Secondary school students enrolled in the AP Computer Science Principles (CSP) course commonly utilize web resources (e.g., tutorials, Q\&A sites) to better understand key concepts in the curriculum. The primary obstacle to using these resources is finding information appropriate for the learning task and student's background. In addition to web search, conversational agents are increasingly a viable alternative for CSP students. In this paper, we study the potential of conversational agents to aid secondary school students as they acquire knowledge on CSP concepts. We explore general purpose, generative conversational agents (e.g., ChatGPT) and custom, fixed-response conversational agents built specifically to aid CSP students. We present results from classroom use by 45 high school students in grades 9-11 (ages 14-17) across six CSP sections. Our main contributions are in better understanding how conversational agents can help CSP students and an evaluation of the effectiveness and engagement of different approaches for CSP exploratory search.

This article proposes a data-driven framework to verify the distributed conditions that guarantee the system-wide stability for interconnected power systems. To guarantee system wide stability, the dynamics of each bus are required to satisfy an output differential passivity (ODP) condition with a sufficient index. These ODP indices uniformly quantify the impacts on the system-wide stability of individual bus dynamics and the coupling strength from the power network. To obtain these indices without explicit physical models, we derive a data-driven linear matrix inequality (LMI) criterion based exclusively on measured input-state trajectories. Furthermore, extracting the optimal ODP index is formulated as a convex semi-definite programming (SDP) problem. Simulations verify the effectiveness of the proposed method under both single-device offline evaluation and system-wide online certification scenarios.

We introduce a method for the selective preparation and detection of quasiparticle wave packets, based on creation operators that generate dressed, localized excitations on top of interacting vacua of (quasi-)one-dimensional quantum lattice theories. This method exploits maximally localized Wannier functions (MLWFs) constructed from quasiparticle bands at intermediate system sizes, enabling the construction of unitary local dressed creation operators. The algorithm allows for species-resolved wave-packet preparation and detection, enabling the separation of known quasiparticle contributions from unknown resonances. We test this approach with matrix product states (MPS) on pure hardcore Hamiltonian QCD on a ladder lattice, detecting scattering outputs and mass resonances.

Software engineering research has experienced rapid growth in both output and participation over the past decades. Yet concerns persist about the field's ability to accumulate, integrate, and reuse knowledge in ways that support long-term progress. To better understand how the community itself perceives these challenges, we analyze responses from the ICSE 2026 Future of Software Engineering pre-survey, which captures perspectives from 280 globally distributed and highly experienced researchers. Our analysis reveals a tension between increasing research productivity and the limited mechanisms available for synthesizing results, tracking evolving claims, and supporting cumulative understanding over time. Building on these observations, we diagnose four interrelated structural breakdowns: papers function as isolated knowledge units with claims embedded in prose; context and provenance are lost as knowledge moves through the publication pipeline; claims evolve without systematic tracking; and incentive structures favor novelty over consolidation. We argue that addressing these barriers requires rethinking the fundamental properties of research artifacts. We articulate four technology-agnostic principles for future research artifacts: structured and interpretable representations of claims and evidence; inspectable and provenance-aware documentation of methodological decisions; long-lived and reusable substrates that evolve beyond publication; and governance mechanisms that align individual incentives with collective knowledge-building goals. We discuss implications for research practice, publication norms, and community infrastructure, positioning FOSE as a venue for experimenting with alternative artifact designs that support cumulative scientific progress.

We propose a method for the prediction of stationary max--stable random fields with $α$-Fréchet marginal distribution $H_α$. The method is suitable to cope with heavy tails for $α\in(0,2)$ and is (approximately) exact in marginal distributions. It is based on a recent extrapolation approach via level sets which requires no moment assumptions. An explicit connection between the excursion metric and the Davis-Resnick distance is established. The existence of the predictor is proven. The non-uniqueness of the forecast is demonstrated on several examples. The method is tested on multiple simulated time series and random fields as well as applied to real data of annual maximum precipitation.

We consider a new treatment for making polyhedron nets referred to as ``apple peel unfolding'': drawing the nets as if we were peeling off appleskins. We define apple peel unfolding strictly and implement a program that derives the sequential selection of the polyhedral faces for a target polyhedron in accordance with the definition. Consequently, the program determines whether the polyhedron is peelable (can be peeled completely). We classify Archimedean solids and their duals (Catalan solids) as perfect (always peelable), possible (peelable for restricted cases), or impossible. The results show that three Archimedean and six Catalan solids are perfect, and three Archimedean and three Catalan ones are possible.

In variety testing, multi-environment trials (MET) are essential for evaluating the genotypic performance of crop plants. A persistent challenge in the statistical analysis of MET data is the estimation of variance components, which are often still inaccurately estimated or shrunk to exactly zero when using residual (restricted) maximum likelihood (REML) approaches. At the same time, institutions conducting MET typically possess extensive historical data that can, in principle, be leveraged to improve variance component estimation. However, these data are rarely incorporated sufficiently. The purpose of this paper is to address this gap by proposing a Bayesian framework that systematically integrates historical information to stabilize variance component estimation and better quantify uncertainty. Our Bayesian linear mixed model (BLMM) reformulation uses priors and Markov chain Monte Carlo (MCMC) methods to maintain the variance components as positive, yielding more realistic distributional estimates. Furthermore, our model incorporates historical prior information by managing MET data in successive historical data windows. Variance component prior and posterior distributions are shown to be conjugate and belong to the inverse gamma and inverse Wishart families. While Bayesian methodology is increasingly being used for analyzing MET data, to the best of our knowledge, this study comprises one of the first serious attempts to objectively inform priors in the context of MET data. This refers to the proposed Bayesian updating approach. To demonstrate the framework, we consider an application where posterior variance component samples are plugged into an A-optimality experimental design criterion to determine the average optimal allocations of trials to agro-ecological zones in a sub-divided target population of environments (TPE).

Proportional-Integral-Derivative (PID) control is used for automatically regulating a measurable quantity to a desired setpoint. It is widely used in different types of classical control electronics. Here, we show how extending the feedback theory in quantum systems to include the derivative and integral parts influences both the transient and steady-state behavior of the amplitude and squeezing of a mechanical quadrature in an optomechanical system. We show that, in contrast to standard proportional feedback, derivative feedback affects both the conditional and unconditional squeezing. Furthermore, we demonstrate how feedback may be employed to drive a mechanical quadrature to track a desired reference signal. Our findings offer new routes for an improved quantum state control and measurement precision.

This paper presents a unified optimization framework for phase change material (PCM) based cooling systems. Thermal management is critical in applications such as photovoltaic (PV) modules, battery packs, and power electronics, where excessive heat reduces performance and lifespan. Designing such systems is challenging because energy dynamics, capacity, heat rejection, and structural constraints must all be considered. Although prior studies have investigated PCM applications and heat transfer enhancement, there are limited efforts that unify such diverse performance objectives through formalized design methods. This paper develops a framework that formulates the PCM design problem using critical energy-based terms, with static and dynamic objectives capturing the PCM physical design and control aspects. Two case studies are used to validate the approach: the first explores passive cooling, and the second implements an active cooling configuration. The results compare the design and control of these systems, showing improvement in individual performance metrics between the two options.

Code generation refers to automatically producing executable programs from user requirements. Recently, researchers have explored approaches to enhance the correctness of generated code with advanced large language models. Although achieving improvements, existing approaches focus on designing reasoning strategies or post-refinement methods to enhance code generation performance. Despite their differences, all these methods share a common assumption: the LLM can correctly understand the given requirement. However, this assumption does not always hold. To fill this gap, we propose REA-Coder, a requirement alignment approach to enhance the code generation performance of LLMs. REA-Coder involves first identifying the requirement content that does not align with LLMs and aligning the requirements. Then, based on the aligned requirements, LLMs generate code and further verify whether the generated code aligns with the requirements, iterating this process of requirement alignment and code generation until generating correct code or achieving the maximum number of iterations. Experimental results show that REA-Coder outperforms all advanced baselines on four LLMs across five programming benchmarks. Concretely, REA-Coder achieves average improvements of 7.93%, 30.25%, 26.75%, 8.59%, and 8.64% on the five benchmark datasets, demonstrating the effectiveness of requirement alignment for improving the code generation performance of LLMs.

We present an analysis of XRISM and NuSTAR data obtained for the nearby low-Eddington active galactic nucleus NGC 7213. Our goal is to examine whether its He-like and H-like iron emission lines can be reproduced by photoionization or collisional ionization processes. Using the broad-band energy coverage of our data (2-60 keV), we first constrained the continuum shape. Then, we focused on the iron-K band in the Resolve spectrum. Gaussian fits to Fe XXV He$α$ and Fe XXVI Ly$α$ lines suggest that they may have different velocity widths: $v_σ=790^{+370}_{-240}$ km s$^{-1}$ for Fe XXV and $v_σ=2610^{+1700}_{-1580}$ km s$^{-1}$ for Fe XXVI. In this case, the He$α$ resonance line (w) and forbidden line (z) have similar intensities of $\approx0.5$-$0.6\times10^{-5}$ ph s$^{-1}$ cm$^{-2}$, while the intercombination lines (x+y) are not significantly detected with upper limits of $\lesssim 0.2\times10^{-5}$ ph s$^{-1}$ cm$^{-2}$. Motivated by the possible difference in the line widths, we tested one- and two-zone photoionized and collisionally ionized models. Our results show that the additional ionized component is not significantly required, and the current data cannot uniquely determine whether photoionization or collisional ionization dominates. Moreover, if the Fe XXV He$α$ complex implies that the weak x+y lines are suppressed relative to the w and z lines, such a structure is difficult to reproduce with either ionization model adopted. Finally, by comparing NGC 7213 with M 81$^\ast$, accreting at a much lower Eddington ratio of $λ_{\rm Edd}\sim 10^{-5}$, we found a decrease in the density of the gas responsible for highly ionized iron emission, which may imply that the density decreases with decreasing $λ_{\rm Edd}$.

We present a new version of FastQSL for locating quasi-separatrix layers (QSLs) -- regions characterized by strong magnetic connectivity gradients, preferential current buildup, and subsequent magnetic reconnection. This version now supports spherical coordinates, utilizing a second spherical coordinate system for tracing magnetic field lines around the polar regions. This approach completely resolves the singularity problem at the two poles. Furthermore, our code accommodates arbitrary mesh shapes for output, can provide both magnetic field and electric current density on the mesh, and can save the traced magnetic field lines. We suggest using $Q_\mathrm{local}$ calculated through a localized mapping to locate (quasi-)separators. By quickly and accurately outputting the footpoint coordinates of magnetic field lines, FastQSL can be used to derive the two key parameters used for modeling solar wind speed and slip-squashing factors for the case of zero boundary flow. Compared with the first version, FastQSL 2 achieves significant improvements in terms of application scope.

Silicon vacancy (VSi) centers in 4H silicon carbide have emerged as a highly promising platform for semiconductor-based quantum technologies, combining excellent spin and optical properties with an industrial-grade, CMOS-compatible material. As these defects are increasingly integrated into practical quantum devices, they inevitably encounter lattice strain. However, while the impact of strain is well documented for other solid-state defects like NV centers in diamond, its specific influence on key VSi spin dynamics such as initialization fidelity and state lifetimes remain largely unexplored. In this work, we address this critical gap by designing fully optical pulse sequences and incorporating the effective spin-3/2 strain Hamiltonian into our analysis. This combined approach allows us to isolate both axial and transverse strain contributions and systematically characterize their effect on the metastable state transition rates. Specifically, we reveal that strain significantly reduces the transition rates from the energetically lowest metastable state to the ground state quartet, leading to decreased photon emission. Supported by first-principles calculations, our findings provide a deeper understanding of VSi spin-strain dynamics, yielding crucial insights for the robust deployment of these centers in realistic, strain-prone environments.

Call detail records (CDR) from mobile phone networks are widely used to study human mobility however CDR data from a single mobile operator are inherently biased because the observed users do not mirror the population distribution. Using data from a major Chilean carrier in Santiago, we observe the user base is skewed by socioeconomic group, so aggregate metrics like radius of gyration are distorted by the population that is actually observed. To correct this sampling bias, we apply multilevel regression and poststratification (MRP), a method that is not yet standard for CDR-based mobility studies. We fit a Bayesian multilevel model for individual mobility using socioeconomic status, gender, and geography, with partial pooling across comunas, and then poststratify the predictions to match census demographics. This approach reduces the naive CDR estimate of average radius of gyration by about 17%. Importantly, a version of the model that uses only geographic information still captures much of the bias, showing that MRP can be useful even when the socioeconomic composition of users is not fully known, as long as spatial patterns of socioeconomic groups exist. This example demonstrates how MRP can provide a principled correction for non-representative CDR-derived mobility estimates, rather than treating the carrier sample as if it were a random population sample.

This paper takes an empirical look at asymptotic runtime growth rates for the most widely used algorithms for solving linear programming (LP) problems across a set of six optimization application areas that are known to produce large and difficult LP models. On the algorithm side, we consider the simplex method, interior-point methods, and PDHG. On the model side, we use a large language model (LLM) to create families of instances in different application areas, allowing us to study model types and sizes that are simultaneously synthetic and realistic. The results indicate that simple regression models typically predict observed runtimes quite well within a model class, and that asymptotic behavior can vary significantly between the different algorithms. This may have a significant impact on which algorithms will be most effective for solving large LP models in the future.

Quantum coherence plays a pivotal role in quantum algorithms. We study the coherence dynamics of the evolved states in Simon's quantum algorithm based on Tsallis relative $α$ entropy and $l_{1,p}$ norm. We prove that the coherences of the first register and the second register both rely on the dimension $N$ of the state spaces of the $n$ qubit systems, and increase with the increase of $N$. We show that the oracle operator $O$ does not change the coherence. Moreover, we study the coherence dynamics in the Simon's quantum algorithm and prove that in overall the coherence is in production when $N>4$ and in depletion when $N<4$.

We report on the design and performance of a two-color dual-oscillator infrared free-electron laser (FEL). The mid-infrared (MIR) FEL at the Fritz Haber Institute (FHI FEL) has been upgraded to include a second oscillator FEL beamline that permits lasing in the far-infrared (FIR) regime from 4.5 μm to 175 μm. In addition, a 500 MHz kicker cavity has been installed downstream of the electron accelerator. It allows to deflect electron bunches of up to 50 MeV energy alternately left and right by an angle of {\pm}2°. It can, thus, split the high-repetition-rate (1 GHz) electron bunch train from the accelerator into two bunch trains of 500 MHz repetition rate each; one is steered to the MIR FEL and the other one to the new FIR FEL. In this two-color mode of simultaneous, synchronized operation the wavelengths in both FELs can be tuned independently over wide ranges of up to a factor of four each by undulator-gap variation. In addition, two-color operation is also available at reduced repetition rates (e.g. 55.6 MHz of both MIR and FIR pulses), as needed for some applications. This unique two-color mode opens up a wealth of novel user applications such as, MIR-FIR pump-probe experiments.

Let $k \in \mathbb{N}$ and let $H_1, H_2, \ldots, H_k$ be simple graphs such that for each $j \in \{ 1, 2, \ldots, k \}$, the vertex set of $H_j$ is $\{ 0, 1, 2, \ldots, n_j - 1 \}$ for some $n_j \in \mathbb{N}$. The ordered Ramsey number $R_\mathrm{ord}(H_1, H_2, \ldots, H_k)$ is the smallest $n \in \mathbb{N}$ for which every $k$-edge-coloring of the complete graph on the vertex set $\{ 0, 1, 2, \ldots, n - 1 \}$ contains $H_j$ as a monochromatic subgraph of color $j$ for some $j \in \{ 1, 2, \ldots, k \}$, with the vertices appearing in the same order as in $H_j$. Inspired by the work of Poljak, we apply the Kissat SAT solver to determine new small two-color ordered Ramsey numbers of various classes of graphs: monotone paths, monotone cycles, alternating paths, stars, complete graphs and nested matchings. In addition, we introduce the cyclic Ramsey numbers $R_\mathrm{cyc}(H_1, H_2, \ldots, H_k)$ as a natural relaxation of the ordered Ramsey numbers, and once again use Kissat to determine various such numbers for the two-color case. By observing structural patterns in the computational results, we determine all ordered or cyclic Ramsey numbers for several pairs of classes of graphs. Furthermore, we obtain some bounds on ordered and cyclic Ramsey numbers where one argument is a connected graph, while the other is a monotone path or a monotone cycle. We also explore how reinforcement learning can be used through the recently developed Reinforcement Learning for Graph Theory (RLGT) framework to obtain lower bounds on ordered and cyclic Ramsey numbers. Finally, we introduce the permutational Ramsey numbers to show how the different Ramsey-type formulations involving standard, ordered and cyclic Ramsey numbers can be unified within a group-theoretic framework.

The pulsar beaming fraction is a fundamental quantity for connecting the observed pulsar population to the intrinsic Galactic population and for constraining pulsar emission geometry. In this study, we estimate the beaming fraction in each observational band (radio, $γ$-ray, and X-ray) and for each TeV survey (H.E.S.S., HAWC, and LHAASO) using TeV-selected pulsar wind nebulae (PWNe) and unidentified (Unid) TeV sources, assuming that the TeV emission from PWNe is approximately isotropic and that Unid sources are PWNe powered by pulsars whose beams do not intersect our line of sight. Within each survey, the inferred beaming fractions $\sim 0.1-0.3$ are comparable across bands. In contrast, the values differ by more than a factor of two between H.E.S.S. and HAWC/LHAASO. This discrepancy likely reflects survey-dependent selection effects, including differences in angular resolution and energy range, and is also consistent with the possibility that HAWC/LHAASO selected samples preferentially include older pulsars associated with more extended PWNe than those in the H.E.S.S. sample. We further show that the inferred beaming fractions can be reproduced within a unified framework using a time-dependent opening angle, and that this framework remains compatible with the statistical properties of the observed pulsar population.

We propose a descriptive, realization-centred framework for detecting and characterising explosive and co-explosive behaviour in economic time series, which we term path-explosive behaviour. Departing from the data-generating-process (DGP) perspective that underlies recursive unit root testing, the approach operates directly on observable path properties of the realised series. Four diagnostic layers -- level geometry, growth rate dynamics, normalised curvature, and log-space behaviour -- yield statistics that discriminate between genuine self-reinforcing multiplicative growth and I(2) dynamics without distributional assumptions or asymptotic critical values. Two theoretically motivated absolute gate thresholds screen detected episodes before a composite intensity score is assigned. Co-explosive behaviour between pairs of series is assessed at the episode level through a Jaccard co-occurrence index and non-parametric intensity concordance measures. The theoretical motivation draws on the path dependence and planning irreversibility literatures to argue that, in settings where discrete institutional decisions shape growth trajectories, a realization-centred characterisation is epistemically more appropriate than a DGP-based test. A simulation study across four DGP regimes validates the framework's discriminating power and conservatism. An empirical application to real house prices, commodity prices, public debt, and Spanish tourism destinations illustrates the empirical content of the path-explosive concept and distinguishes it from speculative bubble detection.

Active matter systems characterized by the interplay of chirality and self-alignment offer a rich landscape for the emergence of non-equilibrium collective behaviors and the development of autonomous materials. We present a versatile experimental platform for studying these dynamics using augmented commercial bristlebots, where custom-designed housings and elastic couplings induce a self-aligning torque and a stable chiral drift. By mapping experimental trajectories to a Langevin-type model, we characterize the single-particle dynamics. In circular geometries, we show that the stability of edge currents is governed by the interaction between intrinsic particle chirality and handedness of the edge current. Furthermore, we demonstrate that transport can be geometrically rectified using a nautilus-shaped obstacle, which acts as a doubly chirality-sensitive ratchet. Finally, we explore the collective dynamics of rigidly linked assemblies, observing spontaneous mode-switching between translational and rotational states in triangular active solids. Our results provide a robust framework for the passive control of active gases and illustrate how geometric constraints can be used to program complex transport properties in synthetic active systems.

Computational complexity has been a major challenge in game-theoretic model predictive control (GT-MPC), as real-time solutions to a game (e.g., Nash equilibria (NEs)) have to be computed at each sampling instant of an MPC. This challenge is especially critical in autonomous driving, where interactions may involve many agents, and decisions must be made at fast sampling rates. We show that this challenge can be addressed through time-distributed solution-seeking iterations designed based on, e.g., Newton and Newton--Kantorovich methods. Specifically, the autonomous vehicle decision-making problem is first formulated as a GT-MPC problem. To ensure solution attainability, a potential game framework is adopted. Within this framework, both potential-function optimization and best-response dynamics are used to seek the NE. To enable real-time implementation, Newton and Newton--Kantorovich methods are employed to solve the optimization problems arising in the NE-seeking algorithms, with their iterations distributed over time. Numerical experiments on an intersection-crossing scenario demonstrate that the proposed methods achieve effective real-time performance.

Reliable prediction of the solar cycle is a formidable challenge, yet it is increasingly vital in our technology-dependent society as solar activity drives space weather. Various methods, including precursors, nonlinear curve fitting and extrapolation, statistical and Machine Learning (ML) models, and dynamo and surface flux transport (SFT) models, were implemented to predict past cycles. Analysing about 100 predictions for Solar Cycle 24 and over 130 for Solar Cycle 25, we find that most methods largely failed to predict the peak correctly: Cycle 24 was statistically predicted to be a strong cycle, whereas Cycle 25 was predicted to be a weak cycle. By and large, predictions made only after the cycle began became closer to reality. ML-based models also produced discouraging results. The polar field and its proxy-based predictions are the most physically supported approach to prediction; however, applying them much earlier, before the solar minimum, may yield inaccurate results. Dynamo models are progressively improving both in understanding and in forecasting; however, they need to improve by accurately assimilating the observed polar field data and additional physics, such as meridional flow variations. Solar dynamo theory, complemented by the SFT model and observations, demonstrates that the prediction of a cycle before the time of its previous cycle's maximum is meaningless. The current solar cycle is declining, and the community is now preparing for the prediction of the next cycle. Thus, this review will guide future studies.

We study the production of $^3_Λ$H and $^4_Λ$H in the $^{3,4}$He($K^-$,$π^0$) reactions at $p_{K^-}=1.0$~GeV/$c$ within the distorted-wave impulse approximation, using the optimal Fermi-averaged $K^-p\toπ^0Λ$ amplitude. Because the $^3_Λ$H ground state is extremely weakly bound, the $d$--$Λ$ wave function becomes spatially extended. We calculate the integrated cross sections $σ_{\rm lab}$ and their ratio $R_{34}=σ_{\rm lab}(^3_Λ{\rm H})/σ_{\rm lab}(^4_Λ{\rm H})$ for forward angles $θ_{\rm lab}=0^\circ$--$20^\circ$. The production strength of $^3_Λ$H and the ratio $R_{34}$ are strongly sensitive to the $Λ$ binding energy $B_Λ$, which is constrained to be approximately 0.05--0.15~MeV by comparison with experimental data from the J-PARC E73 experiment. This indicates that the $^3$He($K^-$,$π^0$) reaction provides a sensitive probe of the weak binding of $^3_Λ$H.

We report the experimental implementation of a Data-Driven Chaos Indicator (DDCI) [Y.~Li \emph{et al.}, Nucl.\ Instrum.\ Methods Phys.\ Res.\ A \textbf{1024} (2022) 166060] for online optimization of the National Synchrotron Light Source II (NSLS-II) storage ring. The DDCI quantifies the predictability of electron beam dynamics using turn-by-turn beam position monitor data. A surrogate model of the one-turn map is first trained, and its out-of-sample predictive uncertainty is then employed as a measurable indicator of chaos. By tuning sextupole magnets to mitigate nonlinear effects, a clear enlargement of the dynamic aperture is achieved, accompanied by a corresponding improvement in injection efficiency.

Turbulent thermal convection governs heat transport in systems ranging from stellar interiors to industrial heat exchangers. Two-dimensional Rayleigh-Bénard convection serves as a paradigm for these flows, reproducing key features such as thin boundary layers, large-scale circulation, and sustained plume dynamics. While Matrix Product State (MPS) methods have demonstrated significant compression of isothermal turbulent fields, their application to buoyancy-driven flows with active thermal coupling has remained unexplored. We apply MPS to two-dimensional Rayleigh-Bénard convection with dynamical simulations up to $\mathrm{Ra} = 10^{10}$. An a priori decomposition of DNS snapshots up to $\mathrm{Ra} = 10^{11}$ shows that the bond dimension $χ$ required to represent the flow fields grows without saturation, in contrast to the plateauing of $χ$ reported for velocity fields in isothermal 2D turbulence. Crucially, however, dynamical simulations solving the governing equations directly in the compressed MPS format at fixed $χ$ show that the $χ$ required to recover statistical observables, such as the Nusselt number, scales significantly more favorably with $\mathrm{Ra}$ than the a priori complexity suggests. At $\mathrm{Ra} = 10^{10}$, a relative error of $1.8\%$ in the mean Nusselt number is achieved with a nearly 9-fold reduction in degrees of freedom, using a $χ$ comparable to that required at $\mathrm{Ra} = 10^{9}$. Spectral analysis confirms the progressive recovery of spatial and temporal scales with increasing $χ$. These findings establish MPS as a scalable tool for simulating thermally driven turbulence, suggesting the method may remain viable for investigations of the ultimate regime at substantially higher $\mathrm{Ra}$.

Little Red Dots (LRDs) are some the most intriguing galaxy populations recently identified at z>~4 with JWST. They constitute the most extreme class of a more abundant population of sources with `V-shaped' spectral energy distributions (SEDs) and compact morphologies, which includes also Little Blue Dots (LBDs). Finding brighter analogues to these sources requires surveying sky areas which are significantly larger than those covered with JWST. Euclid deep images are ideally suited for this purpose. We make use of Euclid near-infrared images, complemented by Spitzer Infrared Array Camera (IRAC) data, over 0.75 sq. deg. of the COSMOS field to select a sample of 233 sources with `V-shaped' SEDs at z>4. Out of those, we identify 16 sources with compactness >1sigma above the median of all z>4 galaxies, which we consider robust LRD/LBD candidates in our sample. The stellar masses of these 16 sources are in the range 10^{8.5} - 10^{10.5} Msun, so they are significantly more massive than typical JWST-selected LRDs/LBDs. Interestingly, half of them are about as old as the Universe at their redshifts. In addition, we find that the median photometric properties of the Euclid LRDs/LBDs are similar to those of the so-called Blue Dust-Obscured Galaxies (Blue DOGs). Less than 10% of all our `V-shaped' SED sources, including only one of the Euclid LBDs, correspond to known AGN. The latter mostly constitute a population disjoint to the `V-shaped' SED sources. Spectroscopic follow up of the Euclid LRDs/LBD candidates remains necessary to probe whether they host BLAGN as fainter analogues do and whether constitute a transition phase from these fainter sources to standard AGN.

At long-baseline neutrino experiments, neutral-current (NC) events accumulate in large numbers but are seldom exploited for new physics searches. We demonstrate their potential using non-standard neutrino interactions (NSI) with quarks as a case study. Charged-current (CC) analyses constrain NSI through matter effects on neutrino propagation, which probe almost exclusively the isoscalar combination of up- and down-quark couplings; the orthogonal isovector combination is suppressed by a factor of $\sim$100. Because NSI also modify NC cross sections in a flavor-dependent way, NC events become sensitive to oscillations: the far-to-near detector ratio acquires a dependence on the beam's flavor composition that probes both isoscalar and isovector couplings with comparable weight. Using existing NOvA data and DUNE projections, we derive the first bounded constraints on isovector NSI from a long-baseline experiment and show that combining CC and NC measurements resolves the individual quark couplings, breaking a degeneracy that persists in either analysis alone.

Quantum protocols require classical signaling, and when classical signals propagate faster than quantum ones, standard rate-loss limits can be surpassed. We introduce an all-photonic measurement-device-independent quantum key distribution protocol that exceeds the single-repeater bound without error correction. When quantum signals travel at two-thirds the classical speed, the key rate scaling approaches $η^{2/5}$. We propose a single-rail, temporally multiplexed architecture that extends twin-field-type protocols to multiple nodes and surpasses their key rate without ideal quantum memories.

We study the onset of two-dimensional secondary shear instability (SSI) in the braid regions connecting primary Kelvin-Helmholtz billows in stratified shear flows. While strain induced by the billows stabilises the braids, it also compresses their tilted isopycnals, enhancing baroclinic shear that enables rapid perturbation growth. By modifying the classical analysis of Corcos & Sherman (J. Fluid Mech. 73, 241-264, 1976) in braid-aligned coordinates and adding an additional stability criterion based on the ratio of strain rate to shear, we develop an inviscid, time-dependent model for the braid and the onset of SSI. We show that the criterion for instability can be achieved significantly earlier than the saturation of the primary billow at sufficiently high initial Richardson number Ri, as increased stratification slows billow growth while accelerating baroclinic shear production in the braid. Two-dimensional direct numerical simulations up to Reynolds numbers Re=10^7 quantify the role of viscosity. At high Re, we find that SSI indeed develops early in the braid, as predicted by the inviscid model, while the primary billow is still growing and before viscosity slows braid thinning. These results provide a mechanistic explanation for field observations of braid-dominated mixing and suggest that, at geophysically relevant Ri and Re, SSI can control the three-dimensional turbulent transition and ensuing diapycnal mixing by preceding and pre-empting both vortex pairing instabilities and secondary convective instabilities in the billow core.