We propose a hybrid quantum device based on the graphene Josephson junctions, where the vibrational degrees of freedom of a graphene membrane couple to the superconducting circuits. The flexural mode-controlled tunneling of the Cooper pairs introduces a strong and tunable coupling even at the zero-point fluctuation level. By employing this interaction, we show that a parametric process can be efficiently implemented. We then investigate foundational and technological applications of our hybrid device empowered by nonlinear interactions, with fast generation of nonclassical mechanical states, and critically enhanced quantum sensing under suitable quantum control. Our work provides the possibility of employing the graphene motional degree of freedom for quantum information processing in circuit quantum nanomechanical structures.

For several decades, experimental and computational studies have been used to investigate the potential functional role of knots in protein structures. A property that has attracted considerable attention is thermal stability, i.e., the extent to which a protein retains its native conformation and biological activity at high temperatures, without undergoing denaturation or aggregation. Thermal stability is quantified by the melting temperature $T_m$, an equilibrium property that corresponds to the peak of heat capacity in differential scanning calorimetry (DSC) experiments. Experimental and computational studies report conflicting effects of knotting on protein thermal stability [M. A. Soler and P. F. N. Faísca, PLoS One 8, e74755 (2013);Y.-C. Chuang, I.-C. Hu, P.-C. Lyu, and S.-T. D. Hsu, J. Mol. Biol. 431, 857 (2019)]. Here, we use extensive Monte Carlo simulations of a simple C-alpha model of protein YibK, with energetics modeled by the Go potential, to show that $T_m$ does not depend on the topological state of the protein. Our simulations further support the view that the discrepancy between the experimental and computational results stems from a pronounced separation of timescales for unknotting and unfolding that is inherent to deeply knotted proteins like YibK. In particular, the timescale separation implies that the complete unfolding-untying transition may not be accessible within the duration of a DSC experiment, whose apparent $T_m$ measurements likely reflect a nonequilibrium distribution lacking unfolded states that are also unknotted.

Trust is one of the cornerstones of human society. One of the evolutionary pressure mechanisms that may have led to its emergence is the presence of incentives for trustworthy behavior. However, this type of reward has received relatively little attention in the context of spatial trust games, which are often used to build models in evolutionary game theory. To fill this gap, we introduce an inter-role reward mechanism in the spatial trust game, so that an investing trustor can choose to pay an extra cost to reward a trustworthy trustee. With extensive numerical simulations, we find that this type of reward does not always promote trust. Rather, while moderate rewards break the dominance of mistrust, thereby favoring investment, excessive rewards eventually stimulate a nonreturn strategy, ultimately suppressing the evolution of trust. Additionally, lower reward costs do not necessarily promote trust. Instead, more costly, but not excessive, rewards enhance the advantage of the original investment, consolidating the clusters of rewarders and improving trust. Our model thus provides evidence about the counterintuitive nature of the relationship between trust and rewards in a complex society.

Many physical, biological, and even social systems are faced with the problem of how to efficiently harvest free energy from an environment that can have many possible states, yet only have a limited number of harvesting protocols to choose among. We investigate this scenario by extending earlier work on using feedback control to extract work from nonequilibrium systems. Specifically, in contrast to that previous work on the thermodynamics of feedback control, we analyze the combined and separate effects of noisy measurements, memory limitations, and limitations on the number of possible work extraction protocols. Our analysis provides a general recipe to construct repertoires of allowed harvesting protocols that minimize the expected thermodynamic losses during free energy harvesting, i.e., that minimize expected entropy production. In particular, our results highlight that the benefits of feedback control over uninformed (random) actions extend beyond just the associated information gain, often by many orders of magnitude. Our results also uncover the effects of limitations on the number of possible harvesting protocols when there is uncertainty about the distribution over states of the environment.

Sharing logical entangled pairs between distant quantum nodes is a key process to achieve fault-tolerant quantum computation and communication. However, there is a gap between current experimental specifications and theoretical requirements for sharing logical entangled states while improving experimental techniques. Here, we propose an efficient logical entanglement distribution protocol based on surface codes for two distant two-dimensional qubit array with nearest-neighbor interaction. A notable feature of our protocol is that it allows postselection according to error estimations, which provides the tunability between the infidelity of logical entanglements and the success probability of the protocol. With this feature, the fidelity of encoded logical entangled states can be improved by sacrificing success rates. We numerically evaluated the performance of our protocol and the trade-off relationship, and found that our protocol enables us to prepare logical entangled states while improving fidelity in feasible experimental parameters. We also discuss a possible physical implementation using neutral atom arrays to show the feasibility of our protocol.

Recently, the isolation of two-dimensional magnetic materials has opened several avenues for possible applications in spintronics. Among these materials, CrSBr has sparked interest due to its relatively high Curie temperature, highly anisotropic lattice structure, and high structural stability. These properties run along with others shared by any atomically thin material such as its outstanding deformation capacity and a strong optical response dominated by excitonic effects. The combination of these properties provides a fairly uncharted playground to explore the interplay between magnetism and optical excitations. Here, we focus our attention on the theoretical optical response of CrSBr under several distinct strain configurations, analyzing the resulting changes to both the excitonic peaks and overall shape of the diagonal components of the linear conductivity tensor.

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.