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Physics Physics

physics Watch Physics

Friday 29 May

Physics and Society · Cross-listed from cs.SI

Persistent Structural Inequality of Online Interactions Across Platforms

Giulio Pecile, Edoardo Di Martino, Edoardo Loru et al. (+3 more)

User interactions on social media platforms are unevenly distributed: a small subset of users consistently captures most of the activity, while the majority remains marginal. Although this pattern is well known and often described by power-law distributions, its consistency across time, platforms, and interaction types has not been systematically assessed. In this study, we analyze user-post bipartite networks from multiple social media platforms. We consider both active contributions (posts) and passive engagement (likes and comments), and quantify distributional properties and inequality using a KL-divergence-based model comparison, an inverse coefficient of variation, and a log-transformed Gini index. Our results show that interaction inequality remains stable over time within each platform. This holds across systems with different sizes, topical focuses, and governance models. These findings indicate that inequality in online engagement is not incidental but reflects structural constraints that shape how visibility and participation are distributed in digital environments.
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All authors Giulio Pecile, Edoardo Di Martino, Edoardo Loru, Simon Zollo, Niccolò Di Marco, Matteo Cinelli

Atomic Physics · Cross-listed from cond-mat.quant-gas

Dimensionality of a strongly interacting 2D-3D Fermi-Fermi mixture from the perspective of superfluid instability and excitation properties

Haruka Takeda, Saki Hirai, Shumpei Iwasaki et al. (+1 more)

We theoretically investigate strong-coupling properties of an attractively interacting Fermi atomic gas, where the Cooper-pair formation occurs between atoms belonging to different dimensional bands. Including pairing fluctuations within the framework of the self-consistent $T$-matrix approximation (SCTMA), we examine how the BCS-type superfluid phase transition temperature $T_\mathrm{c}$ varies as one moves from the 3D-3D to the 2D-3D system, in the wide parameter region with respect to the strength of the pairing interaction. In the 2D-3D limit, we find that, while the mean-field BCS theory predicts $T_\mathrm{c}>0$ in the strong-coupling regime, $T_\mathrm{c}$ is remarkably suppressed down to zero by pairing fluctuations that are strongly enhanced by the mixed-dimensionality of the system. As the origin of this, we clarify that the lower-dimensional (2D) component dominates the superfluid instability, so that the vanishing $T_\mathrm{c}$ is the same phenomenon as that in the 2D-2D case. We also point out that this can already be seen in the mean-field level, when one examines the propagation of the Goldstone mode. On the other hand, we find that the pseudogap phenomenon, which is known as a precursor of Cooper-pair formation, exhibits a 3D character of the 2D-3D system. These results indicate that the dimensionality of a strongly interacting Fermi gas depends on what we observe.
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All authors Haruka Takeda, Saki Hirai, Shumpei Iwasaki, Yoji Ohashi

Physics and Society

Sequence models reveal diagnosis accumulation pathways beyond comorbidity burden in population-scale hospital data

Katharina Ledebur, Mitja Devetak and Peter Klimek

Aging trajectories vary among individuals of similar age and disease burden. Comorbidity indices, e.g. the Elixhauser index, summarize conditions cross-sectionally, but discard the timing, sequence, and pace of morbidity accumulation. Here we ask whether longitudinal hospital diagnosis histories contain information beyond age, sex, and comorbidity burden, and where it is concentrated. Using 13 years of Austrian inpatient data covering 7.4 million patients, we trained a visit-level contrastive transformer to encode diagnosis sequences and inter-admission timing into patient-history embeddings. In a downstream cohort of 1.7 million individuals, embeddings improved prediction over the Elixhauser-based comorbidity model for 93 of 131 incident ICD-10 disease-block outcomes, with a modest median AUC gain of 0.006. Gains concentrated in mental, musculoskeletal, nervous system, and metabolic disorders. We then evaluated event-free survival, defined as remaining alive without accumulating a second unrecorded ICD-10 disease block. The embedding model achieved an AUC of 0.726 versus 0.722 for the comorbidity model. However, among patients with similar age, sex, and comorbidity-model risk, those assigned high residual risk had 132–183 fewer event-free days over five years and observed event rates comparable to low-residual-risk patients more than a decade older. Together, these findings link the embedding's signal to the breadth, recency, and pace of prior disease accumulation.
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Physics and Society · Cross-listed from q-bio.PE

Coordination without communication: beyond optimisation and geometric Brownian motion

G J Milburn and A K Ringsmuth

We introduce a physically grounded framework for coordination in a population based on information constrained feedback in a partially observed stochastic dynamical system. Population size evolves as a continuous time birth death Markov process whose transition rates respond to a shared stochastic measurement signal correlated with the underlying population state. Individuals neither communicate directly nor optimise strategies; instead, coordination emerges from macro to micro feedback mediated by imperfect common information. We show that geometric Brownian motion arises as a limiting case of the conditional dynamics when measurement strength and population statistics satisfy suitable conditions. More generally, varying the signal to noise properties of the measurement channel produces a wider class of stochastic growth processes, including diffusive and jump like regimes, even though ensemble average growth remains exponential. In an appropriate limit the framework recovers the stochastic multiplicative growth model of Peters and Adamou, providing a physical interpretation of coordination as inference and feedback under partial observability.
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Physics and Society · Cross-listed from cond-mat.stat-mech

Competing heterogeneities shape ordering via higher-order interactions

Gangmin Son, Federico Battiston, Deok-Sun Lee et al. (+1 more)

Higher-order interactions admit richer structural heterogeneity than pairwise networks. To understand how heterogeneity impacts collective phenomena we develop a framework based on the cavity method and apply it to the simplicial Ising model on heterogeneous hypergraphs. Unlike in homogeneous structures, group size and node degree play fundamentally different roles: size heterogeneity sharpens the transition via large-group unanimity, while degree heterogeneity softens it as hubs cooperatively seed ordering with non-hubs. Under either type of heterogeneity, continuous–discontinuous double transitions can arise, where the symmetry-breaking continuous transition is driven by pairs or by hubs, respectively. When both heterogeneities coexist, cross-order degree correlations further modulate the phase diagram, with anticorrelation delaying the group-driven discontinuous jump and broadening the hysteretic region. Our results reveal the intricate interplay between size and degree heterogeneities in collective phenomena beyond pairwise interactions.
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All authors Gangmin Son, Federico Battiston, Deok-Sun Lee, K.-I. Goh

Optics

Segment-chirped periodically poled lithium niobate waveguides for broadband supercontinuum generation

Yue Li, Xiaodong Shi, Sakthi Sanjeev Mohanraj et al. (+7 more)

Supercontinuum generation is a key technology in nonlinear optics, supporting a wide range of applications in frequency metrology and spectroscopy. Integrated photonics offers a promising route toward compact and efficient supercontinuum sources, yet extending the bandwidth while maintaining high spectral flatness remains a central challenge. Here we demonstrate an integrated broadband supercontinuum source based on segment-chirped periodically poled lithium niobate (SC-PPLN) nanophotonic waveguides. By discretizing the chirped poling profile into independently optimized segments, this approach enables high-fidelity ferroelectric domain inversion with near-ideal duty cycles and establishes broadband quasi-phase matching, overcoming the domain inhomogeneity and efficiency limitations commonly encountered in conventional chirped poling. The engineered phase-matching landscape supports efficient wavelength conversion and simultaneous activation of multiple second- and third-order nonlinear processes. Experimentally, we achieve a spectrally flat supercontinuum spanning three optical octaves, from 320 nm in the ultraviolet to 2600 nm in the mid-infrared. These results establish segment-chirped poling as a practical strategy for broadband wavelength conversion and supercontinuum generation in integrated photonics.
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All authors Yue Li, Xiaodong Shi, Sakthi Sanjeev Mohanraj, Mengyao Zhao, Xu Chen, Xuan Mao, Qijie Wang, Shouhuan Zhou, Guoliang Deng, Di Zhu

Optics

Transformation of a three-tone phase modulated CW laser field into sequence of short pulses

Rustem Shakhmuratov

This paper presents generation of Fourier-limited pulses from a periodically phase-modulated CW laser field by phase manipulation of its spectral components. Phase modulation in the form of modulus function of sine (MFS) is considered. It allows to produce pedestal-free pulses with controllable repetition rate and duty cycle. Sidelobes of these pulses can be excluded by choosing a proper modulation index. The proposed method allows to produce pulses with 50% duty ratio. It is shown that three-tone modulation of phase allows to simulate MFS phase modulation.
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Optics

Cloaking of Arbitrarily Shaped Large-Scale Objects Through the Injection of Electromagnetic Invisibility Genes

Zirui Xie, Fei Sun, Yichao Liu et al. (+3 more)

Full-space electromagnetic invisibility mainly includes light-bending and scattering-cancellation cloaking. Light-bending cloaking causes double-blind phenomenon and is incompatible with sensing, while scattering-cancellation cloaking allows signal interaction and is more suitable for sensors and communication systems. However, traditional scattering-cancellation cloaking depends highly on target shape and size, making it difficult to realize cloaking for irregular, inhomogeneous and electrically large objects. To solve these problems, this work proposes an electromagnetic invisibility gene injection strategy inspired by biological camouflage. Objects are decomposed into subwavelength units, and customized invisibility genes are injected into each unit according to electromagnetic parameters to achieve overall scattering cancellation. Simulations and microwave experiments verify that this method can realize efficient cloaking for objects with arbitrary shapes, dielectric constants from 2 to 10, and different unit morphologies. This strategy breaks the limits of traditional cloaking and provides a universal, flexible scheme for practical applications such as antenna supports and electromagnetic transparent covers.
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All authors Zirui Xie, Fei Sun, Yichao Liu, Jiale Li, Jianpu Yang, Shuai Zhang

Applied Physics · Cross-listed from cs.AI

BilliardPhys-Bench: Benchmarking Physical Reasoning and Visual Dynamics of Multimodal LLMs

Ben Wang, Xiaogang Li, Ruochen Gao et al. (+6 more)

Current multimodal models handle static image recognition well, but intuitive physical reasoning remains a weakness. Predicting how objects will move and interact from a single image is still difficult for these systems. We present BilliardPhys-Bench, a benchmark for physical reasoning in synthetic billiards environments. Its procedural engine generates randomized scenarios with friction and elastic collisions. The benchmark tests three abilities: (1) predicting ball-to-ball collisions, (2) reasoning about wall bounces, and (3) estimating final ball positions after motion stops. We evaluate recent MLLMs from the GPT, Claude, Gemini, and Qwen families. Performance drops as simulation time increases and scene geometry grows more complex. We also observe a consistent failure mode we call "stasis bias": when the correct physical outcome is harder to infer, models tend to predict no interaction. These findings show where current MLLMs break down on visual dynamics and point toward the need for better physical inductive biases in multimodal architectures.
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All authors Ben Wang, Xiaogang Li, Ruochen Gao, Peiyao Xiao, Chengliang Xu, Zeyu Wang, Zichao Chen, Bing Zhao, Hu Wei

Biological Physics

Optimal transition in underdamped systems with memory

Tianyu Luo and Yunxin Zhang

Optimal finite-time control is essential for energy-efficient operation of nanoscale devices. While existing work has largely focused on transitions between equilibrium states in overdamped systems, many settings of practical interest – including nanomechanical resonators, biomolecular conformational dynamics, and quantum Brownian motion – are governed by underdamped dynamics where both particle inertia and frequency-dependent friction (memory) play a non-negligible role. In this study, we analytically and computationally investigate optimal transitions between nonequilibrium steady states (NESS) for an underdamped particle in a moving harmonic trap with general memory kernels. We find that inertia qualitatively alters optimal control in the presence of memory. Compared to the overdamped case, underdamped dynamics break the time-reversal symmetry, making the forward and backward optimal protocols fundamentally distinct. Across the memory-kernel types examined, the asymmetry, rather than the detailed form of the kernel, governs the structure of the optimal strategy. These results offer a unified framework for optimal control in underdamped systems with memory.
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Chemical Physics

MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentials

Etinosa Osaro, Santosh Adhikari, Stamatia Zavitsanou et al. (+2 more)

Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational throughput under constraints that are not captured by a single training loss. We introduce MLIPilot, an auto-research framework in which tool-calling large language models propose hypotheses, edit MLIP training code, launch HPC jobs, and accept or revert changes using a fixed, physically constrained scorecard. We evaluate MLIPilot on MACE potential optimization using both commercial and open-weight LLM agents, including GPT-5.5, GPT-4.1, Mistral-24B, and Qwen3-32B. The benchmarks span molecular and periodic settings: a QM7-derived dataset for which we generated B3LYP/6-31G(d) energies and forces, and a Cu EMT dataset with periodic copper supercells labeled by ASE's Effective Medium Theory calculator. Across these benchmarks, the strongest agents move initially constraint-violating baselines to accepted models by discovering useful training strategies, including output normalization, loss-function changes, progressive training schedules, and model-capacity adjustments. These results suggest that LLM agents can serve as autonomous operators for scientific machine-learning workflows when their search is constrained by domain-specific validation criteria, shifting part of MLIP development from manual trial-and-error toward auditable, automated experimentation.
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All authors Etinosa Osaro, Santosh Adhikari, Stamatia Zavitsanou, Kelsey Parker, Dario Rocca

Fluid Dynamics

Color-gradient lattice Boltzmann modeling of wetting boundary condition on curved solid boundaries

Malyadeep Bhattacharya, Snigdhadyut Dash, Maneesh Sutar et al. (+3 more)

We introduce a wetting boundary condition for curved solid boundaries within a diffuse interface framework for lattice Boltzmann method. The boundary condition relies on updating the order parameter (color/phase-field) values on ghost nodes inside the solid phase. The ghost node color modification rule, in turn, extends the equilibrium color profile into the solid phase. Numerical simulations performed on an NVIDIA A100 GPU demonstrate that the wetting scheme retains the model's ability to handle large density and viscosity contrasts while producing relatively small spurious currents. The present scheme agrees well with analytical solutions/other numerical works for both static and dynamic contact lines on curved solid boundaries.
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All authors Malyadeep Bhattacharya, Snigdhadyut Dash, Maneesh Sutar, Ravinder Jajoria, Nimalan Mahadevan, Amol Subhedar

Chemical Physics

A Phase Space Signature of Quantum Roaming in Chesnavich's Model

Stephen Wiggins

Roaming reactions occur when a molecule enters a near-dissociation region, avoids immediate separation, and later forms products by a pathway not controlled by the conventional tight transition-state bottleneck. Classical studies have shown that roaming is best understood in phase space: inner and outer transition-state structures, together with their invariant manifolds, organize trapping, return, and dissociation. The corresponding quantum question is less settled. Can a single quantum resonance carry a recognizable signature of the classical roaming region? We address this question in Chesnavich's two-degree-of-freedom model for the ion–molecule reaction $\mathrm{CH}_4^+\rightarrow\mathrm{CH}_3^+ + \mathrm{H}$. Resonance states are computed with a complex absorbing potential and analyzed using diagnostics designed to mirror the classical phase-space picture: radial probability weights derived from the tight and outer transition-state structures, radial Husimi projections, angular-momentum channel weights, and coherent-state probes of the classical periodic orbits. One resonance is distinguished from the rest of the computed resonance ensemble. Its wavefunction is concentrated in the projected region between the inner and outer transition-state structures, its radial phase-space distribution is centered at intermediate radius with nearly zero radial momentum, and its angular structure is consistent with a standing rather than a directed rotating component. We interpret this state as a phase-space-localized quantum analogue of classical roaming. The result provides a controlled example in which quantum roaming is identified directly from a resonance wavefunction and its phase-space diagnostics, rather than only from product-state or scattering signatures.
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Optics

Anti-symmetric Multimode Waveguide Grating-Assisted Narrowband MZI for Programmable Spectral Shaping Units

Qi Wang, Pin Yu, Jia Meng et al. (+3 more)

We present a narrowband integrated Mach-Zehnder interferometer (MZI) capable of precise transmission control within a targeted wavelength band while maintaining out-of-band transparency. This functionality enables its use as a fundamental building block for fully programmable on-chip spectral shaping. The device is implemented on a novel dual-mode (TE0/ TE1) transmission platform, where anti-symmetric multimode waveguide Bragg gratings (AM-WBGs) and asymmetric Y-branches are combined to function as an equivalent narrowband 1*2 or 2*2 coupler. Experimentally, the MZI achieves wide extinction ratio tuning 0 dB to 30 dB across a 2.5 nm bandwidth, with independent and simultaneous control of both wavelength and extinction ratio. Cascaded multiple narrowband MZIs are experimentally characterized, demonstrating independent intensity control at individual wavelengths without cross-interference. Furthermore, the device's application as a tunable, channel-selective optical blocker/passer in high-speed communication systems is experimentally validated. Compared to prior approaches relying on dual-grating-assisted contra-directional couplers, the AM-WBG-based design overcomes fundamental bandwidth limitations caused by unintended intra-waveguide coupling bands. In addition, their single-waveguide-grating structures enhance the reliability of both fabrication and spectral control, while enabling compact spiral configurations for significant miniaturization. These advantages position the proposed MZI a promising, scalable candidate for advanced spectral shaping applications.
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All authors Qi Wang, Pin Yu, Jia Meng, Jihao Wang, Zikun Xie, Rui Cheng

Optics

Quantum Photonic Time Crystals: From Temporal Boundaries to Floquet Light-Matter Interactions

Younsung Kim, Kyungmin Lee, Kun Woo Kim et al. (+1 more)

Photonic time crystals (PTCs) are temporally periodic media whose Floquet spectra can exhibit momentum gaps, parametric amplification, and effective non-Hermitian descriptions, making them an idealized setting for vacuum amplification and nonequilibrium light-matter dynamics. Their classical electrodynamics is now well developed; the quantum side is less so, and this focused review is an attempt to organize what exists. We trace that account from temporal boundaries to homogeneous Floquet media and light-matter dynamics. A single temporal boundary induces Bogoliubov mode mixing and photon-pair creation; in homogeneous bulk media, momentum conservation isolates counter-propagating $(k,-k)$ sectors and yields a two-mode $SU(1,1)$ squeezing structure. Temporal periodicity promotes this to a Floquet problem with band and momentum-gap regimes, compactly described in a fixed Nambu basis. We then relate PTCs to the dynamical Casimir effect and parametric amplification, which share the same pair-creation mechanism but organize it through discrete resonances rather than a momentum-resolved bulk spectrum. We close with light-matter settings: spontaneous-emission decay and modulation-assisted excitation, atom-PTC dynamics, LDOS-based observables and their limits, and finite, dispersive, and experimentally accessible platforms.
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All authors Younsung Kim, Kyungmin Lee, Kun Woo Kim, Bumki Min

Chemical Physics · Cross-listed from q-bio.QM

The Geometry of Activity Cliffs: Representation Dependence and Multi-Scale Characterization of Activity Landscapes

Pawel Dabrowski-Tumanski, Bartosz Topolski, Dariusz Plewczynski et al. (+1 more)

Activity cliffs, structurally similar compounds with large potency differences, are widely treated as intrinsic features of chemical datasets. We argue that apart from target biology, much of our cliff understanding is a consequence of the geometry induced by the chosen molecular representation, not a property of a molecule pair itself. We designed a six-step pipeline to systematically test this hypothesis. The pipeline consists of: assessing pairwise distance geometry, cliff enrichment, activity gradient distribution, persistent homology of the cliff subspace, predictive benchmarking for a chosen pair of an embedding and a metric, and eventually, analysis of the matched molecular pairs and stereoisomers. We applied the pipeline to fifteen configurations of embeddings and metrics to build a benchmark across three distinctive datasets known of activity cliffs challenges. No representation excels on all criteria: Morgan Tanimoto provides the strongest cliff enrichment and cross-scaffold generalization; MolFormer cosine provides the only meaningful stereochemical sensitivity; MACCS and RDKit Dice fingerprints are most sensitive to matched-molecular-pair transformations; ChemBERTa fails uniformly due to embedding collapse. These findings are not a ranking. They reflect the fact that different representations encode different aspects of molecular recognition, and that choosing one implicitly defines what an activity cliff actually is.
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All authors Pawel Dabrowski-Tumanski, Bartosz Topolski, Dariusz Plewczynski, Tomasz Jetka

Optics

Restricted Modulation Freedom Enhances Noise Robustness in Coherent Diffractive Optical Networks

Hyuntae Lim and Kyoungsik Kim

In coherent diffractive optical networks, greater modulation freedom allows more flexible optimization for clean inputs, but its effect on noise robustness and its physical origin remain unclear. We derive an analytical framework that identifies the physical mechanism linking modulation freedom to noise robustness. To establish this connection, we compare a continuous DDNN (C-DDNN) with continuous amplitude and phase modulation and a binary-mask DDNN (BM-DDNN) with binary amplitude modulation. Trained only on clean MNIST data, the seven-layer BM-DDNN has 1.83 percentage points lower clean test accuracy but 32.82 percentage points higher noisy test accuracy under pixel-wise Gaussian noise. This robustness advantage cannot be explained by lower total noise-only intensity at the imaging plane: the BM-DDNN has 3.22 times the noise-only intensity but 8.64 times the clean-signal intensity of the C-DDNN, reducing noise contamination relative to the clean signal. We show that this difference arises from a clean-signal transmission bias generated by spatial correlations between the structured clean-signal field and learned modulation patterns. We quantify this mechanism with a cumulative transmission-bias factor K, linking modulation freedom to relative noise contamination and robustness. The C-DDNN exhibits a stronger suppressive bias (more negative K), whereas the BM-DDNN exhibits a weaker bias (less negative K^{\tilde}), yielding the consistent ordering K<K^{\tilde}. Because K requires only clean-data forward passes, it serves as a robustness screening metric before noisy-input simulations.
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Atomic Physics · Cross-listed from quant-ph

Dissipative generation of spin squeezing in the resolved vacuum Rabi splitting limit

Edwin Chaparro, Eric Yilun Song, Diego Barberena et al. (+3 more)

Harnessing dissipation in the presence of strong symmetries has recently emerged as a promising route for generating entanglement in atomic clocks. However, previous proposals relied on regimes where cavity photons can be adiabatically eliminated, significantly limiting their applicability to experimentally relevant cavity-QED regimes that lie in or near the resolved vacuum Rabi splitting regime. Here we show that symmetry-protected dissipative spin squeezing can be realized even when cavity photons actively participate in the dynamics, extending the experimental relevance of the protocol. We study a three-level ensemble of $^{87}\mathrm{Sr}$ atoms coupled to an optical cavity in the resolved vacuum Rabi splitting regime and demonstrate that, with smooth ramps of the drive amplitude and detunings, the driven-dissipative dynamics enters a stable low-photon regime in which nonadiabatic cavity excitations and sector-resolving photon leakage can be controlled. Within this low-photon operating window, sector-resolving photon leakage is suppressed and the sector-dependent geometric phase realizes effective one-axis twisting. At the end of the protocol the entanglement can also be efficiently transferred directly onto the long-lived clock states by turning the drive off. For experimentally realistic parameters, we theoretically show that more than $25\,\mathrm{dB}$ of squeezing can be generated for $10^5$ atoms, closely saturating the ideal one-axis twisting scaling $\xi_{\min}^2 \propto N^{-2/3}$. At fixed cooperativity, the optimized squeezing remains broadly comparable to the unresolved-regime implementation, while the resolved-regime implementation reaches comparable squeezing on a substantially shorter physical timescale. These results establish symmetry-protected dissipative dynamics as a practical route to beyond the standard-quantum-limit performance in optical-clock platforms.
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All authors Edwin Chaparro, Eric Yilun Song, Diego Barberena, James K. Thompson, Ana Maria Rey, Jeremy T. Young

Computational Physics · Cross-listed from cs.LG

Learning Permutation-invariant Macroscopic Dynamics

Zhichao Han, Mengyi Chen and Qianxiao Li

Accurately modeling the macroscopic dynamics of high-dimensional microscopic systems is of broad interest across the sciences. Many data-driven approaches learn a low-dimensional latent state through an autoencoder trained for pointwise input reconstruction. These methods typically assume a fixed ordering of microscopic degrees of freedom in the input. However, in many settings, such as particle systems, the microscopic state is inherently unordered. This motivates an autoencoder framework that learns permutation-invariant latent representations. To this end, we adopt a permutation-invariant encoder and design the decoder to reconstruct the mass distribution centered at the observed points rather than per-sample reconstruction. We then jointly learn the macroscopic dynamics of the observables together with the latent states. We demonstrate the effectiveness and robustness of the proposed method across a range of microscopic settings, including learning the energy dynamics in interacting particle systems, predicting mixing dynamics in Lennard-Jones fluids, and modeling the stretching dynamics from video data of polymers moving in an elongational force field.
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Fluid Dynamics

A scalable Ewald-free BIE framework for periodic Stokes flow via hierarchical proxy sums

Tianyue Li, Dhairya Malhotra and Shravan Veerapaneni

Particulate Stokes flow in confined, periodic geometries underlies a broad class of problems in biophysics, microfluidics, and the rheology of complex fluids. Boundary integral equation (BIE) methods are a natural tool for such problems, but existing periodization schemes rely either on periodic Green's functions, which are restrictive for complex confining geometries, or on free-space schemes that solve auxiliary proxy strengths alongside the surface densities in an extended linear system whose cost scales unfavorably in three dimensions. We present a BIE framework for three-dimensional particulate Stokes flow in periodic pipes with circular cross-sections, wall-bounded doubly-periodic, and triply-periodic geometries that uses only the free-space Green's function and avoids both Ewald summation and the extended linear system. Proxy sources placed on equivalent surfaces of the kernel-independent FMM (KIFMM) form the auxiliary basis, and contributions from far image boxes are captured by a hierarchical proxy sum made absolutely convergent by a net-force-zero compatibility condition. The resulting periodization precomputation depends only on the periodic-box geometry, independent of the kernel and of the surfaces inside the box, and is reused verbatim across the Stokeslet, stresslet, and rotlet. Combined with high-order adaptive surface discretizations, the method achieves high-order accuracy at $\mathcal{O}(N)$ cost with a single layer of image boxes in the near field. Numerical examples on dense polydisperse suspensions with thousands of particles and on flow through complex periodic channels, together with strong and weak scaling studies, demonstrate efficient performance on systems with millions of degrees of freedom on distributed-memory architectures.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci

Saturated and Anisotropic Magnetostriction in an Altermagnet

Zhiyuan Duan, Qiyun Xu, Peixin Qin et al. (+14 more)

Magnetostriction, a fundamental phenomenon bridging magnetism and mechanics, has enabled a broad spectrum of applications. For almost two centuries, it has been mainly investigated for ferromagnets. Regarding the magnetostriction of antiferromagnets (AFMs), limitedly known examples for both conventional collinear AFMs and noncollinear AFMs predominantly exhibit non-saturating magnetic-field dependence. Herein, we report an easily saturated magnetostriction effect in a prototypical altermagnet - MnTe, which is an emerging class of collinear AFMs with special crystal symmetries. For high-quality MnTe single crystals, the magnetostriction saturates under a moderate field of ~0.7 T with an intriguing two-fold-symmetry anisotropy. First-principles calculations reveal that the saturated and anisotropic magnetostriction originates from symmetry-allowed coupling between elastic strain and its Néel order parameter. These findings break the traditional wisdom on antiferromagnetic magnetostriction.
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All authors Zhiyuan Duan, Qiyun Xu, Peixin Qin, Li Liu, Guojian Zhao, Yuzhou He, Xiaoyang Tan, Sixu Jiang, Jingyu Li, Xiaoning Wang, Qinghua Zhang, Wenhui Duan, Yong Xu, Ziang Meng, Peizhe Tang, Chengbao Jiang, Zhiqi Liu

Computational Physics · Cross-listed from cond-mat.soft

Tensor gradient flow for rod-like liquid crystals from molecular model with closure approximation by quasi-entropy

Yongyong Cai, Jie Xu and Haixin Zhang

In tensor dynamics for liquid crystals derived from molecular models, a common problem is closure approximation. For rod-like molecules, the Bingham closure has proved to outperform other methods because it inherits the gradient flow structure of the molecular model, but is difficult to achieve efficient computations maintaining the gradient flow structure. We propose a closure approximation by the quasi-entropy that has been successfully applied to the free energy, based on which we construct the tensor gradient flow. The quasi-entropy closure has the same symmetry properties as the Bingham closure. The resulting tensor gradient flow is able to constrain the eigenvalues of the tensor within the physical range, guaranteeing the positive definiteness of the dissipation operator given by the higher-order tensors. The quasi-entropy closure is easy to implement since it can be reduced to minimizing an elementary function of three variables. As a result, we construct a numerical scheme preserving the eigenvalue constraints and energy dissipation, with the closure approximation decoupled from solving the scheme. Numerical simulations are carried out for the interface between the isotropic and the uniaxial nematic phase, as well as the defect evolutions, where the higher-order tensors indeed make a difference.
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Atmospheric and Oceanic Physics

Testing the physical reality of tidal bulges in the world's oceans

Yongfeng Yang, Jiajia Yuan and Mingyuan Fan

Persistent alternation of high and low water in coastal and oceanic regions has attracted human attention for millennia. This movement of water is generally explained through the double water bulge model. Although this model has been widely adopted in the scientific literature on tides since the 18th century, the physical existence of water bulges on the Earth's surface has yet to be verified. Herein, we establish a lunar angle phase-dependent statistical analysis of tide patterns at 362,370 oceanic locations spotted by Jason-3 satellite of AVISO in 2021 to address this issue. We show that during lunar angle phases of 0 degree-45 degree and 135 degree-180 degree, which spatially correspond to the water bulging regions expected in the double water bulge model, the number of low tides consistently exceeds that of high tides. Conversely, during lunar angle phase of 45 degree-135 degree, which spatially correspond to the water-depressing region expected in the model, high tides predominantly outnumber low tides. These findings evidently contradict the physical existence of two water bulges in the world's oceans, suggesting that the scientific community should pay additional attention to alternative explanations for tides, such as gravitational forcing mechanism and oceanic basin oscillation-generated driving mechanism.
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Instrumentation and Detectors

Characterizing the energy resolution of the MicroBooNE LArTPC at the MeV scale using monoenergetic features of $^{208}$Tl decays

MicroBooNE collaboration: P. Abratenko, D. Andrade Aldana, J. Asaadi et al. (+188 more)

A detailed understanding of the capabilities and fidelity of low-energy reconstruction is crucial for taking advantage of MeV-scale neutrino physics opportunities in liquid argon time projection chambers (LArTPCs). This study presents a measurement of the resolution of reconstructed energy in the MicroBooNE LArTPC at $\approx 1.5$ MeV. The characterization is performed using monoenergetic signals generated by $2.614$ MeV $\gamma$-rays from $^{208}$Tl decays undergoing pair production in the detector. The resolution is found to be ($7.52 \pm 0.78 \text{(stat)} \pm 0.92 \text{(syst)}$)%. This value is consistent with the MicroBooNE simulation prediction of ($9.70 \pm 0.65 \text{(stat)}$)% at the $1.6 \sigma$ level. This study represents the first ever measurement of LArTPC energy resolution at the MeV scale and provides a pathway for monoenergetic energy calibrations in future experiments using LArTPC detectors.
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All authors MicroBooNE collaboration: P. Abratenko, D. Andrade Aldana, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton, M.B. Brunetti, L. Camilleri, D. Caratelli, F. Cavanna, G. Cerati, A. Chappell, Y. Chen, J.M. Conrad, M. Convery, L. Cooper-Troendle, J.I. Crespo-Anadon, R. Cross, M. Del Tutto, S.R. Dennis, P. Detje, R. Diurba, Z. Djurcic, K. Duffy, S. Dytman, B. Eberly, P. Englezos, A. Ereditato, J.J. Evans, C. Fang, B.T. Fleming, W. Foreman, D. Franco, A.P. Furmanski, F. Gao, D. Garcia-Gamez, S. Gardiner, G. Ge, S. Gollapinni, E. Gramellini, P. Green, H. Greenlee, L. Gu, W. Gu, R. Guenette, L. Hagaman, M. D. Handley, O. Hen, A. Hergenhan, M. Harrison, S. Hawkins, C. Hilgenberg, G.A. Horton-Smith, A. Hussain, B. Irwin, M.S. Ismail, C. James, X. Ji, J.H. Jo, A. Johnson, R.A. Johnson, D. Kalra, G. Karagiorgi, W. Ketchum, A. Kelly, M. Kirby, T. Kobilarcik, K. Kumar, N. Lane, J.-Y. Li, Y. Li, K. Lin, B.R. Littlejohn, L. Liu, S. Liu, W.C. Louis, X. Luo, T. Mahmud, N. Majeed, M.G. Manuel Alves, C. Mariani, J. Marshall, D.A. Martinez Caicedo, F. Martinez Lopez, S. Martynenko, A. Mastbaum, I. Mawby, N. McConkey, B. McConnell, L. Mellet, J. Mendez, J. Micallef, T. Mohayai, A. Mogan, M. Mooney, A.F. Moor, C.D. Moore, L. Mora Lepin, M. A. Hernandez Morquecho, M.M. Moudgalya, S. Mulleria Babu, D. Naples, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, C. Nguyen, L. Nguyen, J. Nowak, N. Oza, O. Palamara, N. Pallat, V. Paolone, A. Papadopoulou, V. Papavassiliou, H. Parkinson, S.F. Pate, N. Patel, Z. Pavlovic, E. Piasetzky, K. Pletcher, I. Pophale, X. Qian, J.L. Raaf, V. Radeka, A. Rafique, M. Reggiani-Guzzo, J. Rodriguez Rondon, M. Rosenberg, M. Ross-Lonergan, I. Safa, C. Sauer, D.W. Schmitz, A. Schukraft, W. Seligman, M.H. Shaevitz, R. Sharankova, J. Shi, L. Silva, E.L. Snider, S. Soldner-Rembold, J. Spitz, M. Stancari, J. St. John, T. Strauss, A.M. Szelc, N. Taniuchi, K. Terao, C.Thorpe, D. Torbunov, D. Totani, M. Toups, A. Trettin, Y.-T. Tsai, J. Tyler, M.A. Uchida, T. Usher, B. Viren, J. Wang, L. Wang, M. Weber, H. Wei, A.J. White, S. Wolbers, T. Wongjirad, K. Wresilo, W. Wu, E. Yandel, T. Yang, L.E. Yates, H.W. Yu, G.P. Zeller, J. Zennamo, C. Zhang, Y. Zhang

Optics

Mid-infrared single-pixel imaging at the single-photon level

Yinqi Wang, Kun Huang, Jianan Fang et al. (+3 more)

Single-pixel cameras have recently emerged as promising alternatives to multi-pixel sensors due to reduced costs and superior durability, which are particularly attractive for mid-infrared (MIR) imaging pertinent to applications including industry inspection and biomedical diagnosis. To date, MIR single-pixel photon-sparse imaging has yet been realized, which urgently calls for high-sensitivity optical detectors and high-fidelity spatial modulators. Here, we demonstrate a MIR single-photon computational imaging with a single-element silicon detector. The underlying methodology relies on nonlinear structured detection, where the encoded time-varying pump patterns are optically imprinted onto the MIR object image through sum-frequency generation. Simultaneously, the MIR radiation is spectrally translated into the visible region, thus permitting infrared single-photon upconversion detection. Then, the use of advanced algorithms of compress sensing and deep learning allows us to reconstruct MIR images under sub-Nyquist sampling and photon-starving illumination. The presented paradigm of single-pixel upconversion imaging is featured with single-pixel simplicity, single-photon sensitivity, and room-temperature operation, which would establish a new path for sensitive imaging at longer infrared wavelengths or terahertz frequencies, where high-sensitivity photon counters and high-fidelity spatial modulators are typically hard to access.
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All authors Yinqi Wang, Kun Huang, Jianan Fang, Ming Yan, E Wu, Heping Zeng

Optics

Mid-infrared single-photon 3D imaging

Jianan Fang, Kun Huang, E Wu et al. (+2 more)

Active mid-infrared (MIR) imagers capable of retrieving three-dimensional (3D) structure and reflectivity information are highly attractive in a wide range of biomedical and industrial applications. However, the infrared 3D imaging at low-light levels is still challenging due to the deficiency of sensitive and fast MIR sensors. Here we propose and implement a MIR time-of-flight imaging system that operates at single-photon sensitivity and femtosecond timing resolution. Specifically, back-scattered infrared photons from a scene are optically gated by delay-controlled ultrashort pump pulses through nonlinear frequency upconversion. The upconverted images with time stamps are then recorded by a silicon camera to facilitate the 3D reconstruction with high lateral and depth resolutions. Moreover, an effective numerical denoiser based on spatiotemporal correlation allows us to reveal the object profile and reflectivity under photon-starving conditions with a detected flux below 0.05 photons/pixel/second. The presented MIR 3D imager features with high detection sensitivity, precise timing resolution, and wide-field operation, which may open new possibilities in life and material sciences.
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All authors Jianan Fang, Kun Huang, E Wu, Ming Yan, Heping Zeng

Optics

High-speed mid-infrared single-photon upconversion spectrometer

Tingting Zheng, Kun Huang, Ben Sun et al. (+6 more)

Sensitive and fast mid-infrared (MIR) spectroscopy is highly attractive in a variety of applications including astronomical observation, pharmaceutical synthesis, and environmental monitoring. However, the performance of conventional MIR spectrometers has long been hindered by the limited sensitivity of narrow-bandgap detectors and/or the deficient brightness of broadband light sources. Here, we devise and implement an ultra-sensitive and broadband MIR upconversion spectrometer, which integrates a supercontinuum source covering 1.5-4.2 $\mu$m based on a silicon nitride nanophotonic waveguide. High-efficiency and low-noise nonlinear frequency upconversion is realized based on coincidence pulsed pumping with spectro-temporal optimization, which enables to leverage silicon detectors for facilitating MIR single-photon spectroscopy at 0.2 photons/nm/pulse. Furthermore, the upconversion-based array spectrometer is manifested with high-speed spectral acquisition rates beyond 200 kHz, which is about ten-fold faster than the state-of-the-art scan rates for FTIR-based spectrometers at a comparable spectral resolution. The achieved features of broadband spectral coverage, single-photon sensitivity, and sub-MHz refreshing rate might open up new possibilities in infrared transient spectral measurements in combustion analysis, high-throughput sorting and reaction tracking, among others.
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All authors Tingting Zheng, Kun Huang, Ben Sun, Jianan Fang, Yongyuan Chu, Hairun Guo, E Wu, Ming Yan, Heping Zeng

Atmospheric and Oceanic Physics

A mathematical framework for dynamic emergent constraints in climate science

Francesco Ragone and Valerio Lucarini

Emergent constraints in climate science are empirical relations that link the response to a forcing of a physical observable to the properties of other observables, with the aim of reducing climate change projection uncertainties. Here we use recent results in linear response theory to develop a mathematical framework for dynamic emergent constraints, a class of emergent constraints linking the response of different observables to the same forcing. We show how traditional dynamic emergent constraints are a special case of more general relations, that we call integral dynamic emergent constraints. These relations allow to compute the response of a predictand as the convolution of the response of a predictor and the proxy Green's function of the predictand-predictor pair. The conditions for the existence of integral emergent constraints are related to the causality of the proxy Green's function and the time scales at which the system is observed. We apply this framework to global warming simulations with the MPI-ESM climate model, to study dynamic emergent constraints between different observables. These results allow to put the theory of dynamic emergent constraints on firm mathematical ground, and suggest a protocol to identify necessary conditions for the existence of such relations in climate data.
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Thursday 28 May

Applied Physics

Coils in thermomagnetic harvesters – a comparative study

Aske Chris Nilsson, Andrea Roberto Insinga, Salvatore De Angelis et al. (+2 more)

Thermomagnetic generators (TMGs) are devices that convert waste heat to electricity through a change in magnetization of a solid material. This causes a changing flux through a coil, which induces an electromotive force per Faraday's law. However, the influence of the coil on the performance of the TMG has not been investigated and existing TMG prototypes merely utilize some coil, not the optimal coil for a given device. In this work we present an analytical and numerical model of a TMG that calculates power by explicitly coupling the TMGs magnetic and electric circuits and use this to analyze the influence of the coil on the TMG performance. We show that TMG power has a linear dependence on coil volume, independent of the specific combination of wire radius and coil turns. The model is validated with experimental data, and finally used to study prototype TMGs presented in literature, where we show that the power of these literature TMGs can be increased by a factor of 10-400 times, had larger coils been used in the prototypes.
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All authors Aske Chris Nilsson, Andrea Roberto Insinga, Salvatore De Angelis, Georgios Potsios, Rasmus Bjørk

Computational Physics

Introducing an Extensible Open-Source Toolkit Suite for Studying Second Harmonic Generation: A Case Study of Depleted Pulsed Gaussian Wave SHG

Mostafa M. Rezaee, Mohammad Sabaeian, Alireza Motazedian et al. (+2 more)

Second Harmonic Generation (SHG) in nonlinear crystals has been extensively investigated, but most existing models still rely on simplifying assumptions. In realistic settings, thermal effects introduce complications that are difficult to capture analytically because the governing equations are highly coupled and nonlinear. Direct experimental characterization is also limited, since studying thermal effects would require spatiotemporal temperature data at every point in the crystal, which is not experimentally accessible. To address these limitations, we have developed a SHG Computational Toolkit Suite, a coordinated collection of independent modeling toolkits that cover different SHG scenarios under various physical conditions. Each toolkit focuses on a particular configuration or coupling mechanism, while the suite as a whole provides well-documented numerical implementations, reproducible workflows, and illustrative examples. Together, this article and the Toolkit Suite provide a coherent infrastructure for computational studies of SHG. It enables researchers to replicate, adapt, and extend our methods without duplicating foundational development efforts, thereby accelerating SHG research and promoting reproducibility.
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All authors Mostafa M. Rezaee, Mohammad Sabaeian, Alireza Motazedian, Fatemeh Sedaghat Jalil-Abadi, Mohammad Ghadri