Radiative coupling between quantum emitters leads to a range of spectacular emission phenomena. Dicke studied the foundations of collectively enhanced and suppressed decay, commonly referred to as super- and subradiance. Collective effects can further result in directionality of the emission, thus offering a complimentary implementation of chiral quantum optics. Waveguide quantum electrodynamics (QED) allows coupling between spatially separated emitters, enabling selective driving. In this work, we control the emission direction for a pair of quantum dots embedded in a bidirectional photonic crystal waveguide offering independent electrical tuning. Notably the emitters are 13 \micro m apart, which corresponds to 26 effective wavelengths, but are nevertheless radiatively coupled. The directionality arises from a dispersive dipole-dipole interaction, which shifts the energy of the collective states, so that the emitter pair effectively forms an artificial molecule. We show that the emission direction can be switched from left- to rightwards by manipulating the relative driving phase while collectively exciting the emitters. In addition, we observe directional photon statistics under continuous driving, with, for example, single photons detected on one output port, and photon pairs on the other. With pulsed excitation, both emitters are fully inverted and correlated photon pairs are observed in time-resolved intensity correlation measurements. This work demonstrates a novel implementation of chiral quantum optics using quantum dots coupled via a non-chiral waveguide, and reports key steps for scaling up as a multi-emitter waveguide QED platform.

Most Internet of Things (IoT) network simulators are packet-level discrete-event systems in which physical-layer (PHY) behavior is approximated through analytical interference rules and precomputed error models. While this enables scalable experiments, it can miss key waveform-level effects such as adjacent-channel leakage, cross-modulation interference between coexisting signals, and receiver imperfections, which are critical in heterogeneous sub-GHz ISM-band coexistence scenarios. This paper discusses these limitations and introduces IQSim, a simulation paradigm based on in-phase/quadrature (IQ) stream mixing. Instead of predicting packet outcomes from abstract collision models, IQSim maintains a shared complex baseband IQStream into which simulated transmissions are inserted as IQ waveforms after propagation processing, and then demodulated by software-based receivers or hardware gateways. We outline the end-to-end workflow, including online or offline waveform generation, IQ-domain propagation, waveform superposition, and delivery to gateways. We also report preliminary prototype results supporting the feasibility of real-time execution.

Causal mediation analysis has become an important and increasingly used framework for evaluating candidate immune response biomarkers in vaccine research. A controlled effects approach has been proposed to estimate controlled risk curves under a counterfactual scenario in which the entire study population is vaccinated and their post-vaccination immune responses are set to a range of fixed levels. This framework performs well when the study population is antigenically naïve, that is, individuals have not been previously exposed to the antigen, as is common in HIV-1 vaccine research and during the early phases of the COVID-19 pandemic. However, the controlled effects framework becomes more challenging to apply in antigen-experienced populations, where prior vaccination or infection has occurred, as in the case of influenza, dengue, and more recent phases of the COVID-19 pandemic. In such settings, a key identification assumption for valid causal mediation analysis, the positivity assumption, is violated: it is no longer plausible to conceive of a hypothetical intervention that sets a post-vaccination immune marker to a fixed level below an individual's baseline immune level. In this article, we introduce a weighted controlled risk approach that targets a subpopulation for whom there is a prespecified probability of attaining a post-vaccination immune marker level. We further generalize this framework to study contrasts of controlled risks for relevant subpopulations. We demonstrate the validity of the proposed estimators through simulation studies and apply the method to reanalyze post-vaccination neutralizing antibody titers against Omicron BA.4/BA.5 as an immune correlate of COVID-19 in the Coronavirus Variant Immunologic Landscape (COVAIL) trial. R code to implement the proposed method can be found on Github: https://github.com/Qijia-He/weighted_CVE.

We present a trajectory optimization algorithm for the traveling salesman problem (TSP) in graphs of convex sets (GCS). Our framework uses an augmented graph of convex sets to encode the TSP specification and solve it exactly as a shortest path problem in GCS. We establish a precise relationship between the landmark Bellman-Held-Karp algorithm and the augmented graph of convex sets with a TSP specification. Additionally, we present a branch and bound heuristic that uses minimum 1-trees to obtain certifiably optimal or near optimal solutions and scales to problems far larger than the exact framework can handle. To assess and certify performance, we explore several alternative lower bounds.

Neutron star mergers are multimessenger sources whose dynamics and signals depend critically on neutrinos and their flavor transformations. We investigate whether fast and collisional neutrino flavor instabilities (FFIs and CFIs) arise in a GW170817-like post-merger accretion disk, and how they develop and relax, by performing global and local classical and quantum-kinetic simulations that resolve anisotropies and inhomogeneities in the full six-dimensional phase space. In the accretion disk, the neutrino radiation field naturally develops electron-lepton-number crossings through the interplay between the more isotropic electron neutrino field and the more anisotropic electron antineutrino field. The neutrino field in the disk is also unstable to CFI, although on longer timescales than the FFI. Using local, multi-energy quantum-kinetic calculations at selected points, we find that the growth of unstable modes is well-predicted by a fully anisotropic linear stability analysis and the flavor transformation increases the heavy lepton neutrino fluxes. CFI likewise enhances heavy-flavor fluxes, shows significant impacts from the growth of multi-energy anisotropic modes, and breaks the symmetry of the heavy-flavor sector by raising the average energy of heavy-flavor antineutrinos above that of heavy-flavor neutrinos. However, the CFI remains subdominant to the FFI in most of the disk. In our global quantum-kinetic simulations with an attenuated Hamiltonian, flavor coherence develops primarily in the polar regions. Because the attenuation causes advection to outpace the growth of the instabilities, coherence and flavor conversion remain artificially suppressed within the disk. These results emphasize the resolution and scaling requirements for future global simulations that capture instability growth, saturation, and advection simultaneously.

In this work, we propose an efficient and transparent green learning pipeline to address the automatic modulation classification (AMC) problem. This pipeline aims to enable receivers to blindly identify the modulation modes of the incoming signals in a computationally efficient way with a small model size. Our method includes the following steps. First, the input signal is transformed into a precise representation through the sparse coding method. Second, various features are extracted from the sparse coding representation with the statistics from the input signal. Third, the classification subspace is hierarchically partitioned with a tree structure to achieve a lightweight model size with good prediction accuracy. The experimental results demonstrate the effectiveness and efficiency in classifying the modulated features and representation of received signals. Compared to lightweight deep learning models, the number of model parameters is reduced by \textbf{41\%}, while the usage of Floating Point Operations (FLOPs) is only $\mathcal{O}(10^{-4})$ of the blind waveform recognition without pre-arranged knowledge of incoming waveforms.

The study investigates the physics of unsteady flow in complex cavity geometries operating in the transonic regime. A two-dimensional Detached Eddy Simulation (DES) approach is used for the preliminary analysis. The cavity configuration examined in this work arises from the integration of a scramjet engine with a launch vehicle. In this integrated geometry, the isolator section serves as a deep sub-cavity, while the Single Expansion Ramp Nozzle (SERN) constitutes the primary cavity. The combined arrangement therefore constitutes a complex cavity-sub-cavity system, which is referred to as such throughout the paper. The qualitative analysis revealed a feedback loop within the complex cavity-sub-cavity system, leading to high-pressure oscillations across the geometry. A monotonic increase in pressure loading is observed with increasing Mach number. Varying the cavity topology demonstrated that modifications to the primary cavity geometry strongly alter shear-layer dynamics and significantly affect the pressure distribution within the cavity-sub-cavity system. To mitigate adverse pressure oscillations, passive control strategies, including trailing-edge wall chamfering and a ventilated (slotted) sub-cavity, are investigated. Among the configurations studied, the slotted sub-cavity case exhibits the most pronounced suppression of pressure loads, particularly on the sub-cavity end wall. Spectral Proper Orthogonal Decomposition (SPOD) analysis also revealed the restructuring of dominant coherent modes in response to topological variations and to the implementation of passive control, providing insight into the underlying governing mechanism.

Addressing the large inefficiencies generated by the Deferred Acceptance (DA) mechanism requires priority violations, but which ones are justifiable? The leading approach is to ask individuals if they consent to waive their priority ex-ante. We develop an alternative question-free solution, in which a priority violation is justifiable whenever the affected student either (i) directly benefits from the improvement, or (ii) is unimprovable under any assignment that Pareto-dominates DA. This endogenous justifiability criterion permits improvements unattainable by the leading consent-based mechanism under any consent structure. We provide a ``just below cutoffs'' mechanism that always finds a strongly justifiable matching whenever DA's outcome is inefficient, and build on it to construct a polynomial-time algorithm that expands justifiable improvements iteratively, converging to a DA improvement that cannot be Pareto-improved by any justifiable matching without strictly expanding the beneficiary set. Finally, we prove theoretically that both the ex-ante consent and the endogenous justifiability frameworks have important limitations in reaching Pareto-efficient outcomes, and use simulations to quantify how binding these constraints are in practice.

Classical multivariate shape analysis relies on covariance-standardized moments, such as Mardia skewness and kurtosis, which are sensitive to outliers and require finite moments. This paper introduces vector median absolute deviation (VMedAD) moments for robust multivariate shape analysis. The proposed framework replaces moment aggregation and covariance standardization with median-based center-outward contrasts defined through data depth, yielding affine equivariance and moment-free vector moments. VMedAD moments provide direction-preserving measures of multivariate skewness and directional peripheral dominance, separating central structure from tail-driven behavior. Consistency, breakdown properties, and affine equivariance are established, and simulation and real dataset examples demonstrate improved robustness and geometric interpretability over classical and projection-based methods.

Over the past 30 years, thousands of exoplanets have been discovered, revealing detailed demographics of planets outside the Solar System. One of the most dramatic features of the planet radius distribution is the radius gap, a lack of planets between $\sim$1.8-2 $R_\oplus$. The radius gap is thought to mark the distinction between rocky and gas planets. Recent research has found that the radius gap may not be present in binary star systems. In past studies of planets in binary star systems, the common assumption has been that all of the planets are hosted by the primary star. In many cases, the radius of the planet would be significantly larger if it were orbiting the companion star, which could potentially affect the true radius distribution. It is possible to identify the host stars of planets through stellar density estimates obtained from transit fitting. Using this method, we made probabilistic estimates for the host stars of a sample of 15 transiting exoplanets across 10 binary star systems hosting either 1 or 2 planets, at least one of which would reside in the canonical radius gap if it was circumprimary. We found that 5 of the planets are highly likely to be circumprimary, while the remainder have ambiguous host stars. The lack of unambiguously circumsecondary planets is caused by physical and observational biases that favor circumprimary planets. Nonetheless, the summed posterior probabilities suggest that the canonical radius gap appears less vacant for planets in binaries.

Close-binary evolution couples Roche-lobe overflow (RLOF), common-envelope (CE) drag, stellar winds, magnetic braking, and gravitational-wave losses, exchanging mass and angular momentum while reshaping orbits and spins. We present interoperable effects in the REBOUNDx extension to REBOUND that embed these processes within high-accuracy N-body dynamics. The suite includes: a momentum-conserving RLOF operator with conservative and systemic channels and configurable specific-j loss; a CE drag model based on Mach-dependent dynamical friction with kick limiting; isotropic Reimers winds, Parker-type thermal winds, and Eddington-limited outflows powered by a parametric stellar-evolution module supplying mass-dependent R and L; magnetic braking via the Verbunt-Zwaan/Kawaler torque with a saturation-aware closed-form spin update; and post-Newtonian corrections 2PN point-mass and spin-spin; 2.5PN radiation reaction. Linear momentum is conserved for conservative transfer, a minimal corrective torque enforces angular-momentum consistency, and adaptive sub-stepping stabilizes evolution near contact. Inter-module flags coordinate wind/RLOF/CE activity. The unit-agnostic framework enables self-consistent, time-resolved studies of close binaries in isolated or dynamically rich settings. Multiple examples and comparisons against other codes are provided in the Appendix. The code is available at https://github.com/malidib/ReboundS .

In this work, we construct an A4-based flavor symmetry model within the framework of the type-I seesaw mechanism to realize a light neutrino mass matrix consistent with mu-tau reflection symmetry. The entire framework is based on the Standard Model gauge symmetry extended by the discrete group A4 x Z2 x Z4. In general, the elements of the light Majorana neutrino mass matrix are complex. The mu-tau reflection symmetric texture of the mass matrix can be realized in a generalized CP symmetry limit. In this symmetry limit, the model predicts a maximal atmospheric mixing angle theta23 = pi/4 and a maximal Dirac CP phase delta = pi/2 or 3pi/2. These features are consistent with current experimental observations, including a near-maximal value of theta23, a non-zero reactor angle, and a preference for delta close to 270 degrees, as indicated by the T2K and NOvA experiments. Non-maximal values of theta23 and delta can be accommodated when one does not restrict to the CP symmetry limit. The model predictions for the mixing angles and the Dirac CP phase delta are then controlled by two parameters. We perform a numerical analysis to identify the allowed values of the model parameters consistent with current global three-neutrino oscillation data. The model successfully reproduces the desired deviations of theta23 and delta from their maximal values, consistent with global fit data, while simultaneously accommodating the observed values of theta12 and theta13.

Observed galactic cosmic ray intensity can be subjected to a transient decrease. These so-called Forbush decreases are driven by coronal mass ejection induced shockwaves in the heliosphere. By combining in situ measurements by space borne instruments with ground-based cosmic ray observations, we investigate the relationship between solar energetic particle flux, various solar activity indices, and intensity measurements of cosmic rays during such an event. We present cross-correlation study done using proton flux data from the SOHO/ERNE instrument, as well as data collected during some of the strongest Forbush decreases over the last two completed solar cycles by the network of neutron monitor detectors and different solar observatories. We have demonstrated connection between the shape of solar energetic particles fluence spectra and selected coronal mass ejection and Forbush decrease parameters, indicating that power exponents used to model these fluence spectra could be valuable new parameters in similar analysis of mentioned phenomena. They appear to be better predictor variables of Forbush decrease magnitude in interplanetary magnetic field than coronal mass ejection velocities.

This paper examines artificial intelligence (AI) companionship as a site where intimate relations are simultaneously produced, extracted from, and governed through datafied systems. Drawing on critical data studies and platform studies, we challenge prevailing narratives that locate harm in user psychology rather than platform architecture. Through in-depth interviews with 20 individuals who have AI companions, we address three questions: what harms do users identify, how do they make sense of those harms, and what do their accounts reveal about the perceived distribution of responsibility among users, platforms, and regulators? Participants identified design-based harms, including unsolicited content generation and safety mechanisms that stigmatized the users they intended to protect, alongside use-based harms centered on emotional dependency they could recognize but not resolve. Users deployed individualized sensemaking strategies, including self-regulation, stigma navigation, and privacy rationalization, bearing the full burden of harm mitigation without platform support. On governance, participants described an accountability vacuum in which platforms deflected blame while users articulated conditional preferences that rejected both prohibition and deregulation. The findings extend responsibilization theory by demonstrating how platform-produced vulnerability becomes self-sustaining through the interpretive labor of users who lack structural alternatives.

During the 2026 ESO La Silla Observing school, about twenty students attended lectures and performed observations to learn various aspects of observational astronomy. The school, which took place during the first two weeks of February 2026, made use of EFOSC2/NTT and HARPS+NIRPS/3.6m. One of the groups was devoted to the study of binary stars. Several projects were considered and followed up by some of the six students in this group. The first subgroup used HARPS to study the Rossiter-McLaughlin effect in binary stars to infer the relative inclination of the rotation axis of the primary with respect to the orbital plane. A detailed study of the contact binary system HD 115264 led to the conclusion that the primary is well aligned, likely as a result of strong tidal forces within the binary. The second subgroup analysed blue straggler stars (BSS) in open clusters, using both HARPS and EFOSC2. With HARPS, they looked at some well-known long-period binary with the aim of determining their chemical abundances, thereby confirming their membership to the cluster, as well as looking for any chemical anomalies that might be explained by mass transfer. EFOSC2 was used to derive radial velocities of rapidly varying BSS. For one of them - the star Rediet - the students clearly detected and analysed the radial velocity variations due to the second overtone pulsation, thereby confirming its delta Scuti character. Finally, one student used EFOSC2 to study planetary nebulae (PN) - taking nice images of some of these intricate objects, as well as doing time-resolved photometry and spectra of some others. In one case, the binary nature of the central star of the PN was proven, confirming some previous estimates done with ZTF. Each subgroup was thus able to obtain useful research results, which we present hereafter.

In this work we study the theoretical Lipschitz stability and propose a low-rank-assisted numerical method for the inverse medium scattering beyond the Born region. The proposed low-rank structure is based on the disk prolate spheroidal wave functions, which are eigenfunctions of both the Born forward operator and a Sturm-Liouville differential operator. We obtain Lipschitz stability for unknowns in a low-rank space in the fully nonlinear case and characterize the explicit Lipschitz constant in the linearized region. We further propose an ensemble Kalman filter to iteratively update the unknown in the proposed low-rank space whose dimension is intrinsically determined by the wave number. Moreover the ensembles are sampled according to a novel trace class covariance operator motivated by the connection between the proposed low-rank space and the Sturm-Liouville differential operator. Finally numerical examples are provided to illustrate the feasibility of the proposed method.

We demonstrate high-performance UWBG AlGaN PolFETs exhibiting a state-of-the-art combination of nearly 1 A/mm on-state current (~ 960 mA/mm) and large breakdown field (> 4.8 MV/cm) in high carrier density (1.15 x 1013 cm-2). Multi-kV robustness is successfully demonstrated exhibiting 1.28 and 2.17 kV by utilizing a gate-connected field plate structures in 3.9 and 6.8 μm LGD, corresponding to the extremely low specific on-resistance of 1.25 and 2.86 mΩcm2, respectively. High RF performance is also achieved, providing fT and fMAX, of 8.5 and 15 GHz, respectively, for 3.9 μm LGD. These results highlight UWBG AlGaN as a platform for both high-voltage RF and power applications.

Here we investigate a possible presence of a fifth force at the Galactic Center (GC), and its potential influence on the stellar orbits around the central supermassive black hole of our Galaxy. For this purpose we simulated the stellar orbits in a Yukawa gravity model that predicts the emergence of a fifth force, and fitted them into the observed orbit of S2 star around Sgr A* at the GC. The fitting was performed using Markov chain Monte Carlo method which enabled us to constrain the parameters of Yukawa interaction describing the strength $δ$ and the range $λ$ of a fifth force. We studied the following cases for a fifth force range $λ$, when it is: i) about a few hundred AU (i.e. deep inside the orbit of S2 star), ii) about a thousand AU (i.e. approximately the size of S2 star orbit), and iii) several thousand AU (i.e. much larger than the size of S2 star orbit). The obtained results showed that as the range $λ$ of a fifth force increases, its strength $δ$ also increases and relative error $Δδ/δ$ decreases. The resulting fifth-force strengths in all three cases are respectively: $δ\sim$ 0.005, 0.02 and 0.15. These results are consistent with the corresponding results of both our previous studies and those of other authors, regardless of the different Yukawa-like potentials used to model a fifth force. In addition, we also studied whether the possible small discrepancies from the prediction of General Relativity for the Schwarzschild precession of S2 star could be caused by a fifth force. For this purpose we used the $f_\mathrm{SP}$ parameter that was recently measured in the case of S2 star by GRAVITY Collaboration in 2020. We found that the obtained estimates in all three cases are compatible, within the error intervals, with the measured value of $f_\mathrm{SP} = 1.10\pm 0.19$.

The adoption of Machine and Deep Learning (ML/DL) technologies introduces maintenance challenges, leading to Technical Debt (TD). Algorithm Debt (AD) is a TD type that impacts the performance and scalability of ML/DL systems. A review of 42 primary studies expanded AD's definition, uncovered its implicit presence, identified its smells, and highlighted future directions. These findings will guide an AD-focused study, enhancing the reliability of ML/DL systems.

We consider a fluid-structure interaction problem involving a viscous, incompressible fluid flow, modeled by the 2D Navier-Stokes equations, through a thin deformable elastic tube, displacement of which is not known a priori. The elastodynamics problem is given by 1D plate equations. The fluid and the structure are nonlinearly coupled via the kinematic and dynamic coupling conditions at the fluid-structure interface. The fluid flow is driven by dynamic pressure data imposed at the inlet and outlet of the tube. We impose the Navier-slip boundary condition at the deformable fluid-structure interface and at the bottom rigid boundary of the fluid domain. Hence, beyond the usual geometric nonlinearities arising from nonlinear coupling in FSI with no-slip, the analysis is more challenging due to the possibility of tangential jumps of the fluid and structural velocities at the moving interface. We first discuss the existence of weak solutions and then establish a `hidden' spatial regularity result for the structure displacement. Our main result proves the existence of a finite time for weak solutions at which the compliant upper boundary meets the lower boundary (i.e., the tube collapses), provided that there is a sufficient pressure drop across the channel. This resolves the ''no-collision'' paradox identified by Grandmont and Hillairet in the no-slip setting in [Arch. Ration. Mech. Anal., 220(3): 1283-1333, (2016)], the counterpart to the present work. To the best of our knowledge, this is the first work that rigorously establishes finite-time contact in a fluid-elastic structure interaction system, thereby validating the model to correctly capture near-contact dynamics.

Type Ia supernova (SN) magnitudes present correlations due to the fact that their peculiar velocities are sourced by the large-scale structure of the Universe. This effect can be used to constrain properties related to the distribution and growth of matter perturbations. We analyze both Pantheon+ and Dark Energy Survey (DES-Y5) SN catalogues in combination with CMB data from Planck PR4 to constrain $σ_8$ in $Λ$CDM, optionally including both curvature and a modified growth index $γ$. We show that SN and CMB datasets are highly complementary and capable of measuring $σ_8$, $γ$ and $Ω_k$ simultaneously. Using only SN, we find $σ_8 = 0.73 \pm 0.22$ ($0.87 \pm 0.31$) for Pantheon+ (DES-Y5) in the base flat $Λ$CDM model. Interestingly, allowing for free $γ$ and $Ω_k$, we find hints of positive curvature: $Ω_k = -0.011 \pm 0.006$ $(-0.014 \pm 0.005)$, which exclude flatness at 2.2$σ$ (3.0$σ$), for the combination of CMB with Pantheon+ (DES-Y5). Such hints do not degrade if we also include a modified amplitude of CMB lensing, parametrized by $A_L$. We find that $γ= 0.519^{+0.061}_{-0.099}$ ($0.461^{+0.085}_{-0.069}$), which are consistent with the predictions of General Relativity. In terms of $fσ_8(z)$, we find $fσ_8(0.024)=0.461^{+0.066}_{-0.035}$ ($fσ_8(0.038) = 0.498^{+0.045}_{-0.050}$) for CMB + Pantheon+ (DES-Y5). Finally, the strong degeneracy between all three $Ω_k$, $γ$ and $H_0$ results in a broader CMB $H_0$ posterior. However, if we include SH0ES $H_0$ data, which is in known strong tension with the CMB in flat $Λ$CDM, we find that the $H_0$ tension is recast in terms of a significantly negative curvature and suppressed growth of structures.

Titanium alloys are widely used in aerospace, biomedical, and energy applications owing to their high specific strength, corrosion resistance, and biocompatibility. Among them, $α$-titanium alloys with a hexagonal close-packed (hcp) crystal structure exhibit characteristic deformation mechanisms governed by crystallographic slip and defect evolution. In this study, the influence of manganese content on the plastic deformation mechanisms of polycrystalline $α$-Ti-2Mn and $α$-Ti-4Mn (at.%) alloys is investigated using molecular dynamics simulations. Atomistic models were subjected to uniaxial loading at room temperature at a strain rate of 10$^9$ s$^{-1}$. The mechanical response was evaluated through stress-strain behavior, structural evolution, dislocation nucleation and interaction, and analysis of the local deformation field. Plastic deformation in these $α$-Ti-Mn alloys is dominated by dislocation nucleation and their subsequent evolution within the hcp lattice. Increasing Mn content leads to higher stress levels and enhanced resistance to plastic deformation, accompanied by changes in dislocation activity and defect evolution.

Ultrawide-bandgap AlN is a promising material for next-generation power electronics; however, its practical implementation is hindered by unstable surface chemistry and the high activation energy of p-type dopants. In particular, high-temperature rapid thermal annealing (RTA), required for forming low-resistance contacts on n-type AlN, leads to the formation of thick and defective surface oxides that degrade heterojunction performance. In this work, we present an interface engineering approach based on fluorination-induced AlFx formation combined with SiNx passivation to suppress defect-assisted leakage in p-Si/n-AlN heterojunction diodes fabricated via semiconductor grafting. A low-damage pseudo-atomic layer etching process is employed to remove RTA-induced oxides and restore a near-stoichiometric AlN surface. Subsequent XeF2 treatment forms an ultrathin AlFx layer, which is stabilized by an atomic-layer-deposited SiNx capping layer prior to p-Si nanomembrane integration. Electrical measurements show that the engineered AlFx/SiNx interface reduces reverse leakage current by several orders of magnitude compared to untreated or oxide-removed AlN surfaces, while preserving forward conduction characteristics. Temperature-dependent analysis indicates strong suppression of Poole-Frenkel emission and a shift of leakage onset to higher reverse bias, ultimately limited by bulk AlN crystal quality. X-ray photoelectron spectroscopy and transmission electron microscopy confirm the formation of Al-F bonds, reduced Al-O content, and the presence of a thin interfacial SiOx/SiON layer. These results establish AlFx/SiNx passivation as an effective strategy for stabilizing AlN interfaces and enabling low-leakage ultrawide-bandgap heterojunction devices.

Given a graph $T$ and a family of graphs $\mathcal{F}$, the generalized Turán number $\mathrm{ex}(n,T,\mathcal{F})$ is the maximum number of copies of $T$ in an $n$-vertex $\mathcal{F}$-free graph. We prove a general theorem which states that for any tree $T$, any family $\mathcal{F}$, and any integer $k$, either $\mathrm{ex}(n,T,\mathcal{F})$ is at least $Ω(n^{k+1})$ or at most $O(\mathrm{ex}(n,\mathcal{F})^{k})$, from which we derive a number of consequences. Our proofs rely on new variants of the classical Helly Theorem for trees which may be of independent interest. As far as we are aware, this is the first known application of Helly theorems for Turán type problems.

Long-term beamforming (LTBF) is a widely-used scalable alternative to instantaneous multi-user MIMO processing that leverages slowly varying spatial channel statistics. VLSI implementations require matrix inversion that become computationally challenging for massive MIMO systems with large number of antennas. In this work, we show that dominant interferers significantly degrade the numerical conditioning of the LTBF covariance matrix, leading to severe performance loss in finite-precision implementations of polynomial and conjugate gradient (CG) based inversion methods. To address this issue, we propose a subspace nulling approach that operates solely on long-term channel statistics and acts as an implicit preconditioning step for LTBF. By projecting the received signal onto the orthogonal complement of the dominant interference subspace, the proposed method reduces the eigenvalue spread of the covariance matrix and improves numerical stability. Through ray-tracing simulations in a realistic 5G scenario, we demonstrate that the proposed method substantially reduces the number of CG iterations required to achieve near-optimal performance across floating-point and fixed-point implementations while preserving the low-overhead nature of LTBF.

This study investigates how Southeast Asian (SEA) immigrant mothers in Taiwan participate in their children's home-based learning. Drawing on semi-structured interviews and diary studies, we explore how these mothers navigate sociocultural constraints while fostering engagement and transmitting cultural values. Despite facing diminished agency and structural marginalization, mothers engage creatively in their children's everyday learning interactions. Guided by a justice-oriented lens, we identify various harms and propose design implications for socio-technical systems that center recognition, reciprocity, and accountability in parent-child learning at the individual, familial, and societal levels. Our contribution lies in foregrounding the role of intersectional identity in parent-child learning and proposing justice-oriented design directions that support the flourishing of immigrant mothers within socio-technical systems.

Device stability is essential for quantum information technologies, where reliable control of electronic states is crucial. Diamond valleytronics offers a promising platform by exploiting the valley degree of freedom to store and manipulate information. In this work, we demonstrate a diamond-based valley transistor with a dual-gate, two-drain architecture that enables tunable valley-polarized transport via gate voltage modulation. By leveraging the significant effective-mass anisotropy of diamond's conduction band valleys, this architecture provides control over spatial distribution and transit times. We further demonstrate that valley-polarized transport in diamond is remarkably robust against thermal variations over macroscopic distances. These results demonstrate the resilience of valley states and highlight diamond's potential for energy-efficient valleytronic devices in next-generation quantum and high-power electronics.

We present the Dartmouth Stellar Evolution Emulator (DSEE), a flow-based stellar evolution model emulator trained on a comprehensive database comprising over eight million evolutionary tracks that vary across twenty input-physics dimensions and span broad ranges in mass and composition. DSEE learns phase-conditioned stellar state snapshots, unifying track and isochrone construction as marginals of one generative model. It delivers continuous interpolation across high-dimensional physics, probabilistic predictions with calibrated credible intervals, and orders-of-magnitude speedups over direct modeling. Validation against current stellar evolution models shows high fidelity across the HR diagrams, while distributional tests recover the full distributions obtained from brute-force Monte Carlo sampling. To broaden impact, DSEE is integrated into the open-source CONF1DENCE package, enabling fast, end-to-end creation of stellar tracks and isochrones. CONF1DENCE includes the ability to make uncertainty-aware age determinations for clusters taking into account observational effects. CONF1DENCE replaces bespoke, fixed-physics grids with a generative, physics-marginalized emulator, setting a practical new standard for stellar modeling and enabling survey-scale analyses with rigorous uncertainty.

The standard type-I seesaw can also be regarded as a low-scale seesaw by using the freedom of the Casas-Ibarra parameterization. In this framework, radiative corrections to the neutrino mass matrix can dominate over the tree-level contribution. We show that a naive use of the Casas-Ibarra parametrization in the presence of 1-loop corrections leads to incorrect predictions for the neutrino oscillation parameters. By using a modified Casas-Ibarra parametrization, in which 1-loop corrections are reabsorbed into the right-handed neutrino mass matrix, we obtain a light neutrino mass matrix consistent with experimental values. On the other hand, we show that physical processes related to right-handed neutrino propagation, such as heavy neutral lepton searches, do not depend on the 1-loop corrections. Moreover, we show that ${\rm Br}(μ\to e γ)$ provides competitive constraints on the parameter space of heavy neutral lepton search experiments for masses above $100$ GeV.

We study supersymmetric indices of the 6d $(2,0)$ theory of $N$ M5-branes on toric Sasaki-Einstein five-manifolds. Embedding the background into a local toric Calabi-Yau four-fold and equivariantly integrating the anomaly polynomial yields a finite-$N$ Cardy-limit formula in terms of equivariant characteristic classes. Separately, using equivariant constant maps in topological string theory and higher-derivative supergravity, we derive a finite-$N$ proposal for the superconformal, twisted and spindle indices of $N$ M2-branes probing arbitrary toric Calabi-Yau four-folds. The M2-brane partition functions depend on the same combination of equivariant classes as the M5 result. Motivated by this match, we generalize the M2/M5 duality recently proposed in arxiv:2601.17114 to an infinite class of M2-brane theories by exchanging the worldvolume and transverse geometries of the two brane systems.