Polaritons are a superposition of light and matter, that combine Strong Interferences (of light) with Weak Interactions (of excitons), making them WISI (Weakly-Interacting, Strongly-Interfering) particles. Their condensation is the main highlight of a field which occupies a unique position at the intersection of quantum optics, condensed matter physics and nonlinear dynamics of driven, dissipative systems. This chapter surveys selected theoretical concepts of polariton condensates' formation, coherence and dynamics, with an emphasis on their distinctions from their atomic counterparts and on points of ongoing controversy. We argue that linear and non-interacting effects are undervalued in polariton physics, and that a significant part of the phenomenology -- including bosonic correlations and coherence buildup -- can often be understood without invoking strong interactions or genuine quantum effects.

The classical Einstein-Langevin theory of Brownian motion assumes a memoryless thermal bath, establishing a universal fractal dimension of $d_v = 3/2$ for the velocity fluctuations of a particle. In this Letter, we demonstrate experimentally and theoretically that fluid-inertial memory effects fundamentally redefine the fractal scaling of these fluctuations. In analyzing highly resolved measurements of Brownian microspheres in liquids, we show that the non-Markovian hydrodynamic thermal noise establishes a distinct velocity fractal dimension of $d_v = 7/4$. Coupled with theoretical analysis of non-equilibrium short-time dynamics and the initial scaling of the velocity autocorrelation function, this result establishes the non-equilibrium universality class of Brownian motion in fluid media possessing a finite non-vanishing density.

Entanglement and interference are among the most fundamental properties of quantum mechanics. In this work, we investigate the role and power of interference in the context of detecting entanglement. We do so from a computational complexity lens by proving that unentanglement gives no additional power to stoquastic Merlin-Arthur verification. For every polynomial number of provers $k=k(n)$, \[ \text{StoqMa}(k)=\text{StoqMa} . \] Conceptually, the proof separates the role of entanglement from the role of interference: once destructive interference is ruled out by stoquasticity, the product-state constraint can be absorbed into a polynomially larger one-witness stoquastic verification. The main analytic ingredient is a positive, value-based de Finetti theorem for separately symmetric extensions. If $M$ is an entrywise nonnegative positive semidefinite contraction on $A_1\otimes\cdots\otimes A_k$, then the nonnegative product value of $M$ is approximated to additive error $ε$ by the largest eigenvalue of \[ Π_R^{<k} (M_{A_{1,1}\cdots A_{k-1,1}A_k}\otimes I) Π_R^{<k}, \qquad R=O\!\left(\frac{k^2\sum_i\log\dim A_i}{ε^3}\right), \] where $Π_R^{<k}$ is the operator on $A_1^{\otimes R} \otimes \cdots \otimes A_{k-1}^{\otimes R} \otimes A_k$ projecting to the subspace $\mathrm{Sym}^R(A_1) \otimes \cdots \otimes \mathrm{Sym}^{R}(A_{k-1}) \otimes A_k$. The spectral relaxation is then realized as an actual one-witness stoquastic verifier. After replacing the uniform permutation averages in the symmetric projectors by inverse-polynomially close dyadic inverse-invariant averages. Consequently, \[ \text{StoqMa}(k)=\text{StoqMa}\subseteq\text{AM}\cap\text{PP}\subseteq\text{PSPACE} . \] The positive de Finetti theorem is isolated as a standalone technique and may be useful in other nonnegative tensor-optimization and stoquastic-verification settings.

Softmax and related normalized response functions are widely used in choice theory, machine learning, and cognitive science. In non-Boolean event structures with overlapping contexts, however, local normalization does not automatically yield a global probability weight. We show that imposing single-valuedness on shared atoms -- equivalently, no-disturbance or consistent connectedness -- collapses generalized softmax rules to coordinate parametrizations of the strictly positive part of the admissible-weight polytope. Any strictly positive admissible weight can be represented in this way, while boundary weights arise as limits. Exotic weights that exceed classical or quantum bounds are therefore properties of the event structure and the chosen weight, not of the normalizing link. The resulting hierarchy separates local normalization, cross-context gluing, Cauchy--Gleason linearity, and physical or cognitive realizability.

Owing to the Chapman-Kolmogorov equation for Markovian dynamics,any equilibrium trajectory of a Brownian particle in a solvent fluid can be viewed as the superposition of an uncountable number of non-equilibrium states. This property permits the unraveling of fine details of fluid-particle interactions at microscales defined by its non-equilibrium properties from the analysis of a single Brownian trajectory and to connect them to the hydrodynamics of the solvent fluid, simply considering the lower-order (second) moments of particle position in trapped conditions. In this way, the acceleration due to thermal-hydrodynamic fluctuational forces is isolated from the other factors and the short-time displacement statistics is completely determined by the correlation properties of the fluctuational thermal-hydrodynamic force. This approach not only confirms the $t^{5/2}$-law obtained by Boynewicz et al. (2026), related to fluid inertial effects, but indicates that this scaling may be superseded by a $t^4$-scaling at very short times once the correlated nature of the stochastic forcings is taken into account. The latter result is related to the regularity properties of particle velocity realizations.

We introduce a Stern--Gerlach (SG) spin-kinetic control parameter for magnetic reconnection. The fully projected branch parameter, $Ξ_0=<Z>/r_L$ compares the SG cross-sheet displacement accumulated during a diffusion-region transit with the relativistic Larmor radius. For an ensemble or partially participating population the relevant effective parameter is $Ξ_{\rm Eff}=P_{eff}Ξ_0$, where $P_{eff}$ represents the surviving branch weight or effective spin/moment projection. Evaluating $Ξ_{\rm Eff}$ across representative space and astrophysical environments reveals a robust hierarchy: SG transport is negligible in the magnetotail, solar corona, active galactic nuclei (AGN)/blazar jets, and pulsar-wind nebulae, but becomes transitional to strong in magnetar current sheets and extreme near magnetar surfaces. We further show, using electron--positron particle-in-cell simulations, that the SG force sorts particles by magnetic-moment projection into opposite sides of a Harris current sheet without measurably changing the global reconnection rate in the tested regime. This identifies magnetars as the clearest natural target for strong-field spin-kinetic reconnection ($Ξ_{\rm eff}\gg 1$) near the surface; transitional in the outer magnetosphere), while SG transport is safely negligible ($Ξ_{\rm eff}\ll 1$) in all heliophysical and jet environments considered, and provides a falsifiable framework for assessing where SG physics is relevant.

Altermagnets (AMs) have recently emerged as a distinct magnetic class bridging central features of ferromagnets (FMs) and antiferromagnets (AFMs), offering new opportunities for spin-based electronics. While they possess zero net magnetization like collinear AFMs, they simultaneously exhibit momentum-dependent spin splitting long thought exclusive to FMs. Despite intense theoretical interest, experimentally accessible materials hosting both altermagnetism and nontrivial band topology remain scarce. EuAgAs, crystallizing in space group $P6_3/mmc$, was previously identified via density functional theory (DFT) as a bulk altermagnetic Dirac semimetal. Contrary to these predictions, our neutron diffraction experiments reveal that the bulk ground state adopts a $\mathbf{q} = (0,0,\tfrac{1}{2})$ AFM structure with an in-plane $\uparrow\uparrow\downarrow\downarrow$ spin sequence. Systematic DFT calculations, however, uncover a remarkable near-degeneracy among competing magnetic orders: the FM and AM configurations lie only $0.11$ and $0.40~\text{meV/f.u.}$ above the AFM ground state, respectively. We further show that while a simple Heisenberg model favors a spin-spiral ground state, the inclusion of non-Heisenberg biquadratic coupling stabilizes the observed commensurate AFM phase. This near-degeneracy renders the magnetic state highly tunable, with DFT predicting a transition to the altermagnetic phase under hydrostatic pressure at approximately $14 \text{ GPa}$, establishing EuAgAs as a controllable platform for accessing topological altermagnetism.

We theoretically investigate acoustic spin resonance in a spatially homogeneous spinor polariton condensate. A longitudinal acoustic wave generates a time-periodic strain-induced effective magnetic field acting on the condensate pseudospin. When this field is transverse to the static in-plane linear-polarization splitting, it resonantly drives polarization oscillations. We show that spin-dependent interactions shift the resonance and produce nonlinear line shapes, while gain, reservoir dynamics, and spin relaxation make the response dissipative and history-dependent, producing amplitude hysteresis. In the presence of lifetime anisotropy, the condensate can develop a bifurcated stationary state with finite circular polarization, and a resonant acoustic drive can switch between the corresponding out-of-plane branches. A Zeeman splitting provides an additional conservative knob for tuning the resonance frequency. Our results identify coherent acoustic driving as a route to resonant, nonlinear, and switchable control of polariton pseudospin dynamics.

This is the first part of a series of papers proving the nonlinear stability of a one-parameter family of continuously self-similar $C^{1,α}$ naked singularity solutions, with $0<α\ll1$, to the spherically symmetric Einstein-scalar field equations. The stability holds for initial perturbations lying in a small open neighborhood of the data generating these naked singularity solutions, measured in a localized Hölder topology. These continuously self-similar naked singularity spacetimes were previously constructed by Christodoulou [D. Christodoulou, Examples of naked singularity formation in the gravitational collapse of a scalar field, Ann. of Math. 140 (1994), 607--653], who also proved their instability to black hole formation under sufficiently rough perturbations [D. Christodoulou, The instability of naked singularities in the gravitational collapse of a scalar field, Ann. of Math. 149 (1999), 183--217], thereby verifying weak cosmic censorship within a rough functional framework. In complete contrast, in this paper, we obtain the first nonlinear stability of these naked singularity spacetimes under general perturbations of the same regularity as the background. We rely on the linearized stability result established in the companion paper [J. Singh and W. Zheng, Nonlinear stability of continuously self-similar naked singularities for the Einstein--scalar field equations II: linearized stability]. Our result underscores the decisive role of the functional framework in formulating the Weak Cosmic Censorship conjecture.

Inclusive deep inelastic scattering factorization combines two features that are often treated separately: an asymptotic reconstruction of the current-current matrix element from hard and long-distance data, and an invariance under finite changes of collinear scheme or operator basis. We formulate these two features as a single proof object. The construction packages the leading-region analysis, overlap subtraction, Wilson-line reduction, finite scheme kernels and physical measurement into a typed, filtered structure on a compactified space of asymptotic regimes. Its central carrier is the balanced hard-collinear core over the interface algebra of finite scheme transformations. The hard QCD input is the construction of a scheme-balanced comparison map from this core to the collinear collar of the regime algebra. Once this comparison is an equivalence through the chosen power accuracy and the measurement descends to convolution, the standard DIS convolution formula follows formally and independently of the chosen scheme presentation. We separate this formal implication from the analytic QCD obligations needed to construct the collar equivalence, describe Collins-style subtraction as descent and Möbius inversion on the region poset, and give a finite check relating $\overline{\mathrm{MS}}$ and DIS presentations. The framework is intended as proof infrastructure rather than as a new calculation of DIS coefficient functions. It supplies diagnostics for missing regions, nonclosed operator sectors, nonbalanced measurements and failed collar equivalences, and it gives a typed interface for future proof-assistant and machine-learning implementations of factorization workflows.

Magnetic order is a fundamental property of materials, governing collective behavior and enabling a broad range of functionalities. Yet magnetic structure remains difficult to determine: experiments are costly and specialized, while first-principles methods often struggle with the noncollinear and incommensurate orders found in real materials. Here we introduce magnetic structure network (MSN), an E(3) equivariant graph neural network that predicts both collinear and non-collinear magnetic structures directly from atomic crystal structures, trained directly on experimentally determined structures from MAGNDATA. By proposing the primitive modulated structure representation (PMSR), we are able to encode commensurate and incommensurate structures in a unified way without symmetry assumptions. The model achieves strong performance across all modulation components and reconstructs experimental magnetic structures with high fidelity. Our approach provides a scalable framework for rapid magnetic structure prediction and opens a route to data-driven discovery of magnetic materials.

The first observation of a new meson state decaying into $B_c^+$ and a photon is presented using a dataset of $pp$ collisions at a centre-of-mass energy $\sqrt{s} = 13$ TeV collected by the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb$^{-1}$. The $B_c^+$ mesons are reconstructed from a three-muon final state from $B_c^+\to J/ψ(μ^+μ^-)μ^+ν_μX$ decays, along with photons reconstructed via conversions to electron-positron pairs in the detector material. The new state is observed with a significance that exceeds 8 standard deviations. The mass difference between the new meson state and the ground-state $B_c^+$ meson is measured to be $64.5 \pm 1.4\text{(stat.)}^{+1.0}_{-1.4}\text{(syst.)}$ MeV. This corresponds to a mass for the observed state of $6339.0 \pm 1.4\text{(stat.)}^{+1.0}_{-1.4}\text{(syst.)}\pm 0.3(m_{B_c^+})$ MeV, where the last uncertainty is due to the precision of the best knowledge of the $B_c^+$ meson mass. The low mass difference value matches the theory expectations for the lowest vector state of the $\bar{b}c$ quarkonium system, the $B_c^{*+}$ meson.

Gravitational models with non-minimal couplings involving functions of the matter Lagrangian and curvature have become popular in recent decades. By coupling the matter Lagrangian directly to the gravitational Lagrangian, one hopes to construct theories that can explain dark energy or dark matter without introducing additional sources. When this matter Lagrangian describes a perfect fluid, some technicalities are involved in its variational formulation. We present a careful derivation of the gravitational field equations together with the complete set of fluid equations. The fluid's equations allow us to define thermodynamic quantities such as temperature, chemical potential and number density and thus allow us to understand the effects of the non-minimal couplings on these quantities. We demonstrate the non-equivalence of the Lagrangian formulations of Schutz and Brown for these types of models and provide a detailed interpretation of our results.

Motivated by recent observations of integer and fractional Chern insulators in rhombohedral graphene stacks aligned with hexagonal boron nitride (hBN), we propose and study a model in which the moiré potential is defined by the pattern of layer-shear strain fields produced by lattice relaxation in these heterostructures. Although these strain fields decrease exponentially with the number of layers, their imprints on electrons residing away from the contact layer are non-negligible. In the absence of a displacement field, lattice relaxation effects amplify the electronic differences among the two different stackings with hBN. These differences, although attenuated at the single-electron level, survive in the so-called moiré-distant regime and are further enhanced with the inclusion of electron interactions. We find that lattice relaxation plays a crucial role in flattening and isolating a valley-polarized Hartree-Fock electron band with $|C|=1$ Chern number. Our results challenge the conventional wisdom on moiré effects in these heterostructures by illustrating the intertwined effects of long-range Coulomb interactions and lattice relaxation, and opens the door to explore different regimes of twist angles and displacement fields for the search for topological states.

Atomic-scale modeling has advanced rapidly through integration of machine learning, yet a key bottleneck remains. Even with an accurate potential energy surface and a clear target material, we still lack a practical atomistic dynamics framework that can simulate how materials form under realistic synthesis and processing conditions. Many processing transformations are governed by rare events in non-idealized evolving environments, while direct molecular dynamics is limited by femtosecond timesteps and short accessible trajectories. Existing acceleration methods often require prior mechanistic knowledge, including reaction coordinates, collective variables, event tables, or pathway guesses, which is rarely available in real experiments. Here we present an E(3)-equivariant deep reinforcement learning framework that enables goal-directed pathway discovery without hand-crafted reaction coordinates. The framework introduces a complementary operating mode for atomistic simulation in which realistic, non-idealized environments can be addressed directly while retaining kinetic plausibility through barrier-aware rewards. As a challenging benchmark, we target silicon dry oxidation, where rare-event pathways in amorphous SiO2 are effectively inaccessible to conventional atomistic methods. We treat an O2 molecule as an agent that performs continuous rigid-body translations and rotations in a Si/a-SiO2 environment. The agent is trained with an episode-level objective that rewards verified O2 dissociation while preferring low effective activation barriers. We demonstrate that the learned policy discovers kinetically favorable O2 diffusion and dissociation pathways in a disordered Si/a-SiO2 environment, progressively improving success rate while reducing effective activation barriers over training. We also discuss how the approach can be generalized to other processing and synthesis problems.

We study how the stationary dynamics of an oscillator chain is modified when coupled to a bath of run-and-tumble particles. First, assuming time-scale separation, we derive the induced Langevin chain dynamics with explicit expressions for the streaming term, friction coefficient, and noise amplitude. At high persistence of the run-and-tumble particle bath, the linear friction turns negative, creating an instability. Second, we find that this anti-damping is arrested at long times due to nonlinear effects, reminiscent of a Rayleigh oscillator. We conclude that a passive harmonic chain can be transformed by its coupling to active matter into a self-sustained fluctuating medium with many-body Rayleigh-like dynamics. That transfer of activity results in pulsations of the displacements, spatial oscillations, and the emergence of persistence in velocities along the chain.

We present fully kinetic two-dimensional, three-velocity-component (2D3V) PIConGPU simulations of a three-beam direct-drive interaction with a 15 $μ$m solid-density cryogenic hydrogen cylinder, establishing a predictive numerical baseline for the operational DRACO ($τ=30$ fs) and upcoming PENELOPE ($τ=150$ fs) laser facilities at HZDR. The simulations resolve charge-separation fields on the order of 3 TV/m and reveal a robust kinematic bifurcation of the accelerated population into a fast (1-5 MeV) ion beam and a slower bulk (1-100 keV) flow. We demonstrate analytically and numerically that the charge-separation front ($v_{hb}$) is an intrinsically non-quasi-neutral electrostatic double layer that lies outside the closure assumptions of radiation-hydrodynamic models. A simple $2v_{hb}$ reflection scaling derived directly from the front trajectory tracks the centroid of the constant-energy fast-ion band under the impulsive 30 fs driver and the time-varying upper edge of the swept fast-ion band under the sustained 150 fs driver, across both intensities ($a_{0}=12.7$ and 22.0), establishing this non-thermal mechanism as the dominant acceleration pathway. We then scan an external axial magnetic field from 0 T to 10 kT. Laboratory-achievable 20 T fields leave all macroscopic observables unchanged; fields at the kT scale progressively magnetise the MeV hot-electron population, quench the laser-driven charge-separation mechanism, suppress the fast-ion band, and more than double the net-inward compression time of the short-pulse driver-while extending the outer target envelope. A geometric equivalence argument maps these kT-scale results onto larger-diameter cryogenic hydrogen jets.

The Boolean Satisfiability (SAT) problem is a canonical NP-complete problem and a natural candidate for quantum acceleration via search-based algorithms. In Grover-based quantum SAT solvers, the dominant computational cost stems from the construction of a reversible oracle that evaluates the Boolean formula, rendering the choice of SAT encoding crucial for overall quantum resource efficiency. Although SAT instances are conventionally expressed in Conjunctive Normal Form (CNF), such encodings typically translate into quantum circuits with significant qubit overhead and high non-Clifford gate complexity. In this work, we investigate an Exclusive-Sum-of-Products (ESOP)-based CNF (e-CNF) representation tailored for quantum SAT solving and analyze its impact on oracle construction. We derive tighter upper bounds on qubit requirements and Clifford+$T$ gate counts for Grover-based SAT solvers when e-CNF encodings are employed in place of standard CNF. In addition, we propose a scalable transformation from Boolean formulas to e-CNF and present a systematic procedure for interpreting e-CNF representations as reversible quantum circuits suitable for oracle implementation. Experimental evaluation on representative SAT benchmarks demonstrates that the proposed e-CNF-based approach yields substantial and consistent reductions in quantum resources, including qubit count, T-gate complexity, and circuit depth, when compared to CNF-based oracle constructions. These results establish e-CNF as an effective quantum-aware SAT encoding that significantly improves the practicality of oracle-based quantum SAT solving.

Inflaton decay inevitably emits gravitons through bremsstrahlung during reheating. We show that the soft part of this emission amplitude, fixed by Weinberg's soft-graviton theorem, becomes an irreducible stochastic gravitational-wave (GW) background after accounting for cosmological evolution. The theorem fixes the infrared branch of the spectrum, $Ω_{\rm GW}\propto f$, independently of the microscopic operator responsible for inflaton decay, while the normalization is controlled by the hard inflaton decay rate and by a phase-space factor. We carry this out for inflaton $n$-body decays, including the phase-space integrals, finding that the maximum of the spectrum scales as $2/n$ relative to the $n=2$ case. The signal can reach $Ω_{\rm GW}h^2\sim \mathcal O(10^{-17})$ at frequencies above the GHz scale. This predicts a stochastic graviton floor from perturbative reheating: a larger signal would require either other processes beyond perturbative bremsstrahlung or inflationary scenarios beyond conventional single-field slow roll.

Stellar streams from disrupted globular clusters are excellent probes of dark matter (DM) subhalos. Observed Milky Way streams display a remarkable diversity of features: spurs, gaps, kinks, cocoons, and density variations, many attributed to subhalo encounters. But how much of this diversity arises from the host itself? We simulate $\sim$15,000 globular cluster streams across four Milky Way-mass halos from the FIRE-2 cosmological simulations, evolved in basis function expansion potentials capturing the evolving disk, halo, and large-scale structure while excluding small-scale perturbers such as DM subhalos and giant molecular clouds. We find that roughly three quarters of streams develop complex features from the host potential, such as spurs, kinks, and cocoon-like envelopes. Even the smoothest streams exhibit 10--25\% width variation along their track and host overdensities and gaps at scales of ${\sim}2^\circ$, squarely in the $1^\circ$--$5^\circ$ range predicted for subhalo-induced gaps. Pericentric distance is the primary predictor of stream morphology, with ${\sim}15$ kpc separating smooth from disturbed streams and circular orbits beyond $\sim$20 kpc producing the smoothest streams. Only $\sim$70 out of $\sim$15,000 streams are free of detectable wiggles in the track at any scale. Analogs to observed features, such as the GD-1 spur and the ATLAS--Aliqa Uma kink, emerge even without the presence of subhalos. As next-generation surveys (LSST, Euclid, and Roman) resolve stream structure across hundreds of streams, the baseline established here, streams evolved without small-scale perturbers, becomes essential for extracting DM substructure constraints.

Quasinormal modes (QNMs) of black holes can exhibit avoided crossings (ACs), in which specific QNM frequencies approach each other while their amplitudes are enhanced and acquire nearly opposite phases, leading to characteristic interference. Resolving such closely spaced modes through black hole spectroscopy is observationally challenging. In this paper, we investigate the detectability of nearly degenerate QNMs in the presence of an AC within a Bayesian framework using three waveform models. We examine how the inference of the complex frequencies and amplitudes depends on the separation between the two QNM frequencies and on the choice of template waveform. We find that resolving the individual QNM frequencies is difficult even under optimistic conditions. On the other hand, collective waveform signatures associated with ACs may still be identified through complementary waveform descriptions, provided that the AC-related modes dominate the observed ringdown signal and contamination from more slowly damped modes is negligible or can be removed.

We present an efficient, nearly optimal quantum algorithm for solving linear matrix differential equations, with applications to the simulation of open quantum systems and beyond. For unitary or dissipative dynamics, the algorithm computes an entry of the solution matrix with query complexity $\widetilde{\mathcal{O}}(ν\mathcal{L} t/ε)$, where the constant $ν$ depends on the problem parameters, $\mathcal{L}$ involves a time integral of upper bounds on the norms of evolution operators, and $ε$ is the error. In particular, $ν\mathcal{L}$ is linear in $t$ for unitary dynamics and can be a constant for dissipative dynamics. Our result contrasts prior quantum approaches for differential equations that typically require exponential time for this problem due to the encoding in a quantum state, which can lead to exponentially small amplitudes. We demonstrate the utility of the algorithm through an end-to-end application, namely the simulation of dissipative dynamics for non-interacting fermions, which can be extended to other quantum and classical systems. We compare with classical algorithms and give evidence of polynomial quantum speedups for systems in a lattice, which become more pronounced for systems with long-range interactions and can be shown to be exponential in general. We also provide a lower bound of $Ω(ν\mathcal{L} t/ε)$ for unitary or dissipative dynamics that proves our algorithm is optimal up to logarithmic factors.

We perform hydrodynamical simulations with radially varying resolution to study the effects of stellar feedback on the radial inflow of gas from the Central Molecular Zone (CMZ, $R\sim200$ pc) to the Circumnuclear Disk (CND, $R\sim5$ pc) of the Milky Way. The simulations include a realistic Milky Way barred gravitational potential, a cooling function coupled to a non-equilibrium chemical network, gas self-gravity, star formation, supernova feedback, and radiation feedback from massive stars computed via on-the-fly radiative transfer. Our main findings are as follows: 1) Stellar feedback drives a radial inflow that decreases monotonically with decreasing Galactocentric radius. The time-averaged inflow rate in our fiducial SNRad simulation, which includes both supernova and radiation feedback, declines from $\langle \dot{M} \rangle\sim5\times10^{-3}$ Msun/yr at $R\sim100$ pc, to $\langle\dot{M}\rangle\sim10^{-4}$ Msun/yr at $R\sim10$ pc, to $\langle\dot{M}\rangle\sim10^{-6}$ Msun/yr at $R\sim1$ pc. 2) The total inflow rate can be broken down into two components driven by two distinct mechanisms. First, feedback-driven turbulence redistributes the angular momentum of gas clouds, producing a smooth (secular) transport of mass inward, similar to a Shakura-Sunyaev viscous accretion disk. This component contributes inflow rates that vary from $\dot{M}\sim5\times10^{-4}$ Msun/yr at $R\sim100$ pc to $\dot{M}\sim10^{-7}$ Msun/yr at $R\sim1$ pc. Second, episodic inflow events can transiently increase the inflow rate by several orders of magnitude, reaching $\dot{M}\sim10^{-3}$ Msun/yr over timescales of $Δt\sim3$-$5$ Myr at $R=10$ pc. 3) The stellar feedback model significantly affects the episodic inflow but has little impact on the smooth component. Simulations including radiation feedback produce substantially more episodic events than those with supernova feedback alone.

We present a case study for how AI coding systems can be used to generate novel scientific hypotheses. We combine a generic coding agent (Google's AntiGravity) with an LLM-driven tree search algorithm (Empirical Research Assistance / ERA) to autonomously generate high-efficiency three-dimensional photovoltaic (3DPV) structures that overcome losses limiting flat solar panels at mid-latitudes. These structures operate by presenting favorable angles to the sun throughout the day, and for illustrative purposes we focus on optimizing performance for a single solar day. Our workflow begins by using AntiGravity to reproduce calculations \cite{bernardi2012solar} showing that 3DPV can have energy densities much higher than stationary flat PV panels. We use these initial designs as the starting point for large scale tree search, where we seek improved solutions and score them for their diurnal yield. The initial tree search leads to nominally more efficient solutions, yet they are caused by algorithmic reward hacking, arising from non-physical design features such as structurally levitating disconnected tiers and exploitations of the discretizations in the optics solver. To counteract this, we develop a workflow where the coding agent iteratively patches the physics engine with constraints to eliminate reward hacking. With reward-hacking eliminated, ERA discovers a series of designs with various constraints and improved performance, including optimal designs with different fixed collector areas, optimizing zenith tracking and avoiding self shadowing. Combining coding agents with tree search (ERA) provides a powerful platform for scientific discovery, for problems whose solutions can be empirically evaluated with a score function.

We present a quantum algorithm for solving algebraic Riccati equations, with applications to quantum-chemical random-phase approximation (RPA) and higher-order RPA theories. Our method block-encodes stabilizing Riccati solutions via Riesz projectors onto invariant subspaces of an associated non-normal matrix, implemented using contour-integral resolvents and quantum singular value transformations. Applied to $m$-particle, $m$-hole RPA, our algorithm yields a block-encoding of the amplitude solution and estimates the electronic correlation-energy density with it. Under localized-orbital sparsity assumptions, the end-to-end cost scales linearly with system size and polynomially with excitation rank $m$, suggesting an exponential advantage in $m$ over plausible classical local-correlation heuristics. More broadly, this work provides a framework for quantum algorithms for nonlinear matrix equations in quantum chemistry and opens a possible route toward developing quantum algorithms for coupled-cluster theory.

We study the \textit{Kaluza--Klein} descent of non-invertible higher-form symmetry defects from eleven-dimensional Supergravity to Type IIA Supergravity. Starting from the eleven-dimensional construction of non-invertible Supergravity defects, we show that the full defect, including its auxiliary topological sector, admits a pushforward along the M-theory circle in the zero-mode Supergravity regime. The seven-dimensional \textit{Chern--Simons}-like auxiliary theory descends to a six-dimensional \(BF\)-type sector. We also show that the compactification of the eleven-dimensional \textit{Bianchi} sector splits into an invertible \(H_{[3]}\)-sector and a twisted non-invertible \(\widetilde F_{[4]}\)-sector, controlled by \(d\widetilde F_{[4]}+H_{[3]}\wedge F_{[2]}=0\). The resulting Type IIA defect algebra contains both an invertible Picard subgroup and non-invertible \(BF\)-dressed defects, with charged probes identified through the standard M-theory/Type IIA brane dictionary.

Accurate estimation of the covariance matrix of cosmic shear statistics is essential for cosmological analyses using current and upcoming wide-area weak lensing surveys. In this work, we investigate analytical methods for computing the Gaussian covariance matrix of the cosmic shear two-point correlation function (2PCF), taking into account the effects of finite survey geometry. We compute the covariance of 2PCF based on the improved Narrow Kernel Approximation (iNKA), with a projection using the Legendre transformation. We also consider other analytical covariance estimators, the $f_{\mathrm{sky}}$ approximation and the weighted quartic-counts method. We evaluate the accuracy of those analytical methods using the convergence fields with the HSC Year 3 survey mask as a test case. We find that the covariance of the 2PCF obtained by using the iNKA does not reproduce the covariance measured directly from Gaussian simulations. Although the iNKA accurately models the diagonal structure of the harmonic-space covariance, residual inaccuracies in the off-diagonal components propagate through the Legendre transformation and significantly affect the real-space covariance. In contrast, the weighted quartic-counts method shows better agreement with the simulations. Our results demonstrate that accurate modeling of the off-diagonal structure of the harmonic-space covariance is crucial for obtaining reliable covariance estimates of real-space weak lensing statistics in the presence of survey window effects.

We present the Data Quality Report Builder toolkit, DQRbuild, a suite of data quality tools that have been developed to vet gravitational-wave events in preparation for the fourth LIGO-Virgo-KAGRA observing run. We explain the main functionality and the many scientific tests that we support. To validate the performance of the tools included in the toolkit, we run a series of tests on all significant candidates shared as public alerts in the third observing run to compare against what was manually reported using human intervention. We find that these automated tools can now identify 96% of the problems identified by humans during this previous observing run, with a 24% false alarm rate. We conclude with a commentary on the prospects and potential challenges for fully automating the process of vetting the data quality for gravitational-wave events identified in future observing runs.

Accurate seasonal runoff forecasts are critical for managing California's reservoirs and water supply for millions of its residents. Winter snow accumulation provides a strong source of predictability of snowmelt-based runoff in the spring and summer months, but progressive hydroclimatic changes in the Sierra Nevada are altering its timing and volume. These changes reduce the skill of statistical forecasts trained on historical data, highlighting the need for improved forecasting systems that can capture the changing dynamics of snowmelt. Here we demonstrate that a collaborative workflow between an agentic AI assistant and an automated code-mutation system, both powered by large language models, can accelerate the development of competitive seasonal runoff forecasting systems. In our framework, the AI agent discovers relevant datasets, synthesizes domain knowledge from prior forecasting competitions and the scientific literature, and explores the space of model architectures, while the code-mutation system refines each of the solutions explored by the agent through Monte Carlo Tree Search over the code space. The resulting system forecasts monthly Full Natural Flow (FNF) at 1- to 6-month lead times across 23 Sierra Nevada watersheds using an adaptive ensemble of three XGBoost quantile regression sub-models with physics-informed feature engineering. Evaluated against California's operational Bulletin 120 forecasts over 2021-2025, the agent-evolved model achieves superior skill for early-season cumulative April-July runoff predictions, reducing watershed-averaged quantile forecast error by up to 29%, and offering a new paradigm for AI-driven scientific model development in the geosciences.

We investigate systems containing objects with negative mass (NMOs). In a system consisting of one object with positive mass and one NMO, a bound state exists even though the force exerted by the NMO on the object with positive mass is repulsive. Unlike a standard system consisting of two objects with positive mass, the gravitational waves emitted from this system exhibit a decrease in frequency and amplitude over time. We propose a model of the time evolution of the Ellis-Bronnikov wormhole, along with a formulation that eliminates the ghost that appears when constructing the Ellis-Bronnikov wormhole, a candidate for an NMO. Furthermore, numerical simulations are performed to obtain the optical appearance of such NMOs. The observed luminosity is also compared with the Schwarzschild black hole and with the Simpson-Visser wormhole, leading to clear differences in the photon ring substructure around the central object.