We consider a linearized inverse scattering problem for elastic waves. We prove that a fully anisotropic perturbation of the elastic parameters around an isotropic and homogeneous reference can be uniquely determined by (single-)scattered waves. We also give a quantitative stability estimate for an isotropic perturbation, and as a consequence a rigidity result is established.

We investigate the asymmetric freezing of a liquid droplet sliding on an inclined cold surface using numerical simulations based on the lubrication approximation. The combined effects of gravity, capillarity, and solidification kinetics on droplet motion, interfacial deformation, and the resulting frozen morphology are examined through systematic variations in substrate inclination, wettability, effective Bond number, and Stefan number. Our results show that sliding prior to and during the early stages of freezing plays a dominant role in governing the asymmetry of the frozen droplet. A tilted ice cusp forms at the droplet tip due to the competition between gravitational forces and capillary resistance, with its orientation and magnitude strongly dependent on substrate wettability and inclination. Greater inclination and increased wettability enhance asymmetry in droplet morphology. Further, highly wetting substrates favor capillary-driven retraction and induce transient liquid motion opposite to gravity during freezing. The evolution of contact-angle hysteresis at both the solid surface and the liquid-ice interface underscores the importance of early-time dynamics, when the unfrozen liquid remains mobile and gravitational effects are most pronounced. Decomposition of the liquid motion into capillary and gravity-driven contributions provides physical insight into contact-line pinning, receding-edge thinning, and the development of asymmetric liquid-ice contact angles. Increasing the Stefan number accelerates freezing, limits sliding-induced deformation, and reduces both the cusp angle and the post-freezing contact-angle contrast. Overall, this study establishes a physical framework for understanding the morphology of frozen droplets on inclined substrates.

Digital computing-in-memory (DCIM) has emerged as a promising solution for large language model (LLM) acceleration by minimizing data transfers between external DRAM and on-chip accelerators while maintaining high precision for superior accuracy. However, existing CIM architectures often overlook weight update latency, which becomes critical as LLM weights are far larger than a single CIM macro capacity. To address this issue, this paper proposes a read-compute/write (RCW) architecture that effectively minimizes weight update latency, along with a nonlinear operator fusion that further mitigates dependencyinduced latency. The proposed RCW reduces decoding computing latency by 21.59% on the Llama2-7B model. In addition, the nonlinear operator fusion mechanism achieves a 69.17% latency reduction through efficient partial accumulation and group-based approximation. Furthermore, a weight-stationary and output column stationary (WS-OCS) dataflow is introduced to reduce both external DRAM access and internal CIM weight updates by 51.6% and 87.6% respectively during the prefill phase of 1024 tokens, leading to an overall 49.76% latency reduction. Fabricated using TSMC 22 nm CMOS technology and operating at 100 MHz, the proposed RCW-CIM achieves 3.28 TOPS and 42.3 TOPS/W, enabling 4.2 ms prefill latency and 26.87 decoded tokens per second for the INT4-weight Llama2 model with dual DDR5-6400 memory.

Massive stars (> 8 $M_\odot$) are known to have high degrees of multiplicity, e.g., with about 60% in triples or higher-order multiples. Such high levels of multiplicity may arise during formation (primary multiplicity) or through dynamical processing of already formed stars in dense clusters (secondary multiplicity). The level of primary multiplicity is an important metric to help distinguish between different formation scenarios, such as core accretion and competitive accretion. The level of secondary multiplicity is expected to evolve with time and be sensitive to local cluster environment. Here we analyze a suite of $N$-body simulations to study bound multiplicity and local projected stellar density, $N_*$, around massive stars within gradually forming star clusters with 50% primordial binaries in the Turbulent Clump Core Accretion (TCCA) paradigm. We find that massive stars rapidly gather triple or higher-order bound companions and enhancements in local $N_*$ via dynamical processes. We study these metrics as a function of environment in a given cluster, quantifying the increasing multiplicity that arises towards cluster centers. We find that secondary multiplicity tends to decrease in more massive clusters due to their higher velocity dispersions, but rises as the mean density of the bound cluster increases. We find our $N_*$ radial profiles are shallower compared to those in the STARFORGE simulations, which form massive stars via competitive accretion. A comparison to the AFGL 5180 system suggests it is better described by TCCA models. However, a larger number of observed systems is needed to better discriminate between these formation models.

Complex quantum systems are often multiscale in nature with strong interactions between different scales. We present a novel idea: iteratively suppressing, rather than tracing out, the fast, high-energy degrees of freedom in strongly correlated quantum systems with multiple energy scales in a non-perturbative way, termed nonadiabatic renormalization group. This leads to a quantum geometric structure of a nested fiber bundle, in which each fiber of a layer is itself a fiber bundle of the next layer. The nonadiabatic renormalization group brings a new type of tensor network states that shares physical legs among ''sites'' and encodes quantum entanglement beyond conventional matrix product states. We demonstrate how to apply the nonadiabatic renormalization group to different types of problems, including an interacting boson model and ab initio quantum chemistry with interacting electrons.

Across science and engineering, mean-field methods have been a powerful and versatile approach for the analysis of systems of many interacting elements. However, common arguments used to characterize an infinite population limit can be quite restrictive from a modeling perspective by requiring that all agents be identical (i.e. symmetric, or homogeneous). In this paper, we consider large interactive particle systems under agent heterogeneity for a class of discrete time teams composed of finitely many species of agents, grouped into symmetric subteams, called clusters. In particular, for the class of discounted, partially exchangeable cost criteria considered, we establish the optimality of centralized joint policies which are exchangeable within each cluster and depend on the agent ensemble only up to the state empirical distribution over each cluster. Following this, a generalization of De Finetti's theorem is used to demonstrate the subsequential convergence of these optimal policies to one which is decentralized (depending on only the local state and distribution over each cluster) and symmetric within each subteam as the population size approaches infinity. This solution is shown to induce a sequence of asymptotically optimal policies for the finite population problems which retain their structure and decentralization. Furthermore, our analysis justifies the optimality of a decentralized McKean-Vlasov team representation involving coupled representative agents for each of the clusters, and establishes a verification theorem/value iterations for the mean-field limit. In this way, we provide an avenue for analyzing complex, cooperative systems with finite heterogeneity and set the stage for further research on learning algorithms.

We propose a novel mechanism for electroweak baryogenesis in which collapsing domain walls formed by an axion-like field replace the bubble walls in a strong first-order electroweak phase transition. The axion-like particle coupling to the Higgs mass term allows domain walls to separate regions with distinct electroweak phases, while the electroweak crossover induces a potential-energy bias that triggers their collapse. The directed wall motion, through the axion-like particle coupling to the electroweak topological term, acts as an effective baryon chemical potential and generates an asymmetry via electroweak sphaleron processes. We show that the observed baryon asymmetry can be obtained from either late-time entropy injection or sphaleron suppression in a weakly broken electroweak domain. The wall collapse also produces a stochastic gravitational-wave background with features distinct from standard electroweak-scale first-order-transition spectra.

We establish isomorphism ranges for the comparison maps between algebraic and topological K-groups, extending classical Quillen-Lichtenbaum conjecture to separated complex schemes of finite type after refinement. Additionally, we generalizes the conjecture through the lens of noncommutative geometry.

Exceptional points (EP) featuring enhanced responsivity and rich dynamics have attracted extensive attentions in device developments and sensing applications. However, it remains debated whether employing EP systems is beneficial in practical sensing applications. Here, we demonstrate that a nonlinear EP in our microwave-frequency acoustic-wave oscillator improves longwave infrared (LWIR) detection under practical conditions. By phase tuning the nonlinear gain, our detector can be operated at different conditions with respect to the nonlinear EP. Compared with operation away from EP, our detector at EP shows a 33-fold improvement in responsivity and an 8.75-fold extension of 3-dB bandwidth. We observe a 6-fold enhancement in signal-to-noise ratio at an input modulation frequency of 6.2 kHz. At the incident LWIR wavelength of 9.6 um, our detector at EP exhibits a noise equivalent power (NEP) of 310 pW*Hz^-1/2 at input frequency of 10 kHz, yielding a figure of merit, product of NEP and time constant, of 9.87*10^-3 pW*Hz^-3/2, a 10-fold improvement over operation away from EP. Our integrated acoustic devices offer a versatile platform for exploring noise dynamics and developing practical sensors that exploit non-Hermitian nonlinearities.

Achieving ultrahigh recording densities with low power consumption is a central challenge for next generation heat assisted magnetic recording (HAMR), as conventional L10 FePt media require intense laser heating due to their high coercivity (Hc) and high Curie temperature (700 K). Here, we address this issue using FePt/FeRh bilayers, where the antiferromagnetic to ferromagnetic transition of FeRh near 350 K generates strong interfacial exchange coupling that assists magnetization switching in the FePt layer. Magnetometry measurements reveal a 40% reduction in Hc from 300 K to 400 K in the bilayer, compared to only 8% in single layer FePt. Temperature dependent MFM directly captures phase transition induced domain evolution, showing a 30% reduction in domain size and enhanced phase contrast. TR-MOKE measurements reveal only a minor (0.4 T) modification of the effective anisotropy field during phase transition, confirming that the intrinsic anisotropy of FePt remains largely preserved. These results demonstrate that the reduction in Hc in FePt/FeRh bilayers is primarily governed by phase transition induced domain wall mobility coupled with interfacial magnetic interactions, rather than by intrinsic anisotropy softening. This mechanism provides a pathway toward efficient magnetization switching under reduced thermal load, making FePt/FeRh heterostructures promising candidates for advanced HAMR media.

The rapid proliferation of harmful and emotionally damaging content on social media platforms has intensified concerns regarding societal harm. While content moderation efforts primarily focus on detecting and removing harmful posts, less attention has been given to mitigating harm through stylistic text transformation while preserving semantic meaning. In this paper, we propose a writing-assistance framework that can reduce societal harm by transforming aggressive, toxic, or emotionally harmful comments into softer, more neutral stylistic forms inspired by Notepad AI, a simple AI writing assistant. Rather than censoring or suppressing speech, we apply controlled stylistic modifications to preserve core informational content while reducing emotional intensity and identity-based attacks. We introduce an Emotion Drift Index (EDI) metric to systematically quantify emotional change and evaluate the effectiveness of stylistic rewriting, thereby reducing harmful interactions in online environments.

Understanding quantum phases and phase transitions in the presence of symmetries is a central objective of quantum many-body physics. A powerful modern paradigm for investigating this problem is topological holography, which relates symmetries in $k$ dimensions to "bulk" topological orders in $(k+1)$ dimensions. While conceptually profound, most existing bulk construction methods rely on sophisticated mathematical formalisms and can be difficult to apply to certain symmetry types. In this work, we propose a physically intuitive and versatile method, termed the layered gauging construction, to systematically generate $(k+1)$-dimensional (liquid or fracton) topological orders from $k$-dimensional generalized symmetries. Roughly speaking, the prescription is to stack many layers of $k$-dimensional quantum systems with certain symmetries into a $(k+1)$-dimensional pile, and then sequentially gauge a diagonal symmetry acting on each nearest-neighbor pair of layers. The detailed procedure depends on the specific symmetry types. We have successfully implemented the method in a number of examples in different spatial dimensions, with symmetries that are conventional, higher-form, subsystem, anomalous, nonabelian, or noninvertible. We hence conjecture the method to be very general. For example, from the subsystem symmetry of the $2d$ plaquette Ising model, we derive the X-cube model and also an anisotropic fracton topological order. Additionally, starting from an anomalous $\mathbb Z_2$ symmetry in $1d$, we construct a new square lattice model realizing the double semion topological order.

Buchbinder and Feldman recently gave a deterministic $(1-1/e-\varepsilon)$-approximation for maximizing a non-negative monotone submodular function subject to a matroid constraint, with query complexity $\widetilde{O}_\varepsilon(nr)$. Their algorithm uses an integer parameter $\ell$, which Buchbinder and Feldman fix to $\ell = 1 + \lceil 1/\varepsilon \rceil$ via a loose bound on $(1+1/\ell)^{-\ell}$. We point out two purely elementary refinements. First, the classical Pólya--Szegő inequality $(1+1/\ell)^{-\ell} \le e^{-1}(1+1/(2\ell))$ replaces the loose step in their proof and permits $\ell = \lceil 1/(2e\varepsilon) \rceil$, shrinking the hidden constant in $\widetilde{O}_\varepsilon(nr)$ by a factor $\approx 2^{0.816/\varepsilon}$. Second, an alternating-series tail bound for $\log(1+t)$ yields the asymptotically sharp inequality $(1+1/\ell)^{-\ell} \le e^{-1}\exp(1/(2\ell) - 1/(3\ell^2) + 1/(4\ell^3))$, matching the true expansion of $(1+1/\ell)^{-\ell}$ through order $\ell^{-3}$ and translating into $\ell_\star = 1/(2e\varepsilon) - 5/12 + O(\varepsilon)$. The asymptotic class $\widetilde{O}_\varepsilon(nr)$ of the query complexity is unchanged in either case; only the implicit constant in $\varepsilon$ is improved. All inequalities in this note are formalized and machine-checked in Lean 4 against Mathlib.

Let $\mathcal{R}$ be an association scheme with nontrivial relations $A_1,\ldots,A_d$. We call $\mathcal{R}$ amorphic if every possible fusion of its nontrivial relations gives rise to a fusion scheme. We define the fusing-relations $3$-hypergraph of $\mathcal{R}$ to be the $3$-uniform hypergraph on the vertex set $\{A_1,\ldots,A_d\}$ such that $\{ A_i, A_j, A_k \}$ forms an edge if it fuses, i.e., fusing $A_i, A_j, A_k$ gives rise to a fusion scheme of $\mathcal{R}$. A $3$-uniform hypergraph is called a $3$-sunflower if, for the edges, the union is the set of vertices and the intersection consists of $2$ vertices. In this paper, we prove that for $d\geq 5$, $\mathcal{R}$ is amorphic if its fusing-relations $3$-hypergraph contains two $3$-sunflowers. As a corollary, for $d\geq 5$, $\mathcal{R}$ is amorphic if and only if all triples of its nontrivial relations fuse.

We study the set of solutions to a parameterized, strongly convex optimization problem whose cost depends on uncertain, bounded parameters. We compute a certified outer approximation of the corresponding set of optimizers, using convergence properties of the projected gradient descent (PGD) algorithm for convex programs. Concretely, by treating the cost parameter as constant but unknown, we interpret the PGD iterates as an uncertain dynamical system and analyze its forward reachable sets. Since PGD converges exponentially to the unique optimizer for each fixed parameter, these reachable sets provide outer approximations of the optimizer set, with an explicit error bound that decays exponentially with the iteration count. We apply system-level synthesis (SLS) on the PGD dynamics to optimize the step-size sequence and obtain reachable-set over-approximations. Our method outperforms existing baselines in over-approximating, with low conservativeness, the minimizer sets of convex programs with uncertain costs and high-dimensional decision variables.

Health messages on social media are typically constructed through combinations of source cues, appeals, frames, and evidence, which jointly shape communication and persuasive effects. However, prior research has largely focused on single elements or simple pairwise interactions, offering insufficient insight into how multiple elements operate together in real-world digital environments. To address this gap, this study adopts a systems perspective to examine multi-element message combinations. Using 1.8 million health-related Weibo posts, we apply clustering analysis to identify recurring combinations and assess their relationships with communication effects. First, four recurring element combinations are identified: Institutional Authority, Narrative, Assertive Appeal, and Contextual Expression. These combinations function as core structures organized around two key elements. Second, stronger communication effects depend not only on core structures but also on peripheral elements aligned with these structures, with combinations of two to four peripheral elements generally showing greater advantages. Third, the optimal level of peripheral complexity varies with source influence, indicating that environmental factors condition the relationship between message combinations and communication effects. These findings show that communication and persuasive effects are shaped by synergies and trade-offs among multiple persuasive elements. Based on this, the study proposes a Core-Periphery-Environment framework to explain how message combinations generate communication effects with persuasive implications on social media. The study extends research from isolated elements to systems combinations and offers practical implications for health communication.

Viscoelasticity governs the locomotion strategies of deformable microorganisms, rendering it a fundamental mechanical property of microbial motility and an integral component in the design of envisioned microbots. Recent studies have shown that it can enable effective propulsion through non-reciprocal body deformations, even under time-reversible actuation. In this work, we investigate the dynamics of model microswimmers driven by reciprocal actuation, wherein the passive body exhibits viscoelastic deformability. We consider two linked-sphere designs, distinguished by the location of actuation: applied at one end (3-sphere design) or at the midpoint of the swimmer body (4-sphere design). Adopting Kelvin-Voigt deformability, we characterize the kinematic performance of both designs: the three-sphere swimmer possesses an optimal actuation frequency, while the four-sphere swimmer exhibits a critical frequency at which the locomotion direction reverses. We examine the swimmer's far-field hydrodynamic signature and find that resulting flow field is characterized by dominant dipolar and quadrupolar contributions, whose magnitudes are sensitive to the relative length of the actuator segment.

High-brightness femtosecond-to-attosecond pulses are indispensable for probing electron dynamics on their fundamental temporal scales. X-ray free-electron lasers (XFELs) at high repetition rates will facilitate high-statistics measurements and time-resolved studies that were previously inaccessible. Although energy recovery linacs (ERLs) are well suited for high-repetition-rate operation, their relatively low peak current poses a major challenge for generating intense ultrashort X-ray pulses. Here, we propose a completely laser-free scheme that fundamentally overcomes this bottleneck through a continuous, phase-stable self-modulation process. By interacting with its own coherently emitted terahertz radiation within a helical wiggler, the electron bunch naturally accumulates a robust, few-cycle energy modulation in its core, even when starting with the intrinsically low peak current typical of ERLs. A downstream dispersion chicane subsequently converts this energy modulation into an isolated, exceptionally sharp current spike. Start-to-end simulations based on a 1~GeV ERL light source demonstrate the feasibility of generating isolated soft X-ray pulses with an average peak power exceeding 4~GW and a pulse duration of about 1~fs at an unprecedented 1.3~GHz repetition rate. The proposed scheme offers a highly practical pathway for advancing ultrafast X-ray generation into the true continuous-wave regime, with transformative implications for the development of next-generation coherent light sources.

This study examines the development, influence, and collaboration patterns in AI-supported social presence research within online learning environments. Utilizing 59 open-access empirical studies from Scopus, the study applies citation analysis, co-authorship mapping, institutional analysis, and keyword clustering using Python-based bibliometric tools. Findings reveal an upward trend in publications since 2020, with research focusing on engagement, AI tools, instructional design, and ethical issues. While countries such as the United States and Brazil are leading contributors, international collaboration remains limited. Ethical concerns related to trust and fairness are emerging but underexplored. The study highlights the importance of ethical integration, interdisciplinary collaboration, and learner-centered AI applications in education.

Sliding ferroelectricity in bilayer hexagonal boron nitride (h-BN) offers compelling prospects for next-generation non-volatile memory, yet the atomistic dynamics of electric-field-driven polarization switching remain poorly understood. Here, we present a fully data-driven, coupled atomistic framework that integrates a fine-tuned MACE machine learning potential (MLP) with an equivariant graph convolutional neural network (EGCNN) for real-time Born effective charge (BEC) prediction, enabling large-scale non-equilibrium molecular dynamics simulations of AB-stacked bilayer h-BN under applied electric fields. By implementing a rigorous real-space path-integral polarization formalism combined with a state-constrained Gaussian convolution background extraction procedure, we successfully isolate the intrinsic spontaneous polarization from the dominant dielectric background. Our simulations reveal that coherent single-domain rigid sliding, completing within 5 ps, constitutes a physically viable ultrafast switching mechanism, and reproduces clean ferroelectric hysteresis loops whose shape is qualitatively consistent with experimental observations.

We consider the modular action of the symmetric group $S_n$ on $R = k[x_1,\ldots,x_n]$ when $\mathrm{char}(k) = p \leq n$. We show that the image of the transfer map $R\to R^{S_n}$ is an elimination ideal $J\cap R^{S_n}$, where $J\subset R^{S_n}[t]$ is generated by $p$ polynomials with generic coefficients. The structure of this elimination ideal depends only on the quotient $q$ when writing $n = qp + r$ with unique remainder $0 \leq r < p$, implying that the image of the transfer also enjoys this stability. We conjecture a determinantal presentation of the elimination ideal and prove it in the case that $q = 2$. Furthermore, we exhibit a GL-equivariant, linear minimal free resolution of a certain initial ideal, allowing us to extract the graded Betti numbers of the elimination ideal.

Fix a finite dimension $d \geq 2$ and a fixed rank-1 PVM $M=\{|e_1\rangle\langle e_1|,\ldots,|e_d\rangle\langle e_d|\}$ on ${\bf C}^d$. Let $P_M:\mathbb{CP}^{d-1}\toΔ^{d-1}$ be a readout map on pure states. We prove that three primitives force the Born rule for this fixed measurement: (i) square-root regularity of $R_M=\sqrt{P_M}$ along Fubini-Study geodesics, (ii) the universal readout Cramer-Rao bound $F_{\rm cl}\leq F_Q$ on smooth pure-state curves, and (iii) operational calibration on basis preparations $P_M([e_i])=δ_i$. The geometric core is a rigidity theorem for Fisher-non-expanding self-maps of the probability simplex: after conjugation by the square-root chart, such maps become round-metric 1-Lipschitz self-maps of the positive spherical orthant, and vertex fixing forces the identity. The main readout theorem is dimensionwise, fixed-PVM, and pure-state only. Escort-class Born uniqueness and the Markov/coarse-graining routes appear as corollaries or alternative routes.

This article introduces novel methodologies for estimating contextual exposure to HIV population viral load using GPS data. We propose a comprehensive analytical framework comprising (i) local (grid-cell level) estimation of HIV population viral load, (ii) derivation of individual activity spaces from GPS trajectories, and (iii) quantification of contextual exposure to HIV within these activity spaces. We integrate HIV surveillance and sociodemographic survey data with GPS-based mobility data collected in rural KwaZulu-Natal, South Africa, to characterize mobility patterns among young adults aged 20-30 years. Using derived measures of mobility and contextual exposure, we assess whether participants' sex and age systematically influence the magnitude, configuration, and heterogeneity of their mobility patterns. Furthermore, we describe analytical approaches to examine how contextual exposure to HIV evolves as activity spaces extend beyond static residential locations, outlining procedures to identify GPS-tracked participants at elevated risk of HIV acquisition. KEYWORDS: Population viral load exposure; GPS-based mobility analysis; Activity space

Under what condition is a random constraint satisfaction problem hard to refute by the sum-of-squares (SoS) algorithm? A sufficient condition is t-wise uniformity, that is, each constraint has a t-wise uniform distribution of satisfying assignments, as shown by the lower bounds of Kothari, Mori, O'Donnell, and Witmer (STOC 2017). This condition is also necessary for random CSPs given by a predicate and uniformly random literals, due to the constant-degree SoS refutation of Allen, O'Donnell, and Witmer (FOCS 2015). For higher degree, Raghavendra, Rao, and Schramm (STOC 2017) gave a refutation for Boolean random CSPs with uniformly random literals, matching the lower bounds optimally in terms of the three-way tradeoff between constraint density, SoS degree, and strength of refutation. Two long-standing open problems are to find a more general sufficient condition for SoS lower bounds, and to refute similar random CSPs not involving literals. We show that for a general random k-CSP, the necessary and sufficient hardness condition is not t-wise uniformity, but t-wise independence. We generalize the optimal three-way tradeoff to any random k-CSP, without assuming a Boolean domain or uniformly random literals. Our analysis involves new Kikuchi matrices for odd order and for asymmetric tensors. It also uses the global correlation rounding technique of Barak, Raghavendra, and Steurer (FOCS 2011). To avoid the running-time penalty of this technique, we also give a spectral refutation algorithm.

A skew Bollobás system $\mathcal{P}=\{(A_i,B_i):1\leq i\leq m\}$ is a collection of pairs of disjoint subsets of $[n]$ such that $A_i\cap B_j\ne\emptyset$ for any $1\leq i<j\leq m$. Denote by $S_1(a, b)$ or $S_2(a, b)$ the maximum size of $\bigcup_{i=1}^m A_i$ or $\bigcup_{i=1}^m B_i$, respectively, over all possible skew Bollobás systems $\mathcal{P}=\{(A_i,B_i):1\leq i\leq m\}$ satisfying $|A_i| \leq a$ and $|B_i| \leq b$ for all $i \in [m]$. It is shown that for any non-negative integers $a$ and $b$, $S_1(a,b)=\binom{a+b+1}{a}-1$ and $S_2(a,b)=\binom{a+b+1}{a+1}-1$.

Context: Documenting Architectural Design Decisions (ADDs) is a critical factor in the software lifecycle, essential for efficient system maintenance, developer onboarding, and preventing knowledge vaporization. Although various templates for Architectural Decision Records (ADRs) have been proposed, there is a lack of empirical evidence comparing them. Goal: To address this gap, this paper aims to identify which ADR template best supports comprehension, usability, and ease of adoption: Tyree/Akerman's template, Nygard's ADR, arc42, Y-statements, and MADR. Method: We compared these templates using the DESMET FA method in a two-step evaluation. First, the two primary authors evaluated the five templates through the DESMET FA, based on their software architecture expertise. The two top-performing templates were then used as treatments in a controlled experiment conducted with undergraduate students. Results: In the preliminary screening by experts, the top-performing templates were those of Nygard and MADR. In the subsequent controlled experiment, Nygard's template outperformed MADR in terms of the Overall Score. Qualitative analysis of participant feedback revealed the factors influencing template preference. The findings indicate that Nygard supports concise and objective documentation, while MADR facilitates structural details and specific architectural requirements. Conclusion: This paper provides an evidence-based strategy for ADR template adoption by offering a comparison between them. The findings present a decision-making guide that assists practitioners and researchers in selecting ADR templates aligned with project constraints, aiming to minimize documentation overhead and increase architectural knowledge retention.

This is the fourth paper of our series investigating the effects of active galactic nucleus (AGN) feedback in the evolution of an elliptical galaxy using the {\it MACER} framework. While previous works considered only AGN radiation and wind, we now add jet feedback. The values of the jet parameters are taken from small-scale general relativity MHD simulations of black hole accretion. We run three models: {\tt FullFeedback}, {\tt JetOnly}, and {\tt WindOnly}. Time-averaged star formation rates are $10^{-1}$, $10^{-2}$, and $10^{-3} \mathrm{M}_\odot\,\mathrm{yr}^{-1}$ in {\tt JetOnly}, {\tt WindOnly}, and {\tt FullFeedback}, respectively. Despite the higher jet power, jet feedback is less efficient than wind due to a small opening angle and low momentum flux. The much lower star formation rate in {\tt FullFeedback} indicates nonlinear coupling between jet and wind, with stronger suppression than the linear sum. The AGN energy dissipation efficiency values (fraction of injected kinetic energy dissipated via turbulence and shock) are 0.64 ({\tt FullFeedback}), 0.48 ({\tt WindOnly}), and 0.26 ({\tt JetOnly}). In the {\tt FullFeedback} model the wind-jet shear results in Kelvin-Helmholtz instability, driving stronger turbulence that effectively converts AGN kinetic energy into heating.

Recent experiments show that optically generated Rydberg excitons in cuprous oxide can neutralize charged impurities, strongly reducing stray electric fields and effectively purifying the crystal. Here, we develop a multichannel theory of Rydberg exciton-impurity scattering that resolves the competing roles of capture, elastic scattering, and inelastic transitions between excitonic states. We find that at high collision energies, as effective under conventional single-photon excitation, purification is reduced relative to Langevin capture. These collisions are accompanied by inelastic redistribution and dominant elastic scattering, including pronounced glory scattering, which suppress purification efficiency. We identify a quantum regime at ultralow collision energies favorable for purification, where only the s-wave contributes: capture is enhanced while elastic and inelastic channels are strongly suppressed. This regime can be accessed via degenerate two-photon excitation of even-parity Rydberg excitons with tunable recoil, additionally enabling the systematic exploration of exciton-impurity scattering over a wide range of collision energies beyond what is readily achievable in atomic counterparts in atomic gas experiments.

Fostering coordinated pro-environmental behaviors at scale is a key challenge for climate mitigation. Individual actions only generate meaningful impact when they diffuse widely and become socially coordinated, yet monitoring such processes remains difficult with traditional survey-based tools alone. In this study, we examine whether large-scale online climate discourse is associated with differences in offline pro-environmental behavior across European regions. We combine geolocated Twitter data from the Climate Change Twitter Dataset (2017-2019) with survey-based measures from the 2019 Special Eurobarometer, focusing on the regional density of climate-related tweets and the average number of self-reported pro-environmental actions. We find a strong positive association between tweet density and pro-environmental behavior that remains robust to socio-economic controls, alternative spatial aggregations, and a wide range of robustness checks. To move beyond aggregate volume, we further decompose online discourse using Natural Language Processing tools that capture distinct social dimensions. While knowledge exchange shows no clear relationship with offline behavior, the prevalence of activism- and social support-related expressions is negatively associated with pro-environmental actions. Overall, our results suggest that online climate discourse can serve as an informative, attention-related signal of regional differences in pro-environmental behavior, but that different forms of online engagement relate to offline action in markedly different ways. More broadly, the study highlights the potential of integrating large-scale digital traces with survey data to investigate collective behavior in socio-environmental systems, while remaining explicitly observational in scope.

We study the semiclassical Ehrenfest trajectories in open quantum systems. We first derive in explicit form the Fokker-Planck equation that governs the time evolution of the mixing measure for a Gaussian mixture. Then, we embed the generalized Ehrenfest theorem recently obtained for open quantum systems into this phase-space picture to study the time evolution of the expectations of observable with respect to the Gaussian mixture. We show how the coherent and irreversible contributions are microscopically separated. Our work provides a transparent phase-space interpretation of the emergence of classical trajectories in open quantum dynamics.