In this paper we consider the Gabor wave front set of ultradistributions in the frame of ultradifferentiable functions. We prove that such a wave front set, defined through a Gabor frame on a regular lattice, is not affected by perturbations of the frame, in two different cases: when we consider $\varepsilon$-perturbations of Christensen type, and when we consider nonstationary Gabor frames.

The Lorentzian-Euclidean black hole has been recently introduced as a geodesically complete spacetime featuring a signature shift at the event horizon where causal geodesics are precluded from reaching the central $r=0$ singularity. In this paper, we investigate the shadows produced by this geometry to identify deviations from the standard Schwarzschild solution. Our analysis reveals an excess intensity in the inner shadow region that points to a potential observational signature of the novel behavior of light rays propagating near the event horizon. This excess could be a probe for horizon-scale modifications of black hole geometries. Furthermore, although the horizon surface of the Lorentzian-Euclidean black hole continuously accumulates photons and energy, we show that its backreaction response differs from that of stable light rings found in various exotic compact objects.

We consider a static open string in arbitrary stationary spacetime, which can represent a heavy quark-antiquark pair within the holographic framework or effective theory. Generally, the string profile is not symmetric with respect to the turning point, and the symmetry restores for a simple string configuration in backgrounds with certain constraints. We identify a wide family of metrics for which the symmetry is preserved, enabling a direct isolation of the linear-in-distance term in the static potential for simple symmetric string configurations, even in non-diagonal backgrounds. As a first example, we apply our formulas to the black brane dual to the $\mathcal{N}=4$ SYM plasma at finite temperature. We find that the separation distance between quarks, $L$, is given in terms of a hypergeometric function, while the potential, $V$, consists of two distinct contributions: a term linear in the separation and a term that involves its derivative by temperature. Analysis of the leading terms in the series expansion reveals that the temperature corrections of the separation distance leads to the "swallowtail" behavior. Further, applying our formulas to the Rindler-AdS spacetime dual to an accelerated $\mathcal{N}=4$ SYM plasma, we obtain analytic expressions for the distance and potential in terms of the elliptic integrals, which in the large Hawking temperature (large acceleration or small curvature) limit come to the conformal results for pure AdS. Then, we show that the distance between quarks decreases, the static potential between them increases, and the characteristic temperatures increase with an acceleration, $a_c$. However, we observe that an acceleration-scaled potential, $a_c V$ as a function of the acceleration-scaled distance, $a_c L$, does not depend on the certain value of the acceleration.

We investigate the class of sequences $w(n)$ that can serve as almost-everywhere convergence Weyl multipliers for all rearrangements of multiple trigonometric systems. We show that any such sequence must satisfy the bounds $\log n\lesssim w(n)\lesssim\log^2 n$. Our main result establishes a general equivalence principle between one-dimensional and multidimensional trigonometric systems, which allows one to extend certain estimates known for the one-dimensional case to higher dimensions.

The Diagnostic Neutral Beam Injector (DNBI) of the RFX-mod2 experiment (Consorzio RFX, Padova) is expected to provide novel and significant information about the Reversed Field Pinch confinement of fusion plasmas. The present DNBI, built by the Budker Institute of Plasma Physics, features an arc discharge H+ source, coupled to a 4-grid 50 keV acceleration system, to produce a 50 ms, 5 A ion beam. This contribution presents the latest upgrades of the DNBI. The High Voltage Deck (HVD) was completely restructured, and the power transfer was simplified to a single phase insulation transformer. The 50 kV distribution circuit was modernized and made safer against breakdowns. Several custom power supplies in the HVD were designed and procured; their electronic boards were developed to be multipurpose in the DNBI, simplifying the system and improving its maintainability. The features of the magnetic insulation power supply and gas valve power supplies are presented in detail. Finally, the new PLC control system was improved for better protection of the CPU against overvoltages and for better scalability and maintainability of the system.

This paper studies the multi-access coded caching (MACC) problem with arbitrary user-cache access topology, which extends existing MACC models that rely on highly structured and combinatorially designed topologies. We consider a MACC system consisting of a single server, $Λ$ cache-nodes, and $K$ user-nodes. The server stores $N$ equal-size files, each cache-node has a storage capacity of $M$ files, and each user-node $k\in[K]$ can access an arbitrary subset of cache-nodes $\mathcal{A}_k\subseteq[Λ]$ and retrieve the cached content stored in cache-nodes $\mathcal{A}_k$. The objective is to design a universal framework for the MACC delivery problem. Decoding conflicts among the requested packets are captured by a conflict graph, and the design of the delivery is reduced to a graph coloring problem, where achieving a lower transmission load corresponds to coloring the graph using fewer colors. Under this formulation, the classical DSatur algorithm achieves a transmission load close to the index-coding (IC) converse bound, thereby providing a practical benchmark. However, its computational complexity becomes prohibitive for large-scale graphs. To overcome this limitation, we develop a learning-driven approach using graph neural networks (GNNs) that efficiently constructs coded multicast transmissions with performance close to the theoretical bounds and generalizes across different user-cache access topologies and numbers of users. In addition, we extend the IC converse bound to MACC systems with arbitrary access topology and propose a low-complexity greedy approximation that closely matches the IC converse bound. Numerical results demonstrate that the proposed approach achieves performance close to the DSatur algorithm and the IC converse bound, while significantly reducing computational complexity, making it well-suited for large-scale MACC systems.

Minimal Flavor Violation (MFV) provides a compelling framework for exploring physics beyond the Standard Model, in which new QCD-singlet fields transforming under the global $\mathrm{SU}(3)^3$ quark flavor symmetry can naturally be stable and act as dark matter (DM) candidates. We show that the DM-MFV framework naturally accommodates the excess in either $K^+ \to π^+ ν\barν$ or $B^+ \to K^+ ν\barν$, while a unified explanation of both channels simultaneously cannot be achieved within a minimal setup containing only a single dark matter multiplet with nearly degenerate masses. Overall, our findings underscore the intricate interplay between MFV-based model building, flavored dark matter scenarios, and precision flavor experiments, highlighting flavored dark matter as a framework that is both theoretically robust and experimentally testable.

In this paper, we establish an analogue of Craig Interpolation Property for a many-sorted variant of first-order hybrid logic. We develop a forcing technique that dynamically adds new constants to the underlying signature in a way that preserves consistency, even in the presence of models with possibly empty domains. Using this forcing method, we derive general criteria that are sufficient for a signature square to satisfy Craig interpolation property.

We investigate the origin of frequency clusters - states where multiple groups of oscillators with distinct mean frequencies coexist. We use the Kuramoto model with inertia, where identical oscillators are globally coupled. First, we study the creation of two frequency clusters in the thermodynamic limit. Via numerical bifurcation analysis, we confirm that two frequency clusters are created by homoclinic bifurcations. Both clusters can lose their phase-synchrony in transcritical or period-doubling bifurcations. Furthermore, we investigate the creation of three frequency clusters in a system of seven oscillators. Here, the frequency clusters are destabilized by a longitudinal and a transversal period-doubling bifurcation, and the frequency clusters are also created by homoclinic bifurcations. We find that the emergence of three or more frequency clusters via a homoclinic bifurcation implies the creation of a triplet locked state, where the frequency differences exhibit a rational relation. Besides the creation of frequency clusters via a homoclinic bifurcation, we state that Hopf bifurcations cannot create frequency clusters in phase oscillators, and frequency clusters can only be created by global bifurcations.

We identify an overlooked Wess--Zumino--Witten structure in the hidden-local-symmetry~(HLS) formulation of vector mesons. The newly identified term generically leads to the topological quantization of the vector-meson anomalous couplings. If confirmed experimentally, this structure would expose the gauge nature of vector mesons in the anomalous sector and single out HLS over matter-field descriptions. The observed success of vector-meson dominance in anomalous interactions can then be explained by topological-action saturation of the odd-intrinsic-parity processes. Precision measurements of $η^{(\prime)}\toπ^+π^-γ^*$ form factors at BESIII and the Super $τ$-Charm Facility can directly test this saturation picture.

In this article we propose a generalization of two known invariants of real networks: degree and ksi-centrality. More precisely, we found a series of centralities based on Laplacian matrix, that have exponential distributions (power-law for the case $j = 0$) for real networks and different distributions for artificial ones.

We consider statistical inference for errors-in-variables regression models with dependent observations under the high dimensionality of the error covariance matrix. It is tempting to prewhiten the model and data that had led to efficient weighted least squares estimation in the presence of the measurement errors, as being practised in the optimal fingerprinting approach in climate change studies. However, it is unclear to what extent the prewhitened estimator can improve the estimation efficiency of the unprewhitened estimator for errors-in-variables regression. We compare the prewhitening and unprewhitening estimators in terms of their estimation efficiency and computational cost. It shows that while the prewhitening operation does not necessarily improve the estimation efficiency of its unprewhitening counterpart, it demands more on the ensemble size needed in the error-covariance matrix estimation to ensure the asymptotic normality, and hence it would requires much more computationally resource.

With great flexibility to adjust antenna positions, pinching antennas (PAs) are promising for alleviating large-scale attenuation in wireless networks. In this work, we investigate the antenna positioning and beamforming (AP-BF) design in a multi-PA multi-user system under probabilistic light-of-sight (LoS) blockage and formulate a power minimization problem subject to per-user signal-to-noise ratio (SNR) constraints. For a single PA, we prove the convexity of the simplified problem and obtain its global optimum. For multiple PAs, we derive closed-form BF structures and develop an efficient first-order algorithm to achieve high-quality local solutions. Moreover, the impact of link correlation on the transmit power is analyzed theoretically. Extensive numerical results validate the efficacy of our proposed designs and the substantial performance advantage of PA systems compared with conventional fixed-antenna systems in a term of power saving.

Properties of ocular fixations and saccades are highly stochastic during many experimental tasks, and their statistics are often used as proxies for various aspects of cognition. Although distinguishing saccades from fixations is not trivial, experimentalists generally use common ad-hoc thresholds in detection algorithms. This neglects inter-task and inter-individual variability in oculomotor dynamics, and potentially biases the resulting statistics. In this article, we introduce and evaluate an adaptive method based on a Markovian approximation of eye-gaze dynamics, using saccades and fixations as states such that the optimal threshold minimizes state transitions. Applying this to three common threshold-based algorithms (velocity, angular velocity, and dispersion), we evaluate the overall accuracy against a multi-threshold benchmark as well as robustness to noise. We find that a velocity threshold achieves the highest baseline accuracy (90-93\%) across both free-viewing and visual search tasks. However, velocity-based methods degrade rapidly under noise when thresholds remain fixed, with accuracy falling below 20% at high noise levels. Adaptive threshold optimization via K-ratio minimization substantially improves performance under noisy conditions for all algorithms. Adaptive dispersion thresholds demonstrate superior noise robustness, maintaining accuracy above 81% even at extreme noise levels (σ = 50 px), though a precision-recall trade-off emerges that favors fixation detection at the expense of saccade identification. In addition to demonstrating our parsimonious adaptive thresholding method, these findings provide practical guidance for selecting and tuning classification algorithms based on data quality and analytical priorities.

We introduce a family of algebras $\mathcal{A}_{M,N}$, $M,N\in\mathbb{Z}$, as an extension of a pair of commuting quantum toroidal $\mathfrak{gl}_1$ subalgebras $\mathcal{E}_1,\check{\mathcal{E}}_1$, wherein the parameters are tuned in a specific way according to $M,N$. In the case $M=\pm 1$, algebra $\mathcal{A}_{\pm1,N}$ is a shifted quantum toroidal $\mathfrak{gl}_2$ algebra introduced in [FJM2]. Conjecturally there is a coproduct homomorphism $\mathcal{A}_{M,N_1+N_2}\to\mathcal{A}_{M,N_1}\hat\otimes\mathcal{A}_{M,N_2}$ to a completed tensor product, whose restriction to the subalgebras $\mathcal{E}_1,\check{\mathcal{E}}_1$ coincides with the standard Drinfeld coproduct. We give examples of $\mathcal{A}_{M,N}$ modules constructed on certain direct sums of tensor products of Fock modules of $\mathcal{E}_1\otimes\check{\mathcal{E}}_1$.

We introduce the shell formula-a framework that unifies the description of partition functions whose pole structures are classified by Young diagrams of arbitrary dimension. The formalism yields explicit closed-form expressions and recursion relations for a wide range of physical systems, including instanton partition functions of 5d pure super Yang-Mills theory with classical gauge groups, as well as gauge origami configurations such as the magnificent four, tetrahedron instantons, spiked instantons, and Donaldson-Thomas invariants in $\mathbb{C}^3$ and $\mathbb{C}^4$.

The Power over Fiber (PoF) technology delivers electrical power by transmitting laser light through a lightweight, non-conductive fiber optic cable to a remote photovoltaic optical converter, which in turn powers sensors or electrical devices. Among the several advantages offered by this solution are spark-free operation in the presence of electric fields, elimination of noise induced by power lines, immunity to electromagnetic interference, and high robustness in hostile environments. The R\&D for the application of PoF in cryogenic environments started at FNAL and BNL (USA) in 2020 to power the Photon Detection System of the DUNE Vertical Drift module. This paper presents the results obtained in the framework of Cryo-PoF project where we developed a single-laser input line system to power an electronic amplifier and the photosensors at cryogenic temperatures. Unlike the DUNE solution, our system allows tuning of the photosensor bias by adjusting the input laser power. We also demonstrate the operation of the optical converter at temperatures down to 4.6 K, opening the possibility of using this technology in a much broader range of applications.

Generic absoluteness is the phenomenon that certain truths in the set-theoretic universe remain stable under forcing expansions. A classical result by Kripke asserts that every complete Boolean algebra completely embeds into a countably generated one, implying that any forcing extension can be realised inside one obtained via a collapse forcing. This observation raises a deeper question: are all forcing notions truly necessary when studying projective generic absoluteness, or does a particular class of forcing notions suffice to capture the same level of invariance? Here we show that, under suitable large cardinal hypotheses, projective generic absoluteness for collapse forcings is indeed equivalent to absoluteness for arbitrary forcings; and we discuss the necessity of these hypotheses, showing that at a low projective level the result holds in ZFC. Thus, we reveal the terminality of collapse forcings since they capture the full robustness of the universe under forcing extensions.

Cumulative geometric frustration can drive self-limited assembly and morphology selection through size-dependent energetic costs. However, the slenderness of quasi-one-dimensional systems generally suppresses the formation of long-range longitudinal gradients. We show that the suppression of longitudinal gradients can be overcome by tuning the ratio between the longitudinal and transverse (shear) moduli. We demonstrate the recovery of cumulative frustration across distinct quasi-one-dimensional systems, each frustrated through a different mechanism, by the introduction of a soft response mode.

Situational awareness for connected and automated vehicles describes the ability to perceive and predict the behavior of other road-users in the near surroundings. However, pedestrians can become occluded by vehicles or infrastructure, creating significant safety risks due to limited visibility. Vehicle-to-everything communication enables the sharing of perception data between connected road-users, allowing for a more comprehensive awareness. The main challenge is how to fuse perception data when measurements are inconsistent with the true locations of pedestrians. Inconsistent measurements can occur due to sensor noise, false positives, or unmodeled disturbances. This paper employs set-based estimation with constrained zonotopes to compute a confidence metric for the measurement set from each sensor. Estimated sets and their confidences are then fused using hybrid zonotopes. This method can account for inconsistent measurements, enabling reliable and robust fusion of the sensor data. The effectiveness of the proposed method is demonstrated in both simulation and real experiments.

The final equilibrium stage of stellar evolution can result in either a black hole or a compact object such as a white dwarf or neutron star. In general relativity, both stationary black holes and stationary stellar configurations are known to be axisymmetric, and black hole rigidity has been extended to several higher curvature modifications of gravity. In contrast, no comparable result had previously been established for stationary stars beyond general relativity. In this work we extend the stellar axisymmetry theorem to a broad class of diffeomorphism invariant metric theories. Assuming asymptotic flatness and standard smoothness requirements, we show that the Killing symmetry implied by thermodynamic equilibrium inside the star uniquely extends to the exterior region, thereby enforcing rotational invariance. This demonstrates that axisymmetry of stationary stellar configurations is not a feature peculiar to Einstein gravity but a universal property of generally covariant gravitational theories, persisting even in the presence of higher curvature corrections.

Real-time adjustments to task difficulty during flight training are crucial for optimizing performance and managing pilot workload. This study evaluated the functionality of a pre-trained brain-computer interface (BCI) that adapts training difficulty based on real-time estimations of workload from brain signals. Specifically, an EEG-based neuro-adaptive training system was developed and tested in Virtual Reality (VR) flight simulations with military student pilots. The neuro-adaptive system was compared to a fixed sequence that progressively increased in difficulty, in terms of self-reported user engagement, workload, and simulator sickness (subjective measures), as well as flight performance (objective metric). Additionally, we explored the relationships between subjective workload and flight performance in the VR simulator for each condition. The experiments concluded with semi-structured interviews to elicit the pilots' experience with the neuro-adaptive prototype. Results revealed no significant differences between the adaptive and fixed sequence conditions in subjective measures or flight performance. In both conditions, flight performance decreased as subjective workload increased. The semi-structured interviews indicated that, upon briefing, the pilots preferred the neuro-adaptive VR training system over the system with a fixed sequence, although individual differences were observed in the perception of difficulty and the order of changes in difficulty. Even though this study shows performance does not change, BCI-based flight training systems hold the potential to provide a more personalized and varied training experience.

Gravitational waves (GWs) are powerful probes of new physics in the early Universe. In particular, GWs induced by primordial isocurvature perturbations encode information of novel dynamics beyond the standard $Λ$CDM model. Existing studies of isocurvature induced GWs focus on a particular type: cold dark matter (CDM) isocurvature. In this work, we present a more comprehensive study of four kinds of isocurvature involving CDM, baryons, neutrinos and free-streaming dark radiation (DR). We first reformulate initial conditions of isocurvature with coupled neutrinos because modes relevant for observations at Pulsar Timing Arrays enter the horizon before neutrino decoupling. With these new initial conditions, neutrino isocurvature is phenomenologically similar to CDM isocurvature up to an overall coefficient, which leads to an interesting conversion of isocurvature between radiation and matter sectors. We then find that the spectrum of isocurvature induced GWs from free-streaming DR is qualitatively different than that from CDM due to the presence of anisotropic stress. Unlike GWs induced by CDM isocurvature that are suppressed at high frequencies due to matter density being suppressed at early times, DR isocurvature induced GWs is proportional to the constant ratio between DR density and total radiation. Finally, we utilize two general parametrizations of the isocurvature power spectrum: a delta function and a broken power law, and derive novel constraints with recent NANOGrav data. Our results set stringent constraints on isocurvature around $10^{6}\,\textrm{Mpc}^{-1}$, which are complementary to cosmological observations at large scales.

We develop techniques to treat massive Kaluza-Klein modes to arbitrary order in perturbation theory. The Higgs mechanism that renders the higher Kaluza-Klein modes massive is displayed. To this end we give an algorithm in perturbation theory that yields new fields with the following characteristics: they are gauge invariant under all higher-mode gauge transformations, which are broken, but they transform covariantly under the zero-mode gauge transformations, which are unbroken. We employ the formulation of field theory in terms of $L_{\infty}$ algebras together with their homotopy transfer, which here maps the gauge redundant fields of gravity to gauge invariant fields. We illustrate these results, as a proof of concept, for Kaluza-Klein theory on a torus. In an accompanying paper these results will be applied to a large class of generalized Scherk-Schwarz backgrounds in exceptional field theory.

In this thesis, we address the problem of constructing the complete supersymmetric description of systems of $N$ nearly coincident Dirichlet $p$-branes (multiple D$p$-brane or mD$p$). A particularly important result is a completely nonlinear action for the 10-dimensional dynamical system of nearly coincident multiple D$0$-branes (mD$0$) which is doubly supersymmetric, i.e. it is invariant under both spacetime (target superspace) supersymmetry and the worldline supersymmetry; the latter is a counterpart of the local fermionic $κ$-symmetry characteristic of a single D$0$-brane (Dirichlet superparticle). This problem is approached in flat superspace using the (spinor) moving frame formalism, which provides us with a geometric framework to the treatment of supersymmetric particles and extended objects ($p$-branes) in higher dimensions. Furthermore, we have initiated the quantization program aimed at development of a field theory of multiple D$0$-branes. This quantization in its complete form is expected to lead to a novel supersymmetric field theory formulated on a superspace extended by additional bosonic and fermionic matrix coordinates, whose development may offer significant insights into the deeper structure of String/M-theory.

As Open Access continues to gain importance in science policy, understanding the proportion of Open Access publications relative to the total research output of research-performing organizations, individual countries, or even globally has become increasingly relevant. In response, dashboards are being developed to capture and communicate progress in this area. To provide an overview of these dashboards and their characteristics, an extensive survey was conducted, resulting in the identification of nearly 60 dashboards. To support a detailed and structured description, a dedicated metadata schema was developed, and the identified dashboards were systematically indexed accordingly. To foster community engagement and ensure ongoing development, a participatory process was launched, allowing interested stakeholders to contribute to the dataset. The dataset is particularly relevant for researchers in Library and Information Science (LIS) and Science and Technology Studies (STS), supporting both empirical analyses of Open Access and the methodological refinement of indicators and policy instruments in the context of Open Science.

We present Egent, an autonomous agent that combines classical multi-Voigt profile fitting with large language model (LLM) visual inspection and iterative refinement. The fitting engine is built from scratch with minimal dependencies, creating an ecosystem where the LLM can reason about fits through function calls--adjusting wavelength windows, adding blend components, modifying continuum treatment, and flagging problematic cases. Egent operates directly on raw flux spectra without requiring pre-normalized continua. We validate against manual measurements from human experts using 18,615 lines from the C3PO program across 84 Magellan/MIKE spectra at SNR~50-250. The raw agreement between Egent and expert measurements is MAD=5-7mA, without any post-hoc per-spectrum correction. Per-spectrum slopes of ~0.85-1.19 around unity reflect differences in global continuum methodology rather than fitting failures. The LLM's primary role is quality control: it confirms good fits (~60-65% of lines are LLM-refined and accepted), flags problematic cases (~10-20%), and occasionally rescues edge cases where tool use improves fits. Agreement between GPT-5 and GPT-5-mini confirms reproducibility, with GPT-5-mini enabling low-cost analysis at ~200 lines per US dollar. Every fit stores complete Voigt parameters, continuum coefficients, and LLM reasoning chains, enabling exact reconstruction without re-running. Egent compresses what traditionally requires months of expert effort into days of automated analysis, enabling survey-scale EW measurement. We provide open-source code at https://github.com/tingyuansen/Egent, including a web interface for drag-and-drop analysis and a local LLM backend for fully offline operation on consumer hardware.

Mutualisms are key for structuring ecological communities, but they are sensitive to environmental change and fluctuations in population size. Consequently, how mutualisms achieve stability remains an open question in ecological theory. Motivated by previous results in competitive and predator-prey interactions, we hypothesize that self-organized pattern formation can act as a key stabilizing mechanism of mutualistic interactions. We test this hypothesis using a two-species reaction-diffusion model of a plant-pollinator system that incorporates non-local plant competition and local mutualistic interactions. We first perform a linear stability analysis to determine the conditions under which non-local competition can trigger vegetation pattern formation. We then compute the bifurcation diagrams for both spatial and homogeneous solutions and find that pattern formation enables coexistence at mutualistic strengths below the threshold required in well-mixed populations. This stability gain increases as environmental conditions worsen, because local maxima in vegetation density create the conditions for community persistence despite globally harsh conditions. Moreover, in the strong mutualism limit, the spatial system exhibits multistability between patterned and homogeneous solutions, creating alternative stable configurations that can buffer against fluctuations in population abundance. Spatial self-organization thus stabilizes mutualistic communities through spatial patterns, potentially driving plant-pollinator persistence in stressed environments, including arid ecosystems.

In this work, we investigate the elastic properties of deflated vesicles and their shape dynamics in uniaxial extensional flow. By analysing the Helfrich bending energy and viscous flow stresses in the limit of highly elongated shapes, we demonstrate that all stationary vesicle configurations are metastable. For vesicles with small reduced volume, we identify the type of bifurcation at which the stationary state is lost, leading to unbounded vesicle elongation in time. We show that the stationary vesicle length remains finite at the critical extension rate. The critical behaviour of the stationary vesicle length and of the growth rates of small perturbations is obtained analytically and confirmed by direct numerical computations. The beginning stage of the unbounded elongation dynamics is simulated numerically, in agreement with the analytical predictions.

We investigate the rotational properties of self-bound strange quark stars using two representative quark matter equations of state (EOS): the vector MIT bag model and the density-dependent quark mass (DDQM) model. Through general-relativistic calculations of uniformly rotating sequences, we analyze their mass--radius relations, moments of inertia, quadrupole moments, surface redshifts, Keplerian frequencies, and energy components. A central result of this work is the full decomposition of the stellar energy budget in rotating strange stars, separating gravitational, internal, rotational, and binding energy contributions. Rotation amplifies the intrinsic EOS differences: the MIT model supports more massive ($M_{\max} \gtrsim 3.3\,M_\odot$) compact stars with larger moments of inertia and greater resistance to deformation, while the DDQM model produces larger radii, less massive stars limited by mass-shedding at lower frequencies. Combined measurements of mass, radius, and frequency can thus break the EOS degeneracy; massive, rapidly rotating pulsars favors MIT-like EOS, whereas larger radii in canonical stars point to a DDQM-like model. These rotational observables, soon to be tightly constrained by NICER and next-generation gravitational-wave detectors, offer a means to test the existence and composition of self-bound quark matter in compact stars.