Motivated by the problem of detecting large and cohesive groups of vertices in real networks, the task of finding large \emph{quasi-cliques} has attracted considerable attention across different research areas. From a computational complexity perspective, strong inapproximability results are known for this problem, yet several heuristics have been proposed to identify large quasi-cliques in real-world networks. Recently, [Pang \emph{et al.}, (WWW 2024)] introduced a similarity-based approach that represents the current state of the art. In this work, we extend that approach to \emph{dynamic} networks, thereby addressing an open problem posed by [Pang \emph{et al.}, (WWW 2024)]. We first present a Baseline fully dynamic algorithm where edges of the network can be both inserted and deleted. The algorithm exactly maintains the same quasi-clique returned by the algorithm by Pang et al. on the current graph, with update time $\widetilde{O}(Δ)$, where $Δ$ is the maximum degree. We then focus on the practically relevant incremental case, where only edge insertions are allowed, and design an algorithm with $O(\log Δ)$ update time. This method leverages a novel technique for dynamically maintaining accurate estimates of vertex $γ$-degrees, a core component of framework by Pang et al., and achieves up to $207\times$ speed-up over the Baseline while preserving comparable solution quality. Finally, we extend the approach to the fully dynamic setting, supporting both insertions and deletions, obtaining up to $21\times$ speed-up with limited and acceptable loss in quasi-clique size and density. We provide a formal analysis of our algorithms and validate them through an extensive set of experiments on real-world datasets.

The correlation between black hole mass, $M_{\rm bh}$, and stellar velocity dispersion, $σ_0$, is revisited using 137 galaxies with quantitative bar strengths and enhanced morphological awareness. Interpreted within the `Triangal' evolutionary framework, gas-rich and gas-poor assembly pathways emerge in the $M_{\rm bh}$--$σ_0$ diagram. To quantify these scaling relations, a versatile Bayesian hierarchical regression code, dubbed the Symmetric COvariance Population Estimator (SCOPE), is introduced. Unlike conditional estimators, SCOPE derives the intrinsic population covariance, natively accommodating asymmetric measurement errors while guaranteeing directional invariance between axes. Primeval, dust-poor S0 galaxies (including dwarf early-type galaxies with $R_{\rm e,gal}\approx1$~kpc) follow a shallow relation ($M_{\rm bh}\proptoσ_0^{2.5\text{--}3.1}$). Explained via the virial theorem, this flattening reframes expectations for intermediate-mass black holes. In contrast, tracing the `Disc Down-sizing' sequence - where dry mergers erase discs - yields a steep relation for massive elliptical and ellicular galaxies ($M_{\rm bh}\proptoσ_0^{7.8\pm1.4}$). The historical practice of applying a single, monolithic scaling relation across all morphological types averages over different formation histories, potentially skewing AGN virial $f$-factor calibrations and systematically under-predicting the ultra-massive black holes needed to generate the nanohertz gravitational wave background. Furthermore, strongly barred, dust-poor S0 galaxies appear offset to higher $σ_0$, while this dynamical signature is lost in the complexities of spiral galaxies. Ultimately, these morphology-dependent relations provide physically-motivated benchmarks for cosmological simulations and a framework for disentangling regimes driven by AGN feedback from those driven by collisionless mergers.

Proton-induced activation represents a major source of instrumental background for high-energy astrophysics missions in low-Earth orbit, where trapped protons, particularly during transits within the South Atlantic Anomaly region, irradiate spacecraft materials and generate radioactive isotopes. Direct Monte Carlo simulations of activation and of the ensuing decays are computationally inefficient, due to the low probability of nuclide production and the large number of decay events required for sufficient statistical accuracy. In this paper we provide a new implementation of an efficient three-step algorithm that decouples isotope production, radioactive-decay evolution, and background synthesis, enabling rapid reconstruction of activation-induced background for arbitrary irradiation histories. The method combines Geant4-based identification of all radioisotopes produced by monochromatic proton irradiations, numerical solutions of the Bateman equations for linearized decay chains, and simulation of the detector response to each isotope decay emissions. The approach greatly reduces the computational cost while maintaining accuracy, as demonstrated through validation against direct simulations, which show excellent agreement over many orders of magnitude in activity and time. This method is applied to two representative case studies: HERMES and eXTP/LAD and WFM, covering different detector technologies and orbital configurations. The presented framework enables fast exploration of design and operational scenarios (e.g., orbit selection, radiation models, or duty cycles) and is well suited for background budgeting and optimization of future high-energy space missions.

In crystalline solids, avoided crossing between acoustic and optical phonons is widely recognized as an effective mechanism for suppressing lattice thermal conductivity ($κ_l$). However, the role of avoided crossings among optical phonons remains largely unexplored due to their weak contribution to heat transport. Here, using first-principles calculations combined with the linearized Wigner transport equation (LWTE), we demonstrate that optical-optical avoided crossings can effectively reduce ($κ_l$) in TlIn$_{0.5}$Ga$_{0.5}$Te$_2$. Pristine TlInTe$_2$ exhibits strong optical phonon-dominated heat transport, where optical phonons contribute nearly 63% of $κ_l$. The phonon dispersion of TlInTe$_2$ shows several crossing points in the optical region, which evolve into avoided crossings after 50% Ga substitution. Irreducible representation analysis reveals that the crossing phonon branches in TlInTe$_2$ belong to different symmetry representations, whereas the corresponding branches in TlIn$_{0.5}$Ga$_{0.5}$Te$_2$ possess the same symmetry representation, which enables phonon modes to couple and results in gap opening at the crossing points. These avoided crossings significantly suppress the optical phonon group velocity, thereby reducing the optical phonon contribution from 63% to 44% and lowering $κ_l$ from 0.568 to 0.482 Wm$^{-1}$K$^{-1}$ at 300 K. Mode-averaged transport analysis further confirms that the suppression of $κ_l$ is primarily governed by reduced phonon group velocity ($v_g$), while enhanced anharmonic scattering provides an additional secondary contribution. Our results establish symmetry-modified optical-optical avoided crossing as an effective route to suppress optical phonon transport and reduce $κ_l$ in systems where optical phonons significantly contribute to heat transport.

We construct cubic Dirac operators and relative cubic Dirac operators for infinite-dimensional quadratic $\mathbb{Z}$-graded color Lie algebras with finite-dimensional components. These operators are defined in completions of the quantum Weil algebra determined by the $\mathbb{Z}$-grading. The same grading fixes the normal-ordering convention. The failure of the normally ordered Casimir to be central, and of the normally ordered cubic Dirac operator to be $\mathfrak{g}$-invariant, is measured by a color analogue of the Kac-Peterson class. If this class is trivial, the Casimir admits a central correction and the cubic Dirac operator admits a corrected $\mathfrak{g}$-invariant form. For the corrected (relative) cubic Dirac operators, we establish Parthasarathy-type square formulas. We also extend the Chern-Weil homomorphism to completed $\mathfrak{g}$-differential algebras and identify the classical element whose quantization is the cubic Dirac operator with the Chern-Simons element associated with the quadratic invariant polynomial defined by $B$. As applications, we consider symmetrizable Kac-Moody superalgebras. In this setting the Kac-Peterson class is trivial, with primitive given by the Weyl vector. For the affine Kac-Moody superalgebra associated to $\mathfrak{osp}(1\vert 2n)$, we compute $\mathrm{ker}\operatorname{D}_{\mathfrak{g},\mathfrak{g}_{\bar{0}}}^{2}$ on integrable highest weight supermodules. We then apply the relative square formula to $ω$-unitarizable highest weight supermodules and obtain a Dirac inequality giving necessary conditions for unitarity. Finally, under assumptions satisfied by Kac-Moody superalgebras such as $\widehat{\mathfrak{sl}}(m\vert n)$, we identify the Dirac kernel with Lie superalgebra cohomology.

We construct analytic solutions to the bumblebee gravity theory in static and spherically symmetric spacetimes, where the bumblebee vector field admits only a non-vanishing temporal component. In particular, we identify the parameter space that allows for asymptotically flat black hole solutions. We further investigate the thermodynamic properties of these black holes and obtained the analytic formulas for the $Y$ charge and $X$ potential, which were introduced in the prior work to ensure the Smarr relation and the first law of black hole thermodynamics. Using the new analytic results, we verify the numerical findings reported in early work and uncover multiple cases missed in the previous numerical analysis. These include: (i) an unbounded charge-mass ratio when the non-minimal coupling parameter $ξ$ is larger than $2κ$, (ii) the emergence of a traversable wormhole configuration for overcharged solutions with $ξ<0$, (iii) the non-monotonic turning behavior of the Hawking temperature as a function of the charge-mass ratio, and (iv) the presence of two divergent points in the constant-$Y$ heat capacity.

The United Kingdom and Europe are moving rapidly from critical minerals target-setting to implementation. The EU Critical Raw Materials Act and the UK's Vision 2035 create ambitious benchmarks for domestic extraction, processing, recycling, circularity, and supply-chain resilience, but many prospective regional resources remain complex, under-explored, historically worked, or economically marginal. This paper argues that implementation will depend not only on permitting reform and project designation, but also on pre-competitive measurement, modelling, and data infrastructure capable of determining which ores, brines, waste streams, and recycling feedstocks can be processed viably and with lower environmental impact. Digital Rock Physics (DRP) should therefore be understood as enabling infrastructure for resource policy rather than as a specialist laboratory method alone. By combining three-dimensional imaging, correlative chemistry, AI-enabled image analysis, and pore-scale modelling, DRP can connect mineral texture and reactive pathways to decisions about ore characterisation, liberation prediction, leaching, Direct Lithium Extraction, mine-waste valorisation, and battery recycling. The paper sets out a UK-European policy agenda built around translational demonstrators, cross-disciplinary training, a Digital Ore Passport standard, a federated Digital Ore Database, and integrated geo-reactive end stations. Treated as shared implementation infrastructure, DRP could help turn critical minerals strategies into practical routes for supply security, resource efficiency, circularity, and more environmentally responsible development.

We propose an AI Agent tailored for link power management in multi-band systems. In S+C+L band span-level study, the agent efficiently solves various optimization objectives. In network-wide evaluation, it delivers 689.0 Tbps gain in total allocated traffic with merely 303 average interactions per power profile.

The purpose of this paper is to establish a local theory of the non-abelian Noether--Lefschetz locus. Given a family of projective manifolds over a complex variety $S$, the isomonodromic deformation of the initial $\mathbb C$-PVHS defines a holomorphic family of flat bundles and defines a real analytic family of Higgs bundles by the non-abelian Hodge correspondence. The non-abelian Noether--Lefschetz locus exactly consists of those points in $S$ on which the isomonodromic deformed Higgs bundle underlies a graded structure. Esnault-Kerz ask whether the non-abelian Noether--Lefschetz locus is precisely the maximal complex analytic subvariety on which the real analytic isomonodromic deformation of Higgs bundles becomes holomorphic. Our main result gives an affirmative answer to this question. The proof is based on the deformation equation of the harmonic metric solved by the non-abelian Hodge correspondence, and we use it to study higher order deformation class of the isomonodromic deformation of a graded Higgs bundle, which is expressed in terms of the differential graded Lie algebra of the joint real analytic deformation. We introduce a sequence of obstruction classes measuring the failure of holomorphicity and show that their vanishing forces the graded structure to lift to arbitrary finite order. This yields a local characterization of the non-abelian Noether--Lefschetz locus in terms of the holomorphicity of the isomonodromic deformation of Higgs bundles.

We address pion transitions involving heavy quarkonium and heavy exotic states in the Born-Oppenheimer effective field theory. Many of these states have a size similar or larger than the typical hadronic scale, and hence the usual QCD multipole expansion breaks down. Unknown low energy functions must be introduced, which at short distances must reproduce the known results of the multipole expansion. In order to determine the long distance behavior of these functions, we propose an interaction Lagrangian for pions and the QCD string. By matching the amplitudes obtained with this Lagrangian to the ones of the Born-Oppenheimer effective field theory in the static limit, we obtain the low energy functions in terms of three universal parameters. As a by product, we also obtain the light quark mass dependence of the string tension. Assuming that the low energy functions are long-distance dominated, we calculate several quarkonium-to-quarkonium and hybrid-to-quarkonium transitions. We estimate the universal constants and provide a phenomenological analysis of the most relevant transitions.

We show that for any uncountable cardinal $κ$, there is a coloring $c: [κ]^2\to ω$ such that $c''A \otimes B = ω$ for any $A, B\subseteq κ$ of order type $ω_1$ that are stationary in their common supremum. In particular, the stationary version of Erdős-Rado theorem and the higher dimensional Friedman's property are both inconsistent. We demonstrate that the theorem is optimal in various ways.

Multiphase turbulence displays stronger intermittency than its single-phase counterpart, yet the origin and geometrical organization of its most intense small-scale fluctuations remain poorly understood. Using direct numerical simulations of the incompressible Navier--Stokes equations with surface tension, we show that the local dissipative cutoff broadens strongly in the presence of interfaces, with dissipative events extending deep into the sub-Kolmogorov range. These events are spatially concentrated around topology-changing interfacial regions, namely breakup and coalescence. A multifractal analysis of the dissipation field further reveals that, while the spectrum above the Kolmogorov length, $η_K$, remains close to the single-phase case except for the most singular tail, the near- and sub-Kolmogorov range develops a markedly broader singularity spectrum supported on sparse intense structures. Our results show that breakup and coalescence do not simply perturb turbulence locally, but imprint a distinct multifractal organization on dissipation in multiphase turbulence.

Protecting proprietary RAG databases from unauthorized redistribution is challenging: existing watermarking methods either inject fabricated relations between real entities, polluting the knowledge base with misinformation, or embed fragile lexical patterns that adversarial paraphrasing easily removes. We propose SentinelRAG, a watermarking framework that embeds style-consistent but fictitious knowledge entries into the RAG database. Our key insight is that synthetic knowledge describing fictitious entities is unlikely to be retrieved by legitimate queries, yet can be reliably triggered through targeted probes known only to the data owner. Experiments on four datasets ranging from 2.9k to 8.8M documents demonstrate that SentinelRAG achieves statistically significant detection $p < 10^{-5}$ across all tested configurations at only a 0.1% injection rate. Compared to the state-of-the-art, our method significantly reduces the false detection rate while maintaining negligible interference with legitimate user queries.

This letter reports a study of associated $Z$ boson and prompt $J/ψ$ production in proton-proton collisions at $\sqrt{s}=13$ TeV with the LHCb detector in the forward rapidity region, using a data sample taken during 2016 to 2018 corresponding to an integrated luminosity of $5.1 \mathrm{fb}^{-1}$. The measured fiducial cross-section is $5.5 \pm 1.5$ pb, significantly exceeding the single-parton scattering expectation of $0.10 \pm 0.08$ pb, indicating that multiparton interactions dominate this process in the explored phase space. Interpreted within the standard double-parton scattering framework, the data yields an effective cross-section $σ_{\mathrm{eff}} = 16.6 \pm 4.7$ mb. This provides a direct experimental constraint on the transverse spatial structure of the proton in a kinematic regime characterized simultaneously by small Bjorken-$x$ and an electroweak hard scale set by the $Z$ boson mass.

Lagrangian turbulence is characterized by intermittent, fat-tailed fluctuations and nontrivial correlations across temporal scales, making a quantitative description of its full multiscale probability distribution a longstanding challenge. A particularly important question is whether unresolved fine-scale fluctuations can be inferred from coarse-grained trajectory information. Here, we address this problem by sampling the conditional distribution of unresolved fluctuations using a diffusion-model prior conditioned on large-scale dynamics obtained through a wavelet-based coarse-graining of Lagrangian trajectories. Using tracer trajectories from direct numerical simulations of homogeneous and isotropic turbulence at $Re_λ\simeq 310$, we show that the reconstructed signals recover scale-dependent intermittent statistics, including high-order structure functions, flatness, and local scaling exponents, together with cross-scale temporal correlations between resolved and unresolved fluctuations. The method also reproduces the broad stochastic variability of intermittent acceleration fluctuations conditioned on the same coarse-grained trajectory, whereas Gaussian-process reconstructions in wavelet representation suppress rare events. Our results show that small-scale Lagrangian intermittency can be modeled as a non-Gaussian conditional stochastic process constrained by coarse-scale dynamics and quantitatively reproduced through data-driven generative sampling.

The wavelength calibration and nightly drift measurements for CARMENES (Calar Alto high-Resolution search for M dwarfs with Exoearths with Near-infrared and optical Echelle Spectrographs) are provided by a combination of hollow cathode lamps and two Fabry-Pérot units. CARMENES consists of two spectrograph, one for the visible part of the spectrum (520-960nm) and one for the near infrared (960-1710nm). Each spectrograph has its own calibration unit and its own Fabry-Pérot. The calibration units are equipped with Th-Ne, U-Ar and U-Ne hollow cathode lamps as well as a flat field lamp. The Fabry-Pérots are optimized for the wavelength ranges of the spectrographs and use halogen-tungsten lamps as light sources. The Fabry-Pérots have a free spectral range of 15GHz for the visible and 12.2GHz for the near infrared which translates to $\sim$17,900 useful emission lines for the visible spectrograph and $\sim$9,700 for the infrared. These lines are used to compute the wavelength solution, and to monitor the instrumental drift during the night. The Fabry-Pérot units are temperature and pressure stabilized and designed to reach an internal stability of better than 10\,cm/s per night. Here, we present the designs of both Fabry-Pérot units and the calibration units.

For photometry of galaxies in the infrared that extend to very low surface brightnesses, it is necessary to observe with telescopes in space. WISE and NEOWISE provide sensitive all-sky access to mid-infrared flux from galaxies at 3.4mum (W1) and 4.6mum (W2) bands. This study is complemented by the availability of accurate Tip of the Red Giant Branch distances for a large fraction of the targets. In this work, photometry is assembled on a complete volume limited sample of galaxies between one and ten Mpc brighter than absolute magnitude -13 in the W1 band. Stellar masses are inferred from W1 fluxes and measured distances. While most of the galaxies are dwarfs, most of the stellar mass is concentrated in a small number of giants.

We extend the symmetry-adapted encoding (SAE) framework to periodic electronic structure, enabling qubit-efficient quantum simulation of crystalline materials. By constructing a $Γ$-point supercell Hamiltonian from a folded $k$-point calculation and systematically identifying all applicable space-group symmetry generators -- including spin-parity, point-group, and crystal translation symmetries -- we obtain qubit Hamiltonians with fewer qubits than the Jordan--Wigner starting point. We benchmark diamond, silicon, 3C-SiC, MgO, NaCl, CsCl, h-BN, wurtzite AlN, $α$-quartz SiO$_2$, and MgF$_2$ using active spaces chosen to preserve complete near-degenerate frontier manifolds across cubic, hexagonal, trigonal, and tetragonal space groups. Across the suite the periodic SAE removes 4--8 qubits. The B2 CsCl benchmark realises eight independent Boolean generators, i.e. a symmetry group isomorphic to $\mathbb{Z}_2^8$, reducing CAS(6,7) from 14 to 6 qubits. This exceeds the $\mathbb{Z}_2^5$ maximum of molecular SAE, where only two spin parities and at most three independent Boolean point-group generators are available, because the folded crystal supplies three additional half-translation symmetries. Noiseless UCCSD-VQE benchmarks against exact diagonalisation in the active-space sector show that the reduced encodings preserve the target energies to well below chemical accuracy while reducing variational parameter counts by $3$--$8\times$ and CNOT counts by up to $309\times$. The largest circuit savings occur when translation and point-group generators act independently in the active space, demonstrating that periodic symmetry can be converted directly into both qubit and ansatz compression. The method is implemented in the open-source QuantumSymmetry package and requires no manual specification of symmetry generators.

We study chiroptical properties of single-layer dielectric membrane metasurfaces with broken in-plane symmetry. In sharp contrast to a common belief that chiral optical phenomena require symmetry breaking in the vertical direction, we show that flat single-layer metasurfaces are capable of strong specific chiral effects. Although the single-layer geometry forbids conventional co-polarized circular dichroism, strong resonant conversion circular dichroism appears to be possible in particular wavelength ranges determined by the spectra of photonic eigenmodes. We explore its origin starting with a $C_4$ rotation-symmetric and in-plane mirror-symmetric membrane metasurface and applying to it various in-plane perturbations. Simultaneously breaking of the in-plane mirror symmetry and lifting the rotation symmetry unlocks resonantly enhanced circular conversion dichroism. We derive selection rules for this effect and trace its origin to eigenmode interference and intercoupling using chiral coupled-mode theory.

In power systems, alternating current optimal power flow (AC-OPF) has been a challenging problem for decades due to its nonconvexity, but fast and efficient solutions are even more needed because of high penetration of large scale renewable generation and load growth. Recently, neural networks (NN) have gained attention in solving AC-OPF, but it is still in an early stage to be applicable for real and large-scale power system operation with topology-changing characteristics. To end this, we propose a novel framework called GraphOPF that considers topology-adaptability, scalability, NN training time, self-supervision, and feasibility altogether. Extensive experiments show that the proposed framework against the baselines is up to 200 times faster in NN training and up to 66 times faster in solving AC-OPF for large-scale power systems including the real Korean power system, while achieving more than 99% feasibility.

We introduce exotic Kloosterman sums and exotic inverted Kloosterman sums attached to non-commutative finite-dimensional semisimple algebras over a finite field $\mathbf{F}_q$, and prove their reduction formulae to exotic Kloosterman and exotic inverted Kloosterman sums over commutative étale $\mathbf{F}_q$ algebras. We then obtain square-root estimates for these sums; for inverted sums an explicit correction term may appear.

Hopfield networks offer a hardware-friendly framework for energy-efficient associative memory, yet their practical realization in memristor crossbar arrays is critically hindered by device-to-device (D2D) variability, which prevents reliable parallel programming. Here, we address this bottleneck through systematic composition engineering of the Ge-Te solid electrolyte in conductive bridge random access memory (CBRAM) devices. By varying the Ge:Te ratio, we identify Ge3.5Te1 as an optimal electrolyte composition that suppresses stochastic resistance variation by approximately three orders of magnitude compared to GeSe-based devices. Raman spectroscopy reveals that this dramatic improvement originates from a bonding network dominated by asymmetric-stretching GeTe4 tetrahedral units, which form interconnected free-volume channels that confine and stabilize Cu+ ion migration pathways. Leveraging this enhanced uniformity, we fabricate a selector-less 16x16 Cu/Ge3.5Te1 CBRAM crossbar array and demonstrate a 4x4 Hopfield associative network capable of learning and recalling binary pattern pairs via fully parallel programming using a half-selection scheme. Successful pattern recall is achieved for up to two stored associations despite the absence of selector elements, establishing a proof-of-concept for selector-free hardware implementations of associative memory. These results highlight the critical role of electrolyte bonding structure in determining memristor uniformity and provide a materials-driven pathway toward scalable, parallel neuromorphic computing systems.

The dynamics of quantum measurements defines a precise relation between the information gained about one physical property of a system and the observable changes in another physical property of the same system. Here, we express this relation in terms of the Hilbert space superpositions of the corresponding eigenstates and show how the probability of an observable physical change can be obtained from the Bayesian update of the probabilities associated with the information obtained in the measurement. Our analysis demonstrates that the superposition principle provides the tightest possible expression of the trade-off between information and back action in a quantum measurement.

We study scalarized extremal black holes in the Einstein-Maxwell-scalar theory with two different scalar couplings to two U(1) fields. This theory is inspired by the bosonic sector of $N=4$ supergravity. Two scalarzied extremal black holes are found with constant secondary scalar hair. We confirm that these are exactly obtained from the standard scalarization and entropy function approach. This may imply that it is not easy to find extremal black holes with primary scalar hair.

Huffman encoding has been an enduring technique for 70+ years, ubiquitous in compression algorithms since its invention. In this paper we propose a new approach to Huffman coding, based on a data structure from wavelet trees. The resulting pivot-coded Huffman (PivCo-Huffman) enables high-performance SIMD-friendly encoding and decoding operations. In our tests PivCo-Huffman consistently outperforms state-of-the-art Huffman codecs in decoding throughput. Additionally, we show how ANS-coding can be selectively applied to skewed nodes in this structure, yielding compression ratios approaching those of ANS-based codecs while preserving very high decompression speeds.

This paper establishes the global well-posedness for the 3D anisotropic MHD system with partial dissipation: $Δ_\mathrm{h}u$ for velocity and $\partial_1^2b$ for magnetic field, near background field $(0,1,0)$. Crucially, only horizontal components $(u^\mathrm{h}_0,b^\mathrm{h}_0)$ need to be small in $H^2(\R^3)$, while $(u^3_0,b^3_0)$ can be arbitrarily large. Our analysis develops novel techniques including component-decoupled energies and iterative control of dangerous nonlinearities using the background field structure. This establishes the global result for anisotropic MHD equations allowing large vertical data, breaking the full-smallness requirement of previous works.

The stellar mass function (MF) and its spatial variation (mass segregation) within star clusters encode signatures of early formation physics and subsequent secular evolution. Yet, a coherent evolutionary picture remains elusive due to conflicting reports regarding the universality of the initial mass function (IMF) and the prevalence of primordial mass segregation. These discrepancies often arise from unresolved binaries, field contamination, and completeness bias. Here, we resolve these issues by analyzing 163 high-fidelity open clusters via a Bayesian forward-modeling framework. We reveal a remarkably simple initial state: young clusters ($\lesssim 300$ Myr) share a mean IMF slope of $-2.29$ in the mass range $M \geq 0.5 M_\odot$, consistent with the Salpeter slope but with an intrinsic scatter of 0.17, and exhibit minimal mass segregation at the onset of gas-free evolution ($\sim$10 Myr). This broadly universal "zero-point" for secular evolution disfavors star-forming scenarios that predict strong primordial segregation or significant IMF variations, and suggests that chaotic cluster assembly and gas expulsion efficiently erase any mild primordial inhomogeneities. By tracing the evolutionary sequence from $10^7$ to $10^{9.8}$ yr, we demonstrate that dynamical processing operates on distinct timescales: mass segregation proceeds rapidly via internal relaxation, whereas global MF flattening due to tidal evaporation becomes dominant only after $\sim$600 Myr. These findings impose robust observational constraints on the physics of star formation and early feedback and establish an empirical baseline for modeling secular stellar dynamics.

We study multipartite entanglement structures in the zero-temperature holographic Weyl semimetal, focusing on tripartite and four-partite structures. For strip regions, we compute the conditional mutual information, the entanglement wedge cross section, tripartite measures $κ$ and the Markov gap, multi-EWCS, and two multi-EWCS based four-partite signals $Δ$ and $g$. These quantities are studied as functions of the strip width $l$ and the tuning parameter across the topological transition. At large $l$, their $l$ dependence takes a power-law form governed by the IR scaling of the system. At fixed large $l$, all these entanglement quantities develop clear features near the critical point, showing that tripartite and four-partite entanglement structures can diagnose the topological quantum phase transition. We further study strips pointing in different directions to probe the anisotropy of the system. The anisotropic large l behavior distinguishes the nontrivial phase from the trivial phase. These results establish multipartite holographic entanglement as a sensitive, nonlocal probe of topological phase transitions and anisotropic IR physics.

Energy efficiency is a critical concern in the deployment and operation of 5G networks, particularly due to the low utilization of 4G and 5G carriers during off-peak hours. While considerable research has focused on designing energy-efficient cell on/off switching strategies that avoid disrupting user connectivity, the integration of operator-specific policies to guarantee particular Quality of Service (QoS) levels has received limited attention. This paper presents a machine learning (ML)-based energy saving strategy, trained using a real-world dataset from a European mobile operator, that enforces operator-defined policies that jointly consider strong throughput requirements and maximum outage tolerance constraints. By tuning the model's class ratios during training, the proposed solution enables operators to manage the trade-off between energy savings and QoS policy compliance prior to deployment in live networks. Evaluation results show that the method provides substantial energy savings while maintaining policy-compliant service levels under realistic 5G operating conditions.

Despite the potential for higher energy efficiency in 5G networks, current 5G Non-Standalone (NSA) deployments often operate suboptimally due to low utilization of 4G and 5G carriers during extended periods. Since base stations are the primary contributors to network energy consumption, implementing cell on/off switching and traffic offloading strategies is crucial for enhancing energy efficiency in current deployments. This paper investigates energy-saving opportunities based on these strategies in a real 5G NSA deployment, utilizing a dataset provided by a European Mobile Network Operator. Using Key Performance Indicators from the dataset, we propose a data-driven framework to evaluate the energy-saving and QoS tradeoff when selectively deactivating underutilized 5G cells and offloading their traffic to 4G cells with enough resources within the same sector and site. Our results demonstrate network-wide cell switch-off opportunities ranging from 17% to 79%, while ensuring data rates between 25 Mbps and 5 Mbps, respectively.