AI for Science

Laser-driven lightsails have emerged as a promising route for accelerating ultralight spacecraft to high speeds using beamed optical energy. Realizing this concept pushes the limits of light-matter interaction, materials science, structural engineering, and nanomechanical design. A central challenge is to create nanophotonic reflectors that combine ultralow mass, large illuminated area, and survival under high optical power densities. No previous experiment has combined these constraints in a single structure sufficient to produce measurable radiation-pressure displacement. Here, we report the largest subwavelength tethered lightsails to date: nanoscale-thickness, millimeter-wide silicon nitride membranes patterned with billions of holes. Despite their subwavelength thickness, they achieve 99% reflection through resonant photonic modes, combining ultralow areal density with high reflectivity. Their compliance enables radiation-pressure displacements of up to 1.75 micrometer, a 50,000-fold increase over previous lightsail optomechanical responses. These thin mirrors are shown to withstand and maintain high reflectivity under directed laser intensities comparable to optical intensities at the surface of the Sun. Together, these results establish a testbed for high-power nanophotonics, directed-energy systems, and light-driven propulsion, defining the practical limits of ultrathin photonic materials under intense optical loading.

Quantum error-correcting codes (QECs) are essential components quantum computation and have deep connections to quantum phases of matter. A key obstruction to passive self-correcting QECs is the presence of string logical operators, which can generate logical errors through constant-energy-barrier processes. Haah's Codes (fracton codes) showed that three-dimensional stabilizer codes can forbid such string logical operators, but their translation-invariant structure supports self-similar fractal logical operators with a logarithmic energy barrier. We introduce the qutrit random cubic codes, a family of local qutrit Calderbank-Shor-Steane stabilizer Hamiltonians with similar cube-check structure as Haah's Code 1 but built from spatially varying stabilizers. We prove that these models retain the no-string property and numerically observe that they have properties distinct from translation-invariant fracton codes: the smallest ground-state degeneracy exponent is $k=2$ for odd $L$ and $k=4$ for even $L$; noncontractible plane-logical operators span the entire logical space; and charge-push diagnostics show that the self-similar fractal operators are absent. These results demonstrate that constrained randomness can fundamentally change the nature of stabilizer codes and improve their self-correction properties. They further point to broader families of quantum error-correcting codes and quantum phases beyond canonical topological and fracton orders.

In this article, we present four different $1+1$D quantum models that realize the Yang-Lee (YL) phase transition under a deformation that preserves $PT$ symmetry. These are the antiferromagnetic Ising spin chain in transverse and longitudinal magnetic fields, the massive Schwinger model, the Blume-Capel model, and the three-state quantum clock model. Using the state-operator correspondence, we identify the YL critical point, compute the scaling dimensions of the lowest operators in each model, and find perfect agreement with the exact results for the YL criticality in two dimensions. Using bosonization for the Schwinger model and the Polyakov-Hubbard transformation for the other models, we show that in all of these quantum models the YL critical point is described, as expected, by a massless bosonic field with an $i ϕ^3$ interaction. In the quantum clock model, this critical field interacts with a massive bosonic field, and we identify the massless and massive states in the Hamiltonian spectrum. In addition, we numerically compute the two-point function of $ϕ$ at the Yang-Lee critical point and show that it grows with distance, in agreement with theoretical expectations.

A variational principle for quantum-state distinguishability is established in many-body systems with generalized symmetries, including noninvertible cases described by fusion categories. Standard fidelity and symmetry-resolved diagnostics emerge as coarse-grained limits of a more refined operational structure. When symmetry actions terminate at entanglement cuts, distinguishability is governed by boundary tube algebras within a symmetry-constrained measurement resource theory. The physically admissible instruments are characterized by complete positivity, entanglement-cut locality, boundary-module covariance, and sequential stability. The resulting optimal measurement structure is uniquely fixed by the center of the boundary tube algebra, $\mathcal{A}_{\mathrm{phys}} = Z\!\left(\mathrm{Tube}_{\mathcal{C}}(\mathcal{M}_A)\right)$, whose primitive idempotents define tube-sector probabilities that refine fidelity-based and symmetry-resolved descriptions. The associated tube positive-operator-valued measures (POVM) are extremal and yield optimal one-shot hypothesis-testing distinguishability under symmetry constraints. The construction is universal across fusion categories and independent of microscopic realization.

Studies of integrable systems have profoundly deepened the fundamental understanding of quantum many-body physics. While equilibrium properties such as ground states and thermodynamics can often be characterized efficiently, accurately characterizing nonequilibrium integrable dynamics remains a significant challenge. Here, we address this problem in the "Rule 201" quantum cellular automaton, an integrable Trotterization of the PXP Hamiltonian. Using the tensor-network approach of the influence matrix, we develop local conditions called generalized zipper conditions that allow exact solutions of local dynamics. We also introduce a numerical bootstrap method for solving influence matrices with finite but relatively large bond dimensions. This uncovers a rich landscape of nonequilibrium behavior exhibiting initial-state dependence. As an example, we investigate the fate of persistent oscillating dynamics under local non-integrable perturbations, and present analytical results for non-thermal relaxation constrained by conservation laws. We also obtain numerically exact results for entanglement growth across a broad class of initial states. Furthermore, from an information-theoretic perspective, we identify a refined structure of multitime correlations termed the hidden Markov order: the memory encoded in the dynamics separates into finite-length and long-range distributed components, which becomes transparent in an exact split-index matrix-product-state representation of the influence matrix. Our approach enables unified investigations of nonthermalizing and thermalizing regimes of nonequilibrium dynamics within a single analytically tractable model, and can be tested experimentally in state-of-the-art quantum simulators such as Rydberg atom arrays.

In this paper, we study the statistical field-theoretic renormalization of active flocks via the MSRDJ action formulation for stochastic systems, focusing on the Toner-Tu theory of `Malthusian flocks', or polar-ordered, momentum non-conserving active fluids where relaxation times for density fluctuations are so short that they can be eliminated as a hydrodynamic variable. Working in the limit of isotropic diffusion in two spatial dimensions, we compute the renormalization of the couplings and their anomalous dimensions to all orders, facilitated by a non-linear realization of a generalized \textit{Galileon} symmetry and its associated Ward identities. We find a range of behavior depending on the parameters of the theory. If $κ$ is the diffusion coefficient and $Δ$ is the variance of the noise, we find a line of fixed points and a marginal vertex instability at $Δ/κ= 2π$. This instability separates Gaussian, and strongly interacting, symmetry-protected gapless phases, realizing non-equilibrium critical behavior beyond conventional Wilson--Fisher criticality. The existence of gapless excitations in both phases can be traced to the soft (Adler zero) theorems associated with the generalized Galileon symmetry, and implies the persistence of long range order when $Δ/κ$ is below the critical value. We revisit and contextualize various claims and counter-claims in the literature in light of our findings, and discuss extensions of our analysis to anisotropic diffusion, and towards flocks where density fluctuations are reintroduced.

Variational infinite matrix product state (iMPS) calculations usually make Hamiltonians with algebraically decaying interactions compatible with standard MPO algorithms by first replacing the target Hamiltonian with a finite-pole sum-of-exponentials surrogate, thereby introducing a Hamiltonian-representation residual. We formulate the fixed-$D$ variational energy without introducing such a surrogate. For a fixed finite-$D$ MPS, the algebraic tail can be summed directly through the connected transfer matrix: the tail $e^{\mathrm{i} Qr}/r^α$ is represented by the matrix function $F_{α,Q}(\widetilde{T}_A)$, with $F_{α,Q}(z)=\operatorname{Li}_α(e^{\mathrm{i} Q}\,z)/z$. We evaluate the resulting matrix-function action using a Krylov method and obtain stable gradients by combining a Fréchet adjoint with implicit fixed-point differentiation. Benchmarks on long-range free fermions and the inverse-square Heisenberg family, including the Haldane--Shastry point, validate the transfer-matrix-function formulation. A long-range Ising-chain calculation illustrates a practical consequence of avoiding a finite-pole Hamiltonian representation. At a fixed, independently known critical field, finite-pole surrogate Hamiltonians can bias a critical diagnostic away from criticality, whereas the matrix-function calculation retains the expected critical signatures of the target algebraic Hamiltonian.

We consider protocols for control of dipolar Bose-Einstein condensates where the critical role is played by the long-range anisotropic interatomic magnetic dipole-dipole interaction. The phase diagram of such a condensate has been explored theoretically and experimentally with certain values of the interatomic scattering length corresponding to superfluid and supersolid phases, where supersolidity appears as a modulation in the ground state density. Preparation of this modulated ground state is challenging, since excitations appear as a result of a finite-time evolution required to produce qualitative changes in the wavefunction density. To solve this problem we consider the time-dependent control of a dipolar Bose-Einstein condensate using shortcuts to adiabaticity techniques, concentrating on design of the time-dependent scattering length, a parameter of the system easily tunable by contemporary experiments. The first technique is the variational approach based on the Euler-Lagrange equations for a separable ansatz describing the evolution of the superfluid state. Secondly, we study the transition from superfluid to supersolid using a direct optimization protocol. We discuss the fidelity of the developed protocols in terms of the evolution time.

Statistical methods are essential for understanding thermodynamic systems with many degrees of freedom. For systems in equilibrium, a very useful method is that of correlation functions, which establish a correlation between a field phi(x), which depends on the spatial position x, and the same field evaluated at another position, phi(x0). Fisher [Journal of Mathematical Physics 5, 944322 (1964)] introduced the autocorrelation function for fluctuations of the order parameter, which has been an important mathematical tool for understanding second-order phase transitions in equilibrium. However, his analysis is restricted to a Euclidean space of dimension d, and an exponent eta is introduced to correct the spatial behavior of the correlation function at T = Tc. In a recent work, Lima et al. [Phys. Rev. E 110, L062107 (2024)] demonstrated that a modern fractional differential analysis is necessary for a complete description of the correlation function at Tc. In this study, we highlight the deep connection among scaling behavior, critical exponents, and fractal geometry. Our results provide a unified geometric interpretation of critical exponents and fractal dimensions, broadly applicable to thermodynamic phase transitions. However, the approach does not apply to topological phase transitions, which lack local order parameters and the associated scale-invariant fractal geometry. We verify its predictions for several cornerstone thermodynamic models: the Ising, Potts, XY, and Heisenberg systems.

Characterising the universal aspects of non-equilibrium quantum many-body dynamics is one of the key goals of this century's physics research. Progress, however, is hindered by the lack of general theoretical frameworks for studying interacting quantum matter far from equilibrium. A recent breakthrough has been the realization that several key non-equilibrium quantities, such as the rate of growth of entanglement or the fluctuations of conserved charges within finite subsystems, can be related to equilibrium properties through a space-time duality that effectively exchanges the roles of space and time. This observation effectively enables the study of non-equilibrium phenomena using tools and concepts borrowed from equilibrium statistical mechanics and thermodynamics. A first proof of principle of this framework, dubbed space-time duality approach (SDA), was provided by interacting integrable systems, where thermodynamic properties can often be characterized exactly, while dynamical quantities typically remain beyond analytical reach. Subsequent developments, however, revealed that the SDA suffered from an intrinsic ambiguity, restricting its applicability to homogeneous quenches and to charge fluctuations arising from symmetric initial states. Here we resolve this ambiguity from first principles and derive closed-form predictions for entanglement growth and charge fluctuations after general quantum quenches. We benchmark our results against the exact analytical solution of the Rule 54 quantum cellular automaton and extensive TEBD simulations of the XXZ chain. Moreover we show that, when specialised to the entanglement entropy, our framework naturally reproduces the predictions of the quasiparticle picture.

When stochastic field dynamics are cast into a path-integral formulation, perturbation theory becomes systematic but the resulting expansion quickly grows combinatorially large. The setting targeted here includes multi-component, multi-dimensional fields with matrix propagators, tensor-valued couplings, and non-Gaussian driving noise specified by arbitrary $n$-point cumulants. Wick pairings grow factorially, and component indices must be routed through the tensor-valued vertices. The useful output is not a raw contraction list, but a diagram table: one entry per topology, with multiplicities, coupling sums, signs, and causal constraints resolved. We present sft-wick, an open-source Python package that constructs these diagram tables and computes their integrals numerically. Given an action and an observable, it enumerates topologically distinct Feynman diagrams, derives their algebraic coefficients, and evaluates the resulting diagram integrals from user-supplied response and cumulant functions. The core algorithm enumerates spatial topologies before routing component indices, avoiding contraction-by-contraction Wick expansion. Response-field constraints, including vanishing response-response contractions, the ito prescription, and the absence of causal response loops, are enforced during enumeration. Predictions are validated against direct Langevin simulation, agreeing to within the simulation's statistical noise.

We formulate reheating as a constrained variational problem in the space of equation-of-state histories, rather than attempting to describe it through microscopic models. We introduce a regularized functional framework that identifies reheating histories which extremize a given cosmological observable under minimal physical assumptions. As illustrative applications, we consider prompt gravitational waves, induced gravitational waves, and primordial black holes. We find that different observables select qualitatively different regions of reheating-history space. These examples demonstrate that cosmological observables define distinct extremal directions in reheating-history space and can therefore be used to systematically explore the space of post-inflationary expansion histories.

The rotational dynamics induced by the non-frontal binary collisions of quantum droplets composed of ultracold alkali atoms are analyzed. A theoretical study is presented within the extended Gross-Pitaevskii equation framework, using experimentally feasible conditions. Numerical experiments elucidate a rich landscape of possible topological excitations in the system that are robust towards measurements. The collision of heteronuclear quantum droplets composed of $^{41}$K and $^{87}$Rb atoms in the incompressible regime, gives rise to dynamical instabilities that spontaneously generate topological defects: vortex rings, dislocation lines, and vortices in one species. Their presence depends on the Weber number and the impact parameter. An experimental proposal for vortex detection in both real and Fourier space using interaction ramps is described.

Deep neural networks (DNNs) have achieved remarkable success in scientific computing, yet they often suffer from spectral bias in capturing oscillatory and multiscale behaviors. In this study, we investigate this limitation by examining the failure of shallow ReLU neural networks in fitting high-frequency functions. This observation identifies two important factors in resolving rapid oscillations: the initial slope scale and the distribution of partition points induced by the networks. Motivated by this analysis, we propose RepNN, a reparameterized neural network model with activation ReLU or tanh designed for high-frequency and multiscale problems. The key idea is to reparameterize the weights and biases in the first hidden layer, which enables effective control of the initial slope scale and provides an appropriate distribution of the initial partition points. Furthermore, treating the reparameterized weights and biases as trainable parameters allows the DNN to achieve adaptive frequency scaling during training. In addition, we derive quantitative estimates for the output and slope magnitudes of the reparameterized DNN to guide the initialization of the proposed method. Numerical experiments, including multiscale one- and four-dimensional function approximations, forward and inverse PDE problems in combination with physics-informed neural networks (PINNs), and operator learning for an earthquake problem using real data, demonstrate that RepNN improves the predicted accuracy of vanilla DNNs in capturing highly oscillatory features with slightly additional computational cost. These results indicate that RepNN provides an effective and flexible approach for overcoming spectral bias and applying DNNs to multiscale problems.

In this work, we investigate the impact of fusion-born alpha particles on core turbulence and transport in the ARC tokamak fusion power plant using linear and nonlinear gyrokinetic CGYRO simulations. A significant reduction in ion-scale turbulent heat and particle fluxes is observed in the inner core (r/a $\leq$ 0.5), which is associated with multiscale interactions between fast ion-destabilized modes, zonal flows, and the background turbulence. A nonlinear upshift in the ITG critical gradient is observed in the simulations with fast alphas compared to those with artificially thermalized alphas. The turbulence reduction is found to scale beneficially with alpha particle density and plasma $β_e$, and the radial extent of the turbulence suppression is limited to the volume containing a significant density of fast particles. The suitability of local gyrokinetics and potential impacts of fast ion effects on fusion performance are discussed.

We study dynamical orthogonal (DO) approximations of stochastic differential equations and investigate their long-time behaviour. The DO formulation represents the solution by a low-rank decomposition and leads to a coupled system consisting of an evolution equation on the Stiefel manifold and a reduced stochastic process. We establish the well-posedness of the strong DO system and derive quantitative error estimates between the original stochastic differential equation and its low-rank approximation in the Wasserstein distance. Our main contribution is the analysis of invariant probability measures for the DO dynamics. Under suitable dissipativity, Lipschitz continuity, and non-degeneracy assumptions on the coefficients, we prove the existence of an invariant probability measure for the strong DO system. The proof combines uniform moment estimates, a Krylov--Bogoliubov argument for an associated frozen system, and a Kakutani-Fan-Glicksberg fixed-point theorem to recover the self-consistent dynamics. We further show that the induced low-rank process admits an invariant probability measure and discuss the structure of invariant measures through several illustrative examples. These results provide a rigorous foundation for the use of dynamical low-rank approximations in the approximation of long-time statistical properties of stochastic dynamical systems.

Charge conjugation violation (CCV) is a central concept in particle physics and appears also for quasiparticles in quantum many-body systems, which typically relies on an embedded external symmetry breaking to the underlying system. An open question is how an intrinsic CCV mechanism could emerge and what its macroscopic consequences would be. We establish sublattice kinks in bipartite fermionic lattices as a concrete setup showing intrinsic CCV. The intrinsic CCV of the sublattice kink is based on the graph-topological nature of the underlying Hamiltonian, with no explicit symmetry breaking taking place. It leads to a population asymmetry of different configurations and imprints a hidden leaf-like structure in the eigenenergy spectrum. The population asymmetry also leads to an imbalanced sublattice-kink production triggered by the vacuum-instability in the quench dynamics. Our work demonstrates the graph topology as the microscopic origin of intrinsic CCV, with the population asymmetry as the macroscopic consequence, of which the proposed setup is highly amenable to experimental implementation via cold-atom quantum simulators.

Fluctuational electrodynamics relies on the assumption that thermal fluctuations in distinct bodies are statistically independent. It is shown that this approximation breaks down in the extreme near-field regime, where hybridization of surface phonon-polaritons across nanometric vacuum gaps generates finite fluctuating-current cross correlations between opposite interfaces. Using a microscopic coupled-oscillator model combined with a Green-tensor formulation of the Poynting vector, the resulting correlation-induced correction to radiative heat transfer is derived. For polar materials, these correlations become significant when the hybridization energy approaches the intrinsic damping rate and can substantially modify conventional fluctuational-electrodynamics predictions at subnanometric separations.

The most compelling evidence for spin-triplet superconductivity has emerged from strongly correlated electron systems, yet whether a substantial spin-triplet component can be realized without strong electronic coupling, by virtue of antisymmetric spin-orbit coupling (ASOC), remains unresolved. We address this question in the weakly-correlated noncentrosymmetric superconductor Nb$_{18}$Re$_{82}$ using low-temperature scanning tunneling spectroscopy on single crystals with different crystallographic orientations. The tunneling spectra exhibit orientation-dependent variations. A symmetry-constrained analysis shows that understanding the complete spectroscopic dataset requires an superconducting order parameter combining a nodal spin-singlet component with a spin-triplet contribution reaching up to half of the singlet amplitude. These results resolve the debated pairing symmetry of Nb$_{18}$Re$_{82}$ and demonstrate that ASOC alone can generate substantial parity mixing, suggesting that triplet superconductivity may be more widespread than previously recognized.

Density-potential inversion for periodic systems within Moreau-Yosida-regularised density-functional theory is investigated, both theoretically and numerically. We develop the framework in a periodic homogeneous Sobolev space and use it to recover the exchange-correlation potential of Kohn-Sham theory through a limiting procedure. A key analytical ingredient is the proof of lower semicontinuity of the non-interacting kinetic-energy functional in the chosen topology. The proximal mapping, together with its algorithmic evaluation, plays a central role in the resulting inversion scheme. Numerical experiments illustrate the performance and properties of the method for both the Kohn-Sham and Gross-Pitaevskii equations.

The tunability and control of topological edge/surface states are crucial for the development of new device applications. In this work, by combining first-principles calculations and Wannier-based tight-binding methods, we show the emergence of quantum spin Hall phases in van der Waals heterostructures formed by stacking two trivial quintuple layers from the Bi$_2$Te$_3$ family. We demonstrate the tunability of the edge states under interlayer strain and external electric field effects, suggesting the possibility of switching topological edge states on/off by external control. Additionally, the quantum spin Hall edge channels remain robust against interlayer twist, highlighting their stability against external perturbations. Our results provide a new way to create and manipulate two-dimensional topological phases in systems based on Bi$_2$Te$_3$ family, which can be valuable for practical applications, such as topological field effect transistors and spintronic devices.

We investigate the magnetic ground states and transverse spin excitations of bilayer and trilayer nickelates within a multi-orbital itinerant framework. For the bilayer system, although Hartree-Fock calculations slightly favor a double-stripe order, the calculated excitation spectrum of the single-stripe state, characterized by an anisotropic low-energy cone at $Q_{\text{BL}}$ and isotropic high-energy excitations near $Γ$, exhibits good qualitative agreement with recent RIXS and neutron scattering experiments. We further identify mirror-even optical interlayer modes at $Q_{\text{BL}}$ whose energies match the mirror-odd modes at $Γ$. For the trilayer system, both mirror-odd and mirror-even spin-density-wave states can be stabilized near $Q_{\text{TL}}$, with the mirror-odd state lower in energy in the parameter regime studied. The mirror-odd state hosts an additional nearly gapless mode dominated by the middle layer, while the mirror-even state contains only one acoustic branch together with two gapped optical modes. Comparison with available RIXS data favors the mirror-odd spin-density-wave scenario. Our results show that magnetic excitations provide a sensitive probe of the magnetic order and support a common itinerant origin of magnetism in multilayer nickelates.

Amorphous silicon (a-Si) is understood to be the canonical continuous random network material, ideally defined by fully fourfold coordination. Here, we show that a defect-free ('ideal') model of a-Si from machine-learning-driven molecular-dynamics simulations [L. A. M. Rosset et al., Nat. Commun. 16, 2360 (2025)], subsequently evaluated with hybrid-level density-functional theory computations, can accurately reproduce the experimentally observed electronic bandgap. We compare this model with one resulting from the Wooten-Winer-Weaire (WWW) bond-switching approach and with other recent approximants to ideal a-Si. More broadly, our work provides a platform for studies of band tails, optical properties, and transport in a-Si.

The topological heavy-fermion model provides a minimal framework for describing the coexistence of localized moments and itinerant Dirac electrons in magic-angle twisted bilayer graphene (MATBG). Several analytical and numerical methods have been applied to this model; however, whether they provide a realistic description of MATBG remains incompletely understood. In this work, we develop an Hubbard operator approach that incorporates non-local correlations beyond the single-site limit. We benchmark the approximate calculations against numerically exact determinant quantum Monte Carlo simulations of a lattice-regularized model. We show that commonly used local approximations, such as Hubbard-I, fail to capture the coupling between localized and itinerant degrees of freedom, leading to incorrect spectral properties in the local-moment regime. In contrast, the Hubbard operator method provides a controlled description of both correlation functions and spectral features over a regime of parameters, in good agreement with exact numerical methods.

We use density functional theory and model Hamiltonians to reveal large spin splitting of bands localized at low-symmetry, ferromagnetic surfaces of bulk antiferromagnets (AFMs). There is great interest in finding new material platforms combining the robustness and ultrafast dynamics of AFMs with large, functional spin splitting which is often restricted to ferromagnets. Here, we show that a subset of AFM surfaces which have symmetry-allowed magnetization can host large spin splitting via bulk degeneracy lifting of sublattice-resolved exchange splittings. Using model Hamiltonians, we show that the spin splitting is maximized for two ferromagnetic surface motifs: terminations with single uncompensated magnetic sublattices, and two-sublattice surfaces whose sublattices are magnetically and electronically compensated in the bulk, but acquire distinct crystal field environments via surface truncation. The latter case can yield FM-like spin splitting magnitudes while also having vanishingly small uncompensated magnetization. In contrast, when surface magnetization arises from relativistic canting on symmetry-connected sublattices, the spin splitting is expected to be small. We confirm these predictions with first-principles calculations of $\mathrm{Cr_2O_3}$ and $\mathrm{FeF_2}$, finding splittings from $\sim10\mathrm{meV}$-$\sim1\mathrm{eV}$ depending on the surface in question. Our findings point to intrinsic surface symmetry breaking as a route to large, functional spin splitting in an expanded range of AFM materials.

Accurate modeling of dielectric screening in van der Waals (vdW) heterostructures is essential for predicting photonic and optoelectronic properties - yet conventional first-principles methods are often hindered by incommensurate lattices and prohibitive computational costs. In this work, we introduce the microscopic Quantum Electrostatic Heterostructure (mQEH) method. mQEH employs a hierarchical and systematically improvable basis set to describe potentials and induced densities, eliminating the need for arbitrary geometric cutoffs and ensuring accurate screening descriptions at all length scales. The mQEH method is combined with a layer projected Bethe-Salpeter Equation (BSE) to enable calculations of optical spectra of experimentally relevant lattice-mismatched vdW heterostructures. Applying the mQEH-BSE framework to a series of transition-metal dichalcogenide (TMD) heterobilayers, we obtain absorption spectra and momentum-indirect exciton energies in excellent agreement with experiment. The framework provides a computationally efficient route to predictive modeling and design of vdW heterostructures with tailored optical properties.

Sub-bandgap optical absorption in AlN between 2 eV and 4 eV is widely observed, but its microscopic origin remains contested. Using photo-induced electron paramagnetic resonance (photo-EPR) and optical absorption spectroscopy on the same samples, we demonstrate a correlation between this absorption band and the neutral charge state of substitutional carbon on the nitrogen site (C$_N$). Hybrid functional calculations of the optical absorption spectra show that a transition involving C$_N$ and the valence band occurs near 3.3 eV, which agrees well with a peak identified within the measured optical absorption between 2 eV and 4 eV. This conclusion requires the combined ability to manipulate the charge state of carbon using photo-EPR and to use first-principles calculations of the absorption line shape that account for the dispersion of the valence band and the energy dependence of the optical matrix elements.

The growth of a thin film of a high-entropy AlCoCuFeNi alloy on a silicon (100) substrate was studied using molecular dynamics modeling. The simulation was carried out using the embedded atom model to describe the interactions among Al, Co, Cu, Ni, and Fe atoms. The interaction between Al, Co, Cu, Fe, Ni atoms and the Si substrate was modeled using the Lennard-Jones potential, while the interaction between silicon atoms was described using the Stillinger-Weber potential. The total simulation time was 50 ns. It was found that small clusters were formed at the first stage of deposition and that crystallization started after approximately 5 ns of simulation, when the characteristic cluster size was about 2 nm. At the end of the simulation, after 50 ns of modeling, the simulated film contained face-centered cubic, body-centered cubic, hexagonal close-packed, and amorphous phases. Analysis of the radial distribution function made it possible to determine nearest-neighbor distances and estimate the lattice parameters of these phases.

Artificial intelligence (AI) agents promise to accelerate drug discovery by compressing interpretation and decision-making loops, but practical deployment requires trusted evaluation on realistic program decisions. We introduce TherapeuticsBench Preclinical Pharmacology (TxBench-PP), a verifiable benchmark for small-molecule preclinical pharmacology and the first focused slice of a broader TherapeuticsBench effort across drug-discovery stages and therapeutic modalities. TxBench-PP tests whether agents can recover accurate conclusions from real-world assay data rather than memorized facts from literature. The benchmark contains 100 evaluations indexed by program stage, assay type, and task structure, spanning mechanism-of-action (MoA) and pharmacodynamic (PD) reasoning, compound-target engagement, causal target validation, developability and safety, and translational efficacy. Agents receive realistic workflow snapshots, inspect files in a coding environment, and return structured answers graded deterministically. Across 16 model-harness configurations, comprising 11 models and 4,800 trajectories, no system reliably recovered preclinical pharmacology decisions. The strongest configuration, Claude Opus 4.8 / Pi, passed 59.3\% of endpoint attempts (178/300; 95\% CI, 51.1-67.6), followed by GPT-5.5 / Pi at 55.3\% (166/300; 47.0-63.6).

Scientific discovery demands intelligence, perseverance, and serendipity across vast search spaces. Today, top scientific capabilities remain siloed--one AI system for biological analysis, another for clinical reasoning, mathematical derivation, or materials simulation--and no pre-designed team can anticipate every skill a question will need. Science Earth is a planet-scale scientific runtime in which any capability--a simulation cluster, a wet-lab robot, a proof engine, a single-cell pipeline--can connect to any other, with collaboration structure emerging from the question itself. Its underlying EACN protocol lets capabilities discover one another, negotiate task ownership, and adjudicate across incompatible evidentiary standards without prior knowledge of who will meet whom. This shifts the organizing challenge from workflow design to open-ended connectivity. Two runs validate this under structurally distinct conditions. In a trans-Pacific higher-order Kuramoto synchronization study, agents identified and corrected a closure-ratio assumption in Ott-Antonsen analytic theory that fails outside the Lorentzian limit, within thirty minutes. In an eight-agent single-cell run on the 4.88M-cell Kang 2024 pan-cancer atlas, heterogeneous capabilities coupled over a 64.9-hour window with one structural external instruction, producing three new result layers and anchoring findings against an independent wet-lab study on an adjacent CCR8- TIGIT+ Treg subset. These cases are a first empirical reading, not a benchmark sweep. They show that when AI capabilities are truly connectable and coordination emerges from the problem, scientific reasoning becomes a distributed, self-correcting process--a step towards scaling AI-native discovery to the planet.