Wilson coefficients in dimension-six effective field theory are constrained in a combined fit to several ATLAS measurements. These inputs probe Higgs-boson processes across multiple production and decay modes, di-Higgs signatures in the $b\bar{b}\gamma\gamma$ and $b\bar{b}\tau\tau$ final states, $WW$ and $WZ$ diboson signatures, electroweak $Zjj$ final states, high-mass Drell-Yan interactions, and $t \bar t$ events in both resolved and boosted topologies. Precision electroweak observables from LEP, SLD, and ATLAS are also included. A total of 48 parameters, including individual Wilson coefficients in the Warsaw basis and linear combinations of Wilson coefficients, are constrained simultaneously. Constraints on two-Higgs-doublet models and heavy-vector-boson models are also obtained by matching a relevant sub-set of the results with their parameters. This combined fit provides the most comprehensive effective field theory interpretation of experimental data by the ATLAS Collaboration to date. No significant deviations from the Standard Model are observed.

The NISQ era places stringent constraints on quantum computation, where noise and decoherence fundamentally limit performance. In classical deep learning, model robustness and resilience to perturbations are well studied: deep neural networks (DNNs) maintain high performance despite pruning, noise injection, and structural perturbations due to inherent redundancy in their representations. A central challenge in quantum machine learning is to transfer this notion of robustness to quantum neural networks (QNNs) under realistic NISQ noise. While classical deep learning exhibits robustness through structural redundancy, analogous principles for QNNs remain underdeveloped. We propose JGRA: a framework for assessing robustness in noise-aware QNNs via Jacobian geometry, capturing model sensitivity to parameter perturbations induced by noise. Our method includes entropy-matched noise calibration, noise-aware training, and noise-conditioned Jacobian extraction, yielding geometric descriptors that link clean-regime structure to noisy inference behaviour. We also empirically demonstrate that these descriptors encode predictive information about robustness under unseen noise.

Data-driven modeling shows significant promise for faster-than-real-time forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must contend with limited, imperfect, and incomplete experimental measurements. In this work, we present an analysis of data-driven surrogate models trained to forecast the time-evolution of experimentally measured cylinder wakes in the subcritical vortex shedding regime. Using a dataset of two-dimensional, two-component particle image velocimetry measurements, we train fully convolutional neural networks, U-Nets, Fourier neural operators, and dynamic mode decomposition-based models to forecast the development of experimentally measured velocity fields. To characterize data-driven approaches contending with transient flow features and limited, imperfect observations, the development of predictions over extended forecast horizons is examined at a fixed Reynolds number (Re = 590). Next, models are trained at a range of Reynolds numbers (Re = 230 to Re = 2920) to investigate the impact of increasingly turbulent and three-dimensional flow phenomena, and the challenges associated with measuring them, on forecast quality. We find that experimentally trained surrogate models can provide meaningful predictions over short time horizons, propagate low-frequency dynamics over longer forecast periods, and achieve faster-than-real-time evaluation. However, the data-driven models struggle to preserve transient flow features and high-frequency energy content when faced with noisy measurements and incomplete state observations. This emphasizes the underlying challenges that remain for data-driven modeling approaches to effectively contend with fluid dynamics in real-world engineering applications, where observations are often imperfect and limited.

A systematic comparison between VMEC and HINT equilibrium calculations has been carried out for Large Helical Device plasmas to clarify the influence of the assumption of the nested flux surfaces at finite beta. Three vacuum magnetic-axis configurations, $R_{\rm axV} = \SI{3.53}{\, m}$, $\SI{3.60}{\, m}$, $\SI{3.85}{\, m}$, are examined for the beta values on the axis in the range $\beta_0 \in [0.0\%, 5.0\%]$. The magnetic-axis position, the rotational transform on the axis, and the plasma volume enclosed by the last closed flux surface are compared between the two codes. At low-$\beta_0$, VMEC and HINT give consistent equilibria, indicating that the nested flux surfaces are largely preserved. Above a configuration-dependent critical $\beta_0$, however, the two solutions begin to diverge, indicating that the nested flux surfaces assumption is compromised. In HINT, the enclosed plasma volume decreases at higher beta because the stochastic magnetic field evolves near the plasma edge, whereas VMEC cannot represent this flux surface breaking due to its assumption of nested flux surfaces. These results show that the 3D equilibrium responses in LHD equilibria become increasingly important from inward- to outward-shifted configurations, mainly through Pfirsch-Schlüter current-driven perturbations of the magnetic field and the resulting edge stochasticity.

In this work, we investigate the use of a quantum circuit as a binary classification model in the context of quantum machine learning. We call this model, binary quantum classifier. First, we describe fundamental concepts of quantum computing and introduce the computational tool used: Qibo, an open-source framework for efficient quantum simulations and quantum hardware control. Then, we describe how to design a binary quantum classifier for the classification of images and small arrays of variables by showing how to input data in the circuit, defining a quantum circuit model Ansatz with trainable parameters and a loss function, and implementing multiple minimizers. We test our quantum classifier with two data sets. The first one is the MNIST data set which is composed of handwritten digits (reduced to only handwritten zeros and handwritten ones for binary classification). We study the behavior of different minimizers by increasing the number of layers of the Ansatz. The second data set represents two different high energy collisions that can occur at colliders such as LHC (CERN). Due to in-time proton-proton interactions known as pile-up, we distinguish two different data sets: "without pile-up" and "with pile-up". These collisions can be represented by images of size 32x32 or by six high-level variables that we call features. By increasing the size of the training data set and the number of layers of the Ansatz, we search for the best minimizer. Splitting the data set in training set and test set, we compute: ROC curve, AUC score, confusion matrices and test set accuracy. For "with pile-up" images, we compare the results obtained with the quantum classifier with a small convolutional neural network. We conclude that is possible to build a binary quantum classifier with a quantum circuit and we highlight its performances and limitations in comparison with classical technologies.

Observations of (giant) planets accreting material within their natal environment are crucial to constrain models for their formation. WRAY 15-1880 (aka RX J1842.9-3532) in the Corona Australis (CrA) complex has a prominent pre-transitional disk, and an age of ~2.8+-0.7 Myr, computed by comparison with isochrones using the accurate dynamical mass derived from disk kinematics. Hence, this star is in the late phases of disk evolution and might host accreting planets. We acquire new polarimetric imaging data with VLT-SPHERE and analyze archive observations taken with VLT-SPHERE, VLT-MUSE, and ALMA, finding a candidate Jupiter-like companion within the disk gap from high-contrast imaging. The mass estimates of the candidate companion, derived from various methods, are consistent with an object in the range of 0.3-7.6 MJup. The spectrum of the candidate companion is consistent with a T3 spectral type, in agreement with expectations of an object of a few Jupiter masses. We find an emission blob North-West of the star in the ALMA data rotating solidly with the candidate companion, that can be interpreted as a vortex/dust trap at the m=1 Lindblad resonance of the planet. Accretion on the candidate planet is not detected from the VLT-MUSE archival data. This may be due to insufficient contrast, an observational geometry that is unfavorable for viewing the planet's surface, or it could indicate that we are merely observing irregularities within the disk. Finally, we identify a microjet extending from the star perpendicular to the disk in these data.

We present a broadband spectral analysis of the neutron star LMXB GRS 1747-312 using $\sim$ 40 ks AstroSat data. The source was observed during the decay phase of the 2017 outburst, with an absorbed 1.0-5.5 keV flux of 1.67$^{+0.04}_{-0.07}\times$10$^{-11}$ erg s$^{-1}$ cm$^{-2}$, corresponding to a luminosity of $\sim$(0.9-1.80)$\times$10$^{35}$ erg s$^{-1}$. The continuum is modeled with thermal Comptonization of blackbody emission and interstellar absorption. A mildly broad iron line at $\sim$6.4 keV is fitted with a disc reflection component. Narrow lines below 2 keV are described by a hot plasma using the XSPEC model APEC. Additionally, there is a potential detection of an emission line at 4.19$^{+0.12}_{-0.10}$ keV with width $\sigma$ = 0.2 $\pm$ 0.2 keV and line flux of 13$^{+10}_{-9}\times$10$^{-5}$ erg s$^{-1}$ cm$^{-2}$. Examination of several short-duration ($\sim$ few kiloseconds) Swift observations at a few times the AstroSat source flux provided upper limits to the line flux of $<$30$\times$10$^{-5}$ erg s$^{-1}$ cm$^{-2}$. The 4.2 keV line likely originates from reflection off the neutron star surface. Shifting the neutral Fe K$_\alpha$ line from its rest energy of 6.4 keV to 4.2 keV requires a redshift of z $\sim$ 0.6, consistent with that expected from the surface of a non-spinning 1.4 M$_\odot$, 10 km radius neutron star. If confirmed, this feature provides a potential direct measurement of gravitational redshift, allowing us to place strong constraints on the neutron star's mass-to-radius ratio and gain valuable insights into the equation of state (EOS) of dense matter.

JWST discoveries of the earliest ($z \gtrsim 9$) supermassive black holes (BHs, $M_\bullet \gtrsim 10^6\,\rm{M}_\odot$) challenge the BH seeding and accretion models of most cosmological simulations. In this work, we compare early BH growth arising from three different accretion prescriptions characterized by distinct scalings between the accretion rate ($\dot{M}_{\rm \bullet}$) and the BH mass ($M_{\rm \bullet}$): the commonly used Bondi-Hoyle model ($\dot{M}_{\rm \bullet}\propto M_{\rm \bullet}^2$), and two free-fall models with shallower scalings ($\dot{M}_{\rm \bullet}\propto M_{\rm \bullet}^{1/2}$ and $M_{\rm \bullet}$). Bondi accretion tends to produce stronger runaway growth than the free-fall models when using heavy ($\sim10^5\,\rm{M}_\odot$) seeds in extreme environments owing to the steeper $M_\bullet$ scaling, but its sensitivity to the local gas sound speed makes it more susceptible to suppression from temperature increases due to AGN and stellar feedback. The free-fall models tend to produce stronger growth for lower-mass seeds ($\sim10^{3-4}\,\rm{M}_\odot$) in moderate environments as they are less dependent on the BH's mass to accrete effectively, however in this regime BH growth remains negligible for all accretion models in the presence of fiducial stellar feedback. Enhancing early BH growth via many BH-BH mergers disproportionately enhances subsequent accretion-driven growth for Bondi due to the steeper $M_{\rm \bullet}$ dependence. Our simulations can thus assemble BHs with masses of $\sim10^6-10^7~M_{\odot}$ at $z\gtrsim9$, as inferred by JWST, under two circumstances: 1) abundant heavy-seed formation that drives BH-BH mergers, or 2) Bondi accretion with weak feedback.

Immersed boundary methods (IBMs) are widely used to simulate flows around complex geometries and moving bodies, but they often involve a trade-off between precision and computational efficiency. Eulerian formulations require special treatments for moving walls and may generate spurious force oscillations, whereas Lagrangian formulations can suffer from slip errors at the immersed surfaces. We propose a novel sharp-interface IBM for incompressible flows involving moving, deformable, and arbitrary-thickness bodies. The method combines a fast tagging algorithm, a two-sided Eulerian forcing strategy, and a consistent mass correction that reduces the splitting error of fractional-step schemes, while preserving the structure of the discrete Laplacian operator. This formulation retains the efficiency of direct Poisson solvers, thus avoiding the overhead of cut-cell, multigrid, and projection-based approaches. The method naturally handles moving boundaries, and yields small transpiration errors with second-order accuracy in the enforcement of the no-slip condition. Numerical tests using rigid, deformable, turbulent, and biologically inspired flows demonstrate the accuracy, robustness, and efficiency of the method, without compromising computational cost.

We study feed-forward ReLU networks with fixed readout and quadratic loss. The aim is to rewrite gradient descent not primarily as a dynamics in weight space, but as a collective dynamics closed in terms of fields defined on the training-set space. For a single hidden layer, the weight variables can be eliminated from the activation dynamics, yielding a closed equation for the residuals governed by a collective kernel that factorizes into an input-geometric matrix and a dynamical co-activation matrix. For deeper networks, the residual dynamics retains a clean layer-wise kernel structure. However, from depth three onward, closure requires a hierarchy of weight-induced Gram operators that mediate information transport across layers. Moreover, the conjugate-field dynamics is governed by operators satisfying a backward pullback recursion, of which the weight-induced Gram operators are the first nontrivial instances.

We present an $\textit{ab initio}$ framework for predicting resonant inelastic X-ray scattering (RIXS) in optically pumped materials. Our methodology is based on the Kramers-Heisenberg formula for the double-differential cross section formulated using the results of the Bethe-Salpeter equation (BSE) from many-body perturbation theory. To extend this approach to the time domain, we incorporate non-equilibrium charge-carrier distributions obtained from real-time, time-dependent density-functional theory (RT-TDDFT). Generalizing the RIXS implementation with respect to arbitrary polarizations, allows us to consider different orientations of incoming and outgoing light. We demonstrate our method's capabilities by studying RIXS at the K-edge of graphite for various non-equilibrium charge-carrier distributions, representing different delay times after optical pumping. Our results reveal angular dependencies in $\pi$- and $\sigma$-orbital-derived spectral regions, in good agreement with experiment.

Inspired by the $P$-wave molecular interpretation of the recently observed vector state $G(3900)$, we analyze the production of its possible pseudoscalar partner, denoted here as $G_0(3900)$, via the radiative decay $Y(4230) \to \gamma G_0(3900)$. The $G_0(3900)$ is interpreted as a $P$-wave molecular state with quantum numbers $J^{PC}=0^{-+}$, dominated by the $D\bar{D}^{\ast}/\bar{D}D^{\ast}$ components. Although not yet experimentally established, such a structure is expected to appear near the $D\bar{D}^*$ threshold and to exhibit characteristic production patterns. The decay is assumed to proceed through a triangle mechanism. Depending on the model parameters and the binding energy of $G_0(3900)$, the resulting branching fraction lies in the range $\mathcal{B}(Y(4230) \to \gamma G_0(3900)) = 3.8 \times 10^{-5} - 3.3 \times 10^{-4}$. Our results offer a pathway to search for signatures of $G_0(3900)$ in radiative channels and also provide a test of the consistency of loop-mediated radiative decays with a molecular description of the $Y(4230)$.

Resonant $Z$-boson production is a cornerstone of precision electroweak physics, with its vacuum line shape set by the $Z$ mass, width, and collision kinematics. We show that a strong laser field can significantly alter this picture. By treating the field nonperturbatively, we find that laser dressing of the incoming fermions alters the effective collision kinematics and opens laser-photon exchange channels, including multiphoton processes, in $e^{+}e^{-}$ collisions. As a result, the $Z$-resonance profile develops distinct intensity-dependent regimes, evolving from the vacuum limit to saturation at intermediate field strengths and to an approximately quadratic enhancement at higher intensities. Additionally, the polarization composition of the produced $Z$ bosons is redistributed. In particular, at high intensities the laser-induced contribution can compensate the intrinsic chiral asymmetry of the electroweak interaction, leading to nearly parity-balanced $Z$-boson production. Our results identify that strong classical fields can dynamically control electroweak resonance phenomena, opening a bridge between strong-field QED and high-energy collider physics.

We analyze five-neighbor particle cellular automata whose conventional two-dimensional fundamental diagrams are multivalued, but whose mean flow is uniquely determined by introducing a second density. We first consider binary rules for which the second density is conserved, and then examine rules for which the second density is not conserved but converges asymptotically. These examples give three-dimensional fundamental diagrams in which the mean flow is determined by the particle density and the second density. We then investigate whether this single-valued structure is preserved under real-valued max-plus extensions. There are some rules where two different max-plus extensions are introduced, and numerical simulations show that both extensions preserve the same single-valued three-dimensional fundamental diagram. These observations imply that, in constructing real-valued max-plus extensions, it is important to choose the flux function and the second density consistently.

We address two mass-dependent properties among early-type galaxies (ETGs): (1) abundance ratios [N/Fe] and [Na/Fe], and (2) the centrally concentrated "UV upturn" at far-UV (FUV) wavelengths, which is likely produced by extreme horizontal branch stars with supersolar helium abundances. Using new HST/WFC3 observations of one FUV-weak and one FUV-bright ETG, we probe the "MP scenario" by Goudfrooij who posited that the UV upturn and the mass-dependent abundance variations of N and Na within and among ETGs are physically connected and produced by dissolution of metal-rich globular clusters, which represent the only galactic environment where mass-dependent enrichment of He, N, and Na is known to occur (i.e., second-generation stars of the "multiple stellar populations" (MPs) phenomenon). We show that passbands F275W and F390W are uniquely sensitive to correlated changes in $Y$ and [N/Fe] in integrated-light photometry when combined with archival data in F475W and F850LP. While F475W-F850LP is found to decrease with increasing radius in both galaxies, consistent with known metallicity gradients, F275W-F390W increases with increasing radius, as expected if the UV upturn is caused by second-generation stars with supersolar $Y$ and [N/Fe]. Furthermore, the radial gradient in F275W-F390W and the implied fractions of He- and N-enhanced stars are found to be significantly larger in the FUV-bright ETG than in the FUV-weak one, consistent with the predictions of the MP scenario.

We study inner products and partial amplitudes of graph states--a commonly employed class of quantum states, which are specified by graphs. We find that the magnitudes of these quantities are simply related to the rank of the adjacency matrix of the graph over F_2 while the phase is determined by the Arf invariant of its quadratic refinement. These facts motivate a nonlocal tensor factorization of the Hilbert space, with respect to which all graph states are products of Bell pairs with unentangled ancillae. These results may illuminate the quantum advantage in the framework of Measurement-Based Quantum Computation and suggest that graph states can be usefully visualized in the language of algebraic topology. In addition, we develop a specialized technique for computing expectation values of qubit-wise permutations in graph states, which is useful for calculating multi-invariants.

Machine-learned interatomic potentials (MLIPs) have had a profound impact on molecular modelling in recent years, promising to resolve the long-standing tension between the scale and accuracy of simulations. There has been a proliferation of new models and designs, and recently the paradigm of ``foundational'' MLIPs has become prevalent. Broadly speaking, foundation models are trained on large diverse datasets and promise to work well for new systems with minimal updates required. However, in such a new and fast moving field, there are many unanswered questions. In this article, we set out to articulate and explore what we see as the most important among these questions. We start by developing a working definition for foundational MLIPs and use this definition to frame the subsequent open questions. Despite the rapid progress in the field of MLIP models, we believe that these are fundamental questions which will continue to define cutting edge research in MLIPs in the years to come.

We study a one-dimensional long-range Su-Schrieffer-Heeger model with third-nearest-neighbor hopping and subject to quasiperiodic disorder. In the clean limit, the model hosts phases characterized by winding numbers $W=-1,0,1$ and $2$. The introduction of quasiperiodic disorder profoundly modifies the phase diagram and induces a series of topological phase transitions. Owing to the competition between topological dimerization and localization, topological Anderson insulating (TAI) phases with different winding numbers emerge and can persist even when the spectral gap becomes nearly closed in the strong-disorder regime. In addition, we uncover multiple reentrant topological phase transitions induced by varying either the quasiperiodic disorder strength or the hopping amplitudes. Remarkably, the system exhibits staircase-like topological Anderson transitions, where the real-space winding number evolves through successive quantized steps with increasing disorder strength. Our results demonstrate that the interplay between long-range hopping and quasiperiodic disorder generates a rich landscape of disorder-induced topological phases and reentrant topological transition phenomena.

We present a rigorous theoretical framework for symmetry breaking and quantum irreversibility arising from stochastic Ito field reversal within a cubic-quintic nonlinear Schrodinger equation (CQ-NLSE) formalism. Starting from three physically motivated considerations, forward and backward nonlinear stochastic differential equations are derived via the Ito calculus. Kinematic time-reversal is shown to be fundamentally incompatible with the Ito stochastic structure, yielding the universal asymmetry-coupling parameter of 2/3. An energy-driven collapse operator proportional to the product of noise strength, local probability density, and excitation energy squared is introduced, amplifying the collapse in high-density, high-excitation regions. Exactly bright soliton solutions are obtained for a quasi-one-dimensional BEC of attractive Li-7 atoms, with forward and backward amplitude ratio of 1.870. Heat map analysis of the parameter planes reveals that the forward collapse operator grows monotonically in time while the backward counterpart decays, achieving a ratio approximately 1030, sharply distinguishing this framework from conventional symmetric collapse models.

Galaxy rotation curves exhibit systematic discrepancies between the observed dynamics and the gravitational contribution expected from baryonic matter. Identifying empirical regularities in these discrepancies may provide insight into the organization of galaxy dynamics. We investigate whether the residual component of galaxy rotation curves contains a common structure across galaxies spanning a broad range of masses and morphologies. Using rotation-curve data from the SPARC and LITTLE THINGS surveys, we analyze residual velocity-squared profiles after accounting for the baryonic contribution and allowing for uncertainties in the baryonic normalization. We find that the residuals are not randomly distributed but instead follow a common linear pattern across a diverse galaxy population. Population-level analysis shows that the data preferentially select this linear residual structure over alternative radial dependences. The residual component separates into a mass-coupled contribution and a second contribution that remains nearly independent of galaxy mass. These empirical trends are observed across both spiral and dwarf galaxy samples. The existence of a common residual structure across galaxies spanning a broad range of masses and morphologies provides a new empirical constraint on theories of galaxy dynamics.

In this work, we adapt and apply techniques from machine learning to the exploration of physics beyond the Standard Model in the leptonic sector. Namely, we employ initialization and optimization, as they are applied in machine learning, to minimize a loss function that describes textures or conditions which we want in the neutrino mass matrix. The model free parameters are explored during the optimization, and after training for a number of optimization steps, we obtain matrices that approximately follow the desired forms, as well as their corresponding optimized parameters. We also discuss extensions and additional applications of the ideas presented here in conjunction with other methods based on artificial intelligence.

We study a class of Sturm--Liouville problems of the form $$ -(p\,y')' + q\,y = \lambda\, p\, y, $$ on a finite interval with complex-valued coefficients, where $p$ is piecewise smooth and $q$ is bounded. We prove that all eigenvalues in the open left half-plane are contained in a bounded set, which implies that only finitely many eigenvalues lie in this region. A canonical instance of this class arises in transverse-magnetic (TM) diffraction by metallic lamellar gratings, a benchmark problem in computational photonics that has been central to the development of Fourier modal methods. These methods exhibit long-standing convergence difficulties in this setting, associated with the loss of definiteness of the underlying operator and the emergence of spurious modes. Our result yields a rigorous criterion for identifying such non-physical modes in low-loss metallic gratings. Numerical examples illustrate the practical utility of the criterion.

Machine-learning interatomic potentials now approach quantum-mechanical accuracy on standard benchmarks, but the training cost of the most expressive equivariant architectures has become a serious bottleneck. We introduce DPA4, an SE(3)-equivariant interatomic-potential architecture with an EMFA (Edge-conditioned, Multi-Focus, Attention) SO(2)-equivariant convolution that combines a low-rank edge-node SO(2)-equivariant product, a multi-focus design for message nonlinearity, and envelope-gated attention for message aggregation. A Lebedev-grid projection further preserves SO(3)-equivariance in the nonlinearity to machine precision. A compiler-friendly conservative energy-gradient training path provides up to $\sim$3 times wall-clock speedup under torch compile. On the compliant Matbench Discovery benchmark, DPA4-Pro attains the best Combined Performance Score (CPS) on the leaderboard, while the 2.76M-parameter DPA4-Air exceeds the accuracy of the 30.1M-parameter eSEN-30M-MP baseline with 10.9$\times$ fewer parameters and 42.9$\times$ less training compute. On SPICE-MACE-OFF, the 5.4M-parameter DPA4-Plus lowers the aggregate molecular energy and force errors of the 6.5M-parameter eSEN baseline by 29% and 30%, while the 2.7M-parameter DPA4-Air still surpasses that baseline with $\sim$2.4$\times$ fewer parameters. Together these results place DPA4 on a new accuracy-cost Pareto frontier on Matbench Discovery and position it as a strong candidate backbone for future multi-task large atomistic model (LAM) pretraining.

The ability to engineer and control quantum states of many-body systems is a central challenge in quantum information science. For a register of $N$ qubits, the full Hilbert space dimension grows exponentially as $2^N$, rendering generic state preparation and control infeasible without exploiting structure or symmetry. A particularly important and physically motivated restriction is to the fully symmetric subspace, spanned by the Dicke states, which are simultaneous eigenstates of collective spin $J=N/2$. Ensembles of Rydberg atoms interacting via electric dipoles in two-dimensional tweezer arrays form a promising platform for achieving such control. However, the finite range of dipole-dipole interactions poses a challenge to generating and controlling the Dicke manifold because the Hamiltonian incurs leakage from the computational subspace. To counteract this leakage, we perform quantum optimal control algorithms on a truncated Hilbert space according to our newly developed method of ``irrep distillation'' (IRD), which captures the process by which the symmetric subspace couples to leakage error-spaces, using only linear-scaling Hilbert dimension. We implement gradient ascent pulse engineering (GrAPE) on control schemes with little or no local addressing, to generate resourceful states like Greenberger-Horne-Zeilinger, Dicke, and extremal quantum states. We benchmark each scheme of IRD-GrAPE for its quantum speed limit (QSL), as well as exactly testing pulse fidelities on small system sizes and predicting fidelities using higher-order IRD on larger systems.

We report that the biaxial birefringence of $\alpha$-MoO$_3$ can activate two spectrally distinct quasi-bound states in the continuum (quasi-BICs) within a single symmetric TiO$_2$ nanobar-pair metasurface, with each resonance governed by a different crystallographic axis pair of the van der Waals crystal. With a full 60\,nm $\alpha$-MoO$_3$ gap fill, a TE resonance at 883.9\,nm ($Q=92$, Fano $q=0.090$) and a TM resonance at 923.2\,nm ($Q=31$, Fano $q=0.393$) are obtained. The Q ratio follows the inverse-square permittivity contrast, $Q\propto(\Delta\varepsilon)^{-2}$, calibrated across both polarization channels. Oblique-incidence sweeps show that the TE channel acts as a dual-null spatial highpass filter with a broadband stopband ($|H|<0.13$ for $|k_x|\leq0.63\,\mu$m$^{-1}$, $T_\mathrm{bg}=0.962$), while the TM channel transfers as $|H|\propto|k_x|$ ($R^2=0.94$), consistent with first-order spatial differentiation. Both operations are verified on a USAF~1951 resolution chart processed in a simulated 4$f$ framework. Channel selection is purely by input polarization angle with no structural modification.

We investigate collective excitations in flat-band superfluids by incorporating the coupled dynamics of pairing (phase and amplitude) and density fluctuations. We demonstrate that for any time-reversal symmetric superfluid system with an isolated flat band, only a single low-energy collective mode emerges in the long-wavelength limit. In contrast to the linearly dispersive Goldstone mode in conventional superfluids, this hybridized mode is gapless at zero momentum but exhibits a quadratic dispersion ($\omega \propto q^2$) at small momenta. We show that the dispersion coefficients of this collective mode are governed by the normal-state quantum metric of the flat band. These analytical predictions are in excellent agreement with numerical calculations. Our results are applicable to any generic $s$-wave flat-band superfluid, provided the flat band is energetically well separated from other dispersive bands.

The $\tau$ anomalous magnetic dipole moment (MDM) $a_\tau = (g-2)_\tau/2$ and electric dipole moment (EDM) $d_\tau$, are precision probes of electroweak dynamics and possible new physics sources, yet both remain weakly constrained experimentally. Treated as generalized form factors, these quantities exhibit a generic $q^2$ dependence for an off-shell interacting photon. For timelike momentum transfer above the $\tau^+\tau^-$ threshold, $q^2 = s > 4m_\tau^2$, the form factors can acquire absorptive imaginary parts. We investigate how such a $q^2$ dependence and the associated imaginary parts are generated from two complementary perspectives: the model-independent Standard Model Effective Field Theory (SMEFT) and a UV-complete Two-Higgs-Doublet Model (2HDM). The effective framework reveals the intimate correlation between $a_\tau$ and $d_\tau$. New CP-violating interactions which generate a non-zero $d_{\tau}$, can also generically have non-zero contributions to $a_\tau$, thereby deeply linking their phenomenological studies. Within the 2HDM, we demonstrate that sizable imaginary parts and significant $q^2$ running can be generated at levels accessible by $e^+e^-$ colliders. Motivated by these features, we propose experimental methods to extract both the real and imaginary components of the dipole form factors. Utilizing these techniques, we show that Belle II and the Super Tau-Charm Facility (STCF) can improve current bounds on $a_\tau$ by more than one order of magnitude. Finally, we highlight that combining measurements across the distinct center-of-mass energies of Belle II and STCF provides a unique, previously unexplored avenue to explicitly obtain information about the $q^2$ evolution of these dipole form factors.

The bulk motion of E-region radar aurora provides a sparsely distributed, direct measurement of the ionospheric electric field in intermittent bursts. We present a tracking procedure for \textsc{icebear} VHF measurements of Farley-Buneman waves. Each cluster is represented as an $\alpha$-shape; frame-to-frame association is a Hungarian linear-assignment problem with a cost combining centroid distance and shape Intersection-over-Union; kinematic prediction amounts to a degenerate Kalman filter. Births, deaths, splits, and mergers are monitored; each tracked trajectory is reduced to per-segment velocities by piecewise-linear regression. We validate against \textit{in-situ} observations. During the G5 storm of 10 May 2024, on closed dayside field-lines, our method recovers a five-second cluster moving at $11{,}240\pm660$~m/s, implying an electric field strength of $\approx 560$~mV/m, a value that exceeds documented sub-auroral thermal emission speeds and the most extreme reported sub-auroral drifts. The detection is consistent with extreme E-field structures appearing as short-lived bursts, representing field variability, and we provide parameterizations of this variability for space weather modeling.

Phononic crystals can confine elastic waves through localized defect states within bandgaps, offering promising opportunities for vibration control and energy localization. However, designing defect states at prescribed frequencies while maintaining adequate separation from other in-gap modes remains a significant challenge. Existing optimization approaches generally treat the target mode indirectly and provide limited control over competing localized modes. This study presents a gradient-based two-stage topology optimization framework for the frequency placement of localized defect modes in periodic elastic media. First, a host unit cell is optimized to create a bandgap around a prescribed frequency. Subsequently, only the defect cell is modified to attract a selected localized mode toward the target frequency while repelling non-target modes away from the central region of the bandgap. The formulation incorporates a smooth mode-selection function that combines mode attraction and repulsion within a unified objective, enabling automatic tracking of the relevant modes throughout the optimization process. Because the localized defect branches of interest are nearly flat, the optimization is performed using only the $\Gamma$-point eigenspectrum, while the corresponding dispersion relations over a reduced irreducible Brillouin zone are evaluated afterwards for verification. Numerical examples involving two material systems and two supercell sizes demonstrate accurate placement of localized resonances, clear separation from competing in-gap modes, and substantial preservation of the host bandgap. The resulting structures exhibit strong elastic-wave localization, highlighting the potential of the proposed approach for the design of phononic devices for vibration confinement and energy trapping.

The interplay between interactions and quantum geometry can drive weakly dispersive bosons into different exotic many-body phases. In this work we study a quasi flat-band model in one dimension that exhibits an extended pair-superfluid phase in the all-flat-band limit. Introducing single-particle hopping leads to an intriguing competition with a more conventional single-particle superfluid: we find that the pair superfluid remains stable for a finite range of the hopping strength until the system eventually transitions into the conventional superfluid phase. In our study, we make use of a variational Gaussian state approach that provides a unified description of the single-particle and pair superfluid phases, regarding both the ground state wavefunction and the collective excitation spectrum. In particular, we derive a general relation between the speed of sound and a ``quantum geometric kernel'', thereby extending earlier connections to the quantum metric, which relied on single-particle mean-field theory. This approach is combined with insights from the two-boson problem and exact diagonalization to map out the full phase diagram of the model. Our results show that the Gaussian approach is a versatile tool for studying a broad range of superfluid phases of interacting bosons in multi-orbital lattices.