Zn-excess
crystals annealed at 1100$^\circ$C, the latter being twice as bright under X-ray excitation. Under X-ray and 365~nm excitation the two optima are separated by a minimum at 800$^\circ$C that coincides with a collapse of the Mn$^{2+}$ EPR population and has no counterpart in the Raman linewidths, identifying transient, defect-compensated oxidation of the dopant rather than
lattice degradation as its origin. The most Zn-rich composition shows neither Mn$^{2+}$ nor Mn$^{4+}$ emission at any annealing stage, whereas its trace Cr$^{3+}$ emission is strong, indicating that Mn is rejected already during growth. Solution stoichiometry therefore acts on two levels, dopant capture and native-defect inventory, while annealing controls dopant valence and
lattice order. The brightest high-temperature phosphor is thus not the nominally stoichiometric one, but the composition whose excess is consumed on its way to stoichiometry.
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All authors Mátyás M. Rudolf, Gábor Bortel, Nikoletta Jegenyés, Árpád Jakab, László Bencs, Ferenc Simon, Adam Gali, Dávid Beke
Data Analysis and Statistics · Cross-listed from astro-ph.HE
A Pipeline for the AI-Assisted Analysis of Imaging X-ray Polarimetry Explorer Observations of Black Hole X-ray Binaries and Limits on Their Polarization Variability
B. Domine, B. Liu, H. Krawczynski et al. (+3 more)
The Imaging X-ray Polarimetry Explorer (IXPE) has opened a new window into the high-energy Universe, with the capability to measure the arrival time, arrival direction, energy, and, for the first time with the required sensitivity, the polarization of X-rays from black holes,
neutron stars, and other
cosmic sources of X-rays. In this paper, we discuss the use of Artificial Intelligence (AI)
agents for the analysis of IXPE data. The pipeline combines an immutable code base with evolving knowledge databases. The generation of analysis projects makes use of a literature data base to judge the novelty of the proposed analysis projects. We emphasize that the analysis requires two types of expert knowledge: detailed instructions about how to reduce the X-ray data, and expert knowledge about how to interpret the results. We employ several levels of auditors that scrutinize the analysis plan, the analysis scripts, and the analysis results for data and method adequacy. The pipeline includes a staggered approach to interpret the analysis results. We present exemplary results from the pipeline applied to IXPE observations of Black Hole X-ray Binaries (BHXRBs) including comparisons of results from the analysis pipeline with published results and a systematic search for polarization degree and polarization angle variability in long IXPE observations. We critically discuss the performance of the pipeline and future avenues for improving it.
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All authors B. Domine, B. Liu, H. Krawczynski, M. Kundu, Shravan Vengalil Menon, Fang Zhou
Atomic Physics · Cross-listed from cond-mat.quant-gas
Experimental observation of Higgs oscillations and their power-law decay across pairing regimes in a cavity QED quantum simulator
Chitose Maruko, Haoqing Zhang, Eliot A. Bohr et al. (+6 more)
Understanding how pairing correlations in
superconductors evolve out of
equilibrium is a central challenge in
quantum many-body physics. In systems with $s$-wave pairing, the character of Cooper pairing evolves continuously from a BCS regime of weakly bound, overlapping pairs to a BEC regime of tightly bound molecules, each with distinct excitation spectra. Here we realize and probe pairing dynamics across these regimes using cold, non-degenerate $^{87}$Rb atoms coupled to an optical cavity with Floquet dressing. Our cavity-QED platform emulates fermionic superfluids through a mapping onto Anderson pseudospins, while optical and microwave control tunes the ratio of interactions to single-particle energies, providing a flexible approach complementary to ultracold Feshbach and ultrafast solid-state platforms. Following a quench, we observe persistent pairing and transient oscillations of the order parameter associated with a collective amplitude (
Higgs) mode. We find that the decay of these oscillations sharply distinguishes weak- and strong-pairing regimes: in the weak-pairing regime, oscillations decay with a power-law exponent $|\alpha|=0.65(8)$, whereas in the strong-pairing regime the decay is substantially faster, with $|\alpha|>1$. The oscillation frequency is set by the minimum quasiparticle excitation energy, directly linking nonequilibrium dynamics to the underlying excitation spectrum. Our results establish nonequilibrium dynamics as a direct probe of pairing character and collective excitations in interacting
quantum systems.
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All authors Chitose Maruko, Haoqing Zhang, Eliot A. Bohr, Leah Huzjak, Anjun Chu, Victor Gurarie, Chengyi Luo, Ana Maria Rey, James K. Thompson
Physics and Society
Diverging paths to dark-matter discovery
Simon Allzén
The scientific discovery of dark matter has been pursued in two very different methodological and epistemic contexts. A microphysical context centered around the laboratory detection of a new particle, and a macrophysical context based on the astronomical identification of a non-luminous gravitating component. The justification for the salience of methodological diversity is that these different methods are complementary ways to discovering aspects of the same entity. The weakly interacting massive particle (WIMP) made this expectation scientifically credible by connecting a particle candidate to a cosmological abundance, experimental searches, and explanations of astronomical phenomena. What happens to this connection when the WIMP loses its central position? I analyze 201,627 NASA Astrophysics Data System records to examine the organization of research following the decline of WIMP prominence. Astrophysics and high-energy physics remain jointly dominant, while WIMP-related mentions decline in both fields and successor candidates receive different degrees of
attention. Concept networks show that WIMP-related research remains central across the literature, even as cross-field connections become less concentrated around it. These indicators measure research
attention; they do not establish what scientists would accept as a discovery. I interpret the findings through a framework distinguishing constitutive identification,
cosmic attribution, explanatory adequacy, and the cross-domain identification needed to connect them. A particle, compact-object population, or gravitational theory can resolve different parts of the inherited problem, and a partial or multicomponent discovery can leave other parts open. 'Diverging paths' describes this branching of possible resolutions.
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Optics
Spatial Nonlocality from Finite Extinction Ratio in BOTDR over Heterogeneous Fiber Links
Giannis Poulopoulos, Constantinos Haliotis, Panagiotis Toumasis et al. (+1 more)
Finite extinction ratio in pulse-modulated Brillouin optical time-domain reflectometry (BOTDR) produces residual inter-pulse Brillouin backscatter outside the nominal pulse gate. We model and experimentally quantify this effect as spatial nonlocality in a heterogeneous fiber link and define the spectral contamination ratio (SCR) as the contaminating Brillouin-band power normalized to the local Brillouin-band power. Measurements were performed using a 1.2 km standard single-mode fiber (SMF) followed by 0.1 km of dispersion-compensating fiber (DCF), whose separated Brillouin frequency shifts allow section-to-section leakage to be resolved spectrally. At 20 m spatial resolution, increasing the extinction ratio from 18.5 to 33.0 dB reduced the SMF-band contamination in the DCF gates from -5.3 to -14.8 dB. Over the 16-33 dB range, the SCR showed fitted slopes of -1.064 and -1.246 dB/dB for the two contamination directions. These results quantify finite-ER-induced spatial nonlocality and provide a link-specific metric for extinction-ratio selection in BOTDR.
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All authors Giannis Poulopoulos, Constantinos Haliotis, Panagiotis Toumasis, Hercules Avramopoulos
History and Philosophy of Physics
The Relation Before Lorenz: Kirchhoff, 1857, and the Symbols Lorenz Inherited
María Florentina Mendoza Urán
A relation between the quantities now called the scalar potential and the vector potential, of the same form, up to a sign, as the one the literature attributes to Ludvig Lorenz in 1867, was written ten years earlier by Gustav Kirchhoff, with the same status: derived, unnumbered and unnamed. This paper documents, on the basis of the 1857 originals, that Kirchhoff obtains the relation as the result of a calculation and does not impose it; that the quantity now called the vector potential bears no name at all in his text, whereas the scalar one bears the name "Potentialfunction", potential function, in both papers; that Lorenz writes those same letters, $\Omega$, U, V and W, and inherits with them the absence of a name for the three components, although the relation he writes is in other quantities, $\alpha$, $\beta$ and $\gamma$, and carries the opposite sign; and that the English translation of one of the two papers suppresses the word "function" from the term "Potentialfunction", with which Kirchhoff names his scalar quantity. The paper concludes that the pattern documented in the 1867 paper predates Lorenz and comes from the source from which he starts: a relation without number or name, components without a denomination, and a vocabulary added later.
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