The landscape of education is changing rapidly, shaped by emerging pedagogical approaches, technological innovations such as artificial intelligence (AI), and evolving societal expectations, all of which demand thorough evaluation of new educational tools. Although large language models (LLMs) present substantial opportunities especially in Higher Education, their propensity to generate hallucinations and their limited specialized knowledge may introduce significant risks. This study aims to address these risks by examining the practical implementation of an LLM-enhanced assistant in a university level course. We implemented a generative AI assistant grounded in a retrieval-augmented generation (RAG) model to replicate a previously teacher-led, time-intensive exercise. To assess the effectiveness of the LLM, we conducted three separate experiments through iterative mixed-methods approaches, including a crossover design. The resulting data address central research questions related to student motivation, perceived differences between engaging with the LLM versus a human teacher, the quality of AI-generated responses, and the impact of the LLM on students' academic performance. The results offer direct insights into students' views and the pedagogical feasibility of embedding LLMs into specialized courses. Finally, we discuss the main challenges, opportunities and future directions of LLMs in teaching and learning in Higher Education.

We study a public decision problem in which a finite society selects a public-good level from a closed interval. Agents either have single-peaked preferences or are completely indifferent over the interval; the latter capture abstention or a "none of the above" stance within the decision process. We study this augmented single-peaked domain. On this domain, we characterize the class of rules called target rules with a default. We show that onto-ness and pairwise strategy-proofness characterize this class of rules.

Modifications to Newtonian dynamics at low accelerations have long been proposed as an alternative to dark matter to explain galaxy rotation curves. More recently, similar corrections have been invoked to interpret anomalies in Cavendish-type laboratory experiments and in the dynamics of wide binary stars, although the latter remain affected by ongoing observational debate. We show that, if deviations from Newtonian gravity occur in the low-acceleration regime, the available data are broadly consistent with a MOND-like interpretation. In this framework, wide binary systems appear to extend the Tully-Fisher relation, well established for galaxies, to much smaller mass scales. Taken together, departures from Newtonian predictions at low accelerations in galaxies, wide binaries, and laboratory experiments may point to a common physical scenario.

This paper presents results from a vehicle-to-vehicle channel measurement campaign conducted in the millimeter-wave (MMW) frequency bands at center frequencies of 60GHz and 80GHz, each with a bandwidth of 2GHz. The measurements were performed in a dynamic oncoming-vehicle scenario using a time-domain channel sounder with high-resolution data acquisition. Power delay profiles were extracted to study the temporal evolution of multipath components, and the root mean square (RMS) delay spread was analyzed to characterize the temporal dispersion of the channel. The results demonstrate differences between the two frequency bands. At 60GHz, the RMS delay spread is well approximated by a Gaussian distribution with a higher median value, while at 80GHz it follows a lognormal distribution with a lower median. Furthermore, the number of resolvable multipath components was found to be nearly twice as high at 60\,GHz compared to 80GHz, highlighting the impact of antenna beamwidth and frequency-dependent propagation mechanisms.

We perform a data-driven study of the doubly charmed tetraquark candidate $T_{cc}^+$. An ensemble of deep neural network classifiers, trained on synthetic amplitudes with controlled analytic structures, identifies a dominant pole topology characterized by an isolated pole on the $[bt]$ Riemann sheet which is robust against left-hand cut effects. A subsequent pole parameter extraction was performed via the uniformized $\mathcal{S}$-matrix and a complementary $\mathcal{K}$-matrix parameterization, which respectively provides a model-independent baseline and dynamical insight on the pole position and trajectory of the resonant state. Using this two-pronged approach, we submit that the $T_{cc}^{+}$ is a shallow $D^0D^{*+}$ bound state in the second Riemann sheet of the complex plane.

Polarization diversity offers significant flexibility for enhancing integrated sensing and communications (ISAC). However, conventional dual-polarized arrays typically require dedicated radio-frequency (RF) chains for each polarization branch, leading to prohibitive hardware costs. To address this, polarization-reconfigurable (PR) antennas have emerged as a cost-effective alternative, enabling polarization flexibility with reduced hardware complexity by driving two polarization branches with a single RF chain. In this paper, we investigate fairness-aware beamforming for ISAC systems equipped with PR antennas. Specifically, we jointly optimize the transmit beamforming and PR control coefficients to maximize the minimum signal-to-interference-plus-noise ratio (SINR) for communication users and the minimum signal-to-clutter-plus-noise ratio (SCNR) for sensing targets. The resulting problem is highly nonconvex and nonsmooth due to the strong coupling among optimization variables in the max-min objective, as well as the nonconvex spherical constraints imposed by the PR antennas. To tackle this, we derive an equivalent smooth reformulation by introducing auxiliary variables and transforming the minimum operators into inequality constraints. Subsequently, we develop an exact-penalty product Riemannian manifold gradient descent (EP-PRMGD) algorithm, which integrates an exact penalty method with Riemannian optimization to guarantee convergence to a Karush-Kuhn-Tucker (KKT) point. Numerical results demonstrate that the proposed PR-enabled ISAC scheme achieves performance comparable to dual-polarized architectures while utilizing only half the RF chains, thereby validating its effectiveness in balancing fairness and hardware efficiency.

In this paper we will prove a strong version of the celebrated purity of the ramification locus theorem in algebraic geometry. Our key input is a Tor-independence result for global sections of étale schemes over excellent regular local rings, which we will prove by tilting to perfect rings.

We present a phonon-magnon extension for the mumax+ micromagnetic framework that implements three surface acoustic wave (SAW) coupling mechanisms: magnetoelastic strain coupling, magneto-rotation coupling arising from the antisymmetric displacement gradient, and spin-rotation (Barnett) coupling from the lattice angular velocity. Six benchmark simulations validate the implementation through SAW-driven domain-wall motion, magnetization switching, magneto-rotation and Barnett field validation, nonreciprocal SAW-magnon absorption from Rayleigh-wave chirality, and spatially resolved coupling in a standing SAW cavity. For the longitudinal geometry (m_0 parallel to k_SAW), we show that the magnetoelastic coupling produces zero transverse torque despite generating a 50 times larger effective field; the magneto-rotation channel provides the sole driving mechanism. The crossover angle below which MR dominates is theta_c approximately 1.1 degrees for YIG parameters. Treating the magneto-rotation coupling constant K_mr as a tunable parameter, we map out the cooperativity phase diagram and show that MR alone can achieve strong coupling (C = 257 for K_mr = 1 MJ/m^3) with an avoided-crossing splitting of 13.6 MHz.

RISC-V-based Trusted Execution Environments (TEEs) are gaining traction in the automotive and IoT sectors as a foundation for protecting sensitive computations. However, the supporting infrastructure around these TEEs remains immature. In particular, mechanisms for secure enclave updates and migrations - essential for complete enclave lifecycle management - are largely absent from the evolving RISC-V ecosystem. In this paper, we address this limitation by introducing a novel toolkit that enables RISC-V TEEs to support critical aspects of the software development lifecycle. Our toolkit provides broad compatibility with existing and emerging RISC-V TEE implementations (e.g., Keystone and CURE), which are particularly promising for integration in the automotive industry. It extends the Security Monitor (SM) - the trusted firmware layer of RISC-V TEEs - with three modular extensions that enable secure enclave update, secure migration, state continuity, and trusted time. Our implementation demonstrates that the toolkit requires only minimal interface adaptation to accommodate TEE-specific naming conventions. Our evaluation results confirm that our proposal introduces negligible performance overhead: our state continuity solution incurs less than 1.5% overhead, and enclave downtime remains as low as 0.8% for realistic applications with a 1 KB state, which conforms with the requirements of most IoT and automotive applications.

Tangle structure trees, introduced in [3], offer a unified data structure that displays all the tangles of a graph or data set together with certificates for the non-existence of any other tangles, either locally or overall. In this paper we apply tangle structure trees to derive new versions of the two fundamental tangle theorems: the tree-of-tangles theorem, and the tangle-tree duality theorem. We extend the tree-of-tangles theorem to $\mathcal F$-tangles that need not be profiles. When $\mathcal F$ consists of stars of separations, as it does in classical tangle-tree duality theorems, we show how to convert tangle structure trees that certify the non-existence of $\mathcal F$-tangles into tree-decompositions that certify this in the way known from graph tangles, as $S$-trees over~$\mathcal F$.

Klimošová, Piguet, and Rozhoň conjectured that any graph with minimum degree $k/2$ and sufficiently many vertices of degree $k$ should contain all trees with $k$ edges. We prove an asymptotic version of this conjecture for dense host graphs. We obtain interesting corollaries: the first is an asymptotic version of the Erdős--Sós conjecture for dense host graphs, which works without any bounded-degree restriction on the guest trees. Secondly, by leveraging recent results by Pokrovsky, we can translate our results to sparse host graphs in the case of bounded-degree guest trees.

We investigate the optical properties of neutral excitons in CdTe/ZnTe quantum dots containing a single Ni2+ ion. We show that the photoluminescence spectra provide a direct spectroscopic signature of strain induced mixing of the Ni2+ spin states. A misalignment between the principal axis of the local strain tensor and the quantum dot growth direction reorients the spin quantization axis of the magnetic ion, reducing the hole Ni2+ exchange interaction at low magnetic field and giving rise to photoluminescence replicas around the partially linearly polarized bright-exciton transitions. A longitudinal magnetic field restores the circularly polarized optical selection rules, allowing the three spin projections S_z = 0, +-1 of the Ni2+ ion to be spectrally resolved. Dark exciton emission appears on the low energy side of the spectra and is dominated at low field by transitions involving spin flips of the magnetic ion. An effective spin Hamiltonian including strain orientation and valence band mixing reproduces the magnetic field evolution of both bright and dark exciton spectra. These results highlight the key role of the local strain environment in determining the spin exciton coupling of transition metal dopants in semiconductor quantum dots.

We present a self-contained investigation on the local and global well-posedness for a system of nonlocal advection--diffusion equations for a heterogeneous population over $\mathbb{R}^d$, $d \in \mathbb{N}$. Each convolution kernel $K_{ij}$, which describes the nonlocal advection of species $i$ according to the distribution of species $j$, is assumed to have its own regularity $\nabla K_{ij} \in L^{q_{ij}}(\mathbb{R}^d),\, 1 < q_{ij} < \infty$. Local well-posedness of the mild solution and its regularity is obtained using semigroup theory and contraction mapping arguments. For families of kernels classified as regular, a global bound is established using a Nash-type inequality. For suitable irregular families of kernels, global boundedness is instead obtained via a smallness condition on the initial data. A one-dimensional numerical example is provided to illustrate the influence of kernel regularity on the solutions.

We study photonic meta-atoms, a unique class of composite solitary wave, supported in nonlinear waveguides. We establish an analogy to one-dimensional soft-core atoms, allowing to describe the complex dynamics via concepts from atomic physics. Higher-order dispersive effects cause specific spectral resonances characteristic for the eigenspectrum of a meta-atom. We demonstrate that subtle changes in this level spectrum causes frequency shifts of the resonances. These shifts consist of isotopic and isomeric contributions that can be distinguished in terms of a simple model. We further demonstrate a generic mechanism that causes a Zeeman-like splitting of resonance lines.

In this paper we consider a family of time-dependent 1-dimensional cubic Schrödinger equation (NLS) with periodic potential. Exploiting semiclassical scaling and multiscale analysis, we derive an effective nonlinear Dirac equation, which describes the dynamics of solutions to NLS spectrally localized around Dirac points.

These lecture notes contain an introduction to quantum simulation of bosonic systems in the continuum, focusing on weakly interacting Bose-Bose mixtures with competing mean-field interactions. When the values of such interactions are fine-tuned to almost completely cancel the mean-field energy, quantum fluctuations become apparent and dominate the behavior of the system, stabilizing an ultradilute quantum liquid phase. An analogous situation appears in single-component dipolar quantum gases. We review the mechanism that gives rise to this exotic quantum liquid, which can form droplets that are self-bound in the absence of any external confinement, and discuss their properties and dynamics in both the mixture and the dipolar cases. In dipolar gases, arrays of dipolar droplets stabilized by quantum fluctuations can establish global phase coherence and form supersolids. In bosonic mixtures, supersolidity can emerge already at the mean-field level through spin-orbit coupling. We discuss the properties of such spin-orbit-coupled supersolids, comparing them to their dipolar counterparts. Specifically, we focus on their periodic density modulation, phase coherence, and peculiar excitation spectrum, which hosts both superfluid and crystal excitations. Finally, we conclude by discussing open research directions in the areas of quantum liquid droplets and spin-orbit-coupled supersolids, in particular at the interface of the two research topics.

Integrated sensing and communication (ISAC) has emerged as a key paradigm for next-generation wireless systems, which allows wireless resources to be used for data transmission and target sensing simultaneously. In this paper, multi-user collaborative target detection in the uplink ISAC system is investigated. To incorporate the target sensing functionality, the system relies on the reuse of uplink signals from the communication users. Specifically, we analyze an uplink multi-user single-input multiple-output (MU-SIMO) communication system with bistatic sensing. Using the channel statistics, we formulate the problem of joint optimal pilot and data power allocation to maximize the uplink ergodic sum rate while meeting communication and sensing quality-of-service (QoS) requirements. To address this non-convex problem, we propose an alternating optimization (AO)-based iterative framework, where the joint power allocation problem is decomposed into two sub-problems. Specifically, the pilot power allocation is optimized using a penalty dual decomposition (PDD)-based gradient ascent algorithm, while the data power allocation is solved via successive convex approximation (SCA). Once the long-term power allocation is determined, the base station (BS) estimates the instantaneous channels using a minimum mean-squared error (MMSE) estimator. Subsequently, based on the estimated instantaneous channel state information (CSI), the receive beamforming for communication users is optimized via another SCA-based method to maximize the sum rate. Meanwhile, the optimal receive beamforming for the target is obtained in closed-form through eigenvalue decomposition (EVD).

We propose a general method for preparing stabilizer states with reduced two-qubit gate count and depth compared to the state of the art. The method starts from a graph state representation of the stabilizer state and iteratively reduces the number of edges in the graph using two-qubit Clifford gates to produce a unitary preparation circuit. We explore various heuristic search and AI-based approaches to optimally choose Clifford gates at each step, the most sophisticated of which is a combination of reinforcement learning and Monte Carlo tree search that we call QuSynth. We apply our method to synthesize code states of various quantum error correcting codes including the 23-qubit Golay code and the 144-qubit gross code, the latter of which is significantly beyond the qubit number that is accessible to prior optimal circuit synthesis methods. We demonstrate that our techniques are capable of reducing the required two-qubit gates by up to a factor of 2.5 compared to previous approaches while retaining low circuit depth.

Finite size fluctuations are a crucial ingredient in kinetic theory of long-range interacting collisionless systems. In this Letter, we introduce a phenomenological theory which predicts an anomalous scaling close to marginal stability for these fluctuations. It also pinpoints the critical window inside which the fluctuations are anomalous, and outside which they are Gaussian. Shrinking very slowly as $N^{-1/5}$, this critical window encompasses a wide region around marginal stability. We confirm our predictions through extended numerical simulations on two different simplified models.

We compute the p-widths, $\{ω_p\}$, for the hemisphere with the standard round metric. This provides the first example of a manifold with boundary for which the $p$-widths are known for all $p$.

High-stakes auctions are often preceded by nonbinding communication between bidders and the seller. Motivated by these practices, this paper examines a two-period model in which two bidders send private cheap talk messages to the seller about their valuations, and the seller decides in the second period whether to run a mechanism or take an outside option that disappears if she chooses to run the auction. The seller has commitment within any mechanism she chooses to run, but no commitment over how she uses any information communicated. Despite having potentially asymmetric posteriors after the communication stage, the seller cannot run discriminatory auctions in equilibrium. Under some natural restrictions, any bidder-symmetric perfect Bayesian equilibrium of this model is a threshold equilibrium where the seller runs a second-price auction with a single reserve if and only if both bidders are above the threshold. The seller is better off being able to commit to the restricted class of mechanisms where she must choose a single reserve price.

We study the coalescence of identical viscous blisters beneath an elastic sheet both experimentally and numerically. Using a time-resolved synthetic schlieren technique, we measure the evolution of the thickness field of the merging blisters and more specifically the dynamics of the coalescence region. To explain this dynamics, we develop a one-dimensional model based on the lubrication approximation, from which we derive scalings to predict the growth of the coalescence neck. We also numerically solve the full non-linear equation to assess the theory and compare to experiments. Our model illustrates that, at short times, the dynamics of coalescence is mainly controlled by the bending of the elastic sheet, leading to a relationship between the coalescence speed and the radius of curvature of the interface at the coalescence neck.

We investigate the orbital evolution of a classical charged particle around a Schwarzschild black hole immersed in an external, uniform magnetic field, taking into full account both local radiation-reaction and the nonlocal tail self-force arising in curved spacetime. Starting from the DeWitt-Brehme equation and its Landau-Lifshitz reduction, we derive analytic expressions for the conservative and dissipative components of the electromagnetic self-force in both the weak-field (Newtonian) and strong-field regimes. By implementing backward-in-time integration of the third-order DeWitt-Brehme equation alongside the second-order Landau-Lifshitz equation, we demonstrate that the so-called orbital widening effect persists even when the tail term is included, and that for astrophysically realistic charge-to-mass ratios the tail contribution to the trajectory is negligible. We further show that this widening is directly controlled by the product of the magnetic field and radiation-reaction parameters and can be captured in the Newtonian limit. Finally, we identify a scaling symmetry showing that simulations with moderate parameter values can accurately represent the dynamics in realistic astrophysical conditions, confirming that orbital widening is a robust phenomenon that can persist even in astrophysical black hole environments.

We establish Bernstein-type theorems for entire constant mean curvature graphs in the three-dimensional light cone $\mathbb{Q}^3_+$ over the horosphere under the assumption that the Gaussian curvature $K$ is bounded below, by showing that such graphs are horospheres or spheres of $\mathbb{Q}^3_+$.

Quantum computing often requires classical data to be supplied to execution environments that may not be fully trusted or isolated. While encryption protects data at rest and in transit, it provides limited protection once computation begins, when classical values are encoded into quantum registers. This paper explores data obfuscation for protecting classical values during quantum computation. To the best of our knowledge, we present the first explicit data obfuscation technique designed to protect classical values during quantum execution. We propose an obfuscation technique that encodes sensitive data into structured quantum representations across multiple registers, avoiding direct exposure while preserving computational usability. Reversible quantum operations and amplitude amplification allow selective recovery of valid encodings without revealing the underlying data. We evaluate the feasibility of the proposed method through simulation and analyze its resource requirements and practical limitations. Our results highlight data obfuscation as a complementary security primitive for quantum computing.

We study the relation between additivity and deduction theorems in the algebraic semantics of congruential modal logic. Additivity of the modal operator is well-known to imply the local deduction-detachment theorem. Our main theme is that deduction properties of modal logic persist far beyond the additive setting. We introduce the notion of a strongly non-additive variety, and then we prove that there are continuum many strongly non-additive minimal discriminator varieties of Boolean frames; equivalently, continuum many strongly non-additive maximal congruential modal logics with deduction-detachment theorem. Moreover, every normal modal logic can be transformed, in an injective way, into a strongly non-additive one while preserving the (local) deduction theorem. Finally, we show that neither the class of congruential modal logics with the local deduction theorem nor its complement is elementary.

Recent advances in artificial intelligence (AI) and natural language processing (NLP) have enabled tools to support systematic literature reviews (SLRs), yet existing frameworks often produce outputs that are efficient but contextually limited, requiring substantial expert oversight.The framework employs a human-in-the-loop process to define sub-SLR tasks, evaluate models, and ensure methodological rigor, while leveraging structured knowledge sources and retrieval-augmented generation (RAG) to enhance factual grounding and transparency. LR-Robot enables multidimensional categorization of research, maps relationships among papers, identifies high-impact works, and supports historical, fine-grained analyses of topic evolution. We demonstrate the framework using an option pricing case study, enabling comprehensive literature analysis. Empirical results reveal the current capabilities of AI in understanding and synthesizing literature, uncover emerging trends, reveal topic connections, and highlight core research directions. By accelerating labor-intensive review stages while preserving interpretive accuracy, LR-Robot provides a practical, customizable, and high-quality approach for AI-assisted SLRs. Key contributions: (1) a novel framework combining AI and expert supervision for contextually informed SLRs, (2) support for multidimensional categorization, relationship mapping, and fine-grained topic evolution analysis, and (3) empirical demonstration of AI-driven literature synthesis in the field of option pricing.

In this paper we characterize the limiting behavior of the principal eigenvalue, $\s_1[-\D,\b,Ø]$, of the boundary value problem \eqref{1.1} as the Lebesgue measure of the underlying domain, $Ø$, tends to zero. Naturally, the domains $Ø$ are assumed to be included on a fixed open set $D$ such that $\b\in\mc{C}(D)$, and they satisfy $\barØ\subset D$. Our main result establishes that, in the classical case when $\inf_{D}\b >0$, $$ \lim_{|Ø|\da 0}\s_1[-\D,\b,Ø] =+\infty, $$ whereas $$ \lim_{|Ø|\da 0}\s_1[-\D,\b,Ø] =-\infty\;\;\hbox{if}\;\; \sup_{D}\b <0, $$ which is a surprising result at the light of the classical existing theorems for Dirichlet boundary conditions. Furthermore, in the special case when $\b>0$ is a constant, we can prove that $$ \lim_{R\da 0}\left( R \s_1[-\D,\b,B_R]\right)=\b \frac{\mathrm{Area}(\p B_1)}{|B_1|}, $$ where, we are denoting $B_\varrho:=\{x\in\R^N\;:\;|x|<\varrho\}$ for all $\varrho>0$.

The chiral-induced spin selectivity (CISS) effect describes an observed correlation between the orientation of an electron spin transported or transferred through a molecule and that molecule's chirality. Suitable molecules are usually arranged as self-assembled monolayers (SAMs), and the primary CISS systems are based on multiple nanometer-long biomolecules exhibiting helical chirality. Aside from these typically thiolate-anchored molecules, phosphonic and phosphoric acid SAMs may well become significant for those CISS applications that require a more robust molecular coupling to metal oxide surfaces. In this work, we report on our studies, employing the aromatic, low-molecular-mass, axially chiral organophosphoric acid derivative 1,1'-binaphthyl-2,2'-diyl hydrogenphosphate (BNP). Grown as a roughly 1 nm thin SAM on top of a NiOx/Ni substrate, a strong circular dichroism signal indicates that the thin films preserved chirality. The CISS response exhibits a high magnetoresistance with a spin polarization of 50-80% when measured using magnetic-conductive atomic force microscopy. For biases above 0.5 V, the magnetoresistance curves could be well fitted to the Fowler-Nordheim (FN) tunneling model. Using a minimal FN model, we determined that, depending on the magnetization direction and the handedness of the molecules, electrons of a certain spin direction face an effective tunneling barrier at high bias, which is either 80 % higher or 40 % lower compared to the barrier for electrons of the opposite spin direction. Due to the small size of the molecules, their compatibility with oxide materials, and their commercial availability, they are excellent candidates for the realization of novel (nanoscale) organic spintronic devices.

We introduce six independent trivariate bicycle (ITB) codes, which extend the bivariate bicycle framework of Bravyi et al.\ to three cyclic dimensions. Using asymmetric polynomial pairs on three-dimensional tori, we construct four codes including a $[[140,6,14]]$ code with $kd^2/n = 8.40$. In the code-capacity setting, the $[[140,6,14]]$ code achieves a pseudothreshold of $8.0\%$ and $kd^2/n = 8.40$, exceeding the best multivariate bicycle code of Voss et al.\ ($7.9\%$, $kd^2/n = 2.67$). With circuit-level depolarizing noise, pseudothresholds reach $0.59\%$ for $[[140,6,14]]$ and $0.53\%$ for $[[84,6,10]]$. On the SI1000 superconducting noise model, the $[[140,6,14]]$ code achieves a per-round per-observable rate of $5.6 \times 10^{-5}$ at $p = 0.20\%$. We additionally present two self-dual codes with weight-8 stabilizers: $[[54,14,5]]$ ($kd^2/n = 6.48$) and $[[128,20,8]]$ ($kd^2/n = 10.0$). These results expand the design space of algebraic quantum LDPC codes and demonstrate that the third cyclic dimension yields competitive candidates for practical fault-tolerant implementations.