We study the flux-dependent quantum inductance of a one-dimensional (1D) semiconductor-superconductor (SM-SC) Majorana nanowire coupled to a quantum dot in an interferometric setup. Although quantum capacitance in this setup enables fast fermion parity readout, as has been demonstrated experimentally, it cannot by itself reliably confirm a protected fermion parity switch, a key signature of non-trivial topology and the existence of Majorana zero modes (MZMs). In realistic devices, disorder can produce avoided crossings or narrow double crossings between the two parity sectors that can mimic the behavior of a protected single parity switching, leading to false positives for non-trivial topological behavior. We show that quantum inductance provides a complementary probe that is directly sensitive to the phase structure of the low energy spectrum, allowing us to distinguish genuine fermion-parity crossings from avoided crossings or narrow double crossings. Using a general Lehmann framework applied to both effective models and full microscopic simulations with disorder, we demonstrate that only a true fermion-parity switch produces the characteristic inductive response of a protected crossing. In contrast, topologically trivial avoided crossings or narrow double crossings yield quantum inductance signatures that are markedly different from those of topologically nontrivial fermion parity crossings. Therefore, our results show that combined measurements of quantum capacitance and quantum inductance provide a robust and experimentally accessible means to identify true fermion-parity switches, corresponding to a nontrivial Pfaffian invariant.

We report the first lattice QCD study of the $s$-wave scattering of the $\bar{D}$-meson and the nucleon at the physical point, utilizing (2+1)-flavor configurations generated by the HAL QCD collaboration with a pion mass of $m_π\simeq 137$ MeV and a lattice spacing of $a\simeq0.084$ fm. By applying the HAL QCD method to the four-point correlation function of the $\bar{D}N$ system, we obtain a leading-order potential of the derivative expansion of the interaction kernel, which is then used to extract the $s$-wave phase shifts of low-energy $\bar{D}N$ scattering. Both the isospin $I=0$ and $I=1$ channels have a short-range repulsive core and a shallow attractive pocket in the intermediate to long-range region, though the $I=0$ channel is more attractive than the $I=1$ channel. We also observe that the $\bar{D}N$ potential exhibits more attraction than the $KN$ potential, which is its analog in the strange sector. In terms of the $s$-wave phase shifts, the $I=0$ channel shows a weak attractive behavior in the low-energy region with a positive scattering length of $0.246 \pm 0.105 (_{-0.051}^{+0.084})$ fm, whereas the $I=1$ channel shows repulsion with a negative scattering length of $-0.086 \pm 0.050 (_{-0.001}^{+0.037})$ fm. No bound states are found in both isospin channels, indicating the absence of a pentaquark state in the $s$-wave $\bar{D}N$ system.

The standard treatment of neutrino oscillations usually relies on factorization which assumes neutrino production, propagation, and detection are independent processes. As a consequence, the total probability is given by the product of production, oscillation and detection probabilities. As next-generation experiments are bringing neutrino physics to a high level of precision, the validity of this assumption must be checked. We present an S matrix treatment of the entire experimental chain, pion decay, neutrino propagation, and nucleon interaction, as a single, coherent quantum process. Our results reveal non-factorizable terms arising from spin and angular correlations between production and detection final states.In the $ΔL=0$ channel, these corrections introduce a $\sim 1\%$ systematic shift in the energy spectrum and a non-vanishing azimuthal asymmetry, important to be taken into account for precision measurements of $δ_{CP}$. For the $ΔL=2$ Majorana channel, we demonstrate that the S-matrix formalism is generating an azimuthal modulation that provides a direct way to access to the Majorana CP phases, which remain hidden in standard factorized effective mass approximations.

We prove that the grand canonical Gibbs state of an interacting two-dimensional quantum Bose gas confined by a trapping potential converges to the complex Euclidean field theory with local quartic self-interaction, when the density of the gas becomes large and the range of the interaction becomes small. We obtain convergence of the relative partition function and convergence in $L^1 \cap L^\infty$ of the renormalised reduced density matrices. The field theory is supported on distributions of negative regularity, which requires a renormalisation by divergent mass and energy counterterms. Unlike previous results in the homogeneous setting of the torus without a trapping potential, the counterterms are not given by a finite collection of scalars but by diverging counterterm functions. This leads to significant new mathematical challenges. For our proof, we also derive quantitative bounds on the Green function of Schrödinger operators and of its gradient, which might be of independent interest.

Understanding how isolated quantum many-body systems thermalize remains a central question in modern physics. We study the onset of ergodicity in a two-dimensional disordered Heisenberg Floquet model using digital quantum simulation on IBM's Nighthawk superconducting processor, reaching system sizes of up to $10\times10$ qubits. We probe ergodicity across different length scales by coarse-graining the system into spatial patches of varying sizes and introducing a measure based on the collision entropy of each patch, enabling a detailed study of when ergodic behavior emerges across scales. The high sampling rate of superconducting quantum processing units, together with an optimal sample estimator, allow us to access patches of sizes up to $3\times3$. We observe that as the Heisenberg coupling $J$ increases, the noiseless system undergoes a smooth crossover from subergodic to ergodic behavior, with smaller patches approaching their random-matrix-theory values first, thereby revealing a hierarchy across scales. In the region of parameter space where classical tensor-network simulations are reliable, small patches or small values of $J$, we find excellent agreement with the error-mitigated quantum simulation. Beyond this regime, volume-law entanglement and contraction complexity growth causes the cost of classical methods to rise sharply. Our results open new directions for the use of quantum computers in the study of quantum thermalization.

The theoretical efficiency of classical shadow tomography is predicated on a perfect Haar-random unitary ensemble, yet this mathematical ideal remains physically unattainable in near-term hardware. Here, we report the experimental discovery of a fundamental accuracy bound on integrated photonic processors: a ``Hardware Horizon'' where the reconstruction error undergoes a sharp phase transition. While the error initially obeys the predicted statistical scaling $\mathcal{O}(M^{-1/2})$, it abruptly saturates at a floor determined by the spectral distortions of the realized unitary group. By deriving a phenomenological error model, we decouple the competing mechanisms of static coherent spectral distortion and dynamic decoherence, demonstrating that this intrinsic noise floor imposes a hard bound that statistical accumulation cannot overcome. These findings establish that the utility of shadow tomography on NISQ (noisy intermediate-scale quantum) hardware is defined by a specific scaling law involving hardware parameters, necessitating active compensation strategies to bridge the gap between theoretical purity and the noisy reality of integrated photonics.

We develop a microscopic theory of thermalisation for a thermometer coupled to a many-body bath beyond standard Markovian and Fermi-golden-rule assumptions. By modeling interaction matrix elements in the non-interacting basis as independent random variables, we derive a diffusion-propagator expression for the reduced dynamics and show that relaxation is controlled by the distribution of interaction-induced level broadenings. The theory predicts a thermalisation timescale set by the inverse typical broadening and yields a non-Markovian generalization of global balance. Exact-diagonalization tests for heavy-tailed L{é}vy couplings, an all-to-all transverse-field Ising model, and the one-dimensional Imbrie model show good agreement with these predictions.

Solving the intricate quantum behavior of interacting particles is key to unlocking the mysteries of condensed matter, but capturing their complex correlations across different scales remains a monumental challenge. We introduce a neural network framework that overcomes this barrier by modeling the full quantum wavefunction of a system, including electrons, nuclei and muons, directly capturing the full quantum effects beyond the Born-Oppenheimer approximation. The neural network approximates joint wavefunction of different interacting particles with a rigorous handling of permutation invariance, enabling simultaneous treatment of nuclear quantum effects and electron-nucleus-muon couplings without explicit excited states. Validated on molecular systems, this approach offers a computationally feasible way to model full quantum phenomena in complex many-body systems, establishing a direct connection between fundamental particle properties and emergent material behavior.

Large language models (LLMs) are growing increasingly capable, prompting recent interest in LLM teams. Yet, despite increased deployment of LLM teams at scale, we lack a principled framework for addressing key questions such as when a team is helpful, how many agents to use, how structure impacts performance -- and whether a team is better than a single agent. Rather than designing and testing these possibilities through trial-and-error, we propose using distributed systems as a principled foundation for creating and evaluating LLM teams. We find that many of the fundamental advantages and challenges studied in distributed computing also arise in LLM teams, highlighting the rich practical insights that can come from the cross-talk of these two fields of study.

A game $G$ is said to have the evil twin property if there exists $G^* \in \{G,G+*\}$ such that $o^+(G) = o^-(G^*)$ and $o^+(G^*) = o^-(G)$. We study sums of wildflowers, games of form $G:H$. We find that a large closed set of sums of wildflowers has the evil twin property, extending work of McKay--Milley--Nowakowski and Lo. Our argument partially generalizes the misère genus theory of Conway to partizan games, and requires proving several general theorems on ways to extend sets with the evil twin property. Many sums of mutant flowers of the form $\{*x_1,\dots,*x_n\}:a$, where $a$ is a number, also have the evil twin property. We also prove that this set of mutant flowers is the largest such closed set with the evil twin property, and that it is $\mathsf{NP\text{-}hard}$ to compute the outcome class of a sum of mutant flowers under either play convention via a reduction from \textsc{3-Sat}. Previous work on this topic was done by McKay, Milley, and Nowakowski, and later Lo.

Persistent spin textures with collinear spin polarization are promising platforms for spintronics applications. However, their typically relativistic spin-orbit origin leads to weak spin splittings and fragile spin coherence. Here, we demonstrate a previously overlooked class of robust collinear spin polarization protected by mirror symmetry in combination with a strong exchange-driven altermagnetic order, which persists even in the presence of spin-orbit coupling. By combining first-principles calculations with a systematic classification of spin and magnetic layer groups, we identify this phenomenon-termed persistent altermagnetic spin polarization (PASP)-to occur in 158 spin layer groups and in representative materials including metallic V$_2$Te$_2$O, insulating La$_2$CuO$_4$, and semiconducting VSI$_2$. Furthermore, we theoretically demonstrate that PASP is ferroelectrically switchable in VSI$_2$. Finally, we show that this PASP switching can lead to large changes in spin-filtering conductance in a model all-altermagnetic junction. Our results open the possibility of employing PASP in all-altermagnetic magnetic memory and spin-transistor devices and establish universal principles of altermagnetism in spin-orbit-coupled monolayers.

IMU-based gesture interfaces are being increasingly adopted as efficient, accessible, and intuitive alternatives to traditional input methods, such as touchscreens and voice. However, current gesture recognition algorithms are tailored to work for specific devices (e.g., smartwatches vs. earbuds) or user populations (e.g., blind vs. sighted users), limiting their generalizability. In this paper, we design UniMotion, a generalized IMU-based gesture recognition framework that works across devices and populations with minimal training samples. To overcome the challenges and high cost of collecting large-scale labeled training data, UniMotion leverages readily available unlabeled human activity data. The UniMotion pipeline comprises two stages: (1) pre-training a motion representation model using abundant unlabeled human activity data, and (2) fine-tuning it with a small amount of labeled gesture data. For pre-training, we introduce a token-based strategy and embeddings that learn to identify and focus attention on the key motion signatures in the temporal data For fine-tuning, we design a text-guided classifier that can reliably differentiate between temporally or semantically similar gestures. We evaluate UniMotion across both hand gestures (captured through a smartwatch) and earbud gestures (captured through earbuds), using data collected from blind and sighted users. Across these diverse devices and user populations, UniMotion achieves an accuracy of 85\%, across an average of 13 gesture classes using only 10\% of labeled data for training. UniMotion significantly outperforms state-of-the-art self-supervised learning approaches and specialized gesture recognition models.

Loop corrections to primordial correlation functions are unavoidable due to the non-linear nature of gravity. Previous works have established a robust framework for computing the renormalised one-loop power spectra of scalar and tensor modes, but primarily in (near) de Sitter backgrounds. In this work, we develop a consistent renormalisation procedure applicable to inflationary backgrounds that strongly break de Sitter symmetries and generate scale-dependent features in the primordial spectra. Our analysis is performed within the Effective Field Theory (EFT) of inflationary fluctuations, allowing for arbitrary time dependence of the Wilson coefficients. We show that both ultraviolet divergences and tadpoles of the theory, despite their strong time and scale dependence, can be cancelled by a finite set of local counter-terms compatible with the EFT symmetries. Importantly, this result only relies on the existence of an initial phase of adiabatic evolution continuously related to the Bunch-Davies vacuum and holds independently of the precise time dependence of the background and of the free-field mode functions. We then study two concrete realisations, corresponding to resonant and sharp features. In both cases, all calculations are carried out exactly in the limit of small feature amplitude. We analyse perturbativity and provide the first explicit demonstration that the renormalised one-loop power spectrum generated by a localised feature along the inflationary trajectory vanishes both at large and small scales. Our scale-dependent renormalisation framework implies that models of primordial features used to fit CMB residuals are consistent with perturbativity bounds, and opens the door to systematic studies of loop corrections in more complicated scenarios relevant for scalar-induced gravitational waves and primordial black holes.

Umbral flashes are manifestations of magnetoacoustic shocks in the solar chromosphere. These phenomena are thought to influence the evolution of chromospheric umbral magnetic fields. However, the impact of these shocks on inferred chromospheric magnetic field oscillations remains unclear. We examined five different sunspots located near the solar disk center, observed with the GRIS instrument installed at the GREGOR telescope. The HAZEL2 Spectropolarimetric inversion code is used to obtain the photospheric and chromospheric line-of-sight velocities and magnetic fields in Si 10827 Å and He 10830 Å spectral lines, respectively, using various inversion strategies. In the inversions with one chromospheric component, three of the sunspots exhibit remarkably stronger magnetic fields accompanying the shocks, while the other two sunspots show striking reductions in the magnetic field. Alternatively, the Stokes profiles can be reproduced by models with two chromospheric slabs, one on top of the other, through two-component inversions. These inversions provide excellent fits even when magnetic field fluctuations are discarded by imposing a constant magnetic field during the whole temporal series. In this scenario, the observed Stokes profiles are interpreted as the result of strong velocity gradients, where the He 10830 Å line is sensitive to both sides of the shock front. Both competing models explaining the spectral profiles during the shocks, either large magnetic field fluctuations or velocity gradients, are critically discussed.

In this paper we present a simple analysis around scaling relations derived from the Schmidt conjecture for star-forming molecular clouds, at the intra-cloud scale. Using a hierarchical tree (dendrograms) above a constant threshold ($A_V$ = 7 mag), we separate individual gas structures in a column density map of the nearby Giant Molecular Cloud Orion A, constructed from Herschel far-infrared maps. These structures define regions of dense molecular gas that can actively form stars. We also estimate their current embedded population using a list of known young stars. From the combined analysis of the column density map and the young star catalog, we construct a series of plots that show the intra-cloud level behavior of three well-known scaling relations: $N_{yso}$ vs. $M_{gas}$, $Σ_{SFR}$ vs. $Σ_{gas}$ and $R_{eq}$ vs. $M_{gas}$. Our dataset, along with other sets from literature, show the validity of a linear relation for $N_{yso}$ vs. $M_{gas}$, from intra-cloud to inter-cloud scales, over three orders of magnitude. We also especulate on the possibility that the relation could be valid over an even larger scale range. Additionally, our data are consistent with the $R_{eq}$ vs. $M_{gas}$ discussed in previous studies. However, our data is not quite in agreement with previously proposed fits for the $Σ_{SFR}$ vs. $Σ_{gas}$ relation, and we discuss the implications of using the free-fall timescale as the main parameter defining the star-forming efficiency in dense gas regions.

The issue of internal fragmentation in data structures is a fundamental challenge in database design. A seminal result of Yao in this field shows that evenly splitting the leaves of a B-tree against a workload of uniformly random insertions achieves space utilization of around 69%. However, many database applications perform batched insertions, where a small run of consecutive keys is inserted at a single position. We develop a generalization of Yao's analysis to provide rigorous treatment of such batched workloads. Our approach revisits and reformulates the analytical structure underlying Yao's result in a way that enables generalization and is used to argue that even splitting works well for many workloads in our extended class. For the remaining workloads, we develop simple alternative strategies that provably maintain good space utilization.

This paper develops a general theory for first-order descent methods whose search directions are restricted to a prescribed dictionary in a reflexive Banach space. Instead of assuming that the linear span of the dictionary is dense, as in the classical Proper Generalized Decomposition framework of Falcó and Nouy or in the universality approach of Berná and Falcó, we introduce a geometric condition based on norming sets that guarantees density through a duality argument. This makes it possible to treat dictionaries arising from tensor formats, neural network units, and other nonlinear or parameterized approximation families within a unified setting. On the algorithmic side, we analyze a simple greedy update rule in which each iterate is obtained by minimizing the energy functional along one direction from the dictionary. Under mild differentiability, Lipschitz continuity, and ellipticity assumptions on the objective, we derive explicit quantitative descent bounds and sharp convergence rates. These include algebraic rates that improve those of classical steepest-descent schemes in Banach spaces, as well as arbitrarily high polynomial rates and exponential convergence in a critical regime. The results apply broadly to convex variational problems, high-dimensional approximation, and structured optimization methods that rely on restricted or compressed search directions.

We present spectral analysis results of deeper (270 ks) NuSTAR observations of the merging galaxy cluster system, ZWCL1856.8+6616, at redshift z=0.304, following a pilot study using shallower (30 ks) NuSTAR data (Tumer et al. 2024). The cluster hosts a double radio relic, pointing to a similar mass head-on collision at/near the plane of sky. We aim to find the relation between radio and X-ray shock features. Using data from both focal plane modules of NuSTAR, we study the temperature structure across the field of view and report on the X-ray detected shock strength at the relic sites. We generate nominal and cross-ARFs with nucrossarf to disentangle photon cross-contamination within regions of interest due to the moderate point spread function of NuSTAR. Here we report one of the strongest X-ray detected shocks in a galaxy cluster merger with M=3.90(+1.64,-0.85) at the Northern relic site, that is unprecedentedly larger than the radio counterpart; M=2.5+/-0.2 (Jones et al. 2021a), and we report Southern shock strength as M=2.36(+0.58,-0.46). We argue that since the Northern relic (or radio shock), is confined in a very small region in the sky, particle acceleration is more efficient and is likely to grow in the post-shock regions. In addition, we search for inverse Compton (IC) emission at the radio relic sites; however, an IC component was not detected.

We propose a unified iterative framework for the solution of frictionless mechanical contact problems, which relies exclusively on the solution of standard stiffness systems. The framework is built upon a two-step fixed-point algorithm: first, the displacement is computed for given contact forces; second, the contact forces are updated based on the displacement solution. The choice of the dual update scheme depends on the numerical contact formulation under consideration. Specifically, the Uzawa iterative scheme is obtained for the Lagrange multiplier formulation, while a penalty-based operator-splitting strategy is proposed for the penalty contact formulation. The main interest of such displacement-force splitting strategy is to involve only standard rigidity matrices in the solving step: no saddle-point or penalized ill-conditionned coefficient matrices have to be handled. Moreover only the right-hand side of the system is updated throughout the iterations, which enables matrix factorization reuse or efficient iterative solvers initialization. The main limitation of such splitting iterative strategies lies in the inherently slow convergence of the underlying fixed-point iterations. Moreover, convergence is guaranteed only within a narrow range of numerical parameter values (i.e., the augmentation or penalty parameter). This work addresses both issues by applying the Crossed-Secant fixed-point acceleration strategy, which substantially improves the convergence rate and renders the iterative schemes effectively parameter-unconstrained. To the best of our knowledge, this contribution provides the first computational demonstration of efficient, parameter-unbounded convergence for such contact formulations. The substantial practical benefits of the proposed approach are illustrated through representative three-dimensional academic and industrial frictionless contact problems.

District heating networks (DHNs) have significant potential to decarbonize residential heating and accelerate the energy transition. However, designing carbon-neutral DHNs requires balancing several objectives, including economic costs, social acceptance, long-term uncertainties, and grid-integration challenges from electrification. By combining modeling-to-generate-alternatives with power flow simulation techniques, we develop a decision-support method for designing carbon-neutral DHNs that are cost-effective, socially acceptable, robust to future risks, and impose minimal impacts on the electricity grid. Applying our method to a Dutch case, we find substantial diversity in how carbon-neutral DHNs can be designed. The flexibility in technology choice, sizing, and location enables accommodating different real-world needs and achieving high electrification levels without increasing grid loading. For instance, intelligently located heat pumps and thermal storage can limit grid stress even when renewable baseload heat sources and green-fuel boilers are scarce. Using our method, planners can explore diverse carbon-neutral DHN designs and identify the design that best balances stakeholders' preferences.

We investigate the hole-doped Kitaev-Heisenberg ($t$-$J$-$K$) model on a two-leg ladder geometry using the density-matrix renormalization group (DMRG). We first consider the behavior of the antiferromagnetic Kitaev (AFK) spin-liquid phase as a function of hopping strength $t$ and doping level. This reveals intriguing pairing tendencies only for $\frac{t}{K} \lesssim 0.65$, consistent with prior results on three-leg ladders, and firmly supports the emerging picture that the physics of doped Kitaev spin liquids strongly depends on the kinetic energy of the doped holes. Analysis of one- and two-hole doping uncovers close links between the spatial profiles of the plaquette operator and the charge density. We construct a doping-dependent phase diagram for antiferromagnetic Heisenberg interactions and intermediate hopping $t=1$. Upon doping, the rung-singlet region develops dominant superconducting correlations. Charge-density-wave correlations dominate at weak doping near the transition to the stripy phase. Spin-density wave-like behavior is found in the AFK and ferromagnetic Kitaev limits, and in the stripy phase.

Understanding how superconductivity emerges and collapses in correlated electron systems remains a central challenge in condensed matter physics. As a recently discovered member of the high temperature superconductor family, bilayer nickelates provide a new opportunity for examining this problem. Their pronounced sensitivity to oxygen stoichiometry, while posing challenges for stabilizing superconductivity, simultaneously offers an effective control parameter for tuning electronic phases. Here we report a superconducting half-dome in compressively strained bilayer nickelate thin films as a function of continuous tuning of oxygen stoichiometry. Starting from an optimally superconducting state, increasing oxygen stoichiometry gradually suppresses superconductivity toward a metallic phase, whereas decreasing oxygen stoichiometry drives a granular superconductor-to-insulator transition while leaving the superconducting onset intact. This half-dome structure can be understood to arise from the contrasting roles played by interstitial oxygen versus oxygen vacancies - namely the dominance of doping versus scattering. Notably, the half-dome emerges consistently across samples with different rare-earth combinations, with or without alkaline-earth doping, revealing a general feature of the bilayer nickelate phase diagram.

Applications like Enterprise Resource Planning (ERP) systems have become an indispensable part of the corporate digital infrastructure. These systems store sensitive data about customers, suppliers, and employees, and thus companies have to process these data in accordance with applicable regulations like the GDPR (the EU General Data Protection Regulation). This can be challenging due to a variety of reasons. For example, prior research has shown that developers sometimes lack knowledge about privacy. In this work, we focus on privacy in ERP systems in the context of an international consultancy firm. We investigate the privacy awareness regarding privacy-by-design and data minimization of two important populations: developers of ERP systems and managers and consultants responsible for services related to ERP systems. Applying thematic analysis, we elicit privacy behavioral models of these two populations using Fogg's Behavioral Model (FBM) framework. Our findings provide a means to stimulate more adequate privacy-related behaviors for developers and consultants.

One of the major open puzzles in the Standard Model of particle physics is the strong CP problem: although Quantum Chromodynamics allows a CP-violating topological $θ$-term, experiments constrain its value to be extremely small. The Peccei--Quinn mechanism resolves this problem by promoting the $θ$-angle to a dynamical field-introducing the axion -- whose dynamics relax the effective angle $θ_\text{eff}$ to a CP-conserving minimum. Here, we investigate the resulting axion physics in a Hamiltonian lattice gauge theory (LGT) by coupling a quantized axion field to the massive Schwinger model with a topological $θ$-term. Using infinite matrix product state techniques, we compute the ground-state properties of the resulting theory and demonstrate that the axion dynamically relaxes $θ_\text{eff}$ to the minimum of the vacuum energy. Consequently, the ground-state energy becomes independent of $θ$, demonstrating the axion-mediated solution to the strong CP problem within a fully dynamical LGT. We further analyze CP restoration and extract the axion mass from the topological susceptibility and excitation spectrum. Our results provide a nonperturbative demonstration of axion dynamics in a quantum LGT amenable to investigation on modern quantum hardware.

We examine neutrino evolution in astrophysical environments where the neutrino flux is very large, including core-collapse supernovae and neutron star mergers. In these environments, the neutrino-neutrino and neutrino-antineutrino interactions are crucial. We include non-forward scattering of neutrinos and anti-neutrinos in a semi-classical treatment. Because of the large scale of neutrino momenta (2-10 MeV), the quantum evolution problem can be treated as a sum over incoherent paths in the and flavor of each neutrino. The phases between different neutrinos are essentially random because of the large kinetic terms. Momentum is conserved at each vertex, and important flavor symmetries are retained. Dynamics in the many-body neutrino system enable rapid equilibration in the energy and angular distributions of all flavors, and an equilibration of products of neutrino and anti-neutrino densities for each flavor at either large or zero background matter density. We also describe the evolution at moderate densities where the mass eigenstates differ for neutrinos and antineutrinos, and with time-varying background matter densities. The evolution maintains relevant symmetries and reduces to standard MSW oscillations in the appropriate limits. The rapid equilibration in energy and flavor can significantly impact energy deposition and nucleosynthesis in high-flux astrophysical environments, and potentially flavor energy relations in terrestrial supernovae neutrino observations.

We consider a family $\mathscr{F}$ of meromorphic functions defined in a domain $D$, a holomorphic function $ψ$ and a homogeneous differential polynomial $ P[f] $ of degree $d$ with weight $w$. In this paper, we prove the normality of $\mathscr{F}$ under certain conditions such as $f\neq 0$, $P[f]\neq 0$ and all the zeros of the function $P[f] - ψ^d$ have multipicity at least $\displaystyle{\frac{w+1}{w-1}}$, for each $f \in \mathscr{F}$.

We present a shifted-geodesic framework for computing gravitational-wave fluxes from spinning test bodies moving on bound orbits of Kerr black holes. The method provides a simple and efficient means of evaluating energy and angular momentum fluxes incorporating the leading effect of the smaller body's spin. Because post-adiabatic corrections, including secondary spin contributions, are subdominant to the leading adiabatic terms, this approximation is well justified. In particular, we find that oscillatory spin terms typically contribute very little to fluxes, but their contribution to the description of orbits is computationally expensive, making such terms a natural target for approximation. In our framework, orbital frequencies and integrals of the motion are perturbed to include spin effects, while the trajectory retains the global structure of geodesic motion. This simplifies the computation of gravitational radiation. The shifted-geodesic approximation is most reliable for orbits with lower eccentricity, lower inclination, and larger semi-latus recta. The approximation becomes less reliable as we approach the separatrix between stable and unstable orbits; fortunately, many inspirals spend less time in this region of parameter space. A diagnostic inspiral evolution shows very small dephasing due to use of the shifted-geodesic approximation ($\approx10^{-2}$ radians over 1 year), confirming that spin-induced flux corrections can be accurately included using this simple modification to a geodesic trajectory. This approximation provides a rapid and convenient way to compute spinning-body orbits, but is not intended to replace more accurate treatments. We propose it as a pragmatic alternative when speed and simplicity are prioritized, enabling efficient EMRI/IMRI flux calculations and supporting parameter-space studies for LISA. (Abridged)

This paper addresses the design of an event-triggered, data-based, and performance-oriented adaption method for model predictive control (MPC). The performance of such a strategy strongly depends on the accuracy of the prediction model, which may require online adaption to prevent performance degradation under changing operating conditions. Unlike existing methods that continuously update model and control parameters from data, potentially leading to catastrophic forgetting and unnecessary control modifications, we propose a novel approach based on statistical monitoring of closed-loop performance indicators. This framework enables the detection of performance degradation, and, when required, controller adaption is performed via reinforcement learning and identification techniques. The proposed strategy is validated on a high-fidelity simulation of a district heating system benchmark.

Are Gaussian measurements enough to distinguish between Gaussian states? Here, we tackle this question by focusing on the max-relative entropy as an operational distinguishability metric. Given two general multimode Gaussian states, we derive a condition, based on their covariance matrices, that completely determines whether or not there exists an optimal Gaussian measurement achieving the max-relative entropy. When the condition is satisfied, we find this optimal measurement explicitly. When the condition is not met, there is a strict gap between the distinguishability achievable by Gaussian measurements and the unconstrained max-relative entropy in which all measurements are allowed. We illustrate our results in the single-mode setting, and show examples of states for which this gap can be made arbitrarily large, revealing novel instances of Gaussian data hiding.

Exotic quantum phenomena often emerge near an electronic delocalization transition (EDT) from an antiferromagnetic insulating phase to a strongly correlated metallic state under pressure. We report the pressure-induced structural and magnetic evolution of the antiferromagnetic insulator CaMn$_2$Sb$_2$. Single-crystal X-ray diffraction reveals a first-order phase transition near 5.4 GPa from a trigonal P-3m1 structure to a monoclinic P2$_1$/m phase, accompanied by a ~7% volume collapse. Residual electron density analysis at intermediate pressures reveals charge localization along Mn-Sb chains, signaling electronic instability preceding the structural transition. Bonding analysis indicates anisotropic Mn-Sb orbital reconfiguration under pressure, driving a distorted square-pyramidal geometry. Neutron scattering confirms the transition and identifies a pressure-induced incommensurate magnetic order, distinct from the ambient antiferromagnetic state. In the monoclinic phase, zigzag Mn chains exhibit antiferromagnetic coupling along the ac-plane, enabled by enhanced orbital overlap. These results establish CaMn$_2$Sb$_2$ as a model system for studying the coupling of structural distortion, charge redistribution, and magnetic order in layered Mn pnictides under pressure.