Papers

We derive a one-dimensional reduction for nonlinear dynamics on simplicial complexes containing both pairwise and triangular (higher-order) interactions. The effective state is defined using a mixed weight determined by the pairwise and triangular degrees of each node. The resulting reduced equation retains two structural coefficients, associated separately with the pairwise and higher-order coupling channels. A fluctuation expansion identifies the closure assumptions underlying the reduction and shows how deviations of individual node states from the effective state contribute to the approximation error. We numerically validate the proposed framework on Gene-regulatory dynamics, the double-well system, and SIS spreading. The states of the reduced model are compared with full-network simulations through coupling-parameter sweeps, steady-state branch calculations, and progressive node-removal experiments on synthetic and real-world networks. The reduced model successfully reproduces the principal transitions and steady-state branches in all three dynamical systems considered. Agreement is strongest for relatively homogeneous networks and deteriorates when structural heterogeneity produces a broader distribution of node states. The closure diagnostics account for this loss of accuracy and indicate when a single effective state is no longer sufficient. The reduction therefore provides a tractable description of resilience in systems with coexisting pairwise and higher-order interactions.

Atomic spin-based comagnetometers are powerful tools for precision sensing and tests of fundamental physics. Compared with the widely used gas-cell comagnetometer systems, cold-atom systems offer access to much shorter distance scales and allow implementation of {optical} quantum control techniques. However, in order to realize long spin coherence times with cold atoms, it is necessary to employ diamagnetic atoms and overcome decoherence induced by light shifts. Here we demonstrate a cold-atom comagnetometer based on the nuclear spins of $^{171}$Yb (spin-1/2) and $^{173}$Yb (spin-5/2), jointly trapped in an optical lattice. Vector light shifts are suppressed by enforcing linear polarization of the lattice, while tensor shifts in $^{173}$Yb are suppressed via the use of a Schrödinger cat state. This enables simultaneous Ramsey interferometry on both isotopes with a spin coherence time of 60 s. We achieve a magnetic noise suppression factor exceeding $3\times10^4$, and determine the ratio of nuclear magnetic moments to 4 ppm precision. Our results establish a new cold-atom platform for spin-based sensing and open pathways toward quantum-enhanced searches for physics beyond the Standard Model.

Transient weather systems are often associated with alternating warm and cold advections of air masses and changing wind directions, which drive coastal ocean and estuarine waters to oscillate quasi-periodically. Quantifying water transport under these meteorological oscillations between inland waterways and the coastal ocean helps interpret land-ocean interactions and the impact of migrating weather systems. The challenge lies in the difficulty of obtaining continuous, long-term direct measurements of transport due to logistical constraints. Here, we apply a method to determine the meteorological tide-induced volume transport of water through an intensive survey, correlating transport values measured by a boat-mounted ADCP with vertically averaged velocities from a bottom-mounted ADCP, which recorded a much longer time series. The correlation is then used to compute transport over the period of the bottom-mounted ADCP deployment. Observations were conducted at Belle Pass, Port Fourchon. The transport data revealed the impact of weather systems, including four cold fronts. A model of volume transport, accounting for rotary cold front wind variations, was applied, where both along-channel and along-coastline wind components contribute to the remote wind effect, leading to a more complex response to passing weather systems. The local wind effect is much smaller than the remote wind effect, and transport is primarily controlled by water level fluctuations resulting from open boundary input. Finally, the channel orientation relative to the coastline is found to be critical in determining both the magnitude and phase of the transport.

Focused very-high-energy electron (VHEE) beams can produce localized dose enhancement at selected depths, but irradiation of a finite target requires coordinated control of multiple focal positions, incidence directions, and beam weights while limiting exposure of nearby organs at risk (OARs). We present Focal-Point Scanning (FPS), a dose delivery and optimization method developed for laser wakefield accelerator (LWFA)-driven VHEE beams. The method is based on a two-dipole focusing system that produces single-plane beam convergence and allows the focal position to be varied by changing the magnetic field strength. FPS distributes focal points throughout the planning target volume and determines focal-point-specific incidence sectors according to the geometry of nearby critical OARs. The method was evaluated using the AAPM TG119 C-shape benchmark and one previously treated lung radiotherapy case. At matched target coverage, FPS reduced the TG119 Core mean dose by approximately one half relative to parallel VHEE and intensity-modulated x-ray plans, approaching the single-field proton pencil-beam-scanning reference. In the lung case, FPS maintained target coverage comparable to the clinical volumetric modulated arc therapy reference while reducing the mean dose to every evaluated OAR; spinal-cord mean and maximum doses decreased by 93.2% and 87.2%, respectively. The evaluated OAR mean doses varied little across rms energy spreads of 0 to 10% and for a flat-top electron spectrum spanning 150 to 250 MeV. These results demonstrate that focal-point-specific angular selection can translate focused-beam physics into effective OAR sparing and support FPS as a planning strategy for broadband LWFA-VHEE radiotherapy.

6G mobile communications impose immersive communication demands for higher data rates and massive connectivity, while emerging integrated sensing-computing-intelligence scenarios require base stations to concurrently enhance computing capability, guarantee service latency, and realize sensing. We propose the Omni-Photonic Base Station-a progressive evolutionary architecture that introduces photonic technologies into three functional domains, namely baseband processing, fronthaul transmission, and the RF front-end, and obtains system-level gains through cross-domain co-design. By introducing photonics, Omni-PBS harnesses the inherent physical advantages of ultra-broad bandwidth, ultra-low propagation latency, and native parallelism to transcend the aforementioned electronic bottlenecks and fulfill the compound demands of 6G scenarios. The optical baseband computing domain employs photonic accelerators to perform linear computation-intensive tasks, improving the energy efficiency of AI inference by one to two orders of magnitude. The analog optical fronthaul domain replaces digital fronthaul with analog radio-over-fiber , which eliminates the ADCs/DACs and digital intermediate-frequency chips in the remote unit and substantially reduces fronthaul bandwidth requirements. The microwave-photonic RF domain breaks through the bandwidth and frequency limitations of electronic RF front-ends via optical true-time-delay beamforming, programmable photonic filtering, and optical heterodyne frequency conversion. The three domains yield system-level gains beyond single-domain summation through four co-design principles: end-to-end optical-domain continuity, cross-domain co-design, optical computing resource scheduling, and joint optimization of functional splitting.

Fluid-structure interaction (FSI) in viscoelastic flows past deformable structures at low Reynolds numbers remains poorly understood, despite its relevance to biological systems such as cilia and flagella, and to engineered microsystems. We investigate viscoelastic FSI in side-by-side flexible cantilever arrays using a bottom-up approach that systematically varies the number of cantilevers and the rheology of the test fluid, comparing weakly shear-thinning (WS) and highly shear-thinning (HS) polyethylene oxide solutions. For both fluids, with increasing Weissenberg number (Wi), an elongated elastic wake develops behind a single isolated cantilever. For multiple cantilevers, the WS fluid undergoes a transition at a critical Weissenberg number (Wi*) from separated to merged elastic wakes, accompanied by the emergence of a divergent flow field and coordinated inward spanwise cantilever deflection. The critical Wi* increases as the number of cantilevers in the array is increased from two to three, demonstrating a strong dependence of the onset on the array configuration. For the HS fluid, wake merger, flow divergence, and inward cantilever deflection are suppressed across the full range of Wi investigated, despite comparable elasticity and the formation of elastic wakes. This contrast shows that elasticity alone promotes wake formation but is insufficient to produce the collective instability, which instead requires both shear-thinning and interactions between neighboring cantilevers. These findings demonstrate that viscoelastic FSI in flexible arrays is governed by the combined effects of fluid elasticity, shear-thinning, and geometric configuration, with elastic wake interactions mediating the collective instability and linking local elastic wakes to array-scale structural response.

We apply persistent homology to a six-layer temporal network model of the Inca Empire (Tawantinsuyu), built from the Qhapaq Ñan road system ($6{,}546$ segments; $12{,}031$~km): 4,492 nodes (4,452 active; 40 isolated removed), $4{,}358$ edges, $57$ temporal snapshots (1400–1572~CE). The complete flag complex yields $\beta_1 = 32$ cycles ($26$ macro-continental, $6$ meso-regional) and $\beta_0 = 264$ components at the finest filtration, evaluated across six layers: infrastructure, Inca political control, Spanish alliance growth, Andean tribute commerce, and Spanish legal/effective administration. Five results. (i) Infrastructure entropy $H_{\mathrm{infra}}=1.486\pm0.0001$ stays constant throughout, indicating no detectable topological disruption of the Qhapaq Ñan at this resolution. (ii) Inca political entropy $H_{\mathrm{inca}}$ is stable through the Cajamarca capture (1532~CE), then collapses to zero by 1537~CE; the dominant break is at Vilcabamba ($F=120.7$), not Cajamarca ($F=11.5$). (iii) Four of six layers reach the critical regime at 1532~CE, while infrastructure stays marginally below threshold ($\mathrm{ICT}=0.495$); trade and political reach the highest values ($\mathrm{ICT}=0.976$, $0.968$), marking Cajamarca as a synchronised multi-layer phase transition. (iv) Spanish legal administration converges to the infrastructure topology by 1572~CE ($W_1=5\times10^{-6}\approx0$): Substitution Topology, infrastructure-preserving collapse via topology transfer. (v) Legal–effective divergence decays from $W_1=0.591$ (1532) to $0.002$ (1572), quantifying resolution of colonial legal fiction. Together, these results support a distinct collapse mode—Substitution Topology—differing from erosion-dominated Roman/Byzantine collapse, Han fragmentation, and Aztec military destruction.

Infrasound signal period is widely used as a proxy for source energy in bolide studies, but the reliability of period-yield relations for small, high-altitude regional meteors has not been systematically evaluated. We analyze 90 infrasound detections from well-constrained regional meteoroid events (source altitudes 20-111 km, ranges 47-268 km) and demonstrate a strong, monotonic decrease in receiver dominant frequency with increasing source altitude (Spearman r_{s} = -0.629, p = 3.3 x 10^11). No detections above 80 km retain dominant frequencies exceeding 3 Hz, and 75% of detections above 100 km are dominated by sub-1 Hz content. Partial correlation analysis indicates this is primarily an altitude effect, not a propagation distance artifact. Near-source dissipation modeling using the generalized Burgers equation supports a physical mechanism: the exponential increase in kinematic viscosity with altitude drives the acoustic Reynolds number downward, imposing frequency-dependent molecular absorption that selectively attenuates high-frequency content within the first 5 km below the source. Our results suggest that this atmospheric low-pass filter systematically modulates the observed period and can bias period-based energy estimates upward by one to two orders of magnitude for sources above 80-90 km when uncorrected period-yield relations are applied. These findings are relevant to any high-altitude infrasound source, including space debris and controlled reentries.

Next-generation submillimeter instruments require gigahertz-scale readout bandwidths to support the growing detector counts of large microwave kinetic inductance detector (KID) arrays. Designed to meet the readout bandwidth and tone-capacity requirements of the CCAT Prime-Cam 850 GHz and 410 GHz instrument modules, we developed our second-generation (Gen2) KID readout system on a Xilinx ZCU111 radio frequency system-on-chip (RFSoC), based on a parallelized overlap-channel polyphase synthesis filter bank and a companion wideband receiving channelizer. This two-octave architecture reads out four independent RF networks, each with 1.024 GHz instantaneous bandwidth and up to 2048 detectors. The polyphase synthesis doubles the baseline channel count and bandwidth, and enables on-the-fly control of individual tone frequency, amplitude and phase, facilitating optimized KID biasing and providing a gateway to tone tracking. These capabilities may also be useful more broadly across Prime-Cam and in similar frequency-division multiplexed (FDM) readout systems. We present the design in DSP simulation, and measurements in RF loopback as well as with two KID test chips, one spanning the full two-octave band. Loopback measurements demonstrate comparable noise performance between the first-generation (Gen1) baseline and Gen2; preliminary on/off-resonance measurements indicate detector-noise-limited operation for the majority of channels; and the digital channel crosstalk is measured and discussed. We report FPGA resource and power utilization and assess scalability toward future large-format KID instruments.

We present the first application of simulation-based inference to resonant inelastic X-ray scattering spectroscopy. Using truncated marginal neural ratio estimation to efficiently restrict the prior and conditional flow matching as the joint density estimator, we infer full posteriors with a modest simulation budget for two Ni$^{2+}$ compounds—NiPS$_3$ as a representative covalent case and K$_2$NiF$_4$ as a more atomic one. We demonstrate that a vision transformer encoder whose tokenization matches the physical layout of the RIXS map yields better-covered and sharper posteriors than generic image encoders. Applying the validated method to experimental NiPS$_3$ and K$_2$NiF$_4$ data, we recover a joint posterior that reveals parameter correlations invisible to point estimators, and a posterior predictive distribution that closely matches the observed spectrum. The amortized posterior unlocks a class of analyses not previously available to the field such as nuisance-marginalized uncertainty quantification, multi-measurement posterior fusion and active experimental design.

We apply persistent homology and a dual-model topological pipeline to a multilayer network of the Aztec Empire (Triple Alliance, 1427–1521 CE), constructed from tribute records and geographic adjacency among 38 nodes (Tenochtitlan-Centro, 36 tribute-paying provinces, and the Tlaxcala enclave) and 208 edges. We report four main results: (i) The tribute (control) layer is a pure extraction tree ($\bettione = 0$, $H = 0.000$ at all epochs): structurally more fragile than any documented configuration in the Roman, Byzantine, or Han administrative datasets analyzed with the same pipeline. (ii) Single-node removal of Tenochtitlan-Centro collapses the giant component from 1.000 to 0.630 and eliminates 30 redundancy cycles simultaneously, a structural asymmetry ratio of $>4$:1 relative to random perturbation. (iii) The Tlaxcala–Puebla region coincides with the dominant $\bettione$ class of the imperial geographic point cloud (persistence $= 22.09$~km, versus $< 3$~km for all others), a structural void that exists identically whether Tlaxcala is modeled as absent or present in the filtration. (iv) A logistic regression confirms that commercial centrality in the geographic layer ($r = +0.462$, $p = 0.004$) is the dominant predictor of early alliance formation, while tribute burden is uncorrelated ($r = -0.033$, $p = 0.845$). These four results define a new imperial collapse mode, the void-occupied tree, in which zero topological redundancy in the control layer coincides with a dominant geometric void occupied by an autonomous enclave—a configuration not previously documented in historical network TDA.

The Carrier–Greenspan hodograph transformation linearises the nonlinear shallow-water equations on a beach of constant slope. We extend the transformation to a moving bottom and identify the family of bottom motions that preserves the Carrier–Greenspan invariants. The bottom gradient must be uniform in space, that is, $h(x,t)=\rho(t)x+\mathcal{B}(t)$, and constant $\rho$ returns the classical slope. For this family a horizontally accelerating frame removes the forcing. The bottom motion then disappears from the hodograph equation, and two quadratures recover the physical variables. If the gradient varies in time, the bed displacement grows without bound offshore and the far field cannot remain at rest. The domain must therefore be finite, although the pivot may be placed anywhere. A bottom-tilting wave maker realises this family. Closed forms follow for the hinge response, for the crest-to-trough steepness of the generated wave, and for the leading nonlinear correction. The correction depends on the point to which the steepness is referred, and so differs between a leading-elevation and a leading-depression wave. Because the hinge is at the beach toe, these closed forms provide the incident wave required by the classical plane-beach solution. The run-up can therefore be predicted from the plate motion alone. The steepness is predicted without a fitted constant and agrees with the reference computations. Sixty-one runs over a level bed, reported here for the first time, carry the test to deeper water and longer plate motions. The measured run-up follows the predicted run-up, with an offset that the inviscid theory does not account for.

Frontogenesis is the process by which ocean fronts–regions of strong horizontal density gradients in the upper ocean–strengthen. It is a highly non-linear phenomenon arising from many competing effects, such as background strain, instabilities, and surface forcing. Vertical mixing plays a complicated role in governing both frontogenesis and the long-term dynamics of ocean fronts. For weak fronts, it has been shown to drive shear dispersion which further weakens the front over long timescales. However, vertical mixing also mixes the vertically-sheared thermal wind velocity, driving the front out of balance and causing a secondary circulation to develop that may strengthen the front. Here, it is shown that vertical mixing can directly act to oppose the frontogenetic secondary circulation, provided the frontal width is larger than a critical value. A non-linear iteration method is described for finding balanced states in which vertical mixing arrests frontogenesis and the parameter dependence of this regime is discussed. Further, existing asymptotic solutions for the buoyancy and velocity fields are extended and found to closely match these balanced states, even outside their region of formal validity.

Collective semantic change in populations of language model agents is a measurable dynamical phenomenon. We present a passive longitudinal instrument called Kopterix that observes the semantic state of an agent population as a sequence of bounded observations under a protocol defined before the observations begin. Each observation divides the sampled feed by post age into surface, mid-stream, and residue layers, which makes semantic differences across content age measurable alongside run-to-run change. We validate the instrument on Moltbook, an agent-native social platform, over a two-month window of scheduled observations, with the periodicity check extended across approximately four months. At the lexical level, rarefied entropy resolves an April-May difference in the evenness of the stored top 200 unigram distributions, and adjacent states are lexically closer than states paired after timestamp shuffling. At the geometric level, grand mean centering exposes the scale of a common embedding direction, and scheduled shuffle checks support a recurring excess in the mid-stream to residue separation relative to the shuffled reference. At the temporal level, detrended scalar quantities and centered layer centroids lose much of their similarity over several hours, and a weaker positive component declines across longer separations with no strong weekly recurrence. Several attractive apparent structures failed their controls, and each reading is limited to the level its controls support. The design applies wherever a population of agents produces a timestamped language environment that can be observed repeatedly and divided by content age.

We present a comparative study of DC electrical breakdown in liquid nitrogen, liquid helium, and liquid argon using a common cryostat, electrode assembly, voltage-ramp protocol, and analysis procedure. This common experimental configuration minimizes systematic differences that often complicate comparisons among cryogenic liquids, including variations in electrode geometry, stressed area, surface finish, and gap spacing. For each liquid, breakdown was characterized as a statistical distribution rather than by a single characteristic voltage, allowing the stochastic nature of the process to be examined. Measurements were performed both near saturated vapor pressure and under modest pressurization to assess the influence of bubble formation and related thermodynamic effects. Liquid argon exhibited a non-stationary "turn-on" behavior, with breakdown voltage increasing over repeated discharges, consistent with evolution of the local impurity environment or electrode surface state. Near saturated vapor pressure, liquid helium showed a bimodal breakdown distribution, with a lower-field component consistent with bubble-mediated processes. Liquid nitrogen exhibited higher breakdown fields than liquid argon and fields comparable to those measured in pressurized liquid helium, within the observed run-to-run variation associated with surface state. Taken together, these results support a comparative framework in which breakdown strength reflects both thermodynamic stability against bubble formation and the transport properties of the dominant negative charge carrier.

We systematically investigate four cosmological models within a parameterized framework that allows for a redshift dependence of \(H_0\): three phenomenological models (\(\alpha\Lambda\)CDM, \(\alpha w\)CDM, and \(\alpha w_0w_a\)CDM), and the $J$CDM model motivated by big bang quantum cosmology. Using cosmic microwave background (CMB) data, baryon acoustic oscillations (BAO), cosmic chronometer (CC) measurements of the Hubble parameter, and three Type Ia supernova samples (PantheonPlus, DESY5, and Union3), we perform Markov chain Monte Carlo (MCMC) analyses to obtain posterior distributions of the model parameters. We also perform separate analyses using early-time and late-time data to assess how each observational epoch affects the model constraints. For the three phenomenological models, the parameter \(\alpha\) describing the redshift evolution of \(H_0\) is consistent with zero within \(2\sigma\). The Hubble constant inferred from the \(\alpha\Lambda\)CDM model is consistent with CMB results, while the $J$CDM model yields a larger Hubble constant but is strongly disfavored by model comparison criteria. Using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) for model comparison, we find that the standard \(\Lambda\)CDM model remains the most favored by the data. Among the four models, the \(\alpha w_0w_a\)CDM model shows a marginal AIC advantage ($\rm \Delta AIC \sim$ -2 to -13). However, this preference does not translate into a reduction of the Hubble tension, which is consistent with existing studies supporting dynamical dark energy. Moreover, none of the models can simultaneously satisfy both the early- and late-time constraints, and the combined datasets alone are insufficient to conclusively determine whether these parametrizations can resolve the tension.

This doctoral dissertation on the foundations of quantum theory isolates and then formalizes a physically relevant concept that I have called "Epistemic Constraint." Here, epistemic constraints are the definite, intersubjectively agreeable, ordinary-language conditions under which experiments are described. The usual formulation of the quantum measurement problem, which I call the Schrodingerian measurement problem, has the structure of an anomaly: if we take quantum theory at face value, we expect no definite values, and yet we see definite values in experiments. The responses to this problem have been either to solve it or to dissolve it. These responses, which have taken the form of interpretation, modification, or reconstruction of quantum mechanics, seek either to derive (conceptually or mathematically) epistemic constraints from within quantum mechanics or suitable modifications of it, as is the case with certain interpretations and modifications, or to posit the epistemic constraint, or parts of it, as a primitive assumption with the goal of deriving quantum mechanics, as is the case in some reconstruction programs. In contrast to the Schrodingerian measurement problem, which had the structure of an anomaly, this dissertation develops the Bohrian Program, which (for lack of a better comparison) has a structure similar to the problem historically associated with Euclid's fifth postulate. It seeks to keep epistemic constraints as primitive in an onto-epistemic sense. It then seeks new physical conclusions from the joint consideration of quantum mechanics and epistemic constraints, without seeking to derive one from the other. Among other results, this leads to a notion of the probability of instantiability of the Born Rule that specifies when to apply the Born Rule and when to apply a unitary transformation to a quantum state.

We report a fixed-order Clauser-Horne-Shimony-Holt (CHSH) acquisition and reporting protocol for two encoded photonic qubits on Quandela's commercial, cloud-accessible Belenos processor, executed end-to-end by external users through the public cloud interface. Each logical qubit is a two-dimensional spatial-mode subspace in the seven-dimensional zero-sum sector of an eight-mode single-photon register, and a target postselected linear-optical controlled-$Z$ (ideal success probability $1/9$) couples the registers on $16$ of $24$ modes. The primary quantity is the operational CHSH score $S$ on accepted logical coincidences, with each complete four-setting pass as the experimental unit. Eight sequential same-day passes each gave a raw score above $2$; session means were $2.40$ and $2.58$ (sample standard deviations $0.15$ and $0.03$), with excess dispersion $Q/\nu=6.1$ ($\nu=7$). Count-pooled secondary descriptors are $S_{\mathrm{count}}=2.485\pm0.019$ and a fixed-ratio efficiency-reweighted model scenario $S^{\mathrm{rw}}_{\mathrm{count}}=2.380\pm0.021$, whose weakest reweighted pass ($2.040\pm0.062$) overlapped $2$ within $1\sigma$. The reweighting is an archived-metadata model scenario, not a corrected platform score; an ad hoc $\kappa\in[1.2,1.8]$ stress scan (not a calibrated uncertainty band) spans $2.341$-$2.441$. Setting order was fixed, the compiled mapping was not returned, and residual remote-setting marginals remain, so the data support an operational reference acquisition rather than an entanglement-witness or cross-platform benchmarking claim. The parity-check terminology labels the encoding subspace; no syndrome measurement was performed. Count records, job identifiers, circuit-construction code, and analysis are openly archived with content hashes for the submitted targets.

Recovering high-resolution states from sparse, low-resolution observations is a central challenge in scientific machine learning and data assimilation. Classical data assimilation exploits temporal information through forecast-analysis cycles, but often requires repeated access to expensive high-resolution forecast models. Generative super-resolution can recover unresolved structure from coarse observations, but is commonly used as a one-shot mapping that does not fully exploit constraints from past states. We introduce Iterative Refinement (IR), a learned data assimilation framework that combines these perspectives. Instead of performing a single coarse-to-fine reconstruction, IR decomposes the task into resolution-wise forecast-analysis operations across a multiresolution hierarchy. At each stage, a shared neural operator with resolution-dependent spectral mode slicing provides a dynamical prior, while a shared conditional diffusion corrector uses the current coarser-resolution state to produce a refined posterior at the next finer resolution. We evaluate IR on one-dimensional stochastically forced Burgers dynamics and two-dimensional Kraichnan turbulence. On the challenging 256x256 Kraichnan benchmark, IR achieves an RMSE of 0.184 and an SSIM of 0.836, outperforming spectral upsampling, one-shot diffusion super-resolution, enhanced deep super-resolution, and an autoregressive forecaster. On the more constrained Burgers testbed, IR remains competitive with one-shot diffusion, which achieves the lowest RMSE. These results show that one-shot generative reconstruction can be effective for simpler settings, while hierarchical forecast-analysis refinement becomes advantageous in strongly multiscale and underdetermined regimes. Overall, IR combines temporal priors, generative correction, and multiresolution reconstruction for learned data assimilation in complex physical systems.

The term "superatom" was introduced over three decades ago to describe clusters that emulate elemental atoms. The field has long been guided by the spherical jellium model, where magic numbers arise from shell closure of delocalized electrons. This Perspective argues that delocalization, not near-sphericity, is what makes a system atom-like. It shows that superatomic shell structure persists under arbitrary point-group symmetry, that superatomicity survives as a tunable quantum state across pressurized, ionized, and chemically precompressed systems, and that the symmetry rules governing superatoms are conditional, deeper than the jellium picture admits. The future of this field lies not in finding more magic numbers, but in exploiting superatomic states as artificial quantum systems at the atomic level.

Self-organized spatial patterns are central to nonequilibrium physics and cell biology, yet locating instabilities in multi-component, reaction-diffusion networks remains challenging because standard eigenvalue analyses scale with the number of biochemical states and rely on reaction kinetics often poorly constrained by experiments. Exploiting the common mass-conserving structure of protein reaction kinetics and the fact that nonlinear feedback is typically confined to membrane reactions while lateral membrane diffusion is negligible, we develop a geometric classification that predicts stationary, and approximately also oscillatory, pattern-forming instabilities from reactive equilibria. The developed criteria reduce the stability analysis from the full component space to the space of conserved species. On this reduced space, slope matrices—describing the change of equilibrium cytosolic densities with respect to total species densities—govern onset. Based on densities in chemical equilibrium, this approach eliminates the requirement of comprehensive kinetic knowledge frequently lacking in experimental systems. Thus, a broad range of instabilities can be understood as mass-redistribution instabilities—self-amplifying mass redistribution caused by shifting local equilibria. We apply these criteria to models for the Escherichia coli Min system and the Caenorhabditis elegans polarity system and show that the reduction extends to the mixed-dimensional dynamics in systems coupling bulk cytosolic dynamics with membrane dynamics on the boundary. Together, these results provide an interpretable, broadly applicable, and experimentally accessible framework for diagnosing and designing pattern formation in multicomponent nonequilibrium systems on the basis of conservation laws.

This document describes the models used in the simulator for the dynamics of a nanoparticle levitated in a Paul trap combined with an optical tweezer. The focus is the coupled evolution between the center-of-mass motion, the internal temperature of the particle, and the effective temperature associated with the mechanical motion. The formulation includes electric and optical forces, gas damping, thermal noise, heat exchange with the gas, thermal radiation, active optical absorption, parasitic absorption, anti-Stokes cooling, and absorption/emission spectra obtained from generic presets, generated bands, or experimental tables loaded by the user

Transient thermal grating (TTG) experiments provide a powerful means of probing material properties and heat-transport dynamics at small spatiotemporal scales through the temporal response to a spatially periodic excitation. However, quantitative interpretation of the measured transient requires a forward model that consistently connects energy deposition, subsequent heat transport, and the detected TTG observable over the experimental timescale. A unified formulation linking these stages remains insufficiently developed in the TTG context. Here, we formulate a continuum, operator-based TTG forward model that describes the sequence from energy deposition through thermal transport to the temporal evolution of the selected spatial temperature mode within a unified transfer-function framework, while leaving the instrument-specific detection process outside the scope of the present formulation. Heat-transport dynamics are represented by a temporal memory kernel, allowing unresolved relaxation processes to be incorporated into the macroscopic response. The framework provides a basis for assessing the identifiability of thermal diffusivity, heat-propagation speed, and heat-flux relaxation time when flux-memory effects are resolved on the experimental timescale. These macroscopic parameters can, in turn, inform the microscopic interpretation of the measured dynamics. Analysis of the resulting model further demonstrates that the observability of heat-flux memory is not equivalent to the presence of oscillations in the measured response. Oscillations can provide a clear signature of finite flux-relaxation dynamics, but their absence does not establish the validity of Fourier heat conduction: finite flux relaxation dynamics need not produce experimentally observable oscillations under all conditions.

Electrons in two-dimensional electron gases in the presence of an out-of-plane magnetic field propagate along the edge with a high velocity of the order of the Fermi velocity. Under microwave and terahertz radiation, photon absorption by these electrons provides a pathway to realising sensitive radiation detection. Here, we develop a detailed quantum theory of the photocurrent generated in such a system by an incident electromagnetic wave and propose an experimental geometry for observing the predicted phenomenon. By using suitably arranged radiation confinement structures, a strong photocurrent generation efficiency can be obtained. We also demonstrate that the resulting photoresponse in III-V semiconductor structures can be orders of magnitude higher than that measured in graphene.

Peripheral nerves buried beneath intact tissue are difficult to visualize during surgery and remain inaccessible to white light wide-field imaging and other surface optical imaging methods. Existing OCT nerve studies have largely relied on exposed nerves or polarization contrast with limited depth penetration, restricting their value for subsurface intraoperative guidance. Here, we introduce, to our knowledge, the first label-free framework for detecting peripheral nerves beneath unopened tissue and resolving their depth using intensity-based OCT structural signatures alone. The framework combines a handheld multimodal probe, integrating swept-source OCT with co-registered white light and autofluorescence imaging, with a “confirm-then-capture” workflow designed for practical surgical use. To enable efficient analysis of sparsely sampled OCT volumes, we develop NerveDetNet, a lightweight 2.5D segmentation network that recovers weak and spatially displaced nerve signals by incorporating spatial context, frame-order information, and shift-tolerant correlations across frames through a dedicated nerve feature correlation module. In ex vivo tissue experiments, NerveDetNet consistently outperformed six representative 2D baselines across all frame spacings, achieving a Dice score of 0.725 under the sparsest sampling condition while using approximately half the model parameters. End-to-end validation demonstrated localization of nerves invisible at the surface and depth-resolved detection up to 1.3–1.4~mm below the tissue surface, with OCT derived depth maps overlaid directly onto the surgical view. Together, these results establish a practical label-free approach for subsurface nerve visualization that supports intraoperative compatibility, enables efficient sparse-volume analysis, and provides depth-resolved guidance without tissue opening, contrast agents, or nerve exposure.

We demonstrate intracavity terahertz (THz) generation via optical rectification in a 50-m-thick lithium niobate crystal placed inside a compact diode-pumped Kerr-lens mode-locked (KLM) Yb:CALGO bulk oscillator. The oscillator operates at a repetition rate of 85 MHz and delivers 83-fs pulses with up to 71 W of average intracavity power, obtained with only 21.4 W of low-cost multimode diode pump power. We generate single-cycle THz pulses with a spectrum extending up to 3 THz, detected by electro-optic sampling with 60 dB dynamic range within 156 s of measurement time (313 averaged traces) and up to 120 W of THz average power. This work combines the high damage threshold, power-handling capability, and cost-effectiveness of thin LN plates with simplicity, compactness, and low-cost multimode diode-pumped solid-state bulk lasers, offering an attractive alternative for high-repetition-rate THz time-domain spectroscopy systems.

A large-eddy simulation (LES) of a laminar separation bubble (LSB) induced by an adverse pressure gradient over a flat plate is performed at an inflow displacement-thickness-based Reynolds number of 410 and a free-stream Mach number of 0.25. With a mean peak reverse flow of 21.4%, the bubble sustains self-excited vortex shedding through a local region of absolute instability, in the absence of any external forcing. Spectral proper orthogonal decomposition (SPOD) applied to the LES data identifies three dominant coherent structures within the LSB: two-dimensional and oblique Kelvin–Helmholtz (KH) waves in the separated shear layer at the vortex-shedding frequency, and stationary spanwise-periodic streaks near reattachment at near-zero frequency. Classical resolvent analysis of the mean flow identifies strong convective amplification of the KH waves over a range of spanwise wavenumbers, but predicts only weak amplification in the low-frequency, streak-forming region, where the leading gain is orders of magnitude smaller and no dominant rank-one mechanism is present. This discrepancy with the SPOD energy indicates that the streaks are not sustained by same-frequency linear amplification, but are instead energized by the intrinsic forcing, which the classical framework treats as an unexplained input. Harmonic resolvent analysis of the time-periodic base flow reveals the underlying mechanism: the base-flow unsteadiness couples the oblique KH wave at the shedding frequency to the stationary streak through cross-frequency amplification, yielding a gain far larger than that of the direct same-frequency amplification. This cross-frequency route provides a likely explanation for how the stationary streaks observed near reattachment are energized.

Singlet fission, the conversion of one singlet exciton into two triplet excitons, has the potential to revolutionize solar energy production by boosting the efficiency of solar cells beyond the Shockley-Queisser limit. However, the practical realization of singlet fission remains an outstanding challenge, and its underlying mechanisms have long been debated. Here we show that singlet fission arises from a distinctive type of collective excitonic entanglement in which the excitons condense into a single particle-hole mode, the same principle that leads to the Bose-Einstein condensation of excitons. Quantitatively, this condensation appears as a large eigenvalue of the particle-hole reduced density matrix (RDM), representing multiple excitons occupying a collective mode. We utilize the particle-hole RDM to capture the intrinsic particle-hole correlations in singlet fission materials including acene crystals and covalently linked pentacene dimers, revealing how structural changes control singlet fission mechanisms and modulate the contributions of charge transfer states. The same characteristic enhancement of excitonic population in a single mode is common to the onset of exciton condensation and the mechanism of photosynthetic energy transfer. Together, our results establish a unifying framework for understanding the origins of singlet fission in terms of collective excitonic entanglement.

We present a pulse-shaper-based dispersion-scan (d-scan) framework for the combined generation and characterization of polarization-tailored femtosecond laser fields. By integrating a programmable $4f$ pulse shaper with polarization-resolved d-scan measurements, the framework enables the programmable synthesis and reconstruction of complex time-dependent polarization states. We demonstrate its capabilities for several classes of vector fields, including counter-rotating circularly polarized pulse pairs, oppositely chirped counter-rotating circularly polarized pulses, polarization-gate pulses, and multi-pulse sequences utilizing polynomial, periodic and discrete spectral phase functions. The reconstructed temporal electric fields and time-dependent ellipticities show excellent agreement with the simulated target fields and accurately reproduce the defining features of each pulse class. By combining the versatility of programmable pulse shaping with the robustness of the d-scan technique, this approach provides a flexible platform for the generation and validation of polarization-tailored ultrashort laser fields in ultrafast photonics and light-matter interaction studies.

Miniature probes extend optical coherence tomography (OCT) into lumens and other confined spaces, but conventional implementations often rely on multiple distal components, fiber processing, and probe-specific interferometer matching. Here, a fully fiber-integrated OCT (F2I-OCT) architecture is demonstrated in which two-photon microfabrication defines not only the terminal imaging optic, but the complete distal optical and interferometric architecture within a single fiber-mounted element. Beam expansion, side-view redirection, common-path reference generation, and terminal imaging are physically integrated while remaining independently designable. This architecture transfers complexity from component fabrication and interferometer matching into three-dimensional optical design, reducing assembly to a print-and-bond process and enabling plug-and-play exchange on the same OCT platform. Terminal optics can be adapted to different working distances, surrounding media, and wavefront transformations without redesigning the upstream architecture. Twenty assembled probes exhibit returned-reference and side-viewing-output power standard deviations of 0.149 dB and 0.071 dB, respectively. The system achieves 93.1 dB sensitivity and enables ex vivo imaging of airway and dental structures. The combination of a common plug-and-play architecture with broad optical design freedom provides a versatile platform for endoscopic and confined-space imaging across diverse biomedical and technical environments.