Ternary hydrides, owing to their chemical diversity and structural tunability, are considered important candidate systems for the exploration of high-temperature superconductivity. In this work, we performed systematic structure searches and superconductivity calculations on the $\mathrm{RbS}{\mathrm{c}}_2{\mathrm{H}}_x$ ternary system over pressures ranging from 150 to 300 GPa. Our results reveal that $\mathrm{RbS}{\mathrm{c}}_2{\mathrm{H}}_{16}$ adopts a highly symmetric cubic structure with space group Fd-$3m$, which is both dynamically and thermodynamically stable down to 150 GPa, featuring a hydrogen-based cage framework. Upon increasing hydrogen content, $\mathrm{RbS}{\mathrm{c}}_2{\mathrm{H}}_{17}$ forms a fully occupied cage structure with enhanced H-H interactions and strengthened Sc-H hybridization. Electron localization function, crystal orbital Hamilton population, and Bader charge analysis collectively indicate that the bonding is dominated by strong H-H covalent interactions, supported by ionic contributions from Sc-H bonds. Electronic structure calculations show pronounced metallicity with Sc-$3d$ and H-$1s$ hybridization dominating near the Fermi level, facilitating strong electron-phonon coupling. The superconducting critical temperatures estimated using the Allen-Dynes modified McMillan formula reach 140 K for $\mathrm{RbS}{\mathrm{c}}_2{\mathrm{H}}_{16}$ at 150 GPa and 190.7 K for $\mathrm{RbS}{\mathrm{c}}_2{\mathrm{H}}_{17}$ at 200 GPa, underscoring the crucial role of hydrogen occupancy in optimizing superconducting behavior. The results indicate that variations in hydrogen content have a noticeable effect on the stability and superconducting characteristics of the $\mathrm{RbS}{\mathrm{c}}_2{\mathrm{H}}_x$ system.

In noisy intermediate-scale quantum (NISQ) era, distributed quantum computing (DQC) has emerged as a promising direction to address limitations in qubit scalability and noise resilience. Entanglement forging is proposed as an important DQC protocol that enables the integration of the quantum computing resources and exhibits significant efficiency in realizing quantum states and dynamics with shallow entanglement. Here, we experimentally demonstrate the entanglement forging process for solving an eight-vertex Max-Cut problem. We execute parametrized quantum circuits on a four-qubit nuclear magnetic resonance quantum processor and successfully achieve the entanglement forging of the ground state for the eight-qubit Max-Cut Hamiltonian by using variational quantum eigensolver. The ground state reconstructed in experiment achieves a fidelity of 95.88% compared with theoretical prediction, which provides three correct solutions to the Max-Cut problem in parallel. Our work demonstrates the feasibility and efficiency of entanglement forging protocol in solving combinatorial optimization problems on NISQ devices, while also advancing the development of distributed quantum computing.

This manuscript reports on the commissioning of the Resonance Ionization Spectroscopy Experiment (RISE) at the BEam COoler and LAser spectroscopy (BECOLA) facility at Facility for Rare Isotope Beams (FRIB). The instrument implements the collinear resonance ionization spectroscopy technique for sensitive measurements of isotope shifts and hyperfine structure of short-lived isotopes produced at FRIB. The existing BECOLA beamline was extended to integrate an electrostatic ion-beam bender and an ion detector at ultrahigh vacuum. An injection-seeded titanium-sapphire laser and a multiharmonic pulsed neodymium-doped yttrium aluminum garnet laser were installed to perform resonant excitation and selective ionization. Commissioning tests were performed to demonstrate the capabilities of the instrument by measuring the hyperfine structure of stable ${}^{27}\mathrm{Al}$ produced in an offline ion source. The RISE instrument is ready and operational for future studies of short-lived isotopes at FRIB.

We investigate critical quantum metrology in a system where a qubit is dispersively coupled to a parametrically driven bosonic field. By engineering a counterdiabatic driving Hamiltonian under realistic physical constraints, we demonstrate a high-fidelity preparation of quantum states near a quantum phase transition. Our protocol extends the application of criticality-enhanced metrology to the short-time regime, offering a significant advantage over nonassisted protocols. The metrological precision is quantified by the quantum Fisher information (QFI) and the signal-to-noise ratio (SNR). Even with a constrained driving strength, numerical simulations reveal a QFI enhancement factor exceeding ${10}^3$ and an SNR enhancement of over ${10}^6$ in this regime. This work opens a promising avenue for critical quantum metrology.

Shot-to-shot fluctuations in electron beams from laser wakefield accelerators present a significant challenge for applications. Here, we show that instead of using such fluctuating beams directly, employing them to drive a plasma photocathode-based wakefield refinement stage can produce secondary electron beams with higher quality and greater stability. Our simulation-based analysis reveals that drive beam jitters are partially compensated by both the insensitivity of beam-driven plasma wakefield acceleration and the decoupled physics of plasma photocathode injection. While beam-driven, dephasing-free plasma wakefield acceleration mitigates energy and energy-spread fluctuations, intrinsically synchronized plasma photocathode injection compensates charge and current jitters of incoming electron beams, and provides a simultaneous quality boost. Our findings suggest that plasma photocathodes could be ideal injectors for hybrid laser-plasma wakefield accelerators, and nurture prospects for demanding applications such as free-electron lasers.

Indefinite causal order has been shown to enable nonclassical refrigeration, with recent experimental verification using an ensemble of nuclear spins in the nuclear magnetic resonance system that boosted prior coefficient of performance (COP) through the approach of density matrix exponentiation (DME). In this paper, we demonstrate an approach to improve the COP of this setup by incorporating an information pool of qubits to absorb the entropic cost of refrigeration. If these qubits are reused until their resources are expended, an increase of the COP beyond the DME approach can be achieved in certain temperature ranges. This improvement is found to hold even for the case when the working body is hotter than the cold bath, and in the prethermalization regimes where further enhancements can be observed. Our work thus introduces a technique to enhance quantum refrigeration with indefinite causal order.

We show that a three-state discrete-time quantum walk (DTQW) on a square lattice, with an SU(3) coin, realizes stroboscopic Floquet phases that host dispersive topological bound states in the continuum (TBICs). Time-independent step operations act as the periodic drive and map the one-step unitary to an effective Floquet Hamiltonian. Chern-number calculations resolve three quasienergy bands and their phase boundaries as the rotation angles are varied, and bulk-boundary correspondence in semi-infinite and fully finite geometries accounts for the edge spectra. At interfaces between media with the same bandwise Chern numbers but different coin parameters, nonchiral edge modes become embedded yet localized TBICs with tunable group velocity and selective excitation, while numerics indicate robustness to moderate coin disorder. Together with feasible routes in trapped-ion, cold-atom, and photonic platforms and an explicit decoherence model, these results identify DTQWs as a controllable setting for protected quantum-state transport and storage, relevant to quantum information and communication technologies.

The generation of unidirectional motion has been a long-standing challenge in engineering of molecular motors. Here, a mechanism driving the rotation is presented based on electron current through helical orbitals on a $\pi$-bonded carbon chain. Such electron current through helical orbitals has been shown to be circulating around the carbon chain. It is natural to expect that the associated electronic angular momentum drives a rotation when the current is turned on. As intuitive as this relation might seem, it is also incomplete because a formal definition of helicality in terms of a physical observable has not yet been given. Such a definition is proposed here. Based on this definition, we show how helicality determines the motor’s sense of rotation. We exemplify the relation between helicality and angular momentum in Hückel models of linear carbon chains (cumulenes and oligoynes). We attribute the previously reported opposite helicality sense of frontier orbitals (highest occupied molecular orbital and lowest unoccupied molecular orbital) to the approximate sublattice symmetry. For oligoynes, this symmetry is hidden in the sense that it does not reduce to a mere labeling of atoms. Sublattice symmetry, combined with time-reversal invariance, allows us to derive Onsager-type reciprocal relations of various linear response coefficients, dictating, e.g., an odd energy dependence of angular momentum response to voltage bias. We propose an observable consequence of the approximate sublattice symmetry: If the carbon chain is employed as an axle of a molecular rotor, the sense of rotation is independent on the direction of the current.

Introducing a lubricant layer between a fluid and a solid substrate endows slippery liquid-infused surfaces (SLISs) with excellent interfacial properties, such as a low sliding angle, repellency toward various liquids, icephobicity, and self-healing capability. Previous studies found that the friction force of a sliding drop on SLISs obeys the Landau-Levich-Derjaguin (LLD) theory, i.e., $F_{\eta }\sim {\text{Ca}}^{2/3}$, with $\text{Ca}$ being the capillary number. In this paper, however, our experiments show that this scaling law holds only at low capillary numbers. We find a distinct decrease in the scaling exponent as the drop accelerates: In the rapid sliding regime, SLISs demonstrate even greater slipperiness than that predicted by the LLD theory. Numerical simulations reveal that this unexpected behavior originates from the incompletely developed state of the back meniscus, while the influence of the front meniscus is insignificant. Compared with the prediction of the Bretherton model, the back meniscus possesses a shorter shear length and a thicker shear layer, therefore reducing friction and enhancing surface slipperiness. An analytical solution is derived to describe the incompletely developed meniscus. This work offers insights into the abnormal frictional behavior when the capillary number of a moving drop exceeds $4\times {10}^{-3}$.

We present a shadow-tomography-enhanced nonorthogonal quantum eigensolver (NOQE) for more efficient and accurate electronic structure calculations on near-term quantum devices. By integrating shadow tomography into the NOQE, the measurement cost scales linearly rather than quadratically with the number of reference states, while also reducing the required qubits and circuit depth by half. This approach enables extraction of all matrix elements via randomized measurements and classical postprocessing. We analyze its sample complexity and show that, for small systems, it remains constant in the high-precision regime, while for larger systems, it scales linearly with the system size. We further apply shadow-based error mitigation to suppress noise-induced bias without increasing quantum resources. Demonstrations on the hydrogen molecule in the strongly correlated regime achieve chemical accuracy under realistic noise, showing that our method is both resource-efficient and noise-resilient for practical quantum chemistry simulations in the near term.

The brain rapidly adapts to new contexts and learns from limited data, a coveted characteristic that artificial intelligence (AI) algorithms struggle to mimic. Inspired by the mechanical oscillatory rhythms of neural cells, we developed a learning paradigm utilizing link strength oscillations, where learning is associated with the coordination of these oscillations. Link oscillations can rapidly change coordination, allowing the network to sense and adapt to subtle contextual changes without supervision. The network becomes a generalist AI architecture, capable of predicting dynamics of multiple contexts, including unseen ones. These results make our paradigm a powerful starting point for models of cognition. Because our paradigm is agnostic to specifics of the neural network, our study opens doors for introducing rapid adaptive learning into leading AI models.

Variational quantum algorithms are often hindered by rugged optimization landscapes. In this work, we investigate the low-weight Pauli propagation (LWPP) algorithm and find that it serves as an unreliable energy estimator for variational circuits. However, we reveal a counterintuitive insight: The Pauli-weight truncation acts as a spectral filter, effectively smoothing out high-frequency local minima while preserving the global basin of attraction in the landscape. We identify this mechanism as landscape alignment, where the approximate landscape becomes a superior navigator compared to the rugged exact landscape. Benchmarks across diverse spin models and molecular systems demonstrate that LWPP-initialized optimization yields order-of-magnitude improvements in accuracy, often finding solutions inaccessible to direct exact optimization. This work reframes LWPP from a flawed simulator into a vital preoptimizer that serves not only as a cheap classical substitute but also as an essential tool for addressing quantum optimization challenges.

The effective Flory-Huggins parameter ${\chi }_e$ is one of the most important characteristics of any multicomponent polymer system. This parameter characterizes the free energy of interaction between monomers of different types and controls the phase behavior of polymer mixtures. In this work, we developed a perturbation theory and derived how ${\chi }_e$ depends on the details of an arbitrary coarse-grained polymer model. After defining ${\chi }_e$ in this way, we found that the models of symmetric polymer blends and diblock copolymer melts behaved universally: Their phase transition points, free energies, and mesoscopic invariant structure factors depended solely on the chain architecture, the invariant chain length $\overline{N}$, and the interaction parameter ${\chi }_{e}N$. To parametrize our perturbative expression for ${\chi }_e$, only the effective coordination number distribution in a reference homogeneous system needs to be measured. This distribution, in turn, can be directly mapped onto coarse-grained model parameters set prior to simulation, which clarifies how model construction influences ${\chi }_e$. Our definition of ${\chi }_e$ enables straightforward quantitative comparison of models with each other and with experiments, which will facilitate the computational design of multicomponent polymer materials.

We show that adding quadratic temporal dispersion to a dynamic-vacuum acoustic model yields a fully analytic, exactly isospectral mapping to the hydrogenic Coulomb problem. In the regime $\omega =D{q}^2$ with $D=\hslash /\left(2m_{\mathrm{eff}}\right)$, a proton-imprinted constitutive profile produces an inverse sound speed $1/c_s^2\left(r\right)=A\left(\omega \right)+C\left(\omega \right)/r$ and hence a time-harmonic operator $({\nabla }^2+k_{\mathrm{eff}}^2)$ that is Coulombic at each bound eigenfrequency. Separation of variables yields the exact hydrogenic eigenfunctions $R_{n\ell }\left(r\right)Y_{\ell }^m(\theta ,\varphi )$; the angular labels $(\ell ,m)$ emerge naturally from the Laplace-Beltrami spectrum on ${\mathbb{S}}^2$ via rotational symmetry and boundary conditions (as in standard quantum mechanics), while localization follows from $A\left({\omega }_n\right)<0$ in a reactive stop band consistent with causal, passive dispersion. While angular-momentum quantization follows directly from rotational symmetry and boundary conditions in standard quantum mechanics (consistent with Noether's theorem), here it emerges within a classical-like dispersive acoustic framework without introducing additional wave-mechanical postulates beyond symmetry and self-adjointness. This highlights dispersion's role in bridging a hydrodynamic description to quantumlike spectral structure. Identifying $q_n\equiv {\kappa }_n$ maps spatial scale to frequency, giving ${\omega }_n=D{\kappa }_n^2\propto 1/n^2$ and reproducing the Rydberg ladder. Calibration to the reduced-mass Rydberg frequency (${\omega }_{*}=2\pi c{R}_H$) fixes $D=\hslash /\left(2\mu \right)$ and $m_{\mathrm{eff}}=\mu$, with no free parameters. We determine the frequency dependence of $A\left({\omega }_n\right)$ and $C\left({\omega }_n\right)$ consistent with the underlying dispersive physics and demonstrate agreement with hydrogenic mode shapes and transition lines. The framework also predicts isotope shifts $[\mu \to \mu (M\left)\right]$ and symmetry-respecting Stark/Zeeman analogues. Dispersion thus renders quantization an emergent consequence of symmetry, boundary conditions, and causal response in a dynamic vacuum.

Anyons are quasiparticles with fractional charge and statistics that arise in strongly correlated two-dimensional systems such as the fractional quantum Hall effect and fractional Chern insulators. Interactions between anyons can lead to emergent phenomena, such as anyon superconductivity as well as anyon condensation that allows for a hierarchical construction of quantum Hall states. In this work, we study how quasihole anyons in a $\nu =1/3$ Laughlin fractional quantum Hall state can be bound together by a sufficiently strong attractive impurity potential. The competition between the repulsive interaction between the quasiholes themselves and the attractive interaction between the quasiholes and the impurity leads to states with different numbers of quasiholes bound to the impurity. Tuning the chemical potential via gating while remaining within a quantum Hall plateau changes the number of quasiholes bound to the impurity. We propose methods for studying these states experimentally, for example, using scanning tunneling microscopy and exciton spectroscopy. While the impurities in traditional platforms such as GaAs heterostructures are typically too weak to observe the binding of anyons, the recently discovered zero-field fractional Chern insulators in twisted ${\mathrm{MoTe}}_2$ offer a platform that may realize the strong-impurity regime.

In this work, we put forward the inclusion of error mitigation routines in the process of training variational quantum circuit (VQC) models. In detail, we define a real-time quantum error mitigation (RTQEM) algorithm to assist in fitting functions on quantum chips with VQCs. While state-of-the-art QEM methods cannot address the exponential loss concentration induced by noise in current devices, we demonstrate that our RTQEM routine can enhance VQCs’ trainability by reducing the corruption of the loss function. We tested the algorithm by simulating and deploying the fit of a monodimensional $u$-quark parton distribution function on a superconducting single-qubit device, and we further analyzed the scalability of the proposed technique by simulating a multidimensional fit with up to eight qubits.