In this letter, we propose a single-field inflation model that realizes a slow-roll-to-ultra-slow-roll transition while keeping the second slow-roll parameter smoothly varying throughout. The model is built through a minimal modification by introducing a simple time dependence in the effective mass term of the Mukhanov-Sasaki equation. We obtain fully analytical solutions for both the background evolution and the curvature perturbations, which makes the parameter dependence of the curvature power spectrum easy to track. To the best of our knowledge, this is the first analytical model that describes a smooth transition of this kind. We also compare its signatures with those of the corresponding sharp-transition counterpart.

Based on multi-frequency radio polarization survey datasets, we investigate the spectral characteristics of the Galactic interstellar medium (ISM) using the polarization frequency analysis (PFA) method, referred to as polarization variance. By comparing this novel PFA technique with the traditional power spectrum approach, and by cross-examining data from two distinct surveys, we aim to reinforce the robustness of our findings. Our analysis reveals that the ISM scaling slope in the Galactic disk is steeper than the classic Kolmogorov slope, whereas the ISM scaling slope in the Galactic halo aligns with the Kolmogorov slope. We suggest a distinct turbulence cascade process operating in the Galactic halo compared to the Galactic disk.

A fluid mechanics problem is solved which technological prototype is a fluid acoustic contact that is an inherent element of ultrasonic non-destructive testing procedures. It is well known that the acoustic contact established with an ordinary fluid suffers from essential disadvantage that is the loss of stability due to the gravity-induced fluid leakage in the course of dynamic scanning. The use of magnetic fluid (MF) is one of the ways to resolve the issue. A compact portion of MF held in place by a permanent magnet enables one to maintain a stable acoustic contact (fluid bridge) under arbitrary orientation of the ultrasonic sensor and, simultaneously, to radically minimize the drain of the contact fluid. The model system under consideration comprises a MF bridge that fills a flat gap, one of whose boundaries moves with constant velocity. Due to its wetting by the fluid, the receding plane carries away a fluid film thus depleting the contact. Theoretical expressions are obtained which define the profile of the film in the dynamic regime and the dependencies of the magnetic fluid drain on the boundary velocity, gap height and configuration of the imposed magnetic field. On that basis the optimal parameters are evaluated which ensure effective retention of the fluid contact under minimal drain of the fluid from it.

In this paper we discuss a well known computing problem -- inference for models with intractable normalizing functions. Models with intractable normalizing functions arise in a wide variety of areas, for instance network models, models for spatial data on lattices, spatial point processes, flexible models for count data and gene expression, and models for permutations. Simulating from these models for fixed parameter values is well studied, starting with work dating back seventy years to the origin of the Metropolis algorithm. On the other hand some of the most practical and theoretically justified algorithms for inference, particularly Bayesian inference, have only been developed within the past two decades. The most computationally efficient algorithms often do not have well developed theory and few if any approaches exist for assessing the quality of approximations based on them. For many problems even the best algorithms can be computationally infeasible. Hence, this is an exciting area of research with many open problems. We explain several key algorithms, providing connections and touching upon practical advantages and disadvantages of each, with some discussion of theoretical properties where they impact practice. We discuss an approach for assessing the accuracy of approximations produced by these algorithms; this diagnostic is particularly valuable for algorithm tuning. While our focus is largely on models with intractable normalizing functions, we also discuss algorithms that are more broadly applicable to models where the entire likelihood function is intractable; these methods are of course also applicable to intractable normalizing function problems.

We consider singularly perturbed gradient flows in Hilbert spaces, driven by a time-dependent, nonconvex, and nonsmooth energy, and address the convergence of their solutions to curves of critical points of the driving energy functional. The degenerating nature of the estimates along the gradient-flow curves calls for novel compactness arguments, which we carefully develop by combining tools from the variational approach to Hilbert and metric gradient flows \cite{RossiSavare06,AGS08}, with fine requirements on the set of critical points of the energy. This leads us to prove that subsequential limits of singularly perturbed gradient flows are Dissipative Viscosity solutions of the limiting problem, i.e., a curves of critical points satisfying a suitable balance between the energy and a defect measure, encoding dissipation. This energy-dissipation balance encompasses information on the dynamics of the process at jump times, recording, in particular, the re-emergence of viscous behavior. Under a suitable rectifiability condition on the critical set, we show that Dissipative Viscosity solutions improve to Balanced Viscosity solutions, which have the key property that the dissipation measure is purely atomic. In the second part of the paper we show that, for smooth energies whose second differential is a Fredholm operator, the condition that the kernel of the Hessian has dimension at most one at every critical point already implies our measure-theoretic assumptions. We further relate them to the transversality conditions from bifurcation theory and show that they have a generic character.

Meeting stringent Time-To-First-Token (TTFT) requirements is crucial for LLM applications. To improve efficiency, modern LLM serving systems adopt disaggregated architectures with diverse parallelisms, introducing complex multi-stage workflows involving reusable KV-block retrieval, collective communication, and P2D transfer. Flows from dependent stages overlap within and across requests on shared bottleneck links, making TTFT highly susceptible to network contention and necessitating stage-aware scheduling. Unfortunately, most existing works schedule flows in a stage-agnostic manner, leading to uncoordinated contention that constitutes a primary cause of SLO violations. In this paper, we present MFS, a holistic multi-stage flow scheduling mechanism designed to maximize TTFT SLO attainment. At its core, MFS approximates the Least-Laxity-First (LLF) scheduling policy without requiring precise knowledge of a request's remaining slack. It achieves this through a Defer-and-Promote principle implemented through a Reverse Multi-Level Queue (RMLQ) structure. By dynamically promoting task precedence as effective laxity diminishes, MFS prioritizes flows with less laxity while preventing requests with loose SLOs from prematurely consuming network bandwidth. We implement MFS as a pluggable module integrated into vLLM, and evaluate it on a 8-server, 32-GPU testbed as well as through large-scale simulations. Our results demonstrate that MFS effectively outperforms state-of-the-art baselines, improving the TTFT SLO attainment by 1.2x--2.4x.

Future electron-positron colliders offer a unique opportunity for high-precision measurements of the top-quark mass, width, strong coupling constant, and top-quark Yukawa coupling via a scan of the $t\bar{t}$ threshold. We present the first prospect study of the simultaneous determination of these parameters, incorporating the latest reference detector design for the Circular Electron-Positron Collider (CEPC). We find that the precision of the top-quark mass measurement can reach a few MeV excluding the theoretical uncertainty on the cross-section, which is nearly two orders of magnitude better than the high-luminosity LHC (HL-LHC) projections. The current theoretical uncertainty of the cross-section calculation is the limiting factor.

Function Secret Sharing (FSS) schemes enable sharing efficiently secret functions. Schemes dedicated to point functions, referred to as Distributed Point Functions (DPFs), are the center of FSS literature thanks to their numerous applications including private information retrieval, anonymous communications, and machine learning. While two-party DPFs benefit from schemes with logarithmic key sizes, multi-party DPFs have seen limited advancements: $O(\sqrt{N})$ key sizes (with $N$, the function domain size) and/or exponential factors in the key size. We propose a DDH-based technique reducing the key size of existing multi-party schemes. In particular, we build an honest-majority DPF with $O(\sqrt[3]{N})$ key size. Our benchmark highlights key sizes up to $10\times$ smaller (on realistic problem sizes) than state-of-the-art schemes. Finally, we extend our technique to schemes supporting comparison functions.

We investigate holographic spectral functions for general Sasaki-Einstein 5-manifolds dual to four-dimensional superconformal field theories, including supersymmetric indices, supersymmetric zeta functions, and supersymmetric determinants. The analytic structure of the supersymmetric zeta function, particularly its residue and special value, allows for the computation of the curvature-squared integral of the Sasaki-Einstein manifold and the subleading holographic anomaly. The reach of this spectral framework is not restricted to toric geometries and accommodates non-toric Sasaki-Einstein manifolds. For toric Sasaki-Einstein manifolds, we develop a combinatorial method to compute the holographic spectral functions and the holographic geometric invariants directly from the toric data.

We report a systematic magnetotransport study on high-crystallinity La$_{1-x}$Sr$_{x}$NiO$_2$ (LSNO) thin films with $x=0.20-0.24$. By conducting pulsed-field transport experiment up to 62 T, we reveal two salient features of the normal-state transport in overdoped LSNO thin films: (1) the magnetoresistance does not follow the Kohler's rule but exhibits a $H$-linear behavior in the high $H/T$ limit and (2) the normal-state $ρ(T)$ below 30 K consistently follows a $T^2$ behavior across the overdoped regime. Our results demonstrate a coexistence of $H$-linear magnetoresistance and $T^2$ resistivity in a model unconventional superconductor and provide new information on the transport characteristics of the normal ground state that host superconductivity in infinite-layer nickelates.

This paper develops an efficient iterative method for computing all zeros of solutions of second order ordinary differential equations. A third order Halleys method is first derived by approximating the solution of an associated Riccati differential equation. To improve computational efficiency, a modified Halleys method is proposed by fixing one of the functions in Halleys scheme as a constant. The modified Halleys method also retains third order convergence. Based on the behavior of the coefficients of the second order ODE, nonlocal convergence results are established for both Halleys and modified Halleys methods. Suitable initial guesses for computing all zeros of solutions of second order ODEs in a given interval are also presented for both methods. Furthermore, algorithms based on the modified Halleys method are developed for to compute all nodes and weights for Gauss Legendre and Gauss Hermite quadratures. A comparative numerical study with recent methods demonstrates the efficiency of the proposed algorithms.

We study a minimal model of disordered systems, the random field Ising model (RFIM) on a generalized Petersen Graph, GP(N,k). This graph has a connected inner and outer loop, where both the loops consist of N nodes constituting a total of 2N nodes. The parameter k satisfies the condition 1<=k<=N/2, such that any site i in the inner loop has i-k and i+k as its two nearest neighbours, apart from its connection to a node on the outer loop. Thus, each node in GP(N,k) has coordination number z=3, and by varying k different connections between the nodes in the inner loop can be obtained. The objective is to study whether different connectivity between nodes in these graphs affects the system's response to an external field when the coordination number is fixed. This is of interest because critical behaviour is absent for z<=3 on a random graph which has been solved exactly as well as on the honeycomb lattice in the context of RFIM. Using single-spin-flip Glauber dynamics at zero temperature, we compare the system's response with the known case of a z=3 random graph and the generalized Petersen graph for various connectivity k, albeit for the same z. Our study finds the absence of critical behaviour on GP(N,k) highlighting the importance of coordination number over varying connectivity between the nodes. Additionally, we explore the case of directed GP(N,k) and compare it with the undirected GP(N,k) results.

We present an empirical argument against the existence of single timeline backward time travel using the price behavior of prediction markets. If rational agents could travel backward in time, binary prediction contracts would converge to degenerate prices (0 or 1) immediately upon market formation. We observe no such behavior across large datasets of resolved contracts. This yields a directly falsifiable prediction and sharpens prior economic arguments while avoiding reliance on physical experimentation. The argument requires only the existence of a single profit motivated agent in the future capable of interacting with markets along a closed timelike curve intersecting the market's spacetime location. We further argue that such agents would have no incentive to conceal trades in causally inert events, where outcomes are independent of market prices, implying that any such activity would be visible in aggregate price behavior. While many worlds interpretations evade this test, we argue that only single timeline models are empirically falsifiable, and prediction market evidence is inconsistent with their existence.

This article introduces and substantiates the concept of Neuro-Linguistic Integration (NLI), a novel paradigm for human-technology interaction where Large Language Models (LLMs) act as a key semantic interface between raw neural data and their social application. We analyse the dual nature of LLMs in this role: as tools that augment human capabilities in communication, medicine, and education, and as sources of unprecedented ethical risks to mental autonomy and neurorights. By synthesizing insights from AI ethics, neuroethics, and the philosophy of technology, the article critiques the inherent limitations of LLMs as semantic mediators, highlighting core challenges such as the erosion of agency in translation, threats to mental integrity through precision semantic suggestion, and the emergence of a new `neuro-linguistic divide' as a form of biosemantic inequality. Moving beyond a critique of existing regulatory models (e.g., GDPR, EU AI Act), which fail to address the dynamic, meaning-making processes of NLI, we propose a foundational framework for proactive governance. This framework is built on the principles of Semantic Transparency, Mental Informed Consent, and Agency Preservation, supported by practical tools such as NLI-specific ethics sandboxes, bias-aware certification of LLMs, and legal recognition of the neuro-linguistic inference. The article argues for the development of a `second-order neuroethics,' focused not merely on neural data protection but on the ethics of AI-mediated semantic interpretation itself, thereby providing a crucial conceptual basis for steering the responsible development of neuro-digital ecosystems.

We present a comprehensive pipeline developed for the image processing of the KMTNet Synoptic Survey of the Southern Sky (KS4) Data Release 1. This pipeline encompasses several key processes, including data quality assurance, astrometry, photometric zero-point (ZP) calibration, bad pixel masking, image stacking, and difference image analysis (DIA). The astrometric solutions were validated by cross-matching with the Gaia EDR3 catalog, achieving sub-pixel astrometric accuracy (< 0.4 arcsec). To ensure spatial consistency, we divided each image into multiple subsections and confirmed that astrometric accuracy was maintained even at the edges. We performed a two-stage photometric calibration. Initial ZP solutions were computed for each individual image frame using the APASS DR9 and SkyMapper DR3 catalogs. Subsequently, we corrected residual spatial variations in the stacked images using Gaia XP photometry. This procedure yielded a 5-sigma depth of 22-23 AB mag across the BVRI bands, with root-mean-square errors of approximately 0.03 mag when referenced to Gaia stars in the magnitude range of 14-19 mag. The processed KS4 images span over 4,000 deg^2 of the southern sky, providing reference images suitable for DIA. This publicly available pipeline also supports real-time processing of newly acquired images, enabling prompt transient detection. We demonstrate its effectiveness through successful applications in gravitational-wave follow-up observations.

Solid-state quantum emitters constitute an essential building blocks of integrated quantum photonic circuits. Among potential emitter platforms, hexagonal boron nitride (hBN) hosts single-photon emitters in an atomically thin lattice amenable to photonic integration. However, multi-step fabrication approaches, limited defect specificity, and poor emission wavelength repeatability limit the performance of hBN quantum light sources relative to established solid-state architectures. Developing methods to induce emitters that are both suitable for planar photonic devices and that exhibit consistent optical properties remains a key objective. In this work, we identify quantum emitters in as-exfoliated carbon-doped hBN that exhibit both stable and repeatable emission energies together with polarization-aligned dipoles. Owing to the high lattice crystallinity, these single-photon light sources demonstrate exceptional spectral stability with a standard deviation of 7 $μ$eV. The emission energy is reproducible and confined within a narrow range of 2.2825 ${\pm}$ 0.0042 eV. Notably, consistent dipole alignment for absorption and emission polarization suggests that the intrinsic defects are of the same nature. The color centers are observed in as-exfoliated hBN without any post-treatment, significantly facilitating further interfacing with planar photonic structures. These reproducible, polarization-aligned quantum emitters in as-exfoliated hBN provide a versatile platform for scalable integration, offering a pathway toward a broad range of quantum technologies.

Existing error-bound-based analyses for stochastic algorithms that exhibit certain descent properties, such as randomized coordinate descent and randomized projection methods, are often limited in scope and typically lead to overly conservative convergence guarantees. To address this gap, we develop an abstract framework for analyzing such stochastic algorithms based on new unified error bound (UEB) conditions. The proposed UEB conditions subsume many common error bound- and Kurdyka--Łojasiewicz-type conditions used in existing studies of algorithms for optimization, convex feasibility, and common fixed point problems. Under the global UEB condition, we establish non-asymptotic in-expectation and asymptotic almost-sure convergence rates for the stochastic algorithms in our framework. Under the local UEB condition, we also show asymptotic almost sure convergence rates. We demonstrate the strength and versatility of our framework through two applications. For the common fixed point problem, we provide comprehensive convergence guarantees for the randomized alternating Krasnoselskii-Mann method under Hölderian error bound conditions. Furthermore, for unconstrained minimization of smooth definable functions, we establish novel convergence guarantees for the randomized subspace descent method, an algorithm subsuming both randomized coordinate and block coordinate descent.

For number $n>1$, let $\mathcal{A}(n) = \{1\leq a<n: n|a^2-1, a|n^2-1 \}$. We show that the size of $\mathcal{A}(n)$ is connected to a property concerning integer evaluations of Fibonacci-like polynomials. In the process, we prove that $|\mathcal{A}(n)|< \log_2 n$, and establish the average value of $|\mathcal{A}(n)|$ to be a little above $2$, asymptotically. But the empirical data up to $n<10^7$ indicate that $|\mathcal{A}(n)|\leq 3$, proving which is left as an open issue.

As we are entering an early-FTQC era, circuit execution protocols with logical qubits and certain error-correcting codes are being discussed. Here, we propose a circuit execution protocol for the space-time efficient analog rotation (STAR) architecture. Gate operations within the STAR architecture is based on lattice surgery with surface codes, but it allows direct execution of continuous gates $Rz(θ)$ as non-Clifford gates instead of $T = Rz(π/4)$. $Rz(θ)$ operations involve creation of resource states $|m_θ\rangle = \frac{1}{\sqrt{2}} (|0 \rangle + e^{iθ} |1\rangle ) $ followed by ZZ joint measurements with target logical qubits. While employing $Rz(θ)$ enables more efficient circuit execution, both their creations and joint measurements are probabilistic processes and adopt repeat-until-success (RUS) protocols which are likely to result in considerable time overhead. Our circuit execution protocol aims to reduce such time overhead by parallel trials of resource state creations and more frequent trials of joint measurements. By employing quadratic unconstrained binary optimization (QUBO) in determining resource state allocations within the space, we successfully make our protocol efficient. Furthermore, we proposed performance estimators given the target circuit and qubit topology. It successfully predicts the time performance within less time than actual simulations do, and helps find the optimal qubit topology to run the target circuits efficiently.

The weak and strong laws of large numbers for time-inhomogeneous Markov chains are studied under general conditions. First, under Drift Condition and Contraction Condition in total variation, we prove the weak law of large numbers. Then, assuming Drift Condition together with a time-inhomogeneous Doeblin minorization, we develop a Nummelin-type splitting and obtain a strong law of large numbers. Our results utilize the invariant measure family in the sense of Liu--Lu (2025), and extend the classical Harris-ergodic LLN to the time-inhomogeneous setting.

The low-excitation states of atomic nuclei in the region around the $N = Z = 28$ shell closure are generally well described by the shell model. Most experimental observables in the iron isotopes $^{56}$Fe, $^{58}$Fe, and $^{60}$Fe ($Z = 26$; $N=30$, $32$, $34$) support a shell-model description. However, the lifetimes of the $4_1^+$ state in $^{58}$Fe in the literature result in a reduced transition strength that deviates markedly from shell-model predictions. There are three independent measurements, all in agreement and all based on the Doppler Shift Attenuation Method (DSAM) or Doppler-Broadened Line Shape method (DBLS). In this work, Coulomb-excitation measurements were performed on $^{56}$Fe and $^{58}$Fe beams to determine the ratios $B(E2; 4_1^+ \to 2_1^+)/B(E2; 2_1^+ \to 0_1^+)$. Thus, $B(E2; 4_1^+ \to 2_1^+)$ is determined relative to the known $B(E2; 2_1^+ \to 0_1^+)$ values. For $^{56}$Fe, $B(E2; 4_1^+ \to 2_1^+) = 23(4)$ W.u., agreeing with the adopted value. However, for $^{58}$Fe, the $B(E2; 4_1^+ \to 2_1^+)$ values obtained (for the various combinations of matrix element signs that could not be firmly established) are all significantly lower than the value derived from the previous lifetime measurements, and are in accord with shell-model calculations. The 1978 DSAM measurement of Bolotin et al., Nucl. Phys. A 311, 75 (1978), has been re-examined. The discrepancy between that measurement and the Coulomb-excitation measurement can be ascribed to the Lindhard-Scharff-Schiøtt (LSS) electronic stopping powers adopted for the DSAM analysis, which considerably overestimate contemporary values. Evidently, lifetime measurements from that era that are based on LSS stopping powers should be used with caution. The revised lifetime data, incorporating current stopping powers, are compared with shell-model calculations.

We review recent results on Radon-Nikodýmification of abstract measure spaces, the particular case of integral geometric measure, and applications to the dual of SBV.

This paper presents a modified iterative approach to solve the variational inequality problem using the double inertial technique in the context of a real Hilbert space. Our iterative technique involves a projection onto a generalized half-space and a self-adaptive step-size rule which works without prior knowledge of the Lipschitz constant of the operator. We establish a weak convergence result for a variational inequality involving a non-monotone cost operator along with weak and strong convergence results for quasi-monotone and strongly pseudo-monotone operators, respectively. Under a simplified framework, linear convergence of the proposed method is also discussed. Additionally, we provide some numerical experiments to demonstrate the effectiveness of our iterative algorithm compared to previously established algorithms in solving real-world applications. Finally, we carry out a sensitivity analysis of our algorithm to demonstrate its effectiveness across various parameter settings.

This letter studies the dynamical properties of safety filters designed based on Control Barrier Functions (CBF). This mechanism, which is popular in safety-critical applications, takes a nominal controller and minimally modifies it to render it safe. Although CBF-based safety filters make the closed-loop system safe, characterizing their additional dynamical properties, such as stability, boundedness, or existence of spurious equilibria, remains a challenging problem. Here, we address this problem for the case of linear systems and an affine CBF constraint. We provide conditions under which the closed-loop system presents undesired equilibria, unbounded trajectories, or the origin is globally exponentially stable.

The intrinsic nature of glass states and glass transitions at the atomic scale remain a fundamental open question in condensed-matter physics and materials science. By combining femtosecond electron diffraction with time-dependent density-functional theory molecular dynamics simulations, we directly observe ultrafast amorphous-amorphous transitions in amorphous GeTe, manifested as rapid Ge-Te (Ge) bond stretching within 0.2 ps and subsequent angle bending of the Ge-Te (Ge)-Ge motif on a 0.5-2 ps timescale. Critically, the ultrafast bond stretching is accompanied by localized oscillation modes with the frequency of 3.10 THz, unambiguously signaling the local Peierls-like bonding structure and the flexibility of these polarized bonds. These ultrafast collective atomic motions provide a direct structural origin for the boson peak and pay the way for systematic optimization of relaxation and crystallization kinetics.

With the ever-increasing digitization of society, the development of materials with low-power memory storage -similar to synapses- is becoming more relevant. The field of iontronic artificial synapses has gained traction, in particular with polymers as the memory-active material which allows for additional bio-compatibility, flexibility and tunability. Polyelectrolyte brushes are an example of stimulus-responsive materials that can be used in iontronic devices. However, the complexity of current neuromorphic devices does not allow us to isolate and understand the role of polyelectrolyte brushes in their synaptic response. In this paper, we show that polyelectrolyte brushes are capable of synaptic behavior in the most simple of electrochemical cell designs. Furthermore, by combining theory and experimental work, we shed light on the role of brushes in this synaptic behavior and their dynamic stimuli-responsiveness to polarity changes for different salt concentrations. The obtained trends and interpretations of the nonlinear potential-current response, paired-pulse experiments, and accumulative learning lay the foundation for designing and developing polymer brush-based neuromorphic devices.

Let $G$ be a finite $p$-group. We construct a $G$-extension $K/k$ of number fields such that the $p$-adic completion of the unit group of $K$ has a prescribed $\mathbb{Z}_p[G]$-module structure, up to free direct summands.

We propose a three-dimensional field theory construction that realizes the vertex algebras associated with the intermediate Lie algebras and the related $C_2$-cofinite minimal $W$-algebras of the Deligne-Cvitanović (DC) series as boundary algebras. The construction is based on the minimal three-dimensional ${\mathcal N}=4$ superconformal field theory coupled to a topological field theory. For a Neumann-type boundary condition compatible with the topological $A$-twist, the algebra of boundary local operators realizes the minimal $W$-algebra $W_{-h^\vee/6}(\mathfrak{g},f_{\text{min}})$. While this boundary condition is not deformable to the $B$-twist, we argue that a holomorphic-topological ($HT^B$) twist instead realizes the level-one affine algebras of the intermediate Lie algebras, providing a uniform three-dimensional origin for these vertex algebra structures.

The phase diagram of self-propelled hard disk systems with Vicsek-type alignment interactions was investigated by event-driven molecular dynamics simulations. The model incorporates two competing order parameters: the polar order-disorder transition associated with collective velocity alignment (Vicsek model) and the orientational order arising from solid-fluid transitions (Alder transition) induced by excluded volume effects. The incompressibility of hard disks suppresses motility-induced phase separation at high packing fractions. Distinctive fluctuations were observed near the transition point, accompanied by anomalous shifts in the transition point as functions of noise intensity and packing fraction. Analysis of local configurational parameters -- specifically, orientational order and circularity of free volume -- provides insight into the microscopic origins of these anomalous phase transition shifts.

Automated Alzheimer's Disease (AD) screening has predominantly followed the inductive paradigm of pattern recognition, which directly maps the input signal to the outcome label. This paradigm sacrifices construct validity of clinical protocol for statistical shortcuts. This paper proposes Agentic Cognitive Profiling (ACP), an agentic framework that realigns automated screening with clinical protocol logic across multiple cognitive domains. Rather than learning opaque mappings from transcripts to labels, the framework decomposes standardized assessments into atomic cognitive tasks and orchestrates specialized LLM agents to extract verifiable scoring primitives. Central to our design is decoupling semantic understanding from measurement by delegating all quantification to deterministic function calling, thereby mitigating hallucination and restoring construct validity. Unlike popular datasets that typically comprise around a hundred participants under a single task, we evaluate on a clinically-annotated corpus of 402 participants across eight structured cognitive tasks spanning multiple cognitive domains. The framework achieves 90.5% score match rate in task examination and 85.3% accuracy in AD prediction, surpassing popular baselines while generating interpretable cognitive profiles grounded in behavioral evidence. This work demonstrates that construct validity and predictive performance need not be traded off, charting a path toward AD screening systems that explain rather than merely predict.