In this paper we obtain a new boundedness criterion for the maximal operator $M$ on variable exponent spaces $L^{p(\cdot)}$. It is formulated in terms of the variable exponent analogue of the well known weighted $A_{\infty}$ condition.

We examine how causal beliefs affect an agent's choices and how feedback on those choices leads to updated causal beliefs. Building on the structural-equations framework for modeling causality, we first examine the general problem of updating causal beliefs in the face of novel (and possibly inexplicable) data. We model an agent who is uncertain of the true causal model, and therefore entertains a probabilistic belief over the set of possible models. We then consider how causal beliefs influence choices by building a model of agency and utility on top of the usual structural-equations framework. Using these two components, we propose a notion of steady state, where the feedback received from an agent's optimal action, given her current beliefs about the true causal model, can be rationalized by those beliefs.

Gravitational wave searches rely on a combination of methods, including matched filtering, coherent analyses, and more recent machine learning based pipelines. For compact binary coalescences, where signals originate from the relativistic dynamics of compact objects, matched filtering remains a central element, but its computational cost will increase substantially with the data volumes and parameter-space coverage required by next-generation interferometers such as the Einstein Telescope. Developing complementary strategies that reduce computational load while preserving detection performance is therefore essential. We investigate a hybrid approach that combines matched-filtering concepts with Convolutional Neural Networks, enabling efficient signal searches without relying on the usual $χ^2$ rejection test. Using simulated data sets that include injected signals in Gaussian noise, transient noise, and physical effects not represented in template bank, such as eccentricity, precession and higher-order modes, we show that the method achieves a detection efficiency comparable to a standard matched-filtering search while offering a more resource efficient pipeline. These results indicate that deep learning assisted searches can support sustainable gravitational-wave data analysis in future detector eras.

The Hopfield model provides a paradigmatic framework for associative memory. Its classical implementation, based on the Hebbian learning rule, suffers from catastrophic forgetting: when one attempts storing too many patterns, the network fails to retrieve any of them. Yet, the Hebbian rule does not take into account that synaptic strength is bounded. Introducing this biologically plausible modification, known as "clipping", eliminates catastrophic forgetting; the model is now able to retrieve the most recently seen memories, eliminating older ones. Yet, its memorization capacity is much reduced with respect to the unclipped case. Here, we investigate the effects of adding a "dreaming" phase on the capacity of a clipped Hopfield model. Following a proposal by Hopfield, Feinstein and Palmer, we assume that during the dreaming phase, the model generates random patterns that are then "unlearned". We show that while clipping still removes catastrophic forgetting, alternating learning and dreaming phases improves the memorization capacity and makes the search for optimal performance more realistic from an evolutionary perspective.

Predictive optical modelling of van der Waals (vdW) heterostructures is critical for meta-optics, near-field photonics and quantum technologies. At their buried interfaces, charge transfer and spatially extended screening challenge local descriptions based on layer-by-layer stacking of fixed permittivity tensors. However, such nonlocal corrections have been established mainly for plasmonic systems at ångström-nanometre scales and are often assumed negligible on optical-wavelength scales. Here we challenge this view by uncovering a mesoscopic nonlocal screening regime, extending up to ~140 nm, at buried charge-transfer interfaces in transition-metal dichalcogenide/α-molybdenum trioxide (TMDC/α-MoO3) phonon-polaritonic heterostructures. Using phonon polaritons as an ultrasensitive probe, we quantify charge transfer from polariton-wavelength shifts and find a thickness-independent saturated response as α-MoO3 is thinned. Rather than merely complicating optical modelling, this nonlocal saturation turns a design-level correction into an opportunity by yielding a transferable cross-material metric. Across more than 120 devices, this metric scales linearly with the work-function difference between the TMDC and α-MoO3. We further identify a lattice-mismatch-set energy threshold for charge transfer, revising Anderson-type band alignment for vdW interfaces.

Scaled Relative Graphs (SRGs) provide an intuitive graphical frequency-domain method for the analysis of Nonlinear (NL) systems, generalizing the Nyquist diagram. In this paper, we develop a method for computing $L_2$-gain bounds for Lur'e systems over bounded frequency and amplitude ranges. We do this by restricting the input space of the SRG both in frequency and energy content, and combining with methods from Sobolev theory. The resulting gain bounds over restricted sets of inputs are less conservative than bounds computed over all of $L_2$, and yield three-dimensional NL generalization of the Bode diagram, plotting $L_2$-gain as function of both input frequency and energy content. In the zero-energy limit, the Linear Time-Invariant (LTI) Bode diagram is recovered, and at the infinite-energy zero-frequency limit, we recover the $L_2$-gain. The effectiveness of our method is demonstrated on an example that resembles Phase-Locked Loop dynamics.

Tracking pixels are used to optimize online ad campaigns through personalization, re-targeting, and conversion tracking. Past research has primarily focused on detecting the prevalence of tracking pixels on the web, with limited attention to how they are configured across websites. A tracking pixel may be configured differently on different websites. In this paper, we present a differential analysis framework: PixelConfig, to reverse-engineer the configurations of Meta Pixel deployments across the web. Using this framework, we investigate three types of Meta Pixel configurations: activity tracking (i.e., what a user is doing on a website), identity tracking (i.e., who a user is or who the device is associated with), and tracking restrictions (i.e., mechanisms to limit the sharing of potentially sensitive information). Using data from the Internet Archive's Wayback Machine, we analyze and compare Meta Pixel configurations on 18K health-related websites with a control group of the top 10K websites from 2017 to 2024. We find that activity tracking features, such as automatic events that collect button clicks and page metadata, and identity tracking features, such as first-party cookies that are unaffected by third-party cookie blocking, reached adoption rates of up to 98.4%, largely driven by the Pixel's default settings. We also find that the Pixel is being used to track potentially sensitive information, such as user interactions related to booking medical appointments and button clicks associated with specific medical conditions (e.g., erectile dysfunction) on health-related websites. Tracking restriction features, such as Core Setup, are configured on up to 34.3% of health websites and 8.7% of control websites. However, even when enabled, these tracking restriction features provide limited protection and can be circumvented in practice.

The observation that optimum circuit size changes by at most $O(n)$ under a one-point truth table perturbation is implicit in prior work on the Minimum Circuit Size Problem. This note states the bound explicitly for arbitrary fixed finite complete bases with unit-cost gates, extends it to general Hamming distance via a telescoping argument, and verifies it exhaustively at $n = 4$ in the AIG basis using SAT-derived exact circuit sizes for 220 of 222 NPN equivalence classes. Among 987 mutation edges, the maximum observed difference is $4 = n$, confirming the bound is tight at $n = 4$ for AIG.

Structure and dynamics of a polymer under confinement gets significantly altered due to the imposed geometric restrictions. Using molecular dynamics simulations, here, we explore the effect of cylindrical confinement on the kinetics of collapse of a homopolymer, when the solvent condition is abruptly changed from good to poor. The observed phenomenology for a range of the cylinder radius $R$, reveals two distinct stages of the collapse. The first stage is highlighted by the formation and growth of local connected clusters resembling a pearl necklace, eventually ending with a single sausage-like cluster. In the second stage, the sausage-like intermediate approaches a spherical globule via surface-energy minimization. These two stages are disentangled using a shape parameter of the individual pearls or clusters, allowing us to also extract the respective relaxation times, and thereby their scaling behaviors with respect to the length of the polymer. We find that the pearl-necklace relaxation time $τ_p$ is independent of $R$. On the other hand, the sausage-relaxation time $τ_s$ varies inversely up to a certain $R$, beyond which it also saturates. From the Arrhenius plots of the temperature dependence of $τ_p$ and $τ_s$, we extract the activation energies $E_{\rm a}$ of the two stages. While the estimated $E_{\rm a}$ for the pearl-necklace stage is independent of $R$, for the sausage relaxation it is significantly higher in the strongly confined case than in the weakly one. Surprisingly, at a fixed temperature, the growth of the average cluster size obeys a universal power law irrespective of $R$. However, for a fixed $R$, the behavior is rather non-universal with respect to temperature. We propose viable scenarios for experimental realization of polymer collapse inside cylindrical nanochannels.

We give necessary and sufficient conditions for a hyperbolic set to be non-chaotic (or, conversely, chaotic) in a certain sense.

We consider a model Hamiltonian, introduced by Fermi in 1936, describing a two-particle system made of a neutron and a harmonically bound proton, where the neutron-proton interaction has the form of a $δ$-potential. For such Hamiltonian we prove the Limiting Absorption Principle and describe the stationary scattering theory. Finally, we derive Fermi's formula for the scattering cross-section valid in the Born approximation.

In 1962, Guido Zappa asked whether a non-trivial coset of a Sylow $p$-subgroup of a finite group could contain only elements whose orders are powers of $p$. Marston Conder gives a positive answer to this question in the case of $p=5$. It is known that the smallest group satisfying the conditions of this problem must be a non-abelian simple group. In this paper, we prove that the smallest group of the Zappa problem could not be an alternating simple group for any prime $p$.

Delegated quantum computation enables a client with limited quantum capabilities to outsource computations to a more powerful quantum server while preserving correctness and privacy. Verification is crucial in this setting to ensure that the untrusted quantum server performs the computation honestly and returns correct results. A common verification method is the quantum cut-and-choose technique. Inspired by classical verification methods for two-party computation, the client uses the majority of the delegated rounds to test the server's honesty, while keeping the remaining ones for the actual computation. Combining this technique with other methods, such as quantum error correction, could help achieve negligible cheating probabilities for the server; however, such methods can impose significant overheads making implementations unfeasible for the near-term future. In this work, we investigate whether cut-and-choose can yield efficient and secure verifiable quantum computation without additional costly techniques. We find that verifiable delegated quantum computation protocols relying solely on cut-and-choose techniques cannot be secure and efficient at the same time.

Hot electrons undergo Auger scattering during their relaxation process has a multiplication effect,which can generate more electrons above the Fermi level, thus improving the efficiency of photoelectric signal conversion.However,the photo-current gain brought by the Auger carrier multiplication is generally limited with a value less than 5,due to the rapid recombination of photo-generated charge-carriers and the inherently low light absorption of two-dimensional materials.Herein,by twisting graphene to an interlayer angle of 10_o,we report a layer-dependent electronic correlations leading to an efficient carrier multiplication gain of 10³.This is primarily offered by the additional localized density-of-states at interface of the bi-layer 10_o,moire graphene,and the enhanced interlayer coupling of electron waves in a five-layer moire graphene superlattice structure.Therefore,we can harvest the hot electrons during their energy relaxation through a thermalized optical phonon bottleneck effect.It is this effect that promotes the accumulated hot electrons to achieve a maximum Auger scattering rate ~ 10¹⁰*ps^-1*cm^-2.Furthermore,the ballistic transport of these hot electrons and Schottky barrier from a 90 nm thick silicon-on-insulator (SOI) silicon effectively block the thermal noise,thus leading to a highly sensitive near-infrared detection characteristic.At a low incident light power of ~ 10^-13 W/cm²,the resulting signal-to-noise ratio is more than 100 dB.The strengthened electromagnetic interaction from highly thermalized optical phonon in stacked moire graphene is utilized in this work.The hot electron multiplication suggests the applicability of Van der Waals moire superlattice architecture for harvesting charge carriers,thus paving the pathway to design infrared single-photon avalanche detectors.

The ABCT variety $V(3,n)$ is the image closure of the rational Veronese map from the Grassmannian $\operatorname{Gr}(2,n)$ to the Grassmannian $\operatorname{Gr}(3,n)$. It was studied by Arkani-Hamed--Bourjaily--Cachazo--Trnka in the context of tree-level scattering amplitudes arising in planar $\mathcal N=4$ supersymmetric Yang-Mills theory and Witten's twistor string theory. From this perspective, $V(3,n)$ is conjectured to be a positive geometry by Lam. In this paper, we study the combinatorial and algebraic geometry aspects of $V(3,n)$ and its subvarieties induced by iteratively taking analytic boundaries of the totally nonnegative part. We interpret these subvarieties as point configurations on $\mathbb{P}^2$ by the Gelfand-MacPherson correspondence. We construct a top-degree meromorphic form on $V(3,n)$ and show that it is a positive geometry, proving Lam's conjecture.

The cooperative effect of Rashba spin-orbit coupling (SOC) and Coulomb attraction in stabilizing topological spin-triplet excitonic condensates (ECs) in two-dimensional electron-hole systems in external magnetic field is investigated by using an unrestricted Hartree-Fock approach combined with the random-phase approximation. At weak electron-hole Coulomb interaction, the intraband Rashba SOC induces spin-momentum locking and topological semimetal behavior, while stronger interaction stabilizes spin-triplet ECs. Increasing the valence-band SOC drives a transition from a topologically trivial EC with coexisting spin-up and spin-down components to a topological spin-up EC only with quantized Chern number $C=2$. The dynamical excitonic susceptibility reveals a soft spin-up triplet mode acting as the precursor of the condensate. These results establish a microscopic mechanism for Rashba SOC-induced topological ECs and suggest realistic situations for their realization in noncentrosymmetric Janus transition-metal dichalcogenides and twisted van der Waals heterostructures.

We investigate the influence of phonon degrees of freedom on the qubit dynamics in Jaynes-Cummings (JC) model. A strong qubit-phonon coupling is considered giving rise to Jaynes-Cummings-Holstein (JCH) model. Under anti-adiabatic conditions, we perform a unitary transformation to make the underlying problem tractable through Redfield-type non-Markovian master equation. Analytical expression for the time-dependent coherence is obtained, incorporating both cavity-induced dissipation and phonon-induced dressing effects. The dynamics of JC model is highly non-Markovian for a narrow spectral width and finite detuning. However, a non-zero phonon coupling suppresses these non-Markovian features by effectively reducing the qubit-cavity interaction strength. {It is observed that polaronic dressing effectively supresses the detuning effects. Furthermore, the coherence-based non-Markovianity measure shows an order-of-magnitude suppression in the JCH model, indicating a new dynamical regime, while memory effects extend over a wider range of spectral densities than in the JC model.

We introduce the application of Time-Dependent Hartree-Fock (TDHF) theory to two key aspects of heavy-ion reaction dynamics for producing superheavy elements: fusion and quasi-fission (QF). For fusion reactions $^{48}$Ca+$^{238}$U, the capture cross sections, fusion probabilities, and evaporation-residue cross sections are calculated using the inputs from TDHF simulations, and the results are found to be in reasonable agreement with available experimental data. For the QF process of $^{48}$Ca+$^{249}$Bk, we show the distribution of the fragments and investigate the impact of the tensor force, significantly enhancing the role of spherical shell effects.

Advanced Persistent Threats (APTs) pose critical challenges to modern cybersecurity due to their multi-stage and stealthy nature. While provenance-based detection approaches show promise in capturing causal attack semantics, current threat provenance practices face two paradoxical issues: (1) expert skepticism, where human analysts doubt the capability of traditional detection models to identify complex attacks; and (2) expert dependence, as analysts cannot manually process large-scale raw logs to detect threats without these models. Consequently, collaboration between humans and traditional models remains the prevailing paradigm. However, this renders investigation quality contingent upon human expertise and frequently results in alert fatigue. To address these challenges, we present ProvAgent, a framework that evolves the threat provenance paradigm from human-model collaboration to a novel collaboration between multi-agent systems and traditional models. ProvAgent leverages the speed and cost-efficiency of traditional models for initial anomaly screening over large-scale logs. By enforcing fine-grained identity-behavior consistency via graph contrastive learning, it profiles entities based on specific attributes to generate high-fidelity alerts. With these alerts serving as investigation entry points, ProvAgent achieves in-depth autonomous investigation through a hypothesis-verification multi-agent framework. Evaluations with real-world datasets demonstrate that ProvAgent outperforms six state-of-the-art (SOTA) baselines in anomaly detection. Through automated investigation, ProvAgent reconstructs near-complete attack processes at a minimum cost of \$0.06 per day.

We report the deterministic experimental realization and controlled fission of magnetic multi-soliton states in a uniform quasi-one-dimensional immiscible two-component Bose gas. We explore the Manakov regime, where the spin dynamics is well described by the easy-axis Landau-Lifshitz equation (LLE). The gauge equivalence between the easy-axis LLE and the attractive nonlinear Schrödinger equation (NLSE) enables the direct construction of magnetic multi-solitons from the well-known NLSE solutions. We observe the two- and three- soliton states, which exhibit robust breathing in quantitative agreement with integrable theory. By introducing a weak, localized perturbation, we controllably break integrability and induce the splitting of a two-soliton into its fundamental constituents. This process reveals the composite structure of multi-soliton states and realizes an experimental analog of the inverse scattering transform.

Topological invariants and their associated anomalies have played a crucial role in understanding low-energy phenomena in quantum field theories. In lattice gauge theory, the standard $\mathbb{Z}$-valued Atiyah-Singer index is formulated via the overlap Dirac operator through the Ginsparg-Wilson relation, but extensions to more general topological invariants have remained limited. In this work, we propose a lattice formulation of the Arf-Brown-Kervaire (ABK) invariant, which takes values in $\mathbb{Z}_8$. The ABK invariant arises in Majorana fermion partition functions with reflection symmetry on two-dimensional non-oriented manifolds, and its definition involves an infinite sum over Dirac eigenvalues that must be properly regularized. By carefully treating the boundary conditions, with and without a domain-wall mass term, we demonstrate that the ABK invariant can be extracted from Pfaffians of the Wilson Dirac operator. We further provide numerical verification on two-dimensional lattices, showing that the $\mathbb{Z}_8$-valued results on the torus, Klein bottle, real projective plane, and Möbius strip agree with those in the continuum theory.

The cores of wide-orbit giant planets can form via pebble accretion if large planetesimals form in the outer regions of protoplanetary discs at sufficiently early times. Streaming instability simulations support mass distributions consistent with Solar System minor body constraints, but when and where planetesimal formation took place remains uncertain. Here, we report on our N-body simulations of core formation through pebble and planetesimal accretion starting from streaming-instability inspired planetesimal mass distributions. We explore two initial radial planetesimal distributions, a ring-like and a spatially more uniform distribution, between 10 and 50 AU. To address the numerical challenge of simulating realistic planetesimal numbers, corresponding to one to ten Earth masses of planetesimals, we made use of GPU acceleration for the N-body interactions (with GENGA) and a newly developed pebble accretion module. We find that the top of the planetesimal mass distribution provides the seeds for core formation through pebble accretion, leading to the formation of multiple giant planets. This is consistent with previous studies not including N-body interactions. Planetesimal surface densities, crudely corresponding to an initial 10% formation efficiency, imply low mean collision rates (around unity) in the gas disc phase. Our simulations show that giant planet formation depends only weakly on the initial locations where planetesimals form, because of rapid dynamical scattering, and on their total mass budget, due to filtering of the pebble flux between embryos. After disc dissipation, giant planet systems stir the remnant primordial planetesimals, making a scattered disc an inherent outcome of giant planet formation. Giant impacts between planetary cores generally appear to be rare in the first 100 Myr.

The matrix Numerov method provides an efficient framework for solving the time-independent Schrödinger equation as a matrix eigenvalue problem. However, for singular potentials such as the Coulomb interaction, the expected fourth-order convergence deteriorates for low angular momenta due to the behavior of the potential near the origin. We show that this loss of accuracy originates from an implicit boundary assumption in the standard formulation. By incorporating analytic near-origin information into the discretized Hamiltonian, we derive simple boundary corrections that restore fourth-order convergence and can even produce higher convergence rates for $s$- and $p$-wave energies. The resulting scheme preserves the simplicity and computational efficiency of the original method while significantly improving its accuracy for singular potentials.

Modern AI and vector search are rapidly converging, forming a promising research frontier in intelligent information systems. On one hand, advances in AI have substantially improved the semantic accuracy and efficiency of vector search, including learned indexing structures, adaptive pruning strategies, and automated parameter tuning. On the other hand, powerful vector search techniques have enabled new AI paradigms, notably Retrieval-Augmented Generation (RAG), which effectively mitigates challenges in Large Language Models (LLMs) like knowledge staleness and hallucinations. This mutual reinforcement establishes a virtuous cycle where AI injects intelligence and adaptive optimization into vector search, while vector search, in turn, expands AI's capabilities in knowledge integration and context-aware generation. This tutorial provides a comprehensive overview of recent research and advancements at this intersection. We begin by discussing the foundational background and motivations for integrating vector search and AI. Subsequently, we explore how AI empowers vector search (AI4VS) across each step of the vector search pipeline. We then investigate how vector search empowers AI (VS4AI), with a particular focus on RAG frameworks that integrate dynamic, external knowledge sources into the generative process of LLMs. Furthermore, we analyze end-to-end co-optimization strategies that fully unlock the potential of the ``virtuous cycle" between vector search and AI. Finally, we highlight key challenges and future research opportunities in this emerging area. This paper was published in ICDE 2026.

In this paper, we introduce a new notion called the \textit{set of missing generators} $\mathcal{M}(g)$ for a generator (or primitive element) $g$ of the cyclic group $\mathbb{Z}_p^*$, where $p$ is an odd prime. The cardinality of $\mathcal{M}(g)$ is established for all odd primes $p$. For primes $p$ of the form $2^iq_1^{j_1}q_2^{j_2}+1$, the collection $V_p = \{ \mathcal{M}(g):g\in \mathcal{G} \}$ forms an equinumerous partition of $\mathcal{G}$ (the set of all generators of $\mathbb{Z}_p^*$), and a digraph defined on the vertex set $V_p$ is a disjoint collection of unicycles of the same size. Thus, for every such prime, an unique triplet $(c,n,e)$ of integers, describing the structure of the digraph of missing generators, can be associated. With the help of cyclic structure, we present a macroscopic additive property of generators of $\mathbb{Z}_p^*$. Further, we show that factoring RSA numbers is computationally equivalent to computing $T(p)$, under the assumption that there exists an absolute constant $k$ such that the set $\{2^iN^j+1: 1\leq i,j<\log^k N\}$ contains a prime for any given odd $N$.

We consider propagation of instability fronts in conservative nonlinear wave systems by the Whitham method. Whitham modulation equations for periodic solutions of the generalized Klein-Gordon equation are solved in the limit of asymptotically large times, when the size of the instability wave region is much greater than the size of the initial localized disturbance, so the solution reaches the self-similar regime. The general self-similar solution is illustrated by two typical examples of the nonlinearity function. It is shown that in these models the instability fronts propagate with maximal group velocity.

Deploying Model Predictive Control on nano-scale aerial platforms is challenging due to the severe computational limitations of onboard microcontrollers. This paper presents an experimental study with computational focus of a dual active-set solver (DAQP) applied to the low-level control of a Crazyflie 2.1 nano-quadcopter. Unlike previous approaches that utilize first-order methods for low-level stabilization or restrict active-set solvers to high-level control, this work demonstrates the successful deployment of a dual active-set method executing at 500 Hz on an STM32F405 microcontroller. We provide a direct benchmark against a state-of-the-art ADMM-based solver (TinyMPC), revealing that the active-set method yields lower execution times for the flight envelopes considered. Furthermore, to manage the complexity of certifying the solver's real-time feasibility, we introduce a data-driven set selection method using Principal Component Analysis. Using this approach, state-of-the-art real-time certification methods can be applied to confirm or reject real-time feasibility already off-line prior to flight. More generally, the experimental results validate that active-set methods are a highly competitive alternative for high-frequency control on resource-constrained hardware and the possibility for their real-time certification adds reliability.

Screening mechanisms are essential components in many modified gravity theories, which satisfy local tests of General Relativity (GR) and address cosmic acceleration on cosmological scales. The strong gravitational lensing of gravitational waves (GWs) offers a unique observational probe into cosmology and fundamental physics. In this paper, we investigate the possibility of testing screened modified gravity theories with strongly lensed gravitational waves. Specially, we develop the refined theoretical and statistical framework, in order to measure the post-Newtonian parameter $γ_{\text{PN}}$ in the presence of screening effects. Specially, the mass-truncated power-law and Navarro-Frenk-White (NFW) models are introduced to quantify the modified lensing potential. Our analysis also addresses the mass-sheet degeneracy (MSD) problem, by incorporating the absolute magnification and time delay measurements accessible through strongly lensed GW systems. We find that individual lensed GW system detected by next-generation GW detectors can provide stringent constraints on the PPN parameter ($γ_{\text{PN}}$) across different screening scales ($Λ$). Therefore, future measurements of strongly lensed GWs have great promise to seek departures from GR on kpc-Mpc scales, due to more precise time delay from lensed GW signals.

A large fraction of the extragalactic sky is obscured by foreground dust and stars along the plane of the Milky Way, leaving a major gap (~ 20%) in whole-sky maps of large-scale structures -- an incompleteness that is even more severe for peculiar velocity samples. This has long limited an unambiguous interpretation of observed cosmic flows and their connection to the underlying mass-density field. We present a new hybrid reconstruction methodology which combines 65,518 galaxy peculiar velocity distances from the CF4++ catalogue (Courtois2025) with 8283 new galaxy redshifts observed near the southern Galactic plane (|b| <= 10 degrees) Zone of Avoidance. A major advance is the inclusion of 2176 high-sensitivity, interferometric HI redshifts obtained with the SARAO MeerKAT telescope which for the first time provide coverage of the innermost 3degrees-wide strip of the southern ZOA and to unprecedented depth. This hybrid redshifts & peculiar velocities approach yields a substantially revised view of the inferred overdensities in and around the ZOA. In particular, the Vela supercluster emerges as a dominant mass concentration, rivaling the Shapley concentration and exceeding the mass associated with Laniakea and the Great Attractor region. With a total mass of 33.8 10^16 Msol, a characteristic radius of 70 hmpc, and a double core morphology at a distance of 189 hmpc, Vela dominates the mass budget and gravitational influence of the southern Zone of Avoidance. These results provide the most complete and dynamically consistent picture to date of the southern Zone of Avoidance and demonstrate the transformative potential of hybrid reconstruction techniques tailored for the next generation of large-scale surveys.

Fluctuations of conserved charges provide a link between high quality theoretical results and precision measurements of heavy ion collisions. We compare results for ratios of the lowest order baryon number susceptibilities from functional QCD approaches to proton number cumulants extracted from experiments. We find that they meet at a specific temperature and chemical potential for each collision energy. This is indicative of the respective freeze-out point. From this self-consistent determination of the freeze-out parameters we extract a prediction for the kurtosis on the freeze-out line. We find quantitative agreement with experimental data where available, despite comparing apples (baryons) with oranges (protons). At a collision energy around 5 GeV, our kurtosis exhibits a peak structure indicative of the critical end point of QCD.