Bluetooth Low Energy (BLE) is widely used in IoT systems because of its low power consumption, interoperability, and reliable bidirectional communication. However, its connection-oriented architecture introduces trade-offs among wake-up latency, throughput, and energy efficiency, limiting its suitability for burst-mode and on-demand sensing applications. Enhanced ShockBurst (ESB), a lightweight connectionless protocol supported by the same 2.4 GHz Nordic Semiconductor hardware, enables fast wake-up and efficient data transmission, but does not provide BLE-level robustness for sustained bidirectional communication. This work systematically benchmarks BLE and ESB on a unified Nordic nRF54L15 platform and proposes Enhanced-BLE, a hybrid framework that integrates the two protocols to extend conventional BLE operation. Experimental results show that ESB nearly halves packet transmission time and energy compared with BLE, doubles the achievable forward throughput, and reduces wake-up latency and energy by nearly twentyfold during intermittent operation. However, ESB reverse transmission may suffer packet loss, whereas BLE maintains reliable bidirectional communication. Enhanced-BLE addresses this trade-off through adaptive radio scheduling and coexistence-aware connection management, combining ESB-based high-throughput forward transmission with BLE-based reliable reverse communication. The framework enables BLE-to-ESB handover within approximately 18 ms and restores BLE operation within 49 ms from standby mode. Enhanced-BLE also achieves approximately twofold higher forward throughput than BLE while reducing wake-up latency. These results demonstrate a practical and hardware-compatible strategy for low-latency, high-throughput, energy-efficient, and reliable 2.4 GHz IoT communication.

The region connection calculus ($RCC$) and Allen's interval algebra ($IA$) are two well-known NP-hard spatial-temporal qualitative reasoning problems. They are solvable in $2^{O(n \log n)}$ time, where $n$ is the number of variables, and $IA$ is additionally known to be solvable in $o(n)^n$ time. However, no improvement over exhaustive search is known for $RCC$, and if they are also solvable in single exponential time $2^{O(n)}$ is unknown. We investigate multiple avenues towards reaching such bounds. First, we show that branching is insufficient since there are too many non-redundant constraints. Concretely, we classify the maximum number of non-redundant constraints in $RCC$ and $IA$. Algorithmically, we make two significant contributions based on dynamic programming (DP). The first algorithm runs in $4^n$ time and is applicable to a non-trivial, NP-hard fragment of $IA$, which includes the well-known interval graph sandwich problem of Golumbic and Shamir (1993). For the richer $RCC$ problem with 8 basic relations we use a more sophisticated approach which asymptotically matches the $o(n)^n$ bound for $IA$.

We show that the log-determinant of leading principal minors of large non-Hermitian random matrices converges in distribution to a 2+1 dimensional Gaussian field, which is logarithmically correlated for the parabolic distance, reminiscent to the Edwards-Wilkinson universality class.

This paper presents a method to approximate regions of attraction of unknown nonlinear dynamical systems from data. Assuming point-wise evaluations of the vector field and known Lipschitz bounds, a polyhedral uncertainty set of admissible dynamics is constructed. This uncertainty description enables the synthesis of a continuous piece-wise affine Lyapunov candidate via a linear program, enforcing a robust decrease condition for all admissible vector fields. The approach allows certification of a region of attraction consistent with the available data. Numerical examples illustrate the effectiveness of the proposed method in extracting certified regions of attraction from sparse data.

We theoretically investigate the formation and dynamics of bright exciton-polariton solitons within systems engineered to support Bound States in the Continuum. By employing a driven-dissipative Gross-Pitaevskii equation coupled with a rate equation for the excitonic reservoir, we demonstrate that BICs provide a robust platform for stabilizing the condensate against radiative decay. Utilizing a Lagrangian variational approach, we derive analytical expressions describing the trajectory and velocity of these bright solitonic excitations. Notably, we find that the propagation of these BIC-engineered solitons exhibits a distinct self-deceleration, eventually bringing them to a halt at a final position dictated by the initial conditions and intrinsic system parameters. Furthermore, we analyze the dynamical stability of these solitons. Our findings offer valuable insights into the manipulation of polaritonic flows in non-Hermitian systems.

Speculative decoding and dynamic sparse attention are two complementary approaches for accelerating long-context LLM inference: the former amortizes target-model execution across multiple verifier queries, while the latter reduces each query's KV-cache working set. Directly combining them, however, exposes a structural mismatch: speculative verification relies on cross-query commonality, whereas dynamic sparse attention assigns query-specific sparse layouts. This mismatch limits KV-block reuse, amplifies NSA's branch-wise overheads, and makes verification strategy selection input- and regime-dependent. We present SSV, a sparse speculative-verification framework that turns dynamic sparse attention into a verification-oriented workload. SSV combines overlap-aware grouped-query execution, refresh/reuse-based NSA kernel fusion, and profile-guided prompt-adaptive orchestration to improve cross-query reuse, reduce selected-index and branch-fusion overheads, and select effective draft-verification strategies under user-specified precision classes. Experiments on NVIDIA H100 GPUs show that SSV achieves up to 3.49x end-to-end throughput over autoregressive NSA decoding and up to 6.86x kernel speedups for sparse speculative verification.

We analyze a simple variant of the Goldfarb-Idnani (GI) dual active-set method for computing variational generalized Nash equilibria of strongly monotone N-player games with convex quadratic costs and shared affine inequality and equality constraints. We show that several properties of the GI algorithm are maintained in spite of having a possibly non-symmetric pseudogradient matrix in the joint KKT system of the game, although convergence to an existing equilibrium is not guaranteed as in the original algorithm. Our numerical results show that the method is potentially competitive with alternative state-of-the-art algorithms, including for computing solutions of game-theoretic linear model predictive control laws.

We explicitly present all coupling conditions required for tree-level unitarity (tree unitarity) in theories with a finite number of massive and massless particles of spin up to 1. They allow us to diagnose tree unitarity of a system using only its particle content in the mass basis, without reconstructing the full Lagrangian. We show that all four-point amplitudes whose high-energy growth is canceled by tree unitarity conditions are on-shell constructible, thereby motivating the recursive construction of four-point amplitudes. By examining their high-energy growth, we derive tree unitarity conditions for four-point amplitudes. Imposing these conditions to simplify the Lagrangian structure, we use the Stückelberg formulation to derive the tree unitarity conditions arising from all higher-point amplitudes. We show that all tree unitarity conditions are fully captured up to five-point amplitudes, ensuring no necessity of examining higher-point ones. We apply our results to systematically examine tree unitarity conditions in the dark sector with a massive dark photon and dark matter particles of spin up to 1, and extract the essential features for mass generation in the massive dark photon case. In addition, we show that our results allow us to conclude that theories without scalars require an infinite tower of vectors and fermions for tree unitarity. Finally unitarity and related issues in the Higgs portal VDM are discussed in brief.

For a finite group $Γ$, acting on a finite group $G,$ we find necessary conditions for which the first $Γ_0$-equivariant Hochschild cohomology of the group algebra $kG$ is non-trivial, where $k$ is a field of characteristic $p$ dividing the order of $G$ and $Γ_0$ is the stabilizer subgroup in $Γ$ of some element in $G.$ For any field $k$ we show that the $Γ$-equivariant Hochschild cohomology of $Γ$-algebras with coefficients in a $Γ$-equivariant bimodule (Jensen, 1996) is isomorphic with some $kΓ$-relative $\operatorname{Ext},$ in the context of relative homological algebra.

Large Language Models (LLMs) have recently shown remarkable progress in code generation, yet their ability to construct complete software repositories from scratch remains poorly understood. A fundamental bottleneck is the lack of verifiable and scalable evaluation: existing benchmarks either focus on patch-based editing or rely on human or LLM-based judgments, which introduce bias and limit reproducibility. In this work, we present RepoZero, the first benchmark that enables fully automated, execution-based verification of repository-level generation from scratch. Our key idea is to reformulate generation as repository reproduction: given only API specifications, an agent must re-implement an entire repository such that its behavior matches the original implementation. This design allows for strict black-box validation via output equivalence, while naturally supporting large-scale construction by reusing existing open-source repositories. To further mitigate data leakage and shortcut solutions, we introduce cross-language constraints and a sandboxed evaluation protocol. Building on this benchmark, we propose an Agentic Code-Test Evolution (ACE) framework that performs iterative test generation and error-driven refinement, enabling effective test-time scaling for repository-level synthesis. Extensive experiments across multiple state-of-the-art LLMs and agent frameworks reveal that even the strongest LLM agents achieve only limited pass rates (30\% - 55\%), exposing a substantial gap between current capabilities and real-world software development requirements. Our results establish RepoZero as a challenging, scalable, and reliable testbed for end-to-end code generation, and highlight self-verification via test generation as a critical direction for advancing LLM-based coding agents.

We investigate the class of continuous-state branching processes with interaction driven by a Lévy-Khintchine type drift (CBDI). These $[0,\infty]$-valued processes capture both dynamics of branching and density-dependence, allowing for cooperation at low population sizes and competition at high densities. Although the interaction breaks the branching property, the Lévy--Khintchine form of the drift induces a Laplace duality. This duality expresses the Laplace transform of a CBDI process in terms of that of another CBDI process, in which the branching and drift-interaction mechanisms are exchanged. The process, stopped upon hitting either boundary $0$ or $\infty$, is uniquely characterized in law by these mechanisms. A Fellerian extension is constructed when the drift is non-Lipschitz and sufficiently strong at a boundary, allowing the process to leave this boundary continuously and possibly re-enter it. We identify parameters, defined in terms of the mechanisms and their associated scale function and potential measure, that determine the boundary behavior at $0$ and $\infty$ (entrance, exit or regular). Settings exhibiting all regimes, including regular-for-itself and non-sticky boundaries, arise when the mechanisms are assumed to be regularly varying. Our approach combines Laplace duality and comparison principles. The duality facilitates the analysis of semigroups and the construction of sharp Lyapunov functions. Comparisons ensure monotonicity and convergence properties of first-passage times.

In this paper, a low-complexity approach for the automorphism ensemble decoder (AED) using successive cancellation (SC) as constituent decoders is proposed. The approach sequentially activates sub-decoders and terminates the decoding process based on pre-optimized parameters, derived from the strong correlation observed between the decoding outcome and the SC path metric. An algorithm is proposed to find a list of early termination thresholds that minimize average decoding complexity subject to a block-error rate (BLER) constraint. For various code parameters and a BLER below $10^{-3}$, simulation results show that average decoding complexity is reduced by a factor of at least $6 \times$, and up to $22 \times$, compared to the original AED complexity, with a negligible degradation in BLER.

Finite local Hilbert-space truncations arise naturally in quantum simulations of lattice field theories and motivate qudit encodings, but their fault-tolerant advantage over qubit encodings remains unclear. We compare the non-Clifford cost of implementing quadratic diagonal evolutions, exemplified by $U=e^{-itϕ_x^2}$ in a uniform field-amplitude discretization of a real scalar field, using either one logical $d$-level qudit or $n_b=\lceil \log_2 d\rceil$ logical qubits. We analyze two standard settings: product-formula simulation and LCU/block encoding, taking the resource metric to be the number of non-Clifford gates after synthesis into a discrete logical gate set. Because tight synthesis bounds for general single-qudit rotations are not known, we express the qudit constructions in terms of embedded two-level $SU(2)$ rotations and derive explicit finite-$d$ break-even conditions for their synthesis cost; these serve as compiler targets for when qudit encodings can outperform the qubit baseline. Within the constructive models studied here, product-formula implementations would require an exponentially stronger per-primitive synthesis advantage for qudits to win asymptotically, while in the LCU setting the qubit encoding is asymptotically cheaper in $d$. Nevertheless, the finite-$d$ threshold analysis identifies low dimensional regions in which qudits can yield meaningful constant-factor savings, particularly for LCU-based implementations. As a secondary analysis of the LCU construction, we use an idealized negligible-overhead qubit-qudit code-switching model to give an absolute $T$-count comparison, and reinterpret the savings as an allowable per-switch overhead budget.

Solar eruptions are sudden ejections of coronal mass and magnetic fields accompanied by intense energy release. The eruptive structure does not always erupt successfully, but sometimes fails to escape the Sun after initiation. The failure of an eruption, however, provides an invaluable opportunity for understanding the intricate mechanism of eruptions. We present a comprehensive observation of a failed prominence eruption on the Sun, taking advantage of multi-viewpoint and multi-messenger imaging. Simultaneous off-limb and on-disk observation gives evidence of magnetic reconnection processes occurring at different sites during the flare. Particularly, in addition to the standard flare reconnection behind the eruption, strong external reconnection occurs on the erupting flux rope, evidenced by a wealth of signatures via multi-wavelength imaging and spectroscopy. The two reconnection processes may play contrasting roles in the flux rope's acceleration and compete in altering the magnetic flux in the rope. As the high rate of external reconnection proceeds, the flux rope and embedded prominence decelerate noticeably and fail to erupt into the heliosphere, under strong magnetic confinement of overlying fields. Our results illustrate a well-defined physical picture for solar eruptive activities and provide insight into the lack of coronal mass ejections found in other solar-type stars.

Planar germanium heterostructures are promising hosts for hybrid quantum devices due to their compatibility with superconductors, low material disorder, and relaxed fabrication constraints. Also, the potentially low density of nuclear spins and strong spin-orbit interaction make germanium attractive for coherent spin physics. However, recent microwave spectroscopy experiments were unable to resolve a spin-splitting of bound states in germanium Josephson junctions, the prerequisite for defining and controlling Andreev spin qubits. Here, we argue that compressive strain is the key mechanism suppressing spin splitting in current devices. Furthermore, we propose unstrained and tensile-strained heterostructures, fully compatible with state-of-the-art growth technology, that significantly enhance the relevant spin-orbit effect. By numerically simulating ballistic Josephson junctions, we predict spin splittings comfortably in the GHz range, more than 2 orders of magnitude larger than compressively strained cases, and all-electric quantum gates in a hundred nanoseconds. Our results establish strain engineering as a key design principle for realizing Andreev spin qubits in germanium-based devices.

We prove that any closed, convex hypersurface in an $(n+1)$-dimensional Riemannian manifold with $\lceil \frac{n}{2} \rceil$-positive curvature operator is a rational homology sphere with finite fundamental group. The same conclusion holds for any $\lceil \frac{n}{2} \rceil$-convex hypersurface, provided that the mean curvature satisfies a sharp pinching condition. Both results follow from more general vanishing and estimation theorems for the Betti numbers of closed $q$-convex immersed hypersurfaces in $(n+1)$-dimensional Riemannian manifolds, under a lower bound on the average of the smallest $(n-p)$ eigenvalues of the curvature operator.

Traditional step-stress accelerated life testing models assume that test units originate from a homogeneous population. Recently, Lu and Kateri (2025) proposed a heterogeneous cumulative exposure based SSALT model to account for the inhomogeneous aging patterns among test units belonging to the same production batch. This paper introduces an alternative yet flexible failure-rate based heterogeneous simple SSALT (h-SSALT) model with Weibull-distributed Type-II censored failure times, allowing heterogeneity to emerge at the second stress level through a finite mixture of m latent subgroups, each characterized by its own failure behavior. The expectation-maximization algorithm is developed for maximum likelihood estimation of the model parameters, exploiting the incomplete data structure arising from both unknown group membership and Type-II censoring. Interval estimation is performed using the missing information identity of Louis (1982) with transformation-based confidence intervals respecting parameter constraints. An extensive simulation study evaluates the finite-sample performance of the proposed estimators and demonstrates, through a quantile-based comparison, that ignoring population heterogeneity leads to systematic bias in lifetime predictions across the entire quantile range, with the most severe consequences at early failure quantiles of direct relevance to warranty period design. A special case comparison confirms that the proposed Weibull failure-rate based formulation reduces to the existing model of Lu and Kateri (2025) when the shape parameter equals unity, validating the proposed framework as a proper generalization. The practical application of the model is further illustrated through simulated and real data analysis examples.

We describe an implementation of the biset category of finite groups as a tower of standard categorical constructions, all of which are implemented in the software projec t CAP for algorithmic category theory. In particular, we describe the composition of bisets as a composition in a Kleisli category of some biadjunction monad. This composition relies on the universal property of the coequalizer completion of a group viewed as a groupoid on one object. Expressing this universal property offers an elegant categorical interpretation of the Schreier-Sims orbit algorithm. Indeed, the implementation relies on every aspect of the algorithm.

The high-frequency gravitational-wave band is often discussed primarily in the context of new physics, but realistic Standard-Model foregrounds remain incompletely characterized. We investigate pulsar polar caps as a physically motivated astrophysical source of high-frequency gravitational waves, generated by repeated discharge cycles in compact near-surface plasma gaps. Our baseline result is population-level: we construct the signal from the Galactic normal-pulsar population rather than from a single especially favorable object. To do so, we calibrate the source dynamics with particle-in-cell simulations performed at real physical scales, with physical pulsar parameters mapped directly onto numerical scales, and then lift the resolved longitudinal discharge to a cap-scale emission model. The gravitational-wave signal is computed in a full Fourier-space framework, retaining finite-source, geometric, and polarization effects explicitly. Within this treatment, the dominant contribution is not the purely electric channel emphasized in some earlier simplified approaches, but a source channel involving the large background magnetic field and discharge-induced transverse fluctuations of magnetic field. Integrating this description over a normal-pulsar population, we find an astrophysical foreground in the MHz-scale high-frequency band that can overlap with and partially obscure the thermal gravitational-wave signal sourced by the plasma of the early Universe. At the same time, the normalization remains sensitive to the modeled assumptions. Although the predicted strain remains far below current experimental sensitivity, pulsar polar caps provide a concrete Standard-Model foreground benchmark in a band often treated as nearly background-free. Alternative source configurations further broaden the plausible signal range around this baseline.

We propose a novel way of detecting gravitons using emission of photons from charged array of quantum harmonic oscillators placed inside of a cavity while the cavity is being pumped with low frequency photons. We observe that when the detector is in its ground state, a single graviton is absorbed by the detector while it jumps a single energy level by simultaneously emitting a photon. We also observe that while the detector de-excites from an higher energy level, it spontaneously emits a high frequency graviton, by absorbing a single photon. This analytical outcome encourages us to propose a very simple tabletop graviton detector model as the transition probabilities can be significantly enhanced by pumping photons in the initial state of the system. This mechanism gives us a physical way to `visualize' the effect of gravitons with a relativistic system. We also show that Dyson's original argument on the non-detectability of gravitons can be completely circumvented using our proposed graviton detector.

Nonlinear optical processes, mediated by multiphoton interactions rather than single-photon response, are routinely exploited to enable a range of light-based functionalities in devices and applications. Nonlinear effects are enhanced through higher intensity fields, which is a limiting strategy owing to potential radiation damage. An alternative strategy relies on the fluctuation redistribution typical of quantum light, but experimental demonstrations at the most fundamental level have been limited. Here we report experimental nonlinear tunnelling ionization of isolated atoms, a pivotal nonlinear process that drives high-harmonic generation and forms the basis of attosecond science, boosted by quantum light -- bright squeezed vacuum (BSV). A BSV light with an average pulse energy of 300 nJ achieves an effective intensity equivalent to that of a coherent light with 7.1 {\textmu}J, demonstrating a more than 20-fold quantum boost in nonlinear effect from BSV light. This boost is revealed by matching the peaks of the photoelectron momentum spectra produced by the BSV and coherent light using angular streaking. Furthermore, we demonstrate control of the effective intensity of the BSV by tuning the correlation function at fixed average pulse energy, establishing a robust method to tailor nonlinear processes via quantum statistics rather than classical intensity scaling. These findings may facilitate the development of quantum-controlled strong-field dynamics using tailored quantum light sources.

This paper presents the first experimental observation and investigation of a lineshape-asymmetry-caused shift (LACS) in a short-baseline atomic interferometer-gravimeter. It is shown that this shift scales inversely with the cube of the free evolution time, $\propto T^{-3}$, and can lead to a noticeable systematic error in the measured value of the gravitational acceleration g at the level of 0.1-1 mGal ($T\approx$ milliseconds). The obtained results are in good agreement with our previous theoretical studies and highlight the importance of accounting for LACS in high-precision absolute measurements of g in compact atomic gravimeters.

This paper investigates the relationship between quantization of measures and metric mean dimension of topological dynamical systems. We introduce the concept of mean quantization dimension for invariant probability measures and establish a classical variational principle: the metric mean dimension of a dynamical system is equal to the maximum mean quantization dimension among all invariant measures. This approach effectively characterizes the complexity of systems with infinite entropy by identifying a measure that captures information across all scales; and yields a fundamental property that allows for the exchange of limits and suprema in the Lindenstrauss-Tsukamoto variational principles, a feat that most known entropy-like maps fail to achieve due to convexity. Nevertheless, we show that the Katok and Shapira entropies do satisfy this property and, therefore, a classical variational principle for the metric mean dimension, for which maximizing measures always exist.

Efficient preparation of nonclassical bosonic states is a central requirement for quantum computing, simulation, and precision metrology. We study resource-efficient quantum state preparation in bosonic qudit systems using the SNAP-displacement (SD) protocol. Existing SD-based approaches typically require a large number of gates and SNAP phases, resulting in complex control pulses with longer ansatz durations and amplified impact of photon-loss and control errors. In this work, we focus on the near- to medium-term regime, in which noisy quantum devices impose trade-offs on the fidelity that can be achieved, which must be taken into account. Specifically, we propose to optimize only a subset of the SNAP phases and introduce three progressively more general sparse ansatzes. To provide fine-grained control and identify the most suitable ansatz for a given target fidelity, we further employ a scalarized multi-objective optimization that trades off fidelity against either the number of phases or the duration of the ansatz. Numerical results for several target states and qudit dimensions up to $d=64$, evaluated through the hypervolume of the Pareto frontiers, show that these sparse ansatzes achieve favorable trade-offs over the fully parameterized SD protocol in both ideal and noisy settings. The advantage is strongest and most consistent when minimizing the number of phases, while improvements in ansatz duration are smaller and more dependent on the target-state family and noise level, suggesting a practical route to more efficient near- and medium-term bosonic state preparation.

Recent advances in large language models (LLMs) have stimulated growing interest in agent-based recommender systems, enabling language-driven interaction and reasoning for more expressive preference modeling. However, most existing agentic approaches remain predominantly user-centric, treating items as passive entities and neglecting the interests of other critical stakeholders. This limitation exacerbates exposure concentration and long-tail under-representation, threatening long-term system sustainability. In this work, we identify this fundamental limitation and propose the first Tri-party LLM-agent Recommendation framework (TriRec) that explicitly coordinates user utility, item exposure, and platform-level fairness. The framework employs a two-stage architecture: Stage 1 empowers item agents with personalized self-promotion to improve matching quality and alleviate cold-start barriers, while Stage 2 performs platform-level sequential multi-objective re-ranking, balancing user relevance, item utility, and exposure fairness. Experiments show consistent gains in accuracy, fairness, and item-level utility. Moreover, we find that item self-promotion can simultaneously enhance fairness and effectiveness, challenging the conventional trade-off assumption between relevance and fairness. Our code is available at https://github.com/Marfekey/TriRec.

Frontier AI Safety Policies concentrate on prevention: capability evaluations, deployment gates, and usage constraints, while neglecting the capacity to coordinate responses when prevention fails. We argue this coordination gap is structural: investments in ecosystem robustness yield diffuse benefits but concentrated costs, generating systematic underinvestment. Drawing on risk regimes in nuclear safety, pandemic preparedness, and critical infrastructure, we propose that similar mechanisms (precommitment, shared protocols, standing coordination venues) could be adapted to frontier AI governance. Closing the gap requires cross-actor "note-exchange" of ex ante if-then response logic, exposing not only triggers but the decision processes that convert signals into actions. Without such architecture, institutions cannot learn from failures at the pace of relevance.

Building upon the spin-1/2 Kitaev model on a honeycomb lattice, the Yao-Lee spin-orbital model provides exactly solvable quantum spin liquids with potentially better stability against perturbations due to the additional degree of freedom. Recently, the microscopic mechanism underlying the Yao-Lee interaction in honeycomb materials has been uncovered, leading to an extended Kitaev-Yao-Lee spin-orbital model when the celebrated Kugel-Khomskii interaction is included. Numerical studies of this model have identified various disordered phases, including a broad region of the nematic phase that is reminiscent of a spin-orbital liquid. Here, we investigate the origin and stability of this nematic phase via thermal and quantum fluctuations using classical Monte Carlo simulations and a generalized spin wave theory appropriate for the spin-orbital model. We demonstrate that the additional spin-orbital degree of freedom gives rise to strong thermal and quantum fluctuations in spin-orbital models, providing insight into the emergence of disordered phases.

Spectral control of closely spaced excitonic transitions is central to valleytronic photonics, nanoscale light sources, and wavelength-encoded sensing. In monolayer molybdenum disulfide (MoS2), the A and B excitons are separated by only tens of meV, making selective excitonic emission control both fundamentally important and technologically challenging. Here, we numerically investigate plasmon-enhanced excitonic emission from monolayer MoS2 coupled to vertically oriented hollow gold nanocylindrical cavities through a dielectric spacer. Finite-difference time-domain simulations combined with a photoluminescence-rate framework enable separate evaluation of excitation enhancement, radiative decay modification, nonradiative quenching, and excitonic charge generation. By tuning the cavity aspect ratio, the localized surface plasmon resonance is selectively aligned with either the A- or B-exciton transition, while the spacer thickness and refractive index regulate near-field coupling and the local density of optical states. Under optimized conditions, the excitation rate is enhanced by up to 4.34-fold and the radiative decay rate by more than 40-fold, yielding photoluminescence enhancements of 143.85 and 87.27 for the A and B excitons, respectively. The cavity also redistributes the relative excitonic peak intensities, producing exciton-selective peak ratios up to 2.4 times higher than those of bare MoS2. These results establish hollow plasmonic nanocavities as geometry-tunable platforms for exciton-selective emission and charge-generation control in atomically thin semiconductors.

Understanding interaction effects among variables is important for regression modeling in various applications. The conventional approach of quantifying interactions as the product of variables often lacks clear interpretability, especially in complex systems. The concept of conditional main effects (CME) provides a more intuitive and interpretable framework for capturing interaction effects by quantifying the effect of one variable conditional on the level of another. A recent method called cmenet further considered the bi-level selection of CMEs by leveraging their natural grouping structure (e.g., sibling and cousin groups) through penalization. However, there are several limitations in the cmenet method, including the coupling ability of penalties for within-group CMEs, lack of adaptiveness for between-group penalties, and restriction to linear models with continuous responses. To overcome these limitations, we propose an adaptive cmenet method for CME selection under the generalized linear model (GLM) framework. The proposed method considers a penalized likelihood approach with adaptive weights to enable effective bi-level variable selection, improving both between-group and within-group selection. An efficient algorithm for parameter estimation is also developed by employing an iteratively reweighted least squares procedure. The performance of the proposed method is evaluated by both simulation studies and real-data studies in gene association analysis.

The process tensor framework to open quantum systems provides the most general description of multi-time correlations in non-Markovian quantum dynamics. A compressed representation of a process tensor in terms of matrix product operators (MPO) can be used for numerically exact calculations of multi-time correlation functions in systems strongly coupled to a non-Markovian reservoir. We show here that the numerical scaling for computing multi-dimensional spectra can be significantly improved using a time-translation invariant MPO representation of the process tensor obtained from the uniform time-evolving matrix product operator (uniTEMPO) method. In particular, this approach provides a spectral representation of the non-Markovian dynamics that gives direct access to correlation functions in Fourier-space, avoiding explicit real-time evolution. We calculate linear and 2D electronic spectra for an example system and discuss the performance and numerical scaling of our simulations.