Papers

High-energy QCD evolution at NLO suffers from large collinear logarithms that make the perturbative expansion of the Balitsky-Kovchegov (BK) equation unstable. We develop a systematic scheme-transformation framework using the Doi-Peliti formalism to relate projectile ($k^+$) and target ($k^-$) factorization schemes. The transformation of high-energy operators and the evolution kernel generates NLO terms that cancel the problematic double collinear logarithm. The resulting NLO BK equation is free of this instability, with only single collinear and double anti-collinear enhancements remaining. Numerical solutions show stable evolution up to $Y=10$ for both Golec-Biernat-Wusthoff and McLerran-Venugopalan initial conditions, providing a consistent path toward combining stable NLO evolution with rotated NLO impact factors.

JWST has discovered an overabundance of UV-luminous galaxies compared to extrapolations from pre-JWST galaxy formation models. Distinguishing between proposed theoretical explanations requires constraining the halo masses of these systems, which can be probed through clustering. However, at $z>10$, low galaxy number densities render traditional clustering measurements challenging. We introduce a novel formalism that uses information about the local environments ($\lesssim$2 arcmin) of individual UV-bright galaxies at $z>10$ to test the galaxy-halo connection implied by theoretical models for the UVLF excess. We create mock JWST observations using (500 cMpc)$^3$ 21cmFAST simulations to forward-model the spatial distribution of fainter photometric candidates around UV-bright galaxies. We find that the distance to the nearest neighbor is sensitive to the stochasticity of the UV luminosity-halo mass relation, and can distinguish between models where UV luminosity is boosted uniformly in galaxies versus models with high stochasticity in UV luminosity at fixed halo mass. As a proof-of-concept, we apply our framework to observations around the two brightest confirmed galaxies at $z>10$, GN-z11 and JADES-GS-z14-0, and find that the lack of neighbors within $<0.5$ arcmin of these sources disfavors models where UV luminosity is boosted uniformly, suggesting that stochasticity is important for explaining their high UV luminosities. We forecast that distinguishing between these models at high significance requires deep imaging surveying $<1.1$ arcmin around $7$-$15$ bright galaxies ($M_{\rm UV}\lesssim-21$) at $z =10$-$12$, dropping to $\lesssim5$ at $z\sim14$, capable of detecting their neighbors down to $M_{\rm UV,lim}\approx-18$. These observations are within reach of JWST, Roman and Euclid surveys, providing a path to constraining the galaxy-halo connection at our redshift frontier.

The quantum data processing inequality asserts that quantum relative entropy is monotonically non-increasing under quantum channels. Here, we promote this fundamental inequality to an exact equality via boundary and surface Poisson integral representations across a complex strip. The relative-entropy loss is resolved into two independent, nonnegative physical mechanisms: an operational Petz recovery component governing state reconstructibility, and a boundary term measuring the mismatch of relative modular dynamics. We further express the loss as the measured relative entropy between the original state and its averaged Petz recovery state plus a nonnegative variational remainder. For the Belavkin–Staszewski (BS) loss, analogous integral representations yield a decomposition into negative log Uhlmann fidelity with an averaged reconstruction plus a nonnegative variational remainder. Furthermore, we establish recovery bounds at any prescribed modular parameter, including the canonical unrotated Petz map, with optimal square-root scaling in the relative entropy loss. The prefactors depend on distinct-eigenvalue counts or logarithmic spectral quantities, improving upon the inverse-power dependence on small eigenvalues in previous bounds.

The disruption of stars by supermassive black holes (SMBHs) as tidal disruption events (TDEs) can produce transient flares across the electromagnetic spectrum. Such flares can be used to probe SMBH properties, accretion physics and stellar dynamics in galactic nuclei. However, it can be difficult to distinguish TDE flares and those arising from other accretion phenomena around SMBHs, such as active galactic nuclei disk instabilities. Repeated flares from the same location can be produced by either such instabilities or by repeated partial disruptions of the same star, with the former expected to be at random intervals and the latter roughly periodic. Repeating nuclear transients can thus be used to distinguish between full and partial TDEs, as well as between TDEs and other accretion phenomena. Here we review observations of such repeating nuclear flares at various wavelengths. As time domain surveys become wider, deeper and faster, and as they accumulate longer baselines of data, more repeating phenomena at various time scales are being revealed. While these events show the potential for constraining several open questions regarding SMBH accretion phenomena, the small number of cases so far, the limited observational coverage for many of them, and the overall diversity of emission and repetition properties observed make it difficult to robustly associate most cases with physical scenarios at this stage. However, in the near future, as more data accumulate, the nature of various classes of repeating nuclear transients should become more clear, and with it the nature of many of the one-time flares as well.

We formulate the low-energy theory of superconducting pairing in the geometric algebra $Cl_{3,0}$. Conventional BCS mean-field theory and its extensions ($s$-, $p$-, $d$-wave, etc.) have algebraic counterparts in an eight-dimensional real multivector space. The construction is a two-level projection: matrix blocks are represented as Clifford multivectors, and their grade-0 projected geometric products extract the scalar blocks from which Hamiltonians are built. The result is an algebraic reconstruction, physically equivalent to the standard complex-matrix formulation. In this reconstruction, the dichotomy of pairing channels acquires an algebraic root: it follows from the fermionic identity $B^\dagger(V)=-B^\dagger(V^{\mathsf T})$, and the Fierz rearrangement is realized by the map $\Phi:G\mapsto Ge_{31}$ (with $e_{31}^2=-1$). This yields a kernel/matrix dictionary: at the effective-kernel level grades $0\oplus3$ correspond to spin singlets and grades $1\oplus2$ to triplets; at the pairing-matrix level the singlet plane is $\mathrm{span}\{e_2,e_{31}\}$. The BCS limit has a double grade identity: kernel grade 0 (scalar glue) and vertex grade 2, a bivector ($i\sigma_2\leftrightarrow e_{31}$). We state three algebraic results: (i) a decomposition theorem for BdG quantum geometry with a null-texture criterion, applied to the chiral-state controversy in CsV$_3$Sb$_5$; (ii) a Fierz sign duality in the four-dimensional Minkowski algebra, with a chirality-reversal extension to two-node Weyl-semimetal models; (iii) an error bound and condition-number structure for tomographic reconstruction under a linear-response probe model. Illustrations include a glue-generation mechanism, a one-loop algebraic renormalization flow whose feeding constant coincides in magnitude with the $\mathfrak{su}(2)$ Casimir, closed-form $\mu=0$ inter-node spectra, and a UTe$_2$ two-phase analysis.

Modeling spatiotemporal coupling is a key challenge in building physical intelligence across scales, from microscopic to macroscopic. Existing models capture such structure broadly through physics-motivated dynamical formulations or learning-motivated architectures. The former provide stronger priors but may constrain flexibility, whereas the latter are more flexible but leave the spatiotemporal coupling largely implicit. We therefore seek an approach that combines flexible learning with an explicit geometric bias for jointly modeling time and space. To this end, we propose Minkowski Positional Encoding (MinkowskiPE), which uses joint temporal and spatial coordinates to parameterize Lorentz transformations applied to query and key features. With MinkowskiPE, the query-key attention score depends on position only through the relative spacetime displacement between the two tokens and is therefore invariant to global translation of the coordinates. This paradigm retains the standard dot-product attention interface and remains compatible with efficient attention implementations. We evaluate MinkowskiPE on microscopic molecular dynamics and macroscopic video prediction tasks, achieving the best results on all nine multi-trajectory molecular evaluations and reducing KTH video-prediction MSE by 9.9% relative to the best baseline while using roughly one-tenth as many parameters.

Understanding quantum phases of matter has long relied on physicists' intuition and mathematical tools such as symmetry and topology. Remarkably successful as these approaches have been, they provide no universal way to explore a Hamiltonian space whose organizing principle is not known in advance. In this work, we introduce a fully autonomous system combining differentiable programming and unsupervised learning for quantum phase discovery. The search evaluates ground-state data along an adaptive trajectory rather than on a predetermined parameter grid. We demonstrate the system with three different solvers and benchmark it against random sampling at equal ground-state-evaluation budgets. On a generalized cluster chain hosting up to $200$ distinct phases, the search finds up to $25$ more phases at the same budget, and matches random sampling given thirty times its budget. On a $50$-parameter Chern insulator, it reaches sectors not obtained by the simple harmonic constructions considered here, in a family whose inverse problem remains open, while recovering all sectors found by sampling. Our results establish autonomous, gradient-driven exploration of Hamiltonian space as a practical route to discovering quantum phases without phase labels or a prescribed target phase.

A sub-grid closure of the scalar-dissipation rate for the Large Eddy Simulation (LES) of turbulent premixed flames is assessed experimentally. Hotwire anemometry is performed to characterize the background turbulent flow, and the Rayleigh scattering measurements are conducted to acquire instantaneous temperature fields, which are used to obtain the scalar dissipation rate. Either methane or hydrogen-enriched (40% by volume) methane is used as the fuel. The Karlovitz number varies between 1.7 and 34.5. The LES filter size is changed from 0.1 to 3.0 times the thermal thickness of the corresponding laminar flames. Both Gaussian and top-hat filtering methods are used. Statistical analyses are performed to investigate the characteristics of the measured, resolved, and unresolved scalar dissipation rate as well as how these are influenced by the normalized filter size, filter type, and the Karlovitz number. It is shown that the algebraic model allows for acceptable prediction of the Favre-filtered, temporally and spatially averaged scalar dissipation rate across the examined test conditions. The experimental measurements are used to gain insight into a key parameter used in the algebraic model. While differences between the previously proposed and our measured value of the model parameter for small Karlovitz number flames are reported, good agreement between our measured values and previously suggested values is obtained for relatively larger Karlovitz number flames. This finding is shown to be consistent across the examined filter sizes and filtering methods, despite the differences in the examined flame configuration of the present experimental study and those of past numerical investigations. This motivates future investigations to assess use of the algebraic model for simulating turbulent premixed flames with an extended range of operation.

Electrolytes under an external magnetic field exhibit a Hall conductivity, much like metals and semiconductors. However, existing theories fail to quantitatively account for their measured Hall conductivities. To make progress toward such a theory, we develop a stochastic density functional framework for electrolytes in a magnetic field. This framework, which we dub odd SDFT, extends the celebrated stochastic density functional theory (SDFT) to incorporate transverse mobilities and chiral time-correlated noise. Using this framework, we calculate the Hall conductivity in the absence of hydrodynamic solvent effects through three approaches: (i) direct response, (ii) Green-Kubo relation, and (iii) a hybrid fluctuation-dissipation relation. We further show that odd SDFT applies more broadly to fluids with broken time-reversal and mirror symmetry, including odd-diffusive fluids and chiral active matter. Our results generalize the relaxation correction of Debye-Hückel-Onsager theory to magnetized electrolytes and provide a foundation for incorporating additional effects mediated by the solvent that could quantitatively reconcile theory and experiments.

Charge regulation refers to the ability of ionizable biomolecules and their counterparts to adjust their ionization state in response to external perturbations, including changes in pH, ionic strength, or electrostatic interactions with neighboring charged species. Here, we use explicit-ion molecular dynamics / charge-regulation Monte Carlo simulations to compute the interaction force between two spherical, charge-regulated nanoparticles as a function of separation, and compare symmetric (chemically identical) and asymmetric (chemically complementary) surface configurations against the constant charge approximation. We find that charge regulation produces up to an order-of-magnitude stronger short-range attraction than constant charge for asymmetric nanoparticle pairs, particularly at low electrolyte concentration, and that charge regulation qualitatively alters the interaction between symmetric, chemically identical nanoparticles, driving a crossover from net repulsion to net weak-attraction as ionic strength decreases. This transition is not observed under the constant charge assumption which shows that charge regulation is not a minor correction but can change both the strength and the sign of nanoscale electrostatic interactions, with implications for the assembly and stability of charge-regulated colloidal systems

Conventional reflectance photoplethysmography (PPG) typically reduces tissue optical responses to one or a few detector channels. Matrix Pinhole Image Sensing (MAPIS) instead simultaneously samples multiple aperture-dependent optical signals. We analyzed 44 recordings of 30 seconds each from a single MAPIS device to characterize the spatial relationships among DC intensity, pulsatile AC, perfusion index (PI), and temporal coherence across Red and infrared channels. AC increased sublinearly with DC at both wavelengths, resulting in higher PI toward lower-DC apertures, consistent with a first-order relative path-sensitivity interpretation. A second counterintuitive spatial trend was observed in temporal coherence: lower-DC and lower-AC apertures exhibited higher autocorrelation and greater cardiac-periodic spectral concentration. IR signals also showed consistently higher temporal coherence than corresponding Red signals. These observations demonstrate that multi-aperture PPG resolves reproducible spatial relationships among optical intensity, fractional pulsatile sensitivity, and waveform coherence that are largely averaged together in conventional single-channel PPG. The present study establishes within-device relationships and motivates controlled studies of the underlying photon-path mechanisms.

Structural observations in polymer chemistry are often rationalized through underlying mechanistic insights. The study of families of mechanisms - and the phenomenology and lawlike behavior that can accompany them - is less common. Here we construct a theory that links a mechanistic feature - the number of nearest neighbors $k$ that influence monomer incorporation - with the accessible copolymer sequence space. We find that the reaction mechanisms can be mapped 1-to-1 to a regular de Bruijn graph of degree $k$. We calculate the periodic copolymer sequences as function of neighbor index $k$, and number of monomers $s$. We show that the number of periodic sequences grows explosively with $s,k$, bounded from below by $s!^{s^{k-1}}/s^k$. We find that periodic k-polymerization is governed by several simple laws describing allowed sequences, number of specific reactions, repeating unit length and the allowed and disallowed sequence coexistence in block copolymers. We formulate Simple Assembly Rules (SAR) that capture commonly observed behavior and design of literature systems, and characterize the possible k-polymerizations they are allowed to access ($k\leq2$) as function of symmetries and illustrate our findings with reported examples from the coordination chemistry and supramolecular chemistry literature. We discuss chemical-structural contributions by which nontrivial ($k>1$) sequences are formed, highlighting the importance steric hindrance, long-range interactions and degrees of freedom.

A unified linear theory is developed for the unsteady loading of finite-chord aerofoils, rigid or porous, in compressible subsonic flow. The formulation combines Possio's integral operator with a convective permeable boundary condition, allowing chordwise-varying admittance while retaining the wake and unsteady Kutta condition. The loading exponents at aerofoil edges and admittance discontinuities keep their incompressible form in terms of the local permeability parameter, so weighted-Jacobi collocation carries over. The solution is verified against published incompressible results and an independent compressible formulation. Gust and heave responses and their indicial counterparts reveal that permeability controls the sensitivity of unsteady loading to compressibility. As permeability increases, the material impedance rather than the surrounding flow sets the pressure jump, but only gradually: at Mach number 0.7 the gust load on a weakly permeable surface changes by a third to a half, and closed-form steady and high-frequency limits for resistive surfaces show that it vanishes only when the permeability parameter greatly exceeds the Mach number. The porous-to-impermeable load ratio, by which a treatment is judged, cannot be obtained by combining incompressible porous and compressible rigid theories, which misjudge it by up to a factor of two. Incompressible theory overestimates this ratio for an acoustically compact chord and underestimates it for a non-compact one, by factors of 1.4 to 4.3 at Mach numbers 0.5 to 0.7 and reduced frequencies 5 to 20, overstating the load reduction. Since compactness depends on Mach number times reduced frequency, the error persists at low speed, exceeding 10 per cent at Mach number 0.05 for reduced frequencies above 10.

Phase diagrams and energy surfaces require low-energy states across a family of Hamiltonians, but solving each parameter point independently is prohibitively expensive. An important question is not how a single labeled eigenstate behaves under parameter variation, but how much information about the low-energy sector is contained in a small set of reference wavefunctions. We show that the physically relevant object is the isolated low-energy subspace itself: it remains well defined through degeneracies and level crossings, and it can be learned efficiently from nearby sampled states. Working in this subspace, we prove that a sampling pattern cancelling the first $q$ nonconstant response orders yields an energy-density error bounded by $d^{2(q+1)}$ for every retained level, where $d$ is the parameter-space sampling distance. For a gapped local ground state on $n$ sites, locality sharpens this to $d^2(nd^2)^q$, identifying $nd^2$ as the natural scaling variable governing the effectiveness of higher-order information from sampled wavefunctions. In a local analytic regime this gives a sampling cost $K=\mathcal{O}([\log(1/\varepsilon)]^D)$ at fixed parameter dimension $D$. Numerical results on Heisenberg and transverse-field Ising chains confirm the distance scaling law and the $nd^2$ collapse. Beyond characterizing learnability, the scaling behavior further provides a finite-size probe of phase transitions near criticality.

X-ray absorption spectroscopy (XAS) is a powerful, element-specific probe for investigating the local structural and electronic properties of materials. However, quantitative analysis remains challenging, necessitating accurate first-principles spectral simulations. In this study, we benchmark first-principles simulations of Ti K-edge X-ray absorption near-edge structure (XANES) against experimental data for nine common titanium compounds. We systematically investigate key physical effects, including quadrupole excitations, thermal disorder, and many-body shake-up. Our results demonstrate that quadrupole excitations and thermal disorder are essential for capturing accurate pre-edge features, while many-body shake-up effects significantly influence the spectral shape of the main- and post-edge regions. By incorporating these effects alongside a band-theory treatment of the core-hole final state, our simulated spectra achieve excellent agreement with experimental data for most of the systems, as evidenced by high similarity scores. The shoulder peak in BaTiO$_3$ at 4980 eV in the experiment is largely missing in simulation. Further analysis shows that more accurate electronic structure theory than semi-local density functional theory is required to capture the correlation effects of the Ba $4f$ orbitals and that defects, such as oxygen vacancies, may also contribute to the shoulder. Beyond tackling specific titanium material systems, this work establishes a robust workflow for generating high-fidelity Ti K-edge XANES databases for titanium compounds, providing a framework that can be generalized to a broad range of materials.

We investigate the positional statistics and thermodynamic properties of a Brownian particle confined in a Harmonic trap. The stiffness of the particle fluctuates in time as the square of the Brownian process. First, in the absence of a thermal bath, we investigate the probability density function of the position of the particle at time $t$. Then, we provide an expression to compute the $n$th positional moment. We evaluate the first four positional moments and discuss their asymptotic behavior in the long-time limit. In contrast to previously studied models of fluctuating stiffness, the current model describes a non-stationary process. Furthermore, we provide the exact expression for the average work performed on the system and the average heat exchanged by the particle with the bath. Their long time behavior again reflects the non-stationary nature of the process. Our theoretical predictions are supported by numerical simulations.

Groups differing in social and economic circumstances often differ markedly in depressive symptom levels, yet their estimated symptom networks show few clear differences. Such null results are often read as evidence that the groups' symptom systems are the same, but they only show that no difference was detected in how symptoms interact. How readily symptoms become present, and how this depends on the contextual conditions under which they are observed, is rarely compared. Building on a slow-fast perspective, we treat depressive symptoms as a relatively fast-changing system embedded in more persistent social, economic, psychosocial, health, and lifestyle conditions that shape symptom activation. Using a cohort of 23,689 adults from Amsterdam, we illustrate this with PHQ-9 depressive symptoms and a composite index of persistent socioeconomic, psychosocial, and health-related conditions, which we call Slow Risk Load (SRL). Participants with high SRL had substantially higher symptom levels than those with low SRL. A standard Network Comparison Test detected no overall difference in network structure, although global strength was modestly higher in the high-SRL group. Ising models, which separate how symptoms co-occur from how readily each becomes present, indicate higher activation under high SRL for eight of nine symptoms, and model comparison consistently favored group-specific activation over group-specific interactions. The slow-fast perspective reframes group network comparisons as a multiple-timescale problem in which network structure, symptom activation, and context should be considered jointly. It places symptom-focused and context-focused interventions at different layers of the same coupled system rather than in competition.

Semantic mismatch between independently trained AI-native agents in heterogeneous networks can impair semantic communications. Hybrid analog-digital semantic equalization can align the incompatible latent representations without retraining the semantic transceivers. We study a practical realization of this approach based on a fabricated dynamic metasurface antenna (DMA), an emerging low-cost, low-power, ultracompact technology for hybrid analog-digital beamforming. We model the DMA-assisted channel using multiport-network theory (MNT), accounting for mutual coupling (MC), structural scattering, and binary lossy tuning states. We use the experimentally estimated MNT parameters of our fabricated 19-GHz DMA prototype with strong MC. We jointly optimize digital pre- and post-equalizers and the DMA at a reference receiver geometry for latent-space alignment, then freeze the digital stages and adapt only the DMA after receiver motion. In our CIFAR-10 image-classification task at the receiver, the jointly optimized system achieves 94.5% accuracy, while DMA-only adaptation restores a median accuracy of 90.3% after receiver motion. Our semantic-aware wave-domain adaptation substantially outperforms semantic-unaware benchmarks. We further observe that varying the DMA configuration across channel uses provides little additional benefit for either semantic-aware or semantic-unaware optimization.

We investigate the dynamics of full counting statistics (FCS) of the growth of the total number of fermions in a one-dimensional non-interacting lattice subjected to a localized particle gain (source) at one edge. The dynamics of the setup is modeled by the Gorini–Kossakowski–Sudarshan–Lindblad (GKSL) quantum master equation. We recast the counting problem that involves counting particle number at every lattice site to a problem where only the local injected site is involved. We employ the Schwinger-Keldysh path integral formalism within the GKSL framework and derive an analytical expression for the cumulant generating function at arbitrary times and obtain a Levitov-Lesovik type formula in the long-time limit, earlier derived for boundary driven setups in the steady-state. For clean lattices with either short- or long-range hopping, supporting single-particle delocalized eigenstates, we show that all cumulants grow linearly with time in the asymptotic regime. Our analytical results are in excellent agreement with direct numerical simulations. These findings establish a general framework for characterizing FCS and quantum fluctuations in driven open fermionic systems with localized particle injection.

The negatively charged boron vacancy is an optically addressable spin centre in hexagonal boron nitride (hBN), but bringing two vacancies together introduces electronic interactions absent from the isolated-defect picture. Here we use density-functional theory at total charge q = -2 to show that atomic-scale placement reverses the preferred collinear spin alignment in monolayer hBN. Among seven configurations, the closest pair, separated by 4.3 angstrom, favours parallel alignment by 27.6 meV within the semilocal approximation. Moving one vacancy by a single lattice vector reverses the preference, and a 7.5 angstrom pair favours antiparallel alignment by 50.7 meV. Numerical controls change these two reference splittings by less than 1 meV; hybrid-functional calculations retain their signs while substantially changing their magnitudes. Local distortions connect the antiparallel preference at 7.5 angstrom to changes in vacancy-state hybridization along an intervening atomic chain. The closest pair instead exhibits a contact-localized spin-density contrast and constrained angular energies that depart from the bilinear Heisenberg form. These results identify a placement-sensitive regime of interacting defects and provide a microscopic foundation for investigating coupled spin centres in atomically thin materials.

Quantum physics-informed neural networks (QPINNs) solve partial differential equations (PDEs) by training parameterized quantum circuits against physics-based residuals, yet the role of the embedding that maps coordinates into quantum states remains insufficiently understood. In this research, we introduce a unified embedding framework that formulates embedding as a functional transformation shaping the feature representation available to the variational circuit, and we propose two embeddings within it. The Linear Quantum Neural Network Trainable Embedding QPINN (LQNN-TE-QPINN) generates data-dependent features with an auxiliary quantum circuit and adds them to the input coordinates, instead of multiplying them as in our previous formulation. The adaptive-frequency QPINN (AdaFreq-QPINN) promotes the frequency-scaling factors of an arccos-Chebyshev encoding to trainable parameters. We evaluate both against direct and fixed analytical frequency encodings and alternative hybrid architectures on one- and two-dimensional Burgers equations. In one dimension, LQNN-TE-QPINN achieves a relative $L_2$ error of 0.0916 with 720 trainable parameters, compared with 0.4501 for direct-encoding QPINN and 0.1233 for a locally adaptive classical physics-informed neural network with approximately eleven times more parameters, while AdaFreq-QPINN attains the lowest error among the analytical embeddings with only four additional parameters. In two dimensions, LQNN-TE-QPINN attains the lowest training objective, although its solution error is not clearly separated from that of a data re-uploading QPINN. Under simulated hardware noise, LQNN-TE-QPINN retains the lowest absolute derivative error while degrading most relative to its noiseless baseline. These results demonstrate that embedding design substantially influences the approximation and optimization behavior of QPINNs.

The renormalization of asymptotically AdS spacetimes in New Massive Gravity is studied using boundary terms constructed with the extrinsic curvature. For generic values of the theory couplings, a single extrinsic boundary term produces a consistent holographic description, as the variation of the total action is finite and expressible in terms of the holographic source. This prescription applies to constant-curvature geometries and non-Einstein solutions with Brown-Henneaux asymptotic conditions. A suitable asymptotic expansion shows the agreement of the resulting holographic stress tensor with the one obtained from the auxiliary-field formulation. At the degenerate point, where the two maximally symmetric vacua coalesce, the Fefferman-Graham expansion admits an additional mode associated with relaxed AdS boundary conditions. A quadratic extrinsic counterterm removes the new divergences and leads naturally to a holographic picture with two independent sources. The corresponding responses obey a modified holographic Ward identity and determine finite conserved charges. Finally, the proper use of the Noether-Wald formalism reproduces the correct charges of the BTZ black hole, non-Einstein AdS waves, and the rotating hairy black hole.

Quantum linear-system algorithms access the coefficient matrix through a block-encoding oracle $U_A$ and the right-hand side through a state-preparation oracle $U_b$. The optimal query complexities of these two oracles are known separately: $O(\kappa\log(1/\varepsilon))$ queries to $U_A$ and $O(\kappa/s)$ queries to $U_b$, where $s=\alpha\|A^{-1}b\|$. Whether a single algorithm can achieve both bounds simultaneously has remained open. We resolve this question affirmatively. Given a constant-factor estimate of $s$, we give a quantum linear-system algorithm that prepares the normalized solution to error $\varepsilon$ using simultaneously $ O\left(\kappa\log\frac1\varepsilon\right)$ queries to $U_A$ and $O\left({\kappa}/{s}\right)$ queries to $U_b$. The algorithm separates state preparation from precision refinement, so only the matrix-query count depends on the target accuracy. We also prove a matching same-instance worst-case lower bound: for every quantum linear-system algorithm and every solution-norm scale, there exists a single Hermitian instance on which that algorithm requires both $\Omega(\kappa\log(1/\varepsilon))$ matrix queries and $\Omega(\kappa/s)$ state-preparation queries. Thus the two oracle complexities can be optimized simultaneously, and the resulting bounds are jointly optimal.

In this work, a globally stiffly accurate Implicit-Explicit (IMEX) Runge-Kutta scheme is developed and implemented in the GBS code [Ricci et al., Plasma Phys. Control. Fusion, 2012], for two-fluid plasma turbulence simulations. The stiffest phenomena, governed by shear Alfvén waves and parallel diffusion, are treated implicitly, while the remaining non-stiff terms are advanced explicitly. This splitting enables time steps well beyond the Courant-Friedrichs-Lewy limit, without incurring the full computational cost of a globally implicit formulation. To efficiently solve the implicit subsystem at each time step, a three-dimensional physics-based preconditioner, inspired by techniques developed in the magnetohydrodynamic (MHD) context, is used. The resulting framework is verified through the method of manufactured solutions and exhibits both algorithmic and parallel scalability. Significant advantages in numerical stability and computational efficiency are demonstrated with respect to an adaptive explicit Runge-Kutta scheme.

All cosmological models are defined through energy and matter, which describe the evolution of the targeted Universe. Whether the content is simple or complex, it can be defined through an effective equation of state (EoS). We study different cosmological models by analyzing the properties of the complete EoS of their fluid contents. We obtained general expressions for the ratio between pressure $p$ and energy density $\rho$, and for their derivative $dp/d\rho$ in terms of deceleration and jerk parameters. We show that, in general, a cosmology whose energy density is constructed from multiple ideal gases cannot be described by the EoS of a single, ideal gas. This is directly related to a variation in the deceleration parameter during the evolution of the Universe. Furthermore, we studied the effective compressibility properties of the EoS, demonstrating that dark energy features of the fluid should be related to the negative compressibility of the contents. These features depend on the dynamics of the jerk parameter for each cosmological system, implying that the knowledge of dark energy evolution is encoded in the third-order derivatives of the scale factor. This approach to understanding the properties of cosmological models indicates that the accelerating evolution of some models, such as the lambda-cold dark matter model ($\Lambda$CDM) or the Chaplygin gas model, is due to the EoS of their nonideal content fluids rather than an associated anomalous (dark energy) nature. On the contrary, models such as $w$-cold dark matter ($w$CDM), $w_0$$w_a$-cold dark matter ($w_0$$w_a$CDM), or Dvali-Gabadadze-Porrati models, include by construction fluids with anomalous content, implying a negative compressibility and an effective dark energy behavior. Our work highlights the importance of treating all contents of the Universe as a nonideal fluid system, with a unique EoS.

We study linearized perturbations of the subextremal Kerr-Newman black hole solution of the Einstein-Maxwell equations. We show how to overcome what Chandrasekhar called the "apparent indissolubility of the coupling between the spin-1 and spin-2 fields" by using a matrix integrating factor for suitably transformed first-order systems that describe the radiative degrees of freedom. For the radial ODEs obtained after angular separation, we prove mode stability on the real axis, i.e., the absence of quasinormal modes with real frequencies, using a Whiting-type transform.

Spectral zeta functions provide a standard tool for regularizing determinants of differential operators in quantum physics. In a previous paper (J. Math. Phys. 66: 083505, 2025), we introduced a $p$-adic spectral zeta function for discrete spectra via a locally analytic interpolation function. In this paper we extend the framework to continuous spectra using the inverse Stieltjes transform. Starting from the resolvent of a bounded operator, we construct a generalized distribution, called the $p$-adic spectral distribution, and define bosonic and fermionic zeta functions and functional determinants. We establish their analytic properties, special value formulas, and Stirling expansions, and show that our previous framework is embedded into the present one in the discrete case. In this approach, the bosonic and fermionic cases exhibit an interesting symmetry. As an application, we consider the position operator in $p$-adic quantum mechanics on an arbitrary compact subset of $\mathbb{C}_{p}$.

Despite its low cosmic abundance, phosphorus is a bioessential element whose prebiotic availability and incorporation into biomolecules remain open questions. Only a few phosphorous containing molecules with P to C bonds have been detected in astronomical environments (CP, CCP, HCP). More complex species have been proposed, but their formation and destruction pathways remain poorly constrained. Gas-phase ion molecule chemistry involving P cations may contribute to organophosphorus formation, particularly in protostellar shocks and outflows, while reactions of ground state P cations with closed-shell neutrals provide benchmarks for spin-forbidden mechanisms. We investigate the reaction of P+ with C$_2$H$_2$ through a joint experimental and theoretical study aimed at revising astrochemical database rate coefficients. Absolute cross sections and branching ratios were measured as a function of collision energy and complemented by high-level electronic structure calculations and a refined capture model accounting for higher-order long-range interactions and intermediate complex formation. Channel-specific rate coefficients were derived in the range from 10 to 5000 K. The reaction produces predominantly HCCP$^+$ + H (branching ratio 99%), while CCP$^+$ + H$_2$ is a minor channel (branching ratio 1%) arising from intersystem crossing from the triplet to the singlet potential energy surfaces. The total rate coefficient at 300 K agrees well with the SIFT value, but it increases with decreasing temperature, deviating from a pure Langevin trend. The reaction should be included in astrochemical models where phosphorus is released as P+, such as during energetic processing of icy grains in shocks. It provides a pathway to linear HCCP$^+$, a potentially relevant precursor to the observed CP and CCP species through dissociative recombination

Predicting the full spin Hall conductivity tensor of a magnetic crystal is difficult because crystallographic and magnetic symmetries do not constrain all parts of the response in the same way. Here, we separate the spin Hall conductivity of altermagnets into time-reversal-even and time-reversal-odd channels and combine symmetry analysis with first-principles calculations for six representative compounds spanning distinct crystallographic classes. The even channel follows crystallographic selection rules consistent with its Berry-curvature Fermi-sea origin. The odd channel is set by magnetic symmetry and can be reshaped by antiunitary operations whose spatial parts originate from screw or glide symmetries. Momentum-resolved analysis further links the even response to spin-orbit-driven avoided crossings and the odd response to anisotropic near-Fermi-level spin-current response textures. By converting crystallographic and magnetic symmetry operations into linear constraints on the full 27-component SHC tensor, this framework provides a computational prescreening route for identifying symmetry-allowed spin Hall channels before dense first-principles transport calculations. Extending the same analysis to 62 spin-split collinear antiferromagnets yields a magnetic-point-group tensor atlas, identifying design limits such as the complete 13/14tensor partition in CuF2 and the one-parameter time-odd tensor compression in MnSe.

An analytical criterion for the disappearance of turbulent flow in a channel is developed within the Alexeev hydrodynamic equations (AHE). The analysis builds on an analytical representation of the streamwise velocity as a superposition of a parabolic component and a nonlinear turbulent component coupled to the transverse velocity field. The critical Reynolds number is obtained from the balance of viscous dissipation of kinetic energy associated with the turbulent component. The resulting critical Reynolds number is expressed analytically as \(Re_c=f(\delta,\gamma,n)\), where \(\delta\) is the Reynolds-independent AHE similarity parameter, \(\gamma\) is the weighting coefficient of the turbulent component, and \(n\) is the transverse-velocity mode number. The criterion describes the disappearance of the turbulent solution as the Reynolds number is decreased and therefore addresses the turbulent-to-laminar transition rather than the linear instability of the laminar solution. Unlike a criterion based on a single universal critical Reynolds number, the AHE criterion predicts a transition threshold that depends on the parameters characterizing the flow. For representative channel-flow parameters, the predicted critical Reynolds number is approximately \(Re_c=1000\text{--}1200\). The predicted threshold is compared with experimental observations of transition and of the persistence of laminar flow in channel flows. The analysis suggests that viscous dissipation provides a mechanism limiting the persistence of the turbulent solution below a critical Reynolds number.%