Light transport in strongly scattering porous photocatalytic materials governs the spatial distribution of absorbed photons and therefore the generation of charge carriers driving photocatalytic reactions. Yet translating measured optical properties of such media into intrinsic reaction rate constants remains challenging, as it requires simultaneously accounting for multiple scattering, boundary losses, photochemical efficiency, and surface kinetics. Here we develop a compact analytical framework that unifies these processes for nanoparticle-loaded photocatalytic slabs. Using a finite-slab diffusion model with extrapolated boundaries, we derive closed-form expressions for the fluence field and couple them to a photochemical quantum efficiency and first-order surface kinetics. The resulting predictors yield intrinsic volumetric and areal rate constants whose dependence on the transport mean free path, optical thickness, and surface-to-volume ratio emerges transparently. Validation against Monte-Carlo photon-migration simulations shows that the diffusion approximation reproduces the fluence and generation-rate profiles with a modest multiplicative mismatch, typically within a factor of about 1.20-1.39, depending on the anisotropy and scattering phase function. This level of agreement is consistent with the known limits of the diffusion approximation and is sufficient to enable reliable, design-oriented predictions. The analytical descriptors introduced here, such as l*, S/V and the extrapolation length zb are general, physically interpretable, and directly integrable into data-driven optimisation and geometry-engineered reactor design. The framework thus provides a versatile and physically grounded tool for photocatalytic systems across diverse applications, including VOC photo-degradation, indoor air purification, and solar-fuel production.

We release CosmoDC2_BCO, a synthetic catalog of gravitational-wave events and electromagnetic counterparts associated with galaxies from CosmoDC2. The catalog provides intrinsic and extrinsic source parameters, signal-to-noise ratios, parameter uncertainties, sky localization areas, and kilonova apparent magnitudes in LSST filters. Our results show that third-generation detector networks substantially increase detection rates and improve parameter estimation. Second-generation detectors, when combined with third-generation ones, significantly enhance sky localization and distance precision, particularly for BNS mergers. Assuming a simplified Target of Opportunity strategy, we estimate that an LSST-like survey, partnered with the CE+ET+LVK network at 70% duty cycle, could detect about 5000 kilonovae with GW counterparts over a 10-year period on a 16000 deg^2 footprint, predominantly from low-mass BNS mergers that produce long-lived supermassive neutron star remnants. While this is a substantial number, it represents only a small fraction of the total neutron star mergers expected to be observed by third-generation networks. These projections rely on several simplifying assumptions-including the adopted merger rate, the kilonova luminosity distribution, and the configuration and scheduling of future surveys-which introduce notable uncertainties. Therefore, the estimated detection numbers should be interpreted with appropriate caution.

Reconfigurable intelligent surface (RIS) is a cutting-edge communication technology that has been proposed as aviable option for beyond fifth-generation wireless communication networks. This paper investigates various group selection strategies in the context of grouping-based self-sustainable RIS-aided device-to-device (D2D) communication with spatially correlated wireless channels. Specifically, we consider both power splitting (PS) and time switching (TS) configurations, of the self-sustainable RIS to analyze the system performance and propose appropriate bounds on the choice of system parameters. The analysis takes into account a simplified linear energy harvesting (EH) model as well as a practical non-linear EH model. Based on the application requirements, we propose various group selection strategies at the RIS. Notably, each strategy schedules the k-th best available group at the RIS based on the end-to-end signal-to-noise ratio (SNR) and also the energy harvested at a particular group of the RIS. Accordingly, by using tools from high order statistics, we derive analytical expressions for the outage probability of each selection strategy. Moreover, by applying the tools from extreme value theory, we also investigate an asymptotic scenario, where the number of groups available for selection at an RIS approaches infinity. The nontrivial insights obtained from this approach is especially beneficial in applications like large intelligent surface-aided wireless communication. Finally, the numerical results demonstrate the importance and benefits of the proposed approaches in terms of metrics such as the data throughput and the outage (both data and energy) performance.

In this work, we have grown $\sim$100 nm thick pristine FeSe films by pulsed laser deposition. The films were structurally characterized with X-ray diffraction and their surface morphology checked through atomic force microscopy. Microwave measurements, performed with a dielectric loaded resonator tuned at the frequency of 8 GHz, allowed the characterization of the samples surface resistance, in view of potential applications in microwave haloscopes for dark matter search. Here, we report the comparison of the microwave properties of FeSe with Fe(Se,Te) thin films, as the temperature is swept from 4 K to 20 K. By applying a constant static magnetic field of 12 T, it was also possible to discern the magnetic field resilience of the two samples. FeSe showed a larger critical temperature drift as the field is applied, while the Fe(Se,Te) response broadens remarkably less. A preliminary analysis of vortex pinning shows margins for optimizing pinning in FeSe.

Recently, the isolation of 2D magnetic materials has opened several avenues for possible new ap- plications in spintronics. Among these materials, CrSBr has sparked interest due to its relatively high Curie temperature, highly anisotropic lattice structure, and high structural stability. These properties ran along others shared by any atomically thin material such as its outstanding defor- mation capacity and a strong optical response dominated by excitonic effects. The combination of these properties provides a fairly uncharted playground where to explore the interplay between magnetism and optical excitations. Here, we focus our attention on the theoretical optical response of CrSBr under several distinct strain configurations, analyzing the resulting changes to both the excitonic peaks and overall shape of the diagonal components of the linear conductivity tensor.

Recently, Korkmaz established the lower bound of $3g - 2$ for the dimension of a faithful representation of the mapping class group of an orientable surface of genus $g \ge 3$. We raise this bound to $4g - 3$ in the setting of surfaces of genus $g \ge 7$. A new ingredient is a finer study of the commutation relations in $\operatorname{PMod}(Σ)$. We use the relations arising from a certain pants decomposition of $Σ_g$ to show that any representation of dimension $\le 4g - 4$ is forced to kill a natural subgroup of the Torelli group. We also establish lower bounds for the dimension of faithful representations of related groups: the Johnson group of a closed surface, arbitrarily low terms of the Johnson filtration of a compact surface with one boundary component, and pure braid groups. These lower bounds grow linearly on the genus of the surfaces and the number of strands of the braids. Finally, we also provide some evidence that greater lower bounds for the low-genus cases should lead to improved lower bounds for $g \gg 0$.

Ellis-Bronnikov wormholes suffer from an unstable radial mode. Here we investigate the evolution of the unstable mode(s) for charged wormholes. We show that the instability remains in the presence of charge, but exhibits a very fast decrease to zero. We hereby make a full study of the spectrum of the unstable radial modes. For so-called supercritical wormholes, two purely imaginary unstable modes merge and continue with degenerate imaginary parts and opposite real parts. By analogy, we conjecture an analogous behavior for rotating chargeless wormholes.

To further reduce the complexity of lightweight speech enhancement models, we introduce a gating-based Dynamically Slimmable Network (DSN). The DSN comprises static and dynamic components. For architecture-independent applicability, we introduce distinct dynamic structures targeting the commonly used components, namely, grouped recurrent neural network units, multi-head attention, convolutional, and fully connected layers. A policy module adaptively governs the use of dynamic parts at a frame-wise resolution according to the input signal quality, controlling computational load. We further propose Metric-Guided Training (MGT) to explicitly guide the policy module in assessing input speech quality. Experimental results demonstrate that the DSN achieves comparable enhancement performance in instrumental metrics to the state-of-the-art lightweight baseline, while using only 73% of its computational load on average. Evaluations of dynamic component usage ratios indicate that the MGT-DSN can appropriately allocate network resources according to the severity of input signal distortion.

Understanding the temporal dependence of precipitation is key to improving weather predictability and developing efficient stochastic rainfall models. We introduce an information-theoretic approach to quantify memory effects in discrete stochastic processes and apply it to daily precipitation records across the contiguous United States. The method is based on the predictability gain, a quantity derived from block entropy that measures the additional information provided by higher-order temporal dependencies. This statistic, combined with a bootstrap-based hypothesis testing and Fisher's method, enables a robust memory estimator from finite data. Tests with generated sequences show that this estimator outperforms other model-selection criteria such as Akaike Information Criterion and Bayesian Information Criterion. Applied to precipitation data, the analysis reveals that daily rainfall occurrence is well described by low-order Markov chains, exhibiting regional and seasonal variations, with stronger correlations in winter along the West Coast and in summer in the Southeast, consistent with known climatological patterns. Overall, our findings establish a framework for building parsimonious stochastic descriptions, useful when addressing spatial heterogeneity in the memory structure of precipitation dynamics, and support further advances in real-time, data-driven forecasting schemes.

Adapting the modulation and coding scheme (MCS) to the wireless link quality is critical for maximizing spectral efficiency while ensuring reliability. We propose SALAD (self-adaptive link adaptation), an algorithm that exclusively leverages ACK/NACK feedback to reliably track the evolution of the signal-to-interference-plus-noise ratio (SINR), achieving high spectral efficiency while keeping the long-term block error rate (BLER) near a desired target. SALAD infers the SINR by minimizing the cross-entropy loss between received ACK/NACKs and predicted BLER values. Based on this inference, SALAD selects the MCS via hypothesis testing: if the SINR is likely underestimated, a higher MCS is selected to accelerate link adaptation under improving channel conditions. To prevent BLER drift from its long-term target, SALAD incorporates a feedback control loop that adjusts the instantaneous BLER target. Over-the-air experiments on a 5G testbed demonstrate that SALAD consistently outperforms the industry-standard outer-loop link adaptation (OLLA). With a single set of parameters, SALAD achieves up to 15% higher throughput and spectral efficiency than multiple OLLA variants across different traffic regimes, while meeting the BLER target.

We introduce the notion of a Calabi--Yau quadruple as a generalization of Iyama--Yang's Calabi--Yau triple. For each $(d+1)$-Calabi--Yau quadruple, we show that the associated Higgs category is a $d$-Calabi--Yau Frobenius extriangulated category, which moreover admits a canonical $d$-cluster-tilting subcategory. Concrete examples arise from the construction of relative cluster categories and Higgs categories in the setting of ice quivers with potentials, as well as from the singularity category of an isolated singularity. As an application, we prove that both the relative Amiot--Guo--Keller's construction and the Higgs construction of a $(d+1)$-Calabi--Yau quadruple take silting reduction to Calabi--Yau reduction.

The pattern of neutrino mixing, usually parameterized by the Pontecorvo-Maki-Nakagawa-Sakata $U_{\rm PMNS}$ matrix, still remains a striking puzzle in particle physics. $U_{\rm PMNS}$ is one of six possible products of multiplying three Euler matrices. Here we discuss the neutrino mixing matrix parameterization for three known flavours of neutrinos based on the SO(3) group represented by one three-dimensional rotation matrix $U_{\rm SO3}$ and the CP-conserving phases $δ_{\rm CP}=0^{\circ}$ and $180^\circ$. The mixing matrix $U_{\rm SO3}$ with cyclic order of the Lie group generators implies $δ_{\rm{CP}}=180^\circ$ for clockwise rotation in three dimensions, a viable scenario for normal mass ordering. We determine a range of rotation angles for $U_{\rm SO3}$ which deviate substantially from the almost maximal mixings in the standard $U_{\rm PMNS}$ scenario, yielding `democratic' values for the mixing angles. On the other hand, $δ_{\rm CP}=0^{\circ}$ CP-conserving case supports near-maximal mixing scenario. With the fixed $δ_{\rm CP}$ value, the $U_{\rm SO3}$ parameterization can be validated or falsified by the next generation of neutrinoless double beta decay experiments and puts a stringent constraint on the absolute neutrino mass. The proposed $U_{\rm SO3}$ neutrino mixing parameterization is suited for independent CP-conserving neutrino oscillation experimental analysis.

We investigate the quantum properties of the truly gauge-invariant and conserved charges of two-dimensional Yang-Mills theories, focusing on lattice QCD in the strong coupling regime. The construction of those charges uses the integral version of the (1+1)-dimensional Yang-Mills equations, and they correspond to the eigenvalues of a charge operator. The gauge invariance of the charges suggests that they are not confined, hence hadronic states may carry them. Using the path integral formalism with imaginary time (Euclidean), we evaluate the correlation functions of those charges on baryon and meson states through functional integrals over the gauge group SU(N) (N=2,3) and Grassmannian variables - the fermionic fields. Our results show that the expectation values of the lowest non-trivial charges are nonzero for baryon and meson states but vanish for non-gauge-invariant states, supporting the interpretation that hadrons indeed carry these charges. While renormalization effects and higher-order contributions remain to be analyzed, these findings point toward a potential link between gauge-invariant charges and confinement.

Leveraging the multilayer realization of programmable metasurfaces, stacked intelligent metasurfaces (SIM) enable fine-grained wave-domain control. However, their wideband deployment is impeded by two structural factors: (i) a single, quasi-static SIM phase tensor must adapt to all subcarriers, and (ii) multiuser scheduling changes the subcarrier activation pattern frame by frame, requiring rapid reconfiguration. To address both challenges, we develop a SIM-enhanced wideband multiuser transceiver built on orthogonal frequency-division multiplexing with index modulation (OFDM-IM). The sparse activation of OFDM-IM confines high-fidelity equalization to the active tones, effectively widening the usable bandwidth. To make the design reliability-aware, we directly target the worst-link bit-error rate (BER) and adopt a max-min per-tone signal-to-interference-plus-noise ratio (SINR) as a principled surrogate, turning the reliability optimization tractable. For frame-rate inference and interpretability, we propose an unfolded projected-gradient-descent network (UPGD-Net) that double-unrolls across the SIM's layers and algorithmic iterations: each cell computes the analytic gradient from the cascaded precoder with a learnable per-iteration step size. Simulations on wideband multiuser downlinks show fast, monotone convergence, an evident layer-depth sweet spot, and consistent gains in worst-link BER and sum rate. By combining structural sparsity with a BER-driven, deep-unfolded optimization backbone, the proposed framework directly addresses the key wideband deficiencies of SIM.

We introduce Verifiable One-Time Programs (Ver-OTPs) and use them to construct single-round Open Secure Computation (OSC), a novel primitive enabling applications like (1) single-round sealed-bid auctions, (2) single-round and honest-majority atomic proposes -- a building block of consensus protocols, and (3) single-round differentially private statistical aggregation without pre-registration. First, we construct Ver-OTPs from single-qubit states and classical cryptographic primitives. Then, assuming a multi-key homomorphic scheme (MHE) with certain properties, we use Ver-OTPs with MHE to construct OSC. The underlying quantum requirement is minimal: only single-qubit states are needed alongside a hardware assumption on the receiver's quantum resources. Our work therefore provides a new framework for quantum-assisted cryptography that may be implementable with near-term quantum technology.

The neutron-proton-electron (npe) matter under strong magnetic field is studied in the context of the covariant Vlasov approach. A covariant relativistic approach based on the Vlasov equation is applied to the study of infinite asymmetric magnetized nuclear matter. We use several relativistic mean-field nuclear models with non-linear terms. The dispersion relations for the longitudinal modes are obtained, and the isovector and isoscalar collective modes are determined in a wide range of densities as a function of the isospin asymmetry, momentum transfer, and magnetic field. A strong magnetic field gives rise to the appearance of low-lying isovector modes that propagate in nuclear matter, not present in non-magnetized matter. Neutron-like modes are essentially not affected by the presence of a strong magnetic field. In the presence of a strong magnetic field, Landau quantization modifies the proton-like collective modes, leading to the emergence of new branches associated with distinct Landau levels. These new modes can propagate even at high densities and exhibit isoscalar or isovector character.

Let $Ω$ be a bounded open planar domain with smooth connected boundary, $Γ$, that has been partitioned into two disjoint components, $Γ= Γ_S \sqcup Γ_N$. We consider the Steklov-Neumann eigenproblem on $Ω$, where a harmonic function is sought that satisfies the Steklov boundary condition on $Γ_S$ and the Neumann boundary condition on $Γ_N$. We pose the extremal eigenvalue problems (EEPs) of minimizing/maximizing the $k$-th non-trivial Steklov-Neumann eigenvalue among boundary partitions of prescribed measure. We formulate a relaxation of these EEPs in terms of weighted Steklov eigenvalues where an $L^\infty(Γ)$ density replaces the boundary partition. For these relaxed EEPs, we establish existence and prove optimality conditions. We also prove a homogenization result that allows us to use solutions to the relaxed EEPs to infer properties of solutions to the original EEPs. For a disk, we provide numerical and asymptotic evidence that the minimizing arrangement of $Γ_S\sqcup Γ_N$ for the $k$-th eigenvalue consists of $k+1$ connected components that are symmetrically arranged on the boundary. For a disk, for $k = 1$, the constant density is a maximizer for the relaxed problem; we also provide numerical and asymptotic evidence that for $k\ge 2$, the maximizing density for the relaxed problem is a non-trivial function; a sequence of rapidly oscillating Steklov/Neumann boundary conditions approach the supremum value.

We propose a novel method to probe gluon linear polarization via energy correlations in hard scattering processes. This approach exploits the characteristic $\cos 2ϕ$ azimuthal modulation in single- and two-point energy correlations within jets initiated by polarized gluons. In contrast to conventional techniques that rely on $k_t$ resummation or intricate jet substructure observables, our method offers a theoretically robust and experimentally accessible avenue for gluon polarimetry. We perform an all-order analysis within the Ciafaloni-Catani-Fiorani-Marchesini (CCFM) formalism, incorporating coherent branching effects to achieve improved precision. Our predictions can be tested at current and future facilities, including the LHC, RHIC, HERA, and the EIC.

We investigate the effects of the Gauss-Bonnet (GB) gravitational trace anomaly on the circular motion of test particles around black holes (BHs) and its implications for quasi-periodic oscillations (QPOs) in various theoretical models. Beginning with the equations of motion, we study the effects on effective potential, angular momentum, specific energy, and the innermost stable circular orbit (ISCO) induced by the anomaly parameter $α$. The fundamental frequencies are calculated. Moreover, we examine several QPO models, including PR, RP, WD, TD, and ER2-ER4, and study the relationship between the upper and lower QPO frequencies as well as the corresponding resonance radii for frequency ratios of 1:1, 3:2, 4:3, and 5:4. Our results show that increasing $α$ leads to deviations from the Schwarzschild case in both upper and lower QPO frequencies correlations and QPO orbital radii, with model-dependent trends. Further, we constrain the BH parameters using the observational data using MCMC analysis. Finally, we calculate the upper and lower QPO frequencies for a few BH candidates on the basis of the RP model using the constrained parameter values and find a good agreement with the observed results.

The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover $\sim$13,600 deg$^2$ to $g \sim 24.0$ and $\sim$27,700 deg$^2$ to $g \sim 22.5$, spanning $\sim$91% of the high-Galactic-latitude sky ($|b| \geq 15^\circ$). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size-luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of $265^{+79}_{-47}$ satellite galaxies with $-20 \leq M_V \leq 0$, half-light radii of $15 \leq r_{1/2} (\rm pc) \leq 3000$, and galactocentric distances of $10 \leq D_{\rm GC} (\rm kpc) \leq 300$. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of $\sim$$2σ$, which can be attributed to the clustering of satellites associated with the LMC.

We present a comprehensive investigation of the influence of Ru concentration on the lattice parameters, atomic magnetic moments, electronic structure, and magnetic anisotropy energy of the full Heusler L2$_1$-type Mn$_2$Ru$_{1-x_p}$Ga alloy, where x$_p$ = 0.0834 p with p=0,...,12. This study combines first-principles calculations with data-driven techniques from artificial intelligence, specifically principal component analysis (PCA), to reveal trends and correlations across multiple structural, magnetic, and electronic descriptors. For each composition, a set of inequivalent atomic configurations was fully optimized. Structurally, the relaxed lattices exhibit anisotropic expansion, with a pronounced elongation of the out-of-plane lattice parameter ($c$) relative to the in-plane lattice vectors, which promotes the development of perpendicular magnetic anisotropy. Our results reveal that an out-of-plane easy axis emerges at intermediate Ru concentrations (25-28%), while low and high Ru levels favor an in-plane orientation or even vanishing anisotropy. The half-metallic character is also modulated by Ru content, appearing selectively at both ends of the composition range. Additionally, the ferrimagnetic coupling between Mn(4a) and Mn(4c) sublattices leads to nearly compensated magnetic moments below 50% Ru content, with a net moment close to zero around 30%. These findings open a pathway toward the design of tunable spintronic materials with co-optimized perpendicular magnetic anisotropy and half-metallicity, making Mn$_2$RuGa a promising candidate for magnetic tunnel junctions, magnetoresistive random-access memory (MRAM) devices, and high-density magnetic storage applications.

Supersolidity - simultaneous superfluid flow and crystalline order - has been realized in quantum atomic systems but remains unexplored in purely photonic platforms operating at weak light-matter coupling. We predict a supersolid phase of light in a plasma-filled optical microcavity, where photons acquire effective mass and interact via nonlocal, plasma-mediated nonlinearities. By deriving a Gross-Pitaevskii equation with a tunable photon-photon interaction kernel, we show that under coherent driving the cavity light field can spontaneously crystallize into a supersolid lattice via modulational instability. Crucially, this supersolid arises from a weak photon-electron coupling enabled by virtual electronic transitions, and it does not require hybrid polariton formation. Using doped semiconductor microcavities, we identify feasible conditions (electron densities $\sim 10^{10}- 10^{11}~\mathrm{cm}^{-2}$ and optical intensities $\sim 10^{2}-10^{4}~\mathrm{W/cm}^{2}$) for experimental realization. This work establishes plasmonic cavities as a platform for correlated photonic matter with emergent quantum order.

For any cluster-tilting object $\mathsf{T}$ in the cluster category $\mathscr{C}_{n}$ of type $\mathbb{A}_{n}$, we construct a rank-four oriented matroid $\mathcal{M}_{\mathsf{T}}$ such that stackable triangulations of $\mathcal{M}_{\mathsf{T}}$ are in bijection with equivalence classes of maximal green sequences with initial cluster $\mathsf{T}$. This generalises the result that equivalence classes of maximal green sequences of linearly oriented $\mathbb{A}_{n}$ are in bijection with triangulations of a three-dimensional cyclic polytope. The definition of the oriented matroid $\mathcal{M}_{\mathsf{T}}$ arises from the extriangulated structure on $\mathscr{C}_{n}$ which makes $\mathsf{T}$ projective.

We present a method for computing the classification groups of topological insulators and superconductors in the presence of $\mathbb{Z}_2^{\times n}$ point group symmetries, for arbitrary natural numbers $n$. Each symmetry class is characterized by four possible additional symmetry types for each generator of $\mathbb{Z}_2^{\times n}$, together with bit values encoding whether pairs of generators commute or anticommute. We show that the classification is fully determined by the number of momentum- and real-space variables flipped by each generator, as well as the number of variables simultaneously flipped by any pair of generators. As a concrete illustration, we provide the complete classification table for the case of $\mathbb{Z}_2^{\times 2}$ point group symmetry.

Metal components are extensively used as current collectors, anodes, and interlayers in lithium-ion batteries. Integrating these functions into one component enhances the cell energy density and simplifies its design. However, this multifunctional component must meet stringent requirements, including high and reversible Li storage capacity, rapid lithiation/delithiation kinetics, mechanical stability, and safety. Six single-atom metals (Mg, Zn, Al, Ag, Sn and Cu) are screened for lithiation behavior through their interaction with ion beams in electrochemically tested samples subjected to both weak and strong lithiation regimes. These different lithiation regimes allowed us to differentiate between the thermodynamics and kinetic aspects of the lithiation process. Three types of ions are used to determine Li depth profile: $H^+$ for nuclear reaction analysis (NRA), $He^+$ for Rutherford backscattering (RBS), and $Ga^+$ for focused ion beam (FIB) milling. The study reveals three lithiation behaviors: (i) Zn, Al, Sn form pure alloys with Li; (ii) Mg, Ag create intercalation solid solutions; (iii) Cu acts as a lithiation barrier. NRA and RBS offer direct and quantitative data, providing a more comprehensive understanding of the lithiation process in LIB components. These findings fit well with our ab-initio simulation results, establishing a direct correlation between electrochemical features and fundamental thermodynamic parameters.

Michaelis-Menten kinetics is one of the most recognized models in enzyme kinetics, crucial for the understanding of biochemical reactions in several metabolic processes. In this study, we perform a stochastic analysis of the Michaelis-Menten kinetics with the introduction of inhibitory mechanisms, which significantly diversifies the study of the reaction. We apply the Fock space formalism to reformulate the master equation, transforming it into a Schrödinger-type equation. We investigate reversible inhibitions and analyze the behavior of the averaged number of substances involved, identifying a stiffness behavior in all scenarios. In a specific case of partial inhibition, we observe that the inhibitor can act as an activator that favors product formation. We calculate the first product formation time (FPFT), which characterizes the time statistic of the first product formation. We observe the emergence of an intermediate time scale in addition to the two known time scales typical in first-passage problems. This intermediate time scale is closely aligned with the slow-binding kinetics observed in experimentally observed enzymatic reactions that involve inhibitors. This intermediate time scale is related to the new pathways introduced by the presence of inhibitors. This study offers a new perspective on inhibited enzymatic reactions, and demonstrates the usefulness of the Fock space formalism in the analysis of complex chemical systems.

Dynamical decoupling is a central technique in quantum computing for actively suppressing decoherence and systematic imperfections through sequences of single-qubit operations. Conventional sequences typically aim to completely freeze system dynamics, often resulting in long protocols whose length scales exponentially with system size. In this work, we introduce a general framework for constructing time-optimal, selectively-tailored sequences that remove only specific local interactions. By combining techniques from graph coloring and classical coding theory, our approach enables compact and hardware-tailored sequences across diverse qubit platforms, efficiently canceling undesired Hamiltonian terms while preserving target interactions. This opens up broad applications in quantum computing and simulation. At the core of our method is a mapping between dynamical decoupling sequence design and error-detecting codes, which allows us to leverage powerful coding-theoretic tools to construct customized sequences. To overcome exponential overheads, we exploit symmetries in colored interaction hypergraphs, extending graph-coloring strategies to arbitrary many-body Hamiltonians. We demonstrate the effectiveness of our framework through concrete examples, including compact sequences that suppress residual ZZ and ZZZ interactions in superconducting qubits and Heisenberg exchange coupling in spin qubits. We also show how it enables Hamiltonian engineering by simulating the anisotropic Kitaev honeycomb model using only isotropic Heisenberg interactions.

The interplay between charge stripes and pairing has long been a subject of scrutiny in a broad class of unconventional superconductors, as in some cases it is unclear whether this interplay benefits the ensuing superfluidity. Experiments that explore the out-of-equilibrium dynamics of these systems aim to tip the balance toward one phase or the other by selectively coupling to relevant modes. Leveraging the fact that competition between stripes and pairing is not exclusive to fermionic systems, we explore the photoirradiation dynamics of interacting hardcore bosons, in which density-wave phase-reversal melting leads to enhanced phase-coherent transport response, as quantified by the dynamic amplification of both the zero-momentum occupancy and the condensate fraction, as well as finite out-of-equilibrium charge stiffness and superfluid weight, for a given system size. Our results, obtained using unbiased methods for an interacting system on a ladder geometry, demonstrate how one can engineer time-dependent perturbations to release suppressed orders, potentially providing insight into the underlying mechanism in related experiments.

We examine the effective field theory (EFT) of maximal chaos through the lens of Krylov complexity and the Universal Operator Growth Hypothesis. We test the relationship between two measures of quantum chaos: out-of-time-ordered correlators (OTOCs) and Krylov complexity. In the EFT, a shift symmetry of the hydrodynamic modes enforces the maximal Lyapunov exponent in OTOCs, $λ_L = 2πT$, while simultaneously constraining thermal two-point autocorrelators. We solve these constraints on the autocorrelator, and calculate the Lanczos coefficients and Krylov exponents for several examples, finding both $λ_K = λ_L$ and $λ_K = λ_L/2$. This demonstrates that, within the EFT, the shift symmetry alone is insufficient to enforce maximal Krylov exponents even when the Lyapunov exponent is maximal. In particular, this result suggests a tension with the conjectured bound $λ_L \leq λ_K \leq 2πT$. Finally, we identify autocorrelator solutions whose power spectra closely resemble the so-called thermal product formula seen in holographic systems.

This work analyzes accelerating and decelerating wall-driven flows by quantifying the upper bound of transient energy growth using a Lyapunov-type approach. By formulating the linearized Navier-Stokes equations as a linear time-varying system and constructing a time-dependent Lyapunov function, we obtain an upper bound on transient energy growth by solving linear matrix inequalities. This Lyapunov method can obtain the upper bound of transient energy growth that closely matches transient growth computed via the singular value decomposition of the state-transition matrix of linear time-varying systems. Our analysis captures that decelerating base flows exhibit significantly larger transient growth compared with accelerating flows. Our Lyapunov method offers the advantages of providing a certificate of uniform stability and an invariant set to bound the solution trajectory.