Reconstructing the parameters that encode the influence between model variables based on time-series measurements represents an outstanding question in the theory of complex network-coupled systems. Here, we propose a solution to this problem for a class of noisy leader-follower consensus algorithm, where one has access to measurements only from the followers but not from the leaders. Leveraging the directed Laplacian coupling of such systems, we present an autoregressive expansion of the observed dynamics which can be truncated at different orders, depending on the memory of the leaders. When their memory is short, this allows one to correctly reconstruct the full dynamical matrix with hidden leader agents, provided some additional assumption on the system to lift the degeneracy in the reconstruction. We illustrate and check the theory using numerical simulations for the cases of both a single and multiple hidden leaders.

In this paper, we show that the application of propagating waves can induce a DC current even in systems with spatial inversion symmetry. We derive the equation for the DC current induced by propagating waves using two methods: perturbation theory and Floquet theory. These two approaches yield consistent results. We then apply the equation to gapless graphene subjected to propagating waves. A nonzero DC current is predicted in graphene with next nearest neighbor hopping terms. Nonperturbative effects arising from a strong wave amplitude are also discussed within the framework of Floquet theory.

We demonstrate, using computer simulations and a non-equilibrium Greens function approach, that the sign of the out-of-equilibrium interlayer exchange coupling (ooeIEC) can change in the presence of an externally applied electrical bias. Our system consists of an insulating section connected to an exchange coupled ferromagnetic (FM) tri-layer, sandwiched between semi-infinite leads. When the exchange coupled trilayer contains a quantum-well state confined in the hybridisation gap (HG) of the FM, we find that a relatively small applied electrical bias can switch the lowest energy state of the tri-layer between parallel (P) and anti-parallel (AP) configurations. We consider three cases for the insulating section; a single tunnelling barrier, a resonant tunnelling barrier and an amorphous insulating barrier and, in each case, show that the bias dependence of the ooeIEC is strongly dependent on the system conductance. We find that the lowest switching current densities are achieved with strongly confined quantum well states.

The material ejected from a binary neutron star merger produces "kilonova," a radioactively powered emission at ultraviolet, optical, and infrared wavelengths. The early-phase spectra of the kilonova AT2017gfo, following the gravitational wave event GW170817, exhibit a strong absorption feature around $1\,\mathrm{μm}$. Helium (He) and strontium (Sr) have been proposed as the candidate elements contributing to this feature. However, due to the lack of consistent modeling including these two elements simultaneously, the exact contributions of each element to this feature remain unclear. In this study, we develop non-local thermodynamic equilibrium ionization models for He and Sr that take into account ionization by high-energy electrons, and estimate the abundances of each element required to reproduce the observed feature. Our modeling indicates that about $1\, \%$ of He or $1\mathrm{-}10\, \%$ of Sr in mass fraction are present in the ejecta moving at $v \sim 0.15 \, c$. This Sr mass fraction nicely agrees with the mass fraction in the solar $r$-process abundance. Based on comparison with nucleosynthesis calculations, our constraints suggest that $r$-process nucleosynthesis in GW170817 occurs at relatively low electron fraction ($Y_{\rm e} \lesssim 0.35$) and low entropy ($s \lesssim 30 \ k_B/\, \mathrm{nucleon}$) conditions. Interestingly, for $Y_{\rm e}$ $\lesssim 0.15$, the observed feature is reproduced by He with a mass fraction expected from $α$ decays of trans-Pb nuclei, which gives an indirect signature for the production of elements beyond the third $r$-process peak.

A measurement of the CKM angle $γ$ and related strong-phase parameters is performed using a novel, model-independent approach in ${B^{\pm}\rightarrow D(\rightarrow K^{0}_{\rm S} h^{\prime+}h^{\prime-}) h^{\pm}}$ decays, where $h^{(\prime)} \equiv π, K$. The analysis uses a joint data sample of electron-positron collisions collected by the BESIII experiment at the Beijing Electron-Positron Collider II during 2010--2011 and 2021--2022, corresponding to an integrated luminosity of 8 fb$^{-1}$, and proton-proton collisions collected by the LHCb experiment at the Large Hadron Collider during 2011--2018, corresponding to an integrated luminosity of 9 fb$^{-1}$. The two datasets are analyzed simultaneously by applying per-event weights based on the amplitude variation over the $D$-decay phase space to enhance the sensitivity to $C\!P$-violating observables. The CKM angle $γ$ is determined to be $γ= (71.3\pm 5.0)^{\circ}$, which constitutes the most precise single measurement to date.

Recent studies document strong empirical support for multifactor models that aim to explain the cross-sectional variation in corporate bond expected excess returns. We revisit these findings and provide evidence that common factor pricing in corporate bonds is exceedingly difficult to establish. Based on portfolio- and bond-level analyses, we demonstrate that previously proposed bond risk factors, with traded liquidity as the only marginal exception, do not have any incremental explanatory power over the corporate bond market factor. Consequently, this implies that the bond CAPM is not dominated by either traded- or nontraded-factor models in pairwise and multiple model comparison tests.

We recently proposed a method called Material Fingerprinting for the rapid discovery of mechanical material models that avoids solving continuous optimization problems. Material Fingerprinting assumes that each material exhibits a unique response when subjected to a standardized experimental setup, which is interpreted as the material's mechanical fingerprint. If a database of fingerprints is generated in an offline phase, a model for an unseen experimental measurement can be discovered in real time by comparing the experimentally measured fingerprint to the fingerprints in the database. In our original contributions, the database comprised a fixed number of material models, each with a fixed number of parameters. To increase the fitting flexibility of Material Fingerprinting, we propose an adaptive model database coupled with an iterative pattern recognition algorithm that refines the material model in each step. This strategy enables Material Fingerprinting to discover arbitrary linear combinations of material models from the database, rather than being restricted to selecting a single model from a predefined set. In comparison to previous works on Material Fingerprinting, this enables the discovery of more complex models, such as multi-term Ogden models or the anisotropic Holzapfel-Gasser-Ogden model. To design the adaptive database, we leverage sums of strain energy density feature functions that depend on isotropic and anisotropic invariants. All modeling features satisfy fundamental physical constraints, and polyconvexity can be optionally enforced via a simple user-controlled switch. We test the method on experimental data stemming from mechanical tests of isotropic rubber materials and anisotropic animal skin tissue.

We study solution-generating techniques based on the Breitenlohner--Maison linear system for extremal, stationary biaxisymmetric black hole solutions in five-dimensional $U(1)^3$ supergravity. Focusing on multi-center configurations over a Gibbons--Hawking base, we analyze both BPS and almost-BPS solutions, including rotating single-center black holes and two-center black rings. After dimensional reduction to three dimensions, the system is described by a coset sigma model with target space $SO(4,4)/[SO(2,2)\times SO(2,2)]$, where solutions are encoded in coset and monodromy matrices. For Bena--Warner BPS solutions, we construct the coset and monodromy matrices and show that they admit an exponential representation governed by nilpotent elements. Although the monodromy matrices generically exhibit double poles, they can be factorized explicitly using the nilpotent algebra of $\mathfrak{so}(4,4)$, reconstructing the solutions. We extend this to almost-BPS solutions and derive the corresponding matrices. While the single-center case exhibits commuting residues, the two-center black ring leads to a more intricate structure with a third-order pole, which disappears when regularity is imposed. Finally, we analyze the extremal limits of the Rasheed--Larsen solution, where the fast-rotating branch is governed by idempotent elements. We also construct an explicit $SO(4,4)$ duality transformation relating the slowly-rotating branch to a single-center almost-BPS solution. These results will provide the BM formalism as a unified framework for extremal multi-center black holes.

The Foundations of Future Communication Systems (FFCS) conference brought together leading researchers from information theory, quantum communication, molecular communication, semantic communication, and secure network design to explore the fundamental principles shaping next-generation communication systems. The event serves as a platform for interdisciplinary exchange, bridging classical Shannon theory, post-Shannon paradigms, quantum information science, and emerging physically grounded communication models. This report compiles the abstracts of all invited talks, contributed presentations, and poster contributions presented at FFCS. The collected works reflect the breadth of contemporary research directions, including identification-based communication, entanglement-assisted networks, semantic and goal-oriented communication, coding for molecular and nanoscale systems, secure authentication mechanisms, and information-theoretic limits of novel physical-layer architectures. A central theme of the conference was the re-examination of foundational limits under realistic physical, architectural, and security constraints. Many contributions move beyond traditional rate-centric perspectives and instead investigate reliability, identification, semantics, resource efficiency, and trust in complex and heterogeneous networks. The inclusion of poster abstracts further highlights emerging ideas, early-stage research results, and innovative cross-disciplinary approaches that contribute to shaping future communication paradigms. By documenting the intellectual landscape presented at FFCS, this report aims to provide a structured overview of current research frontiers and to stimulate continued collaboration across theoretical and experimental domains.

The development of large-scale superconducting quantum computing requires efficient in-situ control methods that allow high-fidelity operations at millikelvin temperatures. Superconducting circuits based on Josephson junctions offer a promising solution due to their high speed, low power dissipation, and cryogenic nature. Here, we report a superconducting quantum controller that enables direct chip-to-chip interconnection with qubits at 10 mK and high-fidelity, all-digital manipulation. Randomized benchmarking reveals a uniformly high average Clifford fidelity of 99.9% with leakage to high energy levels on the order of $10^{-4}$, and an estimated average gate operation energy of 0.121 fJ, demonstrating the potential to resolve the control bottleneck in superconducting quantum computing.

The use of terahertz (THz) and optical radiation for electron acceleration and manipulation of electron bunches has progressed over the last decade to a level where practical devices for THz guns, THz and optical acceleration modules and a wide range of beam manipulations have become possible. Here, we discuss recent progress in optical driven Terahertz generation and its use in charged particle acceleration and beam manipulation devices. The advantages of using shorter wavelength radiation for acceleration are in overcoming breakdown phenomena, therefore enabling higher acceleration gradients than in conventional RF-accelerators albeit with lower bunch charge. The lower pulse energies needed to power the smaller cross section of the accelerating structures is also advantageous. In addition, the shorter wavelengths enable tighter timing control of the generated electron bunches but in return also need more precise timing when multiple stage interactions are required. Early results on THz guns, beam manipulation devices and accelerator structures are discussed as well as basic working principles of dielectric laser accelerators.

Tree-decompositions and treewidth are of fundamental importance in structural and algorithmic graph theory. The "spread" of a tree-decomposition is the minimum integer $s$ such that every vertex lies in at most $s$ bags. A tree-decomposition is "domino" if it has spread 2, which is the smallest interesting value of spread. So that spread 1 becomes interesting, one can relax the definition of tree-decomposition to "tree-partition", which allows the endpoints of each edge to be in the same bag or adjacent bags, while demanding that each vertex appears in exactly one bag. Ding and Oporowski [1995] showed that every graph $G$ with treewidth $k$ and maximum degree $Δ$ has a tree-partition with width $O(kΔ)$. We prove the same result with an improved constant, and with the extra property that the underlying tree has maximum degree $O(Δ)$ and $O(|V(G)|/kΔ)$ vertices. This result implies (with an improved constant) the best known upper bound on the domino treewidth of $O(kΔ^2)$, due to Bodlaender [1999]. Moreover, solving an open problem of Bodlaender, we show this upper bound is best possible, by exhibiting graphs with domino treewidth $Ω(kΔ^2)$ for $k\geqslant 2$. On the other hand, allowing the spread to be a function of $k$, we show that width $O(kΔ)$ can be achieved. This result exploits a connection to chordal completions, which we show is best possible, a result of independent interest.

In this paper, we investigate various key aspects of a static and spherically symmetric black hole with global monopole. Firstly, we analyze the deflection angle in the strong field limit of massive particle by the global monopole. It shows that the angle of deflection increases when the two characteristic parameters for monopole configuration increase. The influence of the global monopole parameter on the lensing observables and the black hole shadow are studied. This shows that larger monopole parameter corresponds to larger shadow radii. The dynamics of timelike geodesics is also investigated in the spacetime. General circular orbits and the innermost stable circular orbits (ISCO) of timelike particles are discussed, highlighting that the monopole parameter significantly affects the circular orbits and the ISCO. In particular, it is observed that the radius of ISCO rises monotonically with $η$. In addition, the Lyapunov exponent is used to analyze the stability of timelike geodesics. The quasinormal modes for electromagnetic perturbation of the black hole with varying $η$ is also investigated. Our findings indicate that increasing the monopole parameter gives rise to gravitational waves with slower damping oscillations. To further validate the derived quasinormal mode spectrum, we discuss the evolution of electromagnetic perturbations in the time domain profile, confirming the presence of the characteristic quasinormal ringing followed by late-time power-law tails.

In this paper, we propose an initial value fomulation of the discrete mean field games on finite graphs (Graph MFG), and design a neural network based approach to solve it. Graph MFG describes infinite, non-cooperative and interactive homogeneous agents move on node states through the edges to optimize their own goals. Nash Equilibrium of the Graph MFG is characterized by a coupled ordinary differential equations (ODE) system, including the discrete forward continuity equation and the discrete backward Hamilton-Jacobi equation. In this paper, we mainly focus on the potential mean field games (Potential MFG) on finite graphs, which has an infinite-dimensional constrained optimization structure. We reformulate Potential MFG as an initial value finite-dimentional optimization problem with dynamics constrains, names Graph MFG-IV. Specifically, the initial condition of the Hamilton-Jacobi equation is regarded as the unique variable, constrained by the coupled Hamilton-Jacobi and continuity equation system as the ODE integrator. This formulation is a reduced-order model, which avoids time-discretization of the infinite-dimensional path and has a much smaller searching space than the general path-wise problem setting. We design a neural network-based approach to solve the Graph MFG-IV problem.

With the increasing accessibility and utilization of multilingual documents, Cross-Lingual Information Retrieval (CLIR) has emerged as an important research area. Conventionally, CLIR tasks have been conducted under settings where the language of documents differs from that of queries, and typically, the documents are composed in a single coherent language. In this paper, we highlight that in such a setting, the cross-lingual alignment capability may not be evaluated adequately. Specifically, we observe that, in a document pool where English documents coexist with another language, most multilingual retrievers tend to prioritize unrelated English documents over the related document written in the same language as the query. To rigorously analyze and quantify this phenomenon, we introduce various scenarios and metrics designed to evaluate the cross-lingual alignment performance of multilingual retrieval models. Furthermore, to improve cross-lingual performance under these challenging conditions, we propose a novel training strategy aimed at enhancing cross-lingual alignment. Using only a small dataset consisting of 2.8k samples, our method significantly improves the cross-lingual retrieval performance while simultaneously mitigating the English inclination problem. Extensive analyses demonstrate that the proposed method substantially enhances the cross-lingual alignment capabilities of most multilingual embedding models.

Maximum distance separable (MDS) and almost maximum distance separable (AMDS) codes have been widely used in various fields such as communication systems, data storage, and quantum codes because of their algebraic properties and excellent error-correcting capabilities. In this paper, we construct a class of extended twisted generalized Reed-Solomon (TGRS) codes and determine the necessary and sufficient conditions for these codes to be MDS or AMDS. Additionally, we prove that these codes are not equivalent to generalized Reed-Solomon (GRS) codes. As an application, under certain circumstances, we compute the covering radii and deep holes of these codes.

Dust in Early-Type galaxies (ETGs) may originate from internal or external sources. In this paper we study the stellar populations of particularly dusty ETGs to search for evidence of the dust's origin. Using the Southern African Large Telescope (SALT), we obtained long-slit optical spectra within the effective radius (R_e), along the major axis of 15 nearby ETGs, selected from the GAMA and Herschel-ATLAS surveys for their high levels of interstellar dust. Using full spectrum fitting and Lick index fitting we analysed their major axis kinematics and stellar population characteristics. We used stellar population models from the newly developed sMILES library and from the empirical MILES library. Kinematic results show that most of our sample of dusty ETGs are rotationally supported and there are no detectable kinematic discontinuities. 12 of our sample of 15 dusty ETGs show evidence of young/intermediate age stellar population components suggesting ongoing/recent star formation. Using simulations, we show that these recent ($\approx$1~Gyr) populations are not artefacts of the fitting process or data. As a check with a control sample we use stacked SDSS spectra and find that dusty ETGs show a component with intermediate age, whereas non-dusty ETGs do not. Age, metallicity and $α$-element abundance ratio increase with increasing central velocity dispersion in the SALT spectra, as seen in previous studies of ETGs, but with larger scatter in our sample. Given our stellar population findings, we discuss formation scenarios that might cause or rule out a high dust/molecular gas content.

We derive a unidirectional asymptotic model for one-dimensional blood flow in viscoelastic arteries. We prove local well-posedness of strong solutions in Sobolev spaces for general parameters and mean-zero periodic data. In the purely elastic BBM regime we further establish global existence and exponential decay for sufficiently small initial data. We also present a numerical study of the reduced model, including comparisons across different viscoelastic and amplitude regimes, and discuss the observed dynamics in connection with the continuation criterion.

Parameterized stable homotopy theory organizes local systems of spectra over homotopy types, governed by a "yoga" of six functors. To provide semantics for the recently developed Linear Homotopy Type Theory (LHoTT), good model categories of these spectra are required, preferably monoidal with respect to the external smash product. We focus on the case of parameterized $H\mathbb{K}$-module spectra ($\infty$-local systems), motivated by recent applications of parameterized homotopy to topological quantum computing. While traditionally treated via dg-categories, we leverage combinatorial model structures on simplicial chain complexes to construct the first dedicated global model structure for $\mathbb{K}$-linear $\infty$-local systems, which offers better control than existing models for general parameterized spectra. In particular, when restricted to base 1-types, our model structure is monoidal with respect to the external tensor product, making it a candidate target semantics for the multiplicative fragment of LHoTT.

We consider the persistence probabilities of an autoregressive chain of order one with continuous innovations. In the case of positive drifts, we show that these persistence probabilities are compound-geometric and satisfy a Baxter-Spitzer factorization generalizing that of the random walk. In the case of negative drifts, we exhibit a discrete Van Dantzig problem, which implies that the Baxter-Spitzer factorization never happens, except in a degenerate case. For positive drifts and log-concave innovations, we show that the first passage time in $(-\infty,0)$ has a log-convex distribution, whereas in the case of negative drifts and log-convex innovations on ${\mathbb R}^+$, it has a log-concave distribution. The case of the bi-exponential innovations is studied in detail, which leads for positive drifts to an additive factorization of the exponential law.

Beam prediction is critical for reducing beam-training overhead in millimeter-wave (mmWave) systems, especially in high-mobility vehicular scenarios. This paper presents a BEV-Fusion based framework that unifies camera, LiDAR, radar, and GPS modalities in a shared bird's-eye-view (BEV) representation for spatially consistent multi-modal fusion. Unlike priorapproaches that fuse globally pooled one-dimensional features, the proposed method performs fusion in BEV space to preservecross-modal geometric structure and visual semantic density. A learned camera-to-BEV module based on cross-attention is adopted to generate BEV-aligned visual features without relying on precise camera calibration, and a temporal transformer is used to aggregate five-step sequential observations for motion-aware beam prediction. Experiments on the DeepSense 6G benchmark show that BEV-Fusion achieves approximately 87% distance- based accuracy (DBA) on scenarios 32, 33 and 34, outperforming the TransFuser baseline. These results indicate that BEV-space fusion provides an effective spatial abstraction for sensing-assisted beam prediction.

We develop a predictor-feedback cooperative adaptive cruise control (CACC) design relying on a multiple-predecessor-following (MPF) topology-based nominal delay-free CACC law. We consider vehicular platoons with heterogeneous vehicles, whose dynamics are described by a third-order linear system subject to actuation delay, along with vehicle-to-vehicle (V2V) communication delay. The design achieves individual vehicle stability, string stability, and zero, steady-state speed/spacing tracking errors, for any value of the actuation delay. The proofs of individual vehicle stability, string stability, and regulation rely on employment of an input-output approach on the frequency domain, capitalizing on the delay-compensating property of the design, which enables as to derive explicit string stability conditions on control and vehicle models parameters. The theoretical guarantees of string stability and the respective conditions on parameters are illustrated also numerically. We present consistent simulation results, for a ten-vehicle platoon, illustrating the potential of the design in traffic throughput improvement, as compared with a predictor-feedback CACC design in which, each ego vehicle's controller utilizes information only from a single preceding vehicle. We also present simulation results in a realistic scenario in which the leading vehicle's trajectory is obtained from NGSIM data.

Safety and assurance cases risk becoming detached from the understanding needed for responsible engineering and governance decisions. More broadly, the production and evaluation of critical socio-technical systems increasingly face an understanding challenge: pressures for increased tempo, reduced scrutiny, software complexity, and growing use of AI generated artefacts may produce outputs that appear coherent without supporting genuine human comprehension. We argue that understanding should become an explicit, assessable, and defensible component of decision making: what developers, assessors, and decision makers grasp about system behavior, evidence, assumptions, risks, and residual uncertainty. Drawing on Catherine Elgin's epistemology of understanding, we outline a conceptual foundation and then use Assurance 2.0 as an engineering route to operationalize using structured argumentation, evidence, confidence, defeaters, and theory based automation. This leads to two linked artefacts: an Understanding Basis, which justifies why available understanding is sufficient for a decision, and a Personal Understanding Statement, through which participants make their grasp explicit and challengeable. We also identify risks that automation may improve artefact production while weakening understanding, and we propose initial directions for evaluating both efficacy and epistemic impact.

Quantum circuit complexity quantifies the minimal number of gates needed to realize a unitary transformation and plays a central role in quantum computation. In this work, we investigate the complexity of quantum circuits through coherence and imaginarity resources. We establish a lower bound on the circuit cost by the Tsallis relative $α$ entropy of cohering power, which is shown to be tighter than the one presented by Bu et al.[\textit{Communications in Mathematical Physics} 405, no. 7 (2024):161] under restrictive conditions. As a consequence, we obtain the relationships between the circuit cost and the coherence generating power via probabilistic average in terms of skew information/relative entropy, and present explicit bounds of the circuit cost for typical quantum gates. Moreover, we derive lower bounds on the circuit cost via the imaginaring power of the circuit, induced by the Tsallis relative $α$ entropy and relative entropy. We demonstrate that imaginarity can yield nontrivial constraints on the circuit cost even when coherence-based lower bounds are zero (e.g., for the $T$ gate), which implies that imaginarity may provide advantages under certain circumstances compared with coherence. Our results may help better understand the connections between quantum resources and circuit complexity.

Let $C$ be a complex projective integral curve with planar singularities. In this note, we study numerical relations among its versal deformation space, moduli space of stable maps, and compactified Jacobian. In particular, we correct a statement by Fantechi--Göttsche--van Straten on the multiplicity of the $δ$-constant stratum of the versal deformation space at $[C]$. We also give a necessary and sufficient condition for the original claim to hold.

The role of trust within Human-Computer Interaction is being redefined. With the increasing omnipresence, autonomy, and opacity of technology, users often struggle to understand the capabilities and limitations of systems. In this article, we present the results of an empirical study designed to provide a practical, evidence-based interpretation of trust propensity assessment using the Human-Computer Trust Scale (HCTS). We outline the process used to develop a guideline for interpreting the instrument's results and explain the rationale for our decisions, advocating for calibrating trust in technology within HCI. Our findings demonstrate that the HCTS is a promising tool for conducting an initial evaluation of propensity to trust, but that such an assessment requires reflection and interpretation that should be considered within the context of the interaction.

This paper presents a set of algorithms for computing the reachability graph of Petri Net Product Lines (PNPLs). These algorithms address the combined challenges of concurrency and variability that arise from product-line configurations. The proposed approach integrates symbolic state representations with family-based variability handling to generate a compact, parameterised reachability graph that captures behaviour across all products without exhaustive product enumeration. The main contributions are threefold. First, we introduce a symbolic state encoding adapted to PNPL semantics. Second, we define a family-preserving successor generation procedure that applies feature constraints during exploration. Third, we propose reduction techniques to mitigate state-space explosion, including on-the-fly merging of equivalent symbolic states and selective abstraction of irrelevant state details. We prove soundness and completeness of the construction with respect to standard per-product semantics and analyse computational complexity. An implementation integrated into our modelling tool demonstrates substantial savings in memory and time compared with naive product-based exploration, while preserving diagnostic and verification capabilities. The results indicate that the method enables practical reachability analysis for realistically sized product-line models, thereby facilitating verification and design-space exploration in configurable concurrent systems.

We present the first study of the Chiral Magnetic Effect (CME) using transverse spherocity as an event-shape classifier in Pb+Pb collisions at $\sqrt{s_{NN}} = 5.02$ TeV, simulated with the A Multi-Phase Transport (AMPT) model with a realistic CME implementation. Transverse spherocity separates events into jetty and isotropic topologies based on the geometric distribution of transverse momentum. Unlike traditional event shape engineering methods, which use the flow vector as an event classifier that is itself contaminated by the very backgrounds it is intended to suppress, spherocity provides a cleaner, geometry-driven classification that avoids this circular limitation. CME inclusion shifts the spherocity distribution toward more isotropic events, confirming its sensitivity to CME-induced charge separation. The charge-dependent azimuthal correlator $Δγ$ and correlated background coupled with elliptic flow are consistently higher in jetty events. The scaled ratio $Δγ/v_2$ shows enhanced values for isotropic events, confirming effective background suppression after elliptic flow scaling. Our results demonstrate that isotropic event selection via transverse spherocity provides a cleaner and more reliable environment for CME searches by simultaneously suppressing flow-driven and resonance-decay backgrounds, making it a powerful complementary method to existing flow-vector-based methods.

In this paper, we describe a gradient-free method to solve a system of equations, and we use it to construct two families of pseudo-periodic planar solutions of the 4- and 6-body problem. The method is a stochastic black-box procedure that uses only function evaluations. For the 4-body problem, bodies 1 and 2 have mass 1 and move opposite to each other, and bodies 3 and 4 have mass $m_2$ and also move opposite to each other. For the 6-body problem, bodies 1, 2, and 3 have mass 1 and move on the vertices of an equilateral triangle centered at the origin, and bodies 4, 5, and 6 have mass $m_2$ and also move on the vertices of an equilateral triangle. In both cases, we compute families of periodic solutions by imposing return conditions up to rotation and relabeling.

The research complements and extends the scope of the work reported in the article "LED-based multibeam photoacoustics combined with electrical circuit-based modeling for the analysis of multispecies mass transport through thin membranes" (arXiv:2602.20902). In particular, this work investigates the impact of the sample's absorption properties on the ability to quantify slow mass transport processes in thin membranes under optically transparent and semi-opaque conditions. The theoretical framework is based on the Green's function approach as formalized by Mandelis. Owing to the separation of photoacoustic and mass transport timescales, the heat distributions are assumed to follow the temporal mass concentration profiles predicted by a Fickian diffusion process. The approach is further examined and validated using experimental data on pigment transport into a thin porous membrane. Detailed experimental results are provided in the referenced paper.