Papers

We propose a component-selective scheme for improving two-photon sources in a cavity-coupled two-atom system, where a single cavity mode interacts with two two-level atoms driven by phase-controlled classical fields of the same frequency. By controlling the atomic detunings and driving phase, the system can be tailored toward optimized cavity-field two-photon blockade or strongly correlated fluorescence photon-pair emission. When the two-cavity-photon component is enhanced, the cavity field exhibits optimized two-photon blockade with simultaneous suppression of unwanted one- and three-photon components at a comparable two-photon population. In another parameter regime, strongly correlated fluorescence photon pairs can also be generated from the two atoms by selecting the double-atomic-excitation component in the same two-excitation manifold. This approach provides a route toward high-quality and versatile two-photon sources, with potential applications in few-photon quantum optics and quantum information processing.

Detecting terrestrial exoplanets in the habitable zones of nearby stars remains a critical challenge. Such planets can be \(10^8\) to \(10^{10}\) times fainter than their host stars and lie at diffraction-limited angular separations, where starlight strongly obscures the companion signal. Here we present an adaptive quantum measurement method for estimating the number, positions, and brightnesses of mutually incoherent point sources in the sub-Rayleigh, ultra-high-contrast regime, operating at contrasts down to \(10^{-8}\) – five orders of magnitude beyond previous quantum imaging approaches to exoplanet detection. The method adopts a spatial-mode basis that is updated to maximize the quantum Fisher information per detected photon. Estimation is performed by maximum likelihood in log-brightness coordinates, and the source count is determined by Bayesian-information-criterion (BIC) model selection directly from photon-count statistics, without a tunable detection threshold. For point sources within sub-Rayleigh separations and with brightness ratios spanning eight orders of magnitude, the method reconstructs complete scenes with a mean success rate of \(72.5\%\). Furthermore, it is robust to misalignment, maintaining a \(71.3\%\) success rate under offsets of up to six pixels. These results demonstrate that terrestrial exoplanets can be detected below the Rayleigh limit, a regime previously inaccessible to direct imaging.

We consider the recently constructed Segal–Sugawara vectors for the orthosymplectic Lie superalgebras. We calculate their images with respect to the Harish-Chandra homomorphism and extend this calculation to the associated Sugawara operators and Casimir elements. We also produce higher Gaudin Hamiltonians and elements of the quantum shift-of-argument subalgebras in the orthosymplectic enveloping algebra. In the Appendix, we review analogous results for the general linear Lie superalgebras.

Understanding the cycling of interstellar medium (ISM) between the galactic plane and off-plane regions is crucial for tracing the evolution of disk galaxies. We present $^{12}$CO($J=1-0$) multi-pointing observations of the edge-on, Milky Way-like galaxy NGC 4565 obtained with the Nobeyama 45-m telescope, with an angular resolution of 14 arcsec, corresponding to about 0.8 kpc. Along a prominent dust filament, we detect significant CO emission at three off-plane positions above the galactic plane. After evaluating possible beam-pattern contamination, the detections remain robust. The derived per-beam molecular masses are $M_{\rm mol} \simeq (2.1-4.3) \times 10^7 M_\odot$. While the off-plane spectra show broader effective line widths, $\sigma_{\rm eff}=83-115$ km s$^{-1}$, than the disk spectra, they contain CO components consistent with the local disk rotation. The mean observed off-plane CO intensity fraction is about 0.34. Comparison with geometrically thin-disk models suggests that this large fraction is best explained by gas above the disk. The large $\sigma_{\rm eff}$ values are partly attributable to a high-velocity component with molecular gas mass $M_{\rm mol}^{\rm HV} \sim 10^7 M_\odot$ that is offset by about 100 km s$^{-1}$ from the local disk velocity. The kinetic energy of this component is estimated to be $E_{\rm kin} \sim 10^{54}$ erg. Such a large energy requirement is difficult to explain by disk-driven feedback in NGC 4565, which has a Milky Way-like star formation rate. External inflow is therefore one possibility.

Negative linear compressibility (NLC) is the counterintuitive phenomenon in which a crystallographic axis expands under hydrostatic pressure. A related phenomenon, zero linear compressibility (ZLC), occurs when an axis shows no length change under pressure. Both responses are rare and arise in materials with highly anisotropic mechanical properties. Motivated by recent reports of anomalous behavior in metal cyanides - including negative thermal expansion and NLC - we use first-principles calculations to investigate the potential of the MCN family (M = Ag, Au, Cu) to exhibit ZLC or NLC. Our simulations reveal three main findings. First, we predict the existence of previously unreported phases: the P6mm phase for AgCN and CuCN, and the R3m phase for AuCN. Second, all six members of the MCN family studied exhibit extreme elastic anisotropy, which indeed leads to ZLC or NLC in each case. Third, we identify a mechanism for these responses distinct from previously reported ones. The mechanism arises from the unique "bamboo forest" geometry of the material: weakly interacting rigid rods whose sparse packing allows pressure to be accommodated through changes in packing density rather than rod compression. This mechanism enables the anomalous response to persist over a wide pressure range, contrasting favorably with other materials that exhibit similar behavior. Our findings expand the relatively small family of materials known to exhibit ZLC or NLC and provide deeper insight into the microscopic origin of these unusual mechanical responses.

We present a variational framework in which (i) guiding-center kinetics, (ii) macroscopic force balance with gyrotropic pressure, and (iii) quasisymmetry (QS) appear as facets of a single structure. Starting from a guiding-center Vlasov–Maxwell action, constrained variations yields the guiding-center kinetic equation and Maxwell equations. Without phenomenological closure, momentum conservation yields $\mathbf J \times \mathbf{B}/c = \nabla \cdot \Pi$. This framework recovers the classical result that, for any equilibrium distribution built on the invariants of the reduced motion, the parallel projection of this balance holds identically, so that pressure anisotropy is a kinematic consequence of magnetic-moment conservation together with the variation of $B$ along field lines, rather than a modeling choice. We connect QS to an integrability condition expressed in coordinate-free form. We then derive an explicit expression for the current crossing the flux surfaces. Its flux-surface average vanishes identically in a QS field, but it vanishes pointwise only if $p_\parallel+p_\perp$ is a flux function. Combined with the parallel identity this forces $p_\parallel = p(\psi) + K(\psi)B^2$ and $p_\perp = p(\psi) - K(\psi)B^2$, consistent with the anisotropic equilibria obtained from a constrained Kruskal–Kulsrud functional, in which $(p_\parallel+p_\perp)/2$ is a flux function [Phys. Rev. E 104, 015213 (2021)]. The structure arises from the kinetic moments without a Lagrange multiplier. For such equilibria the parallel current in a QS field follows in closed form, with a single resonance at $\iota = N/M$ in place of the dense set of resonant obstructions of a generic three-dimensional field. Finally, QS is a Noether symmetry, so its breaking is measured by the non-conservation of the associated momentum. We construct a distribution-weighted residual and relate it to existing QS metrics.

We compare the apparent directions of rotation in the plane of the sky of active galactic nuclei (AGNs) and their host galaxies. The direction of rotation of the galaxy was inferred from the direction of the spiral arms, while the direction of rotation of the AGN was inferred from spectropolarimetry, where the change in relative polarization position angle (PA) across broad lines is believed to be caused by equatorial scattering. The numbers of co-rotating and counter-rotating AGNs are equal. Studies of the relative position angles of radio jets have implied that there is a "zone of avoidance" where jets avoid being in the plane of disk galaxies. We point out that bi-conical narrow-line-region outflows also avoid the plane of the host galaxy. The equal numbers of co-rotating and counter-rotating AGNs exclude the hypothesis that the "zone of avoidance" is due to a lack of large tilts of the black hole rotating axis relative to the host galaxy rotation axis. Our results imply that the relative orientations of spin axes are random, at least for the black hole mass range we consider. We propose that changes in the broad-line polarization PA with wavelength that do not closely follow the predictions of the simple equatorial scattering model are a consequence of the scattering dust being clumpy. We note a couple of cases of possible changes in PA over several years, which, if real, could be due to motions of the dust clumps or changing anisotropy of the continuum emission.

We investigate rotational properties and universal relations of slowly rotating Bose-Einstein condensate dark stars in the context of General Relativity, both at the mean-field level and when the leading beyond-mean-field Lee-Huang-Yang correction is retained self-consistently. Adopting the polytropic $n=1$ equation of state appropriate to a dilute, self-interacting Bose gas, parameterised by the boson mass $m$ and the $s$-wave scattering length $a_s$, we integrate the Tolman-Oppenheimer-Volkoff equations together with Hartle's dipole equation for the frame-dragging angular velocity, and we compute the moment of inertia, the gravito-electric tidal Love number and the dimensionless tidal deformability. The resulting equilibrium sequences yield gravitational masses in the $1$–$2\,M_{\odot}$ range with radii of $10$–$20\,\mathrm{km}$, squarely within the window presently probed by NICER and the LIGO-Virgo-KAGRA network. We observe that the LHY term produces a measurable reduction of the dimensionless moment of inertia at fixed compactness, whilst the I-$\Lambda$ universal relation is preserved to within a few per cent. We supply polynomial fits for the I-$\Lambda$ and I-$C$ relations, and show that the LHY footprint is large enough to serve as a clean diagnostic of beyond-mean-field quantum physics in a putative dark star population, complementing existing dark matter constraints from pulsar masses and from the equation-of-state interpretation of the unusually light compact remnant HESS~J1731-347.

By generating heavy-ion collision data with the ultrarelativistic quantum molecular dynamics (UrQMD) model, a multiphase transport (AMPT) model, and the JAM model, the impact parameter ($b$) in Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 4 and 11 GeV is reconstructed using supervised learning and unsupervised learning in machine learning (ML). In supervised learning, the performance of ML algorithm is cross-checked by using data obtained from these three transport models. It is found that the typical mean absolute error (MAE) which measures the average magnitude of the absolute difference between the true and predicted $b$ is between 0.2-0.4 fm, even when training ML algorithm with data generated from one model but testing with data from others. While the conventional method (i.e., a polynomial fit to multiplicity as a function of $b$) only works for data generated from the same model. In the classification task, the present ML-based method also shows significantly superior results compared to the traditional approach. In unsupervised learning, the K-means clustering algorithm is used to partition collision events directly from experimental-style observables, showing that the algorithm autonomously identifies six clusters corresponding to different centrality classes without relying on predefined model-based binning. Our study demonstrates the strong robustness of using an ML algorithm trained on transport-model data for impact-parameter determination, and indicates that this method has the potential to be generalized to handle real experimental data.

Ground-based seeing imprints size-dependent biases on galaxy structural parameters, yet the high-resolution space-based imaging needed to improve these measurements currently covers only a small fraction of the sky. We close this gap with a generative model that produces Euclid-like VIS predictions from DESI imaging of Bright Galaxy Survey (BGS) targets. Our predictions remain Fourier-correlated with Euclid VIS images down to 0.37”, compared with 1.41” and 1.00” for the DESI $r$- and $z$-band inputs, corresponding to improvements by factors of ${\sim}3.8$ and ${\sim}2.7$, respectively. Although this correlation does not extend down to 0.16”, the characteristic Euclid VIS PSF FWHM, structural measurements from these predictions already show reduced biases relative to the DESI $r$-band structure measurements: the Petrosian radius bias falls to +0.072” (from -0.845”), independent of galaxy size; the bias in the Sérsic effective radius ($R_{\rm e}$) drops to -0.018” (from -0.322”); and the Sérsic-index bias to +0.093 (from +0.262). We release these predictions over the Euclid DR1 footprint as the Euclid-like Predictions of BGS (E-BGS), which can be blindly validated once DR1 is public.

We study the atom-atom correlation length in an atomic array coupled to a waveguide under the Bragg condition with delayed non-Markovian interactions caused by a finite photon propagation time. Starting from a single excited atom, the excitation partially spreads among all atoms, reaching a steady state. The remaining excitation localizes near the initially excited atom, and the atom-atom correlation length decreases as a power law with the interaction delay. This localization phenomenon reveals how the delay-induced non-Markovian behavior affects the correlation transport in waveguide QED systems.

Fluid injection into the earth's crust can induce small and frequent earthquakes in the subsurface. Predicting their sizes and temporal occurrences via statistical analysis is crucial for safe operations in unconventional oil and gas recovery, enhanced geothermal systems, and geologic carbon storage. Here we show that a simple micromechanical model of slip avalanches in slowly deforming solids predicts the slip statistics observed over drastically different spatial scales, namely meter-scale microseismic observations and nanometer- to micrometer-scale nanoindentation experiments can be described with this model. Microseismic catalogs extracted from high-pressure fluid injection operations into geological basins with various lithologies and nanoindentation experiments on shale across a wide range of temperatures and mineral compositions yield statistics consistent with model predictions. This universality across materials, temperatures, and scales is consistent with the prediction that the slip statistics result from only a few basic properties. Previously debated deviations of the statistics in layered sedimentary formations are explained by finite-size and stress-integrative effects resulting from mechanically weak bedding planes. The slip statistics therefore provide important information about the structure and scales of the bedding planes. Conversely, the basin structure can also be used to predict the probability distribution for the sizes of triggered microseismic events.

Using a Green's-function formalism, we study the spin-resolved local spectral function of a resonant impurity coupled to a two-dimensional $d$% -wave altermagnetic substrate. It is found that the interplay between direct tunneling from the impurity to the scanning tunneling microscopy (STM) tip and altermagnet-mediated tunneling gives rise to a dual Fano resonance in the absence of an external magnetic field. Moreover, the anisotropic spin-dependent oscillations of the local density of states and the corresponding Fano factors provide information on the altermagnetic splitting strength from complementary local and global perspectives. In addition, spin-selective tunneling can be achieved by tuning the Fermi energy and the tip position. In the presence of a strong magnetic field with Landau-level quantization, the dominant scanning tunneling spectroscopy (STS) signature appears as a spin-dependent nodal structure in real space: the nodal mismatch between opposite spin channels produces a large local spin contrast. These results establish resonant-impurity STM/STS as a phase-sensitive local probe of altermagnetic band anisotropy.

Unsteady thin-airfoil theory (UTAT) coupled with discrete-vortex methods has been widely employed in reduced-order aerodynamic modeling. Due to the non-uniqueness of potential-flow solutions, the Kutta condition is imposed to determine the circulation around the airfoil. Although the unsteady Kutta condition is commonly associated with the zero-loading condition at the trailing edge, its implications for the continuity of the vortex-sheet strength remain comparatively underexplored. In particular, the classical series expansion employed for the bound vorticity in unsteady thin-airfoil theory is not uniformly convergent at the trailing edge, leading to mathematical inconsistencies in the vortex-sheet and pressure distributions. In this context, the present work seeks to advance the mathematical framework of unsteady thin-airfoil theory through a physically consistent formulation of the bound vortex-sheet strength for the Wagner problem. A recurrence relation is derived for the Wagner coefficients, allowing the construction of a uniformly convergent series expansion for the bound vorticity. The proposed formulation ensures continuity between the bound and wake vortex sheets while simultaneously recovering zero pressure loading at the trailing edge, thereby providing a mathematically consistent representation of the unsteady Kutta condition. To investigate the implications of the modified framework, a discrete-vortex method based on UTAT is developed and compared with the classical formulation. The results demonstrate that the proposed approach eliminates spurious oscillatory behavior near the trailing edge and significantly improves the regularity of the computed vorticity and pressure distributions.

We investigate the thermoelectric and magnetic properties of Si-substituted $n$-type and Ti-substituted $p$-type Heusler alloy Fe$_2$VAl using the bipolar random Anderson model, which has been introduced recently to study antisite-defect effects associated with the sign change of the Seebeck coefficient in thermally quenched Fe$_2$VAl. Based on the electronic states of both $n$-type and $p$-type compounds, with the rigid-band shift of the Fermi energy and a temperature-dependent scattering rate taken into account, we elucidate how antisite defects simultaneously influence thermoelectric transport and local magnetic moments. We find that the magnetic moments are enhanced in $n$-type Fe$_2$VAl, whereas they are suppressed in $p$-type Fe$_2$VAl compared with the undoped compound. These contrasting magnetic responses highlight the impact of antisite spin polarization on thermoelectric properties and demonstrate the crucial role of antisite defects in realizing magneto-thermoelectric functionalities in Heusler-type alloys.

Hollow-core fiber (HCF) is often presented as a modestly improved transmission medium that can be inserted into networks originally designed for solid-core silica. We argue instead that recent progress – most notably the reported attenuation below 0.1 dBkm$^{-1}$, together with a broad low-loss window, reduced propagation delay, and extremely low optical nonlinearity – makes it timely to reconsider which long-standing design conventions are fundamental to optical communication and which are specific to silica fiber. By reviewing implications at the physical-layer, transceiver, and network-architecture levels, we suggest that the most durable benefits of HCF may arise not from its use as a drop-in replacement, but from cross-layer co-design. We also outline the studies and experimental demonstrations needed to determine where such advantages are genuinely achievable.

It is well known that the quantum value of an XOR nonlocal game, where the winning condition depends only on the XOR of the two players' output bits, may be approximated in polynomial time. We study a variant of the XOR game model, which we call tilted XOR games, where the winning condition can additionally depend on only one of the output bits. We show that this dramatically increases the expressive power: the computational complexity of the problem of approximating the quantum value of tilted XOR games to constant precision is RE-complete. Also, our result extends to succinct versions of tilted XOR games, where the questions can be polynomial-length binary strings, generated by a polynomial-time verifier. For classical strategies, the distinction between XOR games and tilted XOR games is inconsequential. Håstad (J. ACM, 2001) shows that they are both NP-complete to approximate, by using a reduction from linear systems to XOR games. Our approach is to show that this is also quantum-sound, but as a reduction from linear system games to tilted XOR games. Since titled XOR games are a special case of binary games (where each party outputs a single bit), our result implies that binary games are RE-hard to approximate.

We study the error-correcting properties of pure-state holographic geometries, in which mixed boundary subregions are replaced, via the surface/state correspondence, by the Ryu–Takayanagi (RT) geodesic bounding their entanglement wedges. In AdS$_3$/CFT$_2$ we derive a cross-ratio threshold relation $\eta'/\eta = e^{\Delta H/2}$ for the connected/disconnected transition of the entanglement wedge when two holes are punched in such a geometry. The quantity $\Delta H$ is sourced entirely by geodesics ending on RT boundaries. It shifts the standard two-interval threshold $\eta = 1/2$, and we classify when its sign is fixed by the pattern of hole endpoints. Turning to code properties, we show that the recursive hole-punching underlying uberholography cannot start within an RT-boundary, while an untouched asymptotic boundary can still fractalize, and we find numerically that in the configurations we study it does so with the universal fractal dimension $\alpha \approx 0.786$. The resulting upper bounds on price and distance are nevertheless procedure dependent. In the configurations we study, punching holes on the asymptotic boundary while retaining the RT-boundary yields strictly tighter bounds than first tracing out the RT-boundary and then fractalizing.

Companies developing some of the world's most powerful artificial intelligence systems are surprisingly diligent in how they map out the risks their technologies present. Yet the risk landscape that lies between emerging frontier models and their economically successful and societally beneficial deployment is becoming increasingly hard to navigate. Complicating this further, many frontier AI companies maintain more than one account of what could go wrong with their technologies. This paper documents the divergence between these accounts by comparing safety and compliance documents published by Anthropic, OpenAI, Google DeepMind and Meta between 2023 and 2026, and considers what the resulting record reveals about how these companies select the risks they manage. As these documents are timestamped and archived, they provide a valuable public record of institutional risk selection in progress. From this record the paper identifies four filters that determine which risks tend to survive in self-authored frameworks (measurability, severity, auditability and competitive cost) and introduces the "safety differential" as the gap between the risk landscape a company selects for itself, and the one regulators select for it. While acute, quantifiable risks appear across documents, less tractable risks such as harmful manipulation are articulated fluently where law compels disclosure, yet remain absent from most self-chosen frameworks. This is an exclusion that follows from how these institutions define risk. Drawing on scholarship on institutional risk selection and the framework of risk innovation, the paper shows how redefining risk as a threat to value can help explain how risks become "orphan risks," how it indicates where future blindsides may occur, and how it points to lightweight tools for de-orphaning risks that frontier AI's safety apparatuses are not currently organized to address.

We consider observables $X$ whose realizations in a sampled dataset are restricted, for example by measurement resolution, to a finite set of distinguishable categories within their possibly infinite theoretical domain. Given the probabilities of observable categories, we study the coarse-grained probability mass of families of possible datasets generated through a forward sampling process. The combinatorial construction induces an intrinsically discrete $p$-value defined directly from the sampling process rather than through additional probabilistic structure on observables. Specifying the sample means of $d+k$ arbitrary functions $g_\alpha(X)$ defines a linear family of datasets whose probability mass is obtained as a weighted sum over integer lattice points contained within the associated polyhedron. To overcome the intractable large-$N$ combinatorics, we derive via saddle-point techniques a density approximating these probability masses in the continuum limit of forward sampling within the multinomial universality class. As a demonstration, we consider conditional sampling, where $d$ structural means are fixed while $k$ means vary over admissible datasets. The information geometry emerging from the saddle-point density, together with the spherical symmetry arising at large $N$ from the intrinsic $p$-value construction, enables efficient computation of the $p$-value in the Laplace approximation via the $\chi^2_k$ distribution. The resulting statistic is given by the semi-analytic expression $2N$ times the Kullback-Leibler divergence between the information projections associated with the corresponding structural and observed linear families. These projections can be computed efficiently via standard numerical routines converging for sufficiently well-behaved sample means.

Recently, Suetsugu $\textit{at al.}$ reported microscopic signatures of an imaginary charge density wave (iCDW) and TRSB in CsV$_3$Sb$_5$ at $T^* \approx 120$ K, attributing nuclear quadrupole resonance (NQR) linewidths and asymmetric Zeeman-perturbed NQR (Zp-NQR) lineshapes to chiral loop currents in [arXiv:2605.05101; https://doi.org/10.1038/s41567-026-03339-8]. In this Comment, we demonstrate that these observations are not evidence of exotic physics but are instead fully explained by crystalline mosaicity and pre-transitional CDW fluctuations. Through exact diagonalization of the full nuclear-spin Hamiltonian, we show that the observed asymmetric lineshapes arise naturally from an angular mosaic spread in the Zp-NQR regime, completely reproducing the data without the need for internal magnetic fields. Furthermore, we reveal that the reported emergent local field ($h_{\text{loc}}$) is an artifact resulting from unjustified and unreported fitting constraints, and the use of an approximate perturbative model. Strikingly, we point out that this local-field model required for the proposed iCDW produces features that are absent in the data. Addressing the recent Reply by Suetsugu $\textit{at al.}$ [arXiv:2608.24927v1], we show that these core issues remain unresolved: the linewidth follows a standard Curie-Weiss law with no phase transition at $T^*$, and their definition of mosaicity overlooks well-documented strain-mediated lattice distortions. Most critically, when the full Hamiltonian is solved exactly and the artificial fitting constraints are removed, the inferred loop-current signature vanishes ($h_{\text{loc}} \to 0$). We therefore conclude that the claim of an iCDW state in in Ref. [arXiv:2605.05101; https://doi.org/10.1038/s41567-026-03339-8] is unsupported by the data, arising instead from incomplete spectral simulations and inadequate theoretical modeling.

No single AI weather model excels at all variables, pressure levels, and lead times. Rather than building yet another architecture, we reframe the forecasting problem as one of coordination. Here we present Feitian Adaptive Ensemble Weather (FTAE-Weather), a lightweight framework that learns, through deep reinforcement learning, when and where to trust each member of an open pool of pretrained forecasters. A tactical Weight-Agent reads the current atmospheric state and assigns variable- and horizon-specific fusion weights, while a strategic Evolve-Agent periodically prunes underperforming models and absorbs newly released ones. Asynchronous prediction caching keeps training cost independent of the slowest constituent model. Adding fewer than 0.01 percent extra parameters, FTAE-Weather reduces RMSE by from 17.2 percent to 78.3 percent over the best individual model in 10 atmospheric variables and outperforms conventional ensemble baselines across lead times from 72 to 360 hours. The framework thus converts a growing, fragmented inventory of specialist models into a single prediction system that strengthens as the field of AI weather forecasting releases new architectures-turning model diversity from a coordination challenge into a compounding scientific advantage.

Control signals and kinematics in batoid swimming are difficult to measure experimentally, making body-fluid interaction models essential for studying their underlying locomotion principles. To address this challenge, we developed a body-fluid interaction model of batoid-type swimming that is appropriate for both neural control study and engineering design. The body trunk is modeled as a rigid body with six degrees of freedom. The flexible pectoral fins attached to the trunk are modeled by a tensegrity structure consisting of rigid struts and elastic cables that resembles a biological musculoskeletal system. The fin is actuated by changing the tension of elastic cables distributed across the fin surface, enabling controllable and realistic deformation. Utilizing an analytical fluid force model, the body-fluid interaction model is exercised through simulation examples that respectively investigate the speed difference between tension actuation and fin kinematic waves, the effects of fin stiffness and resonance exploitation on swimming performance, and the different fin kinematics resulting from different body inertial motions.

Weak magnetic fields influence a wide range of biological processes, yet the underlying mechanisms are poorly understood. The radical pair mechanism (RPM), which involves quantum spin dynamics, is a leading hypothesis. Here we show that weak magnetic fields modulate morphological pigmentation – specifically, the number of perioptic melanophores – in Xenopus laevis tadpoles in a field-strength-dependent manner. The response is light- and eye-dependent. The observed field-strength dependence is quantitatively consistent with a radical pair model. These properties are reminiscent of the light-dependent magnetoreception that is thought to operate in migratory birds, and establish amphibian pigmentation as a tractable vertebrate system for the study of radical-pair quantum biology.

Multilayer cloud detection from active–passive observation is vital for numerical weather prediction. In this study, channel selections derived from threshold-based algorithms are embedded as feature-engineering priors into a 1D-CNN, and machine learning (ML) is used to learn latent physical relationships to simplify physical retrievals for operational deployment. The results show that the 1D-CNN achieves a multilayer-cloud probability of detection ($\mathrm{POD}{\mathrm{mul}}$) of 0.620 and a false alarm rate ($\mathrm{FAR}{\mathrm{mul}}$) of 0.240, outperforming the conventional threshold algorithm ($\mathrm{POD}{\mathrm{mul}} = 0.558$, $\mathrm{FAR}{\mathrm{mul}} = 0.369$). These results demonstrate that prior physical knowledge derived from radiative transfer theory can serve as an effective feature-engineering prior. Further experiments show that ML-revealed physical mechanisms can also enhance traditional algorithms. Replacing AGRI channel 12 (C12, centered at $10.8~\mu\mathrm{m}$) with channel 13 (C13, centered at $12.0~\mu\mathrm{m}$) increased $\mathrm{POD}{\mathrm{mul}}$ from 0.558 to 0.609 without materially affecting $\mathrm{FAR}{\mathrm{mul}}$. However, for AHI, substituting the $11.2~\mu\mathrm{m}$ channel with the $12.3~\mu\mathrm{m}$ channel yielded negligible improvement. In addition to spectral response function (SRF) mismatches, a primary contributing factor is the channels' on-orbit radiometric stability. Hence, physics-informed machine-learning methods appear promising for advancing remote-sensing AI, while sensor-specific characteristics must be considered during operational transfer.

Modified black-hole entropies can induce effective spacetime geometries and thereby provide a thermodynamic route for investigating thin-shell wormholes. In this work, we construct symmetric cut-and-paste wormholes from the generic entropic lapse function $F_{\mathcal S}(r)=1-4\pi M/\mathcal S'(r)$ and formulate the Darmois–Israel junction conditions directly in terms of the lapse and of the entropy derivatives. We derive the surface stresses, shell energy-condition combinations, conservation equation, and radial effective potential, and then apply the formalism to the Bekenstein–Hawking, Barrow, Tsallis–Cirto, Rényi, Kaniadakis, logarithmic, loop-quantum-gravity-inspired, and exponential entropy prescriptions. The analysis shows that the symmetric construction requires negative surface energy density throughout every admissible positive-lapse domain, although entropy deformations can significantly modify the horizon structure, the allowed throat region, and the localization of the surface stresses. Within the parameter domains considered here, all examined constant-barotropic branches are linearly radially unstable, despite quantitative changes in their near-horizon scales. In contrast, a variable Chaplygin shell can support stable configurations, with the stability domains determined jointly by the entropic geometry, the throat radius, and the radial exponent of the shell equation of state. These results establish a unified framework for comparing entropy-induced black-hole geometries as thin-shell wormhole seeds and show that stability is governed not by the entropy deformation alone, but by its interplay with the dynamical response of the matter localized at the throat.

Speculative window decoders hide quantum error-correction decoder latency by guessing the cross-boundary decisions that link adjacent decoding windows, running downstream work on the guess, and verifying lazily. SWIPER and ARTERY each build one predictor, about 90% accurate; neither built the verifier side. We build it on a reconstructed SWIPER harness (Stim rotated surface code, minimum-weight matching). A predictor-only bracket shows the cross-boundary decision is local, the achievable accuracy reaching about 0.999 within three rounds, with small, diffuse headroom over SWIPER. We establish a worst-case temporal blast-radius bound, its probability core machine-checked in Lean4 and conditional on a modeling reduction we then test: a misprediction's effect decays exponentially in the commit width, so the radius is one and speculation adds no error floor. We falsify that reduction shot by shot and find the real mechanism, clearest at near-threshold noise, is a global minimum-weight re-pairing. A compiler pass derives SWIPER's restart policy from these numbers; a runtime executor confirms on the harness that the loop recovers exactly and removes the serial commit-chain stall up to a small penalty. A second decoder (union-find) settles which results are decoder-agnostic: the predict-verify-recover wrapper and the structural phenomenology, while the absolute magnitudes and the min-weight mechanism are matching-specific.

Nonlocal quantum field theories achieve perturbative ultraviolet finiteness by inserting gauge- and diffeomorphism-covariant entire-function regulators into all kinetic terms. These operators can be viewed as nonlocal smearing maps acting on sources in the Einstein equations. In this paper I show that, when the same entire-function regulator responsible for UV-finite loops is applied to the energy-momentum tensor of a point mass, the resulting static, spherically symmetric solution develops a regular de~Sitter core in place of a curvature singularity.

The bibliography of scientific papers lists items with variable degree of relevance for the contents of the paper itself. If we could identify the sources, i.e., the works that actually inspired the paper, their citations can help us uncover the genesis of scientific projects and would be more representative of the actual importance of papers and authors than the standard citation counts, when all references are considered. Here we present an analysis of the backbone of science, i.e., the network of citations between papers and their sources. The latter are extracted from the full body of papers via Large Language Models (LLMs), which are currently very capable of correctly identifying the context in which a paper is cited. Using two different but related prompts, we find that the LLMs select only a small set of references, not taken at random, and that the resulting backbone networks are quite similar to each other with respect to their in-degree distributions, modularity, transitivity, and degree correlations. Backbone networks have higher heterogeneity in their in-degree distributions, compared to the full network, but the most cited papers are usually the same, with some important exceptions. Citation rankings among authors are also remarkably stable. We conclude that the full citation network, despite its redundancy with respect to the backbones, presents a reliable picture of the relative citation impact of papers and authors.

Highly successful drugs, such as transition-state inhibitors, were designed by mimicking the precise geometry of enzymatic transition states, a strategy that requires quantum chemistry accurate enough to specify molecular structure at sub-Å\ resolution. A central challenge during such a quantum chemistry simulation is that classical single-reference method can deviate substantially from the exact energy at strongly correlated transition states. We study the breakdown due to multireference character by studying a model system with a multireference transition state. In this work we present a proprietary PexMachina solver which reproduces the exact ground-state energy throughout the transition state scan, while single-reference methods struggle for certain geometries to achieve chemical accuracy.