A series of glass-shell $\mathrm{D}{}^3\mathrm{He}$ gas-filled implosions was carried out on the OMEGA Laser Facility. In these experiments, the thicknesses of the glass shells were varied from 4.2 to 9.4 $\mu \mathrm{m}$, producing implosions that spanned from shock-to-compression-dominated emission. Data from several diagnostics were used to infer the conditions and nuclear yields for the $\mathrm{D}{}^3\mathrm{He}$-p and DD-n reactions during shock and compression burns. From the inferred yields and ion temperatures, the deuterium fractions in the hot spot during both emission phases were estimated. It is found that there is a substantial surplus ($\sim 5\%$) of deuterium in the hot spot compared to the initial fill fraction during both shock and compression phases for all implosion types. This is the first measurement indicating persistent species separation throughout both phases of inertial confinement fusion (ICF) implosions. In ICF implosions, deviations from a 50:50 species ratio will decrease the fusion rate, directly impacting performance. Future ICF implosion design work would benefit from including models that capture multi-ion dynamics.

Free-electron interactions with optical near fields are conventionally described as one-dimensional energy ladders, in which multicolor photon-exchange pathways can become spectrally degenerate. In this work, we show that coupling a single free electron to commensurate two-color optical vortices can unfold this degeneracy, realizing a tunable synthetic lattice spanned by the electron energy and orbital angular momentum (OAM). The resulting single-particle dynamics map the free-electron light interaction onto an effective tight-binding Hamiltonian whose primitive hopping vectors and coupling anisotropy are controlled by the optical OAM charges and near-field amplitudes. We use this construction to emulate a Lifshitz transition in the synthetic quasienergy band structure, identified by a topological reconnection of the zero-quasienergy contour and the associated Van Hove singularity in the density of states. We further show that the generated electron state exhibits tunable intraparticle energy-OAM mode nonseparability, which serves as a diagnostic of the synthetic-lattice geometry. These results establish free electrons as a tunable platform for synthetic-band engineering, combining electron-wavefunction control with ultrafast electron-microscopy and nanoscale near-field techniques.

We report a direct demonstration of quantum-enhanced sensing in the Fourier domain by comparing single- and two-photon interference in a fiber-based interferometer under strictly identical noise conditions. The simultaneous acquisition of both signals provides a common-mode reference that enables a fair and unambiguous benchmark of quantum advantage. Spectral analysis of the interferometric outputs reveals that quantum correlations do not increase the amplitude of the modulation peak, but instead lower the associated noise floor, resulting in the expected 3 dB improvement in signal-to-noise ratio. This enhancement persists in the sub-shot-noise regime, where the classical signal becomes indistinguishable from the spectral background while the two-photon contribution remains resolvable. These observations establish quantum supersensitivity in the Fourier domain as an operational and broadly applicable resource for precision interferometric sensing.

Inertial confinement fusion implosion design requires simultaneous optimization of strongly coupled target and driver parameters across high-dimensional design spaces. Existing automated design approaches typically rely on nondifferentiable radiation-hydrodynamics codes treated as black boxes, making optimization increasingly expensive as dimensionality grows. In this work, we present a differentiable simulation approach for high-dimensional inverse design of inertial confinement fusion implosions. Automatic differentiation through a differentiable implosion physics model, driven by an external pressure pulse, provides gradients of implosion objectives with respect to design parameters, enabling gradient-based optimization. The framework is applied to 25 kJ OMEGA-scale direct-drive implosions, optimizing 500-parameter laser pulses across sampled target geometries. The optimized pulse recovers a near-isentropic rise to peak power without that structure (i.e., pulse shape) being imposed. Neural-network pulse parametrizations are additionally explored as a means of accelerating design-space exploration. These results establish differentiable implosion modeling as a promising tool for inertial confinement fusion design, while motivating further work on adjoint robustness and higher-fidelity differentiable simulators.

Guiding relativistically intense laser pulses in low-density plasmas enables extended acceleration lengths in laser-plasma accelerators (LPAs), allowing for the production of multi-GeV electron beams. Quantitative interpretation of such experiments is often limited by substantial uncertainties in key plasma parameters, particularly the transverse density profile of hydrodynamic optical-field-ionized channels. Distinct plasma density distributions can produce similar terminal beam energies, complicating efforts to infer the underlying interaction physics from measurements at the accelerator exit alone. By combining longitudinally resolved electron beam diagnostics with independent measurements of laser spectral evolution in a 10 GeV LPA, we establish a multiobservable constraint on plasma density profiles. Once plasma down ramps are taken into account, excellent agreement is observed with simulation over the entire accelerator length for two plasma channel sizes. The validated simulations indicate that extending the accelerator length to 65 cm would increase the electron beam energy to 15 GeV. They also point the way to achieving $\sim 20\mathrm{GeV}$ electron beams in $\sim 70\mathrm{cm}$ via linear matching using the same 24 J laser energy.

We identify an instability mechanism in pressure-driven viscoelastic channel flows bounded by porous walls. Unlike the elastoinertial center mode in impermeable channels or the classical porous-wall mode in Newtonian flows, the instability uncovered here is wall localized and arises from the coupling of polymeric stress transport with interfacial momentum leakage. Elastic normal stresses concentrate disturbances at the fluid-porous interface, while permeability simultaneously enables slip-driven stress amplification and dissipative leakage, producing a wall-confined elastoinertial mode. The resulting instability occurs at Reynolds and Weissenberg numbers well below classical thresholds and exhibits a nonmonotonic dependence on permeability. In the strongly elastic limit, the onset is governed by interfacial stress localization rather than inertial amplification, rendering inertia nonessential. These findings show that permeability not only shifts stability boundaries but also reorganizes the instability mechanism itself, establishing a boundary-driven route to transition in porous-bounded viscoelastic flows.

Attosecond pulses from free-electron lasers have opened the doors to atomic site-specific studies of bound electronic dynamics on their natural, subfemtosecond timescales. Key to their success has been electron beam shaping techniques enabling the generation of subfemtosecond current spikes with peak currents on the order of 10 kA. We demonstrate in an rf linac the generation of current spikes with extreme chirps on the order of $350\mathrm{MeV}/\mu \mathrm{m}$, directly competitive with the chirps expected from beam-driven plasma wakefield accelerators. Leveraging chirp-taper compensation, we use these highly chirped beams to generate hard x-ray attosecond pulses with bandwidths exceeding 30 eV, a factor of 2 beyond previous demonstrations. We simultaneously present the first explicit experimental evidence of chirp-taper compensation in an attosecond x-ray free-electron laser, finding that optimal tapering improves the bandwidth and pulse energy by factors of 2 and 5, respectively, for our conditions. In addition to the immediate utility of such broadband hard x-ray pulses, electron beams with such extreme chirps can be utilized for unique new experimental modalities by performing further compression after the undulators. Such postlasing compression can enable subsequent superradiant light emission at longer wavelengths or direct excitation of quantum systems with the beam’s intense space-charge field for unique attosecond pump-probe possibilities.

Given the rapid advances in quantum computing hardware, establishing strategies for verifying the correctness of quantum computations has become increasingly important. Exploiting the fact that the axial anomaly in gauge theories is exact to all orders in perturbation theory, we propose the axial anomaly as a nontrivial benchmark for quantum simulations of lattice gauge theories. We simulate axial charge production in ${\mathbb{Z}}_N$ lattice gauge theories on the trapped-ion quantum computer “Reimei.” After taking the U(1), infinitesimal time, and infinite volume limits, we successfully reproduce the anomaly coefficient within statistical uncertainties, even without error mitigation. Our results demonstrate that the axial anomaly can be simulated on current quantum computers and serves as a verification test of quantum computations.

Understanding the emergence of macroscopic irreversible hydrodynamics from the reversible unitary dynamics of isolated quantum many-body systems remains a fundamental challenge. Conventional approaches often force spin density dynamics into purely diffusive models, obscuring the microscopic interplay of pressure, spin current, and local friction. Furthermore, reconciling true irreversibility with strictly unitary evolution raises fundamental questions about the role of the observer's temporal resolution. In this paper, we introduce a fully data-driven framework based on generalized extended dynamic mode decomposition integrated with the Mori-Zwanzig projection. By expanding the observable dictionary to explicitly include spin currents, we directly extract the Navier-Stokes hydrodynamic coefficients from a chaotic XXZ spin chain across varying temporal coarse-graining scales. Our unconstrained extraction reveals a clear physical dichotomy: The mechanical elasticity $\left(c^2\right)$ is intrinsically derived from the exact unitary dynamics, preserving strict microscopic reversibility. In contrast, the macroscopic friction $\left(\gamma \right)$ and kinematic viscosity $\left(\nu \right)$ exhibit zero net dissipation, oscillating rapidly around zero in the exact-derivative limit. We demonstrate that genuine macroscopic transport cannot be established without finite temporal coarse graining. By introducing a finite observation timescale $(\mathrm{\Delta }{t}_{\mathrm{cg}}>0)$, the system passes through a distinct crossover timescale where these reversible fluctuations average out, establishing an intermediate functional regime that yields strictly positive friction and viscosity. We further show that the coarse-grained generator constitutes a predictive reduced model requiring only $O\left(N\right)$ macroscopic observables, and that the sign of the emergent friction is inherited from the causal, forward-in-time direction of the coarse-grained inference: Time-symmetric estimators yield zero net dissipation at any coarse-graining scale. Our results demonstrate that macroscopic friction in isolated quantum systems is not an absolute property, but an emergent phenomenon dictated by the temporal resolution and the causal direction of the observer's coarse-grained description.

End-to-end pumps utilizing edge-localized states offer a promising route to operate as connecting buses, supplying efficient and robust connectivity between non-neighboring elements in a network. Here, we investigate a finite quasiperiodic Fibonacci-type photonic chain and demonstrate its ability for end-to-end pumping, with only small and simple changes to the system. First, we use a tight-binding formalism to numerically show that a localized pumping state can be transferred between opposite ends of the system, with only a small structural change to the chain. Then, we experimentally implement this end-to-end pump in an array of coupled optical waveguides, where light propagation is effectively described by the tight-binding model under the paraxial approximation, enabling direct correspondence between theory and experiment. We numerically simulate and experimentally demonstrate pumping by injecting light into a single waveguide at one end of the setup, which activates a localized pumping state. As the light propagates along the waveguide array, it is also pumped to the other end. We further show that pumping remains robust against structural deformation, such as controlled defects in the waveguide array. Our results establish that quasiperiodic Fibonacci-type photonic lattices are a robust and experimentally viable platform for disorder-resilient state transfer.

We investigate the nonequilibrium dynamics of core-hole excitations in a one-dimensional fermionic few-body system consisting of a spin-polarized Fermi bath coupled to a single heavy mobile impurity. The bath is initially prepared in a particle-hole configuration by emptying a selected bath single-particle orbital, while the impurity is displaced with respect to the center of the bath confinement potential. The quench dynamics are initialized by suddenly switching on the impurity-bath interaction. To resolve the resulting dynamics, we combine two complementary ab initio approaches, namely, the MultiLayer MultiConfiguration Time-Dependent Hartree method for mixtures and a multichannel Born-Oppenheimer framework. We show that the postquench response is governed by the interaction strength, impurity confinement, mass imbalance, and the location of the initially prepared hole within the Fermi sea. The density evolution and impurity center-of-mass motion reveal a competition between mixing and demixing of impurity and bath, while the von Neumann entropy demonstrates the buildup of pronounced many-body correlations. Most importantly, the occupation dynamics of the initially emptied orbital identifies deep core holes as substantially more robust against refilling than bulk or edge vacancies. Our results establish core-hole excitations as robust dynamical many-body features in trapped ultracold fermions and provide a controlled route toward probing orthogonality response, correlation buildup, and hole refilling in real time.

The size and organization of biomolecular condensates formed by liquid-liquid phase separation are set by multiple cellular mechanisms that are not yet fully understood. Here, we identify a transport-driven mechanism: Stochastic binding of phase-separating proteins to cytoskeletal motor proteins, followed by active redistribution along filament networks, generates an effective long-range repulsion that arrests coarsening and selects a finite condensate size. A minimal diffusion-transport model, analyzed by linear stability theory and three-dimensional simulations, reveals a transition from macroscopic to microphase separation at remarkably low binding/release fractions, corresponding to minute motor-bound populations. Tuning motor binding rates $b$ or transport velocities enables sublinear control of condensate sizes ($L\sim b^{-1/4}$) from a few hundred nanometers up to the micron scale. The selected length scale is robust to the intrinsic shot noise of the binding-release reactions. In anisotropic cytoskeletal environments, transport asymmetry drives morphological transitions from spherical to cylindrical condensates, independently of the thermodynamic parameters. This mechanism provides a versatile, spatiotemporally programmable route to condensate organization and informs the design of synthetic active emulsions with tunable architectures.

Demonstrating the practical utility of noisy intermediate-scale quantum hardware for recurrent tasks in computer-aided drug discovery is of paramount importance. We tackle this challenge by performing three-dimensional hydration-site prediction in protein pockets on a quantum computer. Formulating the water placement problem as a quadratic unconstrained binary optimization, we use a hybrid approach coupling a classical three-dimensional reference-interaction site model to an efficient quantum optimization solver to run various hardware experiments up to 123 qubits. Matching the precision of classical approaches, our results reproduced experimental predictions on real-life protein-ligand complexes. Furthermore, through a detailed resource estimation analysis, we show that accuracy can be systematically improved with increasing number of qubits, indicating that full quantum utility is within reach as devices scale in the near term. The method has potential for assisting simulations of protein-ligand complexes for drug lead optimization and setup of docking calculations.

Liquid-liquid phase separation underlies phenomena ranging from protein condensate formation to the phase coexistence of synthetic polymers. Although the random phase approximation (RPA) is widely used to predict such phase behavior, its quantitative accuracy for binodals of polymer solutions, particularly outside the high-density regime, remains incompletely characterized. Here, we develop a field-theoretic loop expansion in homopolymer systems by identifying the inverse polymer density ${\rho }^{-1}$ as the Planck constant $\hslash$ in quantum field theory. We calculate the leading-order and next-to-leading-order corrections to the RPA free energy, denoted as $\mathrm{RPA}+$ and $\mathrm{RPA}++$, respectively. Testing the binodal predicted by the $\mathrm{RPA}+$ against molecular dynamics simulations of bead-spring chains with Gaussian pair interactions, we find that the $\mathrm{RPA}+$ qualitatively improves the dilute-phase coexistence density over the RPA, while the critical point error remains comparable to that of the RPA. Our results establish the loop expansion as a systematic route for refining the RPA-based binodal predictions for polymer phase separation.

We present a combined density-functional theory and dynamical mean-field theory (DFT+DMFT) study of the full structural phase space of rutile-based vanadium dioxide $\left({\mathrm{VO}}_2\right)$, including also the less studied M2 and T phases, using an unconventional bond-centered orbital basis. The use of bond-centered orbitals allows us to treat all main phases of ${\mathrm{VO}}_2$, and the structural transitions between them, using one consistent approach with moderate computational cost and without prepattering of the structure into dimerized and undimerized V-V pairs. We obtain two distinct insulating states on the two different types of vanadium chains in the M2 phase, a singlet insulator on the dimerized chains and a Mott insulator on the zigzag-distorted chains, which, however, are strongly coupled in the M2 phase and thus the metal-insulator transition always occurs concomitantly for both types of sites. We also demonstrate that the M2 phase corresponds to a local energy minimum in the structural phase space of ${\mathrm{VO}}_2$, the stability of which, apart from the internal structural distortion, depends crucially on the unit cell strain relative to the undistorted rutile phase. Our calculations further indicate that the symmetry-distinct triclinic T phase corresponds electronically to either an M1- or an M2-type insulator with an abrupt transition as a function of distortion. Finally, we disentangle the effect of the dimerization and zigzag distortions by constructing hypothetical structures that contain only one site type, finding that the zigzag distortion strongly favors emergence of the Mott-insulating state, as a function of both distortion and on-site interaction.

Hole-spin qubits enable fast, all-electrical spin manipulation through electric-dipole spin resonance (EDSR), arising from two microscopic mechanisms rooted in their intrinsically strong spin-orbit interaction. Depending on how the electric field acts on the quantum dot, the spin can be driven either by a modulation of its $g$ factor or by a displacement of the wavefunction. Here, we demonstrate in situ control over the dominant EDSR driving mechanism of a hole-spin qubit in a silicon fin field-effect transistor by applying microwave signals to two different gate electrodes, thereby tuning the orientation of the local electric field. We measure the effective $g$ factor, its electrical tunability, and the Rabi frequency as functions of magnetic-field orientation. Their distinct angular dependencies, analyzed using a $g$-matrix formalism, allow us to identify the underlying driving processes and track their relative contributions for different drive configurations. By selecting the drive electrode, we can switch from a regime dominated by $g$-factor modulation to one with a strong contribution from wavefunction displacement. This in situ tunability provides direct experimental access to both spin-driving mechanisms and offers a route toward optimized spin-qubit performance.

Optimal processes in stochastic thermodynamics represent a frontier for understanding the control and design of nonequilibrium systems, with broad practical applications in biology, chemistry, and nanoscale/mesoscale systems. Optimal transport theory and thermodynamic geometry have emerged as leading optimal control methodologies, but both rely on slow-driving and close-to-equilibrium assumptions. An optimal control framework in stochastic thermodynamics for finite-time driving remains elusive. Here, we solve an optimal control problem for driving the control parameters of a discrete-state far-from-equilibrium process from an initial to a final value in finite time. Optimal driving protocols are derived that minimize the total finite-time dissipation cost of the driving process. Our framework reveals that discontinuous end-point jumps are a generic, model-independent physical mechanism that minimizes the optimal driving entropy production—“geometric thermodynamic far-from-equilibrium shortcuts in swift state-to-state transformations”—whose importance is further amplified in far-from-equilibrium systems. The thermodynamic and dynamical interpretation of discontinuous end-point jumps is formulated. An exact mapping between the finite-time and slow-driving optimal control formulations is elucidated, advancing the state of the art in optimal transport theory and thermodynamic geometry, which has been the prevailing paradigm for studying optimal processes in stochastic thermodynamics under slow-driving assumptions. Our framework opens up a broad range of applications to the thermodynamically efficient control of far-from-equilibrium systems in finite time, and thereby a route toward their efficient design principles.

Berry monopoles are point degeneracies in parameter space where the Berry curvature emanates radially, analogous to magnetic monopoles. Here, we report the adiabatic merging and splitting of Berry monopoles in a bilayer photonic crystal slab combining one genuine and one synthetic momentum. Two monopoles approach, merge, and split within this hybrid parameter space. The process is described by an effective coupled-mode model and confirmed by full-wave simulations. We further propose a scheme to experimentally probe the Berry monopole merging and splitting by monitoring the evolution of chiral edge states localized at the interface between two topological phases with inverted band structures.

We investigated the size dependence of the metal-insulator transition (MIT) in Cr-doped ${\mathrm{V}}_2{\mathrm{O}}_3$ nanocrystals by photoemission spectroscopy using complementary probing depths, together with magnetic susceptibility measurements. Photoemission spectra show that MIT signatures persist down to an average particle size of 5.6 nm, and magnetic susceptibility measurements exhibit a nearly size-invariant transition onset. The contrast between surface-sensitive and deeper-probing photoemission spectra reveals that the transition survives in the nanocrystal interior. At the same time, the spectra indicate a systematic suppression of coherent quasiparticle weight with decreasing size, pointing to the growth of an insulating surface dead layer. These results demonstrate that nanoscaling does not intrinsically eliminate the MIT itself, but progressively enhances the influence of surface-driven insulating behavior, thereby providing insight into the practical limits of miniaturizing Mott-based devices.

Data-driven machine learning has established a robust foundation for reconstructing nonlinear dynamical systems from observations, primarily for the purposes of forecasting and control. However, most existing efforts focus on recovering specific observed dynamics rather than the generative synthesis of new ones. Inspired by image fusion and style transfer, we introduce a neural network framework termed neural dynamical transfer learning (NDTL) to create new systems with prescribed dynamics from pairs of parent nonlinear dynamical systems. By computing fundamental dynamical signatures, including the intrinsic dimension, the Kaplan-Yorke dimension, the invariant measure statistics, and the Lyapunov spectrum, we demonstrate that NDTL preserves key features inherited from the parent models while simultaneously generating novel dynamics. Beyond these validation examples, NDTL induces a criterion for dynamics classification, creates stable oscillatory coexistence in the Hastings-Powell food chain model, produces interpretable epidemiological models, and provides a chaotic source for image encryption.