We predict superconductivity for the carbon–boron clathrate ${\mathrm{SrB}}_3{\mathrm{C}}_3$ with $T_c=27\text{–}43\mathrm{K}$ for Coulomb pseudopotential (${\text{μ}}^{*}$) values between 0.17 and 0.10 using first-principles calculations with conventional electron–phonon coupling. Electrical transport measurements, facilitated by an in situ experimental design compatible with extreme synthesis conditions ($>3000\mathrm{K}$ at 50 GPa), show nonhysteretic resistivity drops that track the calculated magnitude and pressure dependence of superconductivity for ${\text{μ}}^{*}\approx 0.15$, and transport measurements collected under applied magnetic fields indicate superconductivity with an onset $T_c$ of approximately 20 K at 40 GPa. Carbon-based clathrates thus represent a class of superconductors similar to other covalent metals like ${\mathrm{MgB}}_2$ and doped fullerenes. Carbon clathrates share structures similar to superconducting superhydrides with wide potential for tunable properties, and covalent C–B bonds allow metastable persistence at ambient conditions.

Power-law distributions appear in a large variety of situations and influence our understanding of various physical phenomena. Their identification and characterization are notoriously difficult because of the large fluctuations inherent to empirical data and also because of the unknown range over which the power-law behavior holds. Furthermore, the data on which one is trying to detect power laws are affected by technical constraints and experimental limitations. Here, we show how a power-law distribution is modified by two fundamental limitations: the spatiotemporal resolution and the time window. We consider a time series of events or states and investigate the interevent time probability density function (PDF) or the PDF of the duration of a state. We present in detail how each limitation affects the PDF and derive mathematical expressions that relate the observed distribution to the true one: the resolution globally affects the shape of PDF while preserving the asymptotic exponent and the time window introduces a nonexponential cutoff. We demonstrate that, instead of looking for a simple power law in experimental data, one should fit the data with the modified PDF that we derived for given experimental constraints. We apply our theory to data from an experimental study of the transport of mRNA-protein complexes along dendrites. The presented mathematical theory widens our understanding of the identification and characterization of power-law distributions in experimental data and can be used in a broad spectrum of science fields.

Coherent control of traveling acoustic excitations in a waveguide system is an interesting way to manipulate and transduce classical and quantum information. So far, these interactions, often based on optomechanical resonators or Brillouin scattering, have been studied in the steady-state regime using continuous waves. However, waveguide experiments are often based on optical pump pulses, which require treatment in a dynamic framework. In this paper, we present an effective Hamiltonian formalism in the dynamic regime using optical pulses that links waveguide optomechanics and cavity optomechanics, which can be used in the classical and quantum regime including quantum noise. Based on our formalism, a closed solution for coupled-mode equation under the undepleted assumption is provided and we found that the strong coupling regime is already accessible in current Brillouin waveguides by using pulses. We further investigate several possible experiments within waveguide optomechanics, including Brillouin-based coherent transfer, Brillouin cooling, and optoacoustic entanglement.

We present an agent-based model (ABM) of a financial market with $n>1$ risky assets, whose price dynamics result from the interaction between rational fundamentalists and trend-following imitative noise traders. The interactions and opinion formation of the noise traders are described by an extended $O\left(n\right)$ vector model, which generalizes the Ising model used previously in ABMs with a single risky asset. Efficient rejection-free transition probabilities are derived to describe realistic investment decisions at the microlevel of individual noise traders. The ABM is validated by testing for several characteristics of financial markets such as volatility clustering and fat tails of the distribution of returns. Furthermore, the model is able to account for the development of endogenous bubbles and crashes. We distinguish three different regimes depending on the traders' propensity to imitate others. In the subcritical regime of the $O\left(n\right)$ vector model, the traders' opinions are idiosyncratic and no bubbles emerge. Around the critical value of the $O\left(n\right)$ vector model, cross-sectionally asynchronous bubbles emerge. Above the critical value, small random price fluctuations may be amplified by noise traders herding into a given asset, which then impels fundamentalists to reequilibrate their more valuable portfolios that have become unbalanced, thus pushing the prices of the other assets upward. The resulting transient increase of the momenta of these assets triggers a reorientation of the noise traders' portfolios that further amplifies the burgeoning bubbles. We have thus identified a mechanism by which the cautious risk-adverse contrarian rebalancing strategy of fundamentalists leads to systemic risks in the form of cascades of bubbles spreading the whole financial market.

Perovskite nickelates possess an intimate connection among the structural, electronic, and magnetic orders. We investigate how crystal-field disorder induced by cation size variance impacts the emergence of macroscopic magnetic, structural, and electronic behaviors in single crystal high-entropy oxide nickelate films. The degree of variation in cation sizes hosted on the lattice is found to strongly influence critical ordering temperatures. Resonant x-ray scattering and density functional theory describe how high-variance systems produce local lattice distortions that can be used to manipulate charge disproportionation. The disorder induced shifts to local structure are shown to function as a critical order parameter capable of decoupling the nickelates’ distinctive magnetic ground state and metal-insulator transition from its charge ordered state, making it possible to stabilize room-temperature ordered phases not observed in low-variance ternary compounds.

Here, we propose an idea to realize noncollinear ferrimagnetic orders with a considerably high magnetization $\mathbf{M}$ and their coupling with an improper ferroelectric (FE) order in hexagonal ${\mathrm{LuFeO}}_3$ type systems which exhibit interesting topological orders. These magnetic and magnetoelectric phenomena are driven by the antisymmetric Dzyaloshinskii-Moriya interactions between the magnetic ions and their coupling with the ferroelectricity. The proposed two-sublattice magnetic system, generated by a specific charge-ordered state, forms multiple energetically close, noncollinear ferrimagnetic orders. This offers a platform to manipulate the microscopic magnetic interactions and to trigger spin-reorientation (SR) transitions by various efficient means. The two-sublattice structure was realized in the hexagonal phase of ${\mathrm{LuFeO}}_3$ doped with electrons. The proposed electron-doped systems are expected to exhibit switchable electric polarization ($P\sim 6–15 \mu \mathrm{C}/{\mathrm{cm}}^2$), considerably high magnetization ($M\sim 1.1–1.3{\mu }_B/\mathrm{Fe}$), and magnetic transition near room temperature ($\sim 275–290\mathrm{K}$). Based on the coupling between the magnetic interactions and the FE primary order parameter observed in this system, microscopic mechanisms to achieve electric field $\mathbf{E}$ induced SR transitions and ${180}^{\circ }$ switching of the direction of $\mathbf{M}$ are discussed.

A topological mechanism of the emergence of chimeralike oscillation modes (CLOMs) consisting of coherent synchronous firings and incoherent nonsynchronous oscillations is proposed in excitable scale-free networks (ESFNs). It is revealed that the topology heterogeneity of the network is responsible for forming and maintaining the CLOM in the ESFN, which is definitely different from the mechanism of the normal oscillation mode (NOM) possessing only a single dynamical mode in homogeneous excitable systems. An effective-driving approach is proposed, which provides a criterion for the formation of the CLOM in excitable complex networks. Our contributions may shed light on a perspective of CLOMs in complex systems, and can help us understand competitions and self-organizations of NOM and CLOM in excitable systems with topological homogeneity and heterogeneity.

Analysis of high-resolution time series data from the human and mouse gut microbiomes revealed that the gut microbial dynamics can be characterized by several simple scaling laws. It is still unknown if those scaling laws are universal across different habitats, e.g., different body sites, host species, or even free-living microbial communities. Moreover, the underlying mechanisms responsible for those scaling laws remain poorly understood. Here, we demonstrate that those scaling laws are not unique to gut microbiome, but are universal across different habitats, from human skin and oral microbiome to marine plankton bacteria and eukarya communities. Moreover, we find that completely shuffled time series yield very similar scaling laws (up to the change of some exponent values), which prompts us to conjecture that the universal scaling laws in various microbiomes are largely driven by temporal stochasticity of the host or environmental factors. To quantify the temporal stochasticity of those microbiome time series, we perform noise type analysis, finding that the noise types for those time series are all dominated by white and pink noises, indicating their very weak temporal structure and strong temporal stochasticity. Finally, we leverage a simple population dynamics model with both deterministic interspecies interactions and stochastic noise to confirm our conjecture. In particular, we find that the emergence of those scaling laws is jointly determined by interspecies interactions and linear multiplicative noises. The presented results deepen our understanding of the nature of scaling laws in microbial dynamics.

Radiative damping is a strong dissipation source for the quantum emitters hybridized with propagating photons, electrons, or phonons, which is not easily avoidable for on-chip magnonic emitters as well that can radiate via the surface acoustic waves of the substrate. Here we demonstrate in an array of on-chip nanomagnets coupled in a long range via exchanging the surface acoustic waves that a point defect in the array, which can be introduced by the local magnon frequency shift by a local biased magnetic field or the absence of a magnetic wire, strongly localizes the magnons, in contrast to the well spreading Bloch-like collective magnon modes in such an array setting. The radiation of the magnon defect states is exponentially suppressed by the distance of the defect to the array edges. Moreover, this defect state is strikingly inertial to the non-Hermitian topology that localizes all the extended states at one boundary. Such configuration robust magnon defect states towards radiation-free limit may be suitable for high-fidelity magnon quantum information storage in the future on-chip magnonic devices.

The supersolid phase characterized by the superfluid and long-range spatial periodicity of crystalline order is central to many branches of science ranging from condensed matter physics to ultracold atomic physics. Here we study a self-ordered checkerboard supersolid phase originating from dynamical spin-orbit coupling for a transversely pumped atomic Bose-Einstein condensate trapped in a ring cavity, corresponding to a superradiant anti-Tavis-Cummings phase transition. In particular, an undamped gapless Goldstone mode is observed in contrast to the experimentally realized lattice supersolid with a gapped roton mode for Dicke superradiance. This zero-energy mode reveals the rigidity of the self-ordered superradiant phase, which spontaneously breaks a continuous translational symmetry. Our work will highlight the significant opportunities for exploring long-lived supersolid matter by utilizing dynamical spin-orbit coupling in controllable optical cavities.

The bulk photovoltaic (BPV) effect, a second-order nonlinear process that generates static current under light irradiation, requires centrosymmetric broken systems as its application platform. To realize measurable BPV photocurrent in spatially centrosymmetric materials, various schemes such as chemical doping, structural deformation, or electric bias have been developed. In this paper, we suggest that the magnetic proximity effect via van der Waals (vdW) interfacial interaction, a contact-free strategy, also breaks the centrosymmetry and generates large BPV currents. Using the ${\mathrm{Bi}}_2{\mathrm{Te}}_3$ quintuple layer as an exemplary material, we show that magnetic proximity effect from $\mathrm{Mn}{\mathrm{Bi}}_2{\mathrm{Te}}_4$ septuple layers yields a finite and tunable shift and injection photocurrents. We apply group theory and first-principles calculations to evaluate the layer-specific shift and injection current generations under linearly polarized light irradiation. We find that the magnetic injection photoconductivity that localized on the ${\mathrm{Bi}}_2{\mathrm{Te}}_3$ layer can reach $>70\times {10}^8\mathrm{A}/\left({\mathrm{V}}^2\mathrm{s}\right)$, so that a one-dimensional linear current density on the order of 0.1 mA/nm can be achieved under an intermediate intensity light. In addition to charge current, we also extend our discussions into spin BPV current, giving pure photogenerated spin current. The vertical propagation direction between the charge and spin photocurrents suggests that they can be used individually in a single material. Compared with previously reported methods, the magnetic proximity effect via vdW interface does not significantly alter the intrinsic feature of the centrosymmetric material (e.g., ${\mathrm{Bi}}_2{\mathrm{Te}}_3$), and its manipulation can be easily achieved by the proximate magnetic configurations (of $\mathrm{Mn}{\mathrm{Bi}}_2{\mathrm{Te}}_4$), interlayer distance, and light polarization.

We investigate the nature of the quantum phase transition out of density-wave phase in a spinless fermion model with nearest- and next-nearest-neighbor interaction at one-third filling. Using extensive density matrix renormalization group (DMRG) simulations, we show that the transition changes it nature. For weak next-nearest-neighbor coupling the transition is of Kosterlitz-Thouless type, in agreement with bosonisation predictions. For large next-nearest-neighbor repulsion we provide numerical evidences that the transition belongs to the Pokrovsky-Talapov univerality class describing a nonconformal commensurate-incommensurate transition. We argue that the change of the nature of the transition is a result of incommensurability induced by frustration and realized even at zero doping. The implications in the context of the $XXZ$ chain with next-nearest-neighbor Ising interaction is briefly discussed.

Moiré patterns made of two-dimensional (2D) materials represent highly tunable electronic Hamiltonians, allowing a wide range of quantum phases to emerge in a single material. Current modeling techniques for moiré electrons require significant technical work specific to each material, impeding large-scale searches for useful moiré materials. In order to address this difficulty, we have developed a material-agnostic machine learning approach and test it here on prototypical one-dimensional (1D) moiré tight-binding models. We utilize the stacking dependence of the local density of states (SD-LDOS) to convert information about electronic band structure into physically relevant images. We then train a neural network that successfully predicts moiré electronic structure from the easily computed SD-LDOS of aligned bilayers. This network can satisfactorily predict moiré electronic structures, even for materials that are not included in its training data.