A quantum transducer, when working as a microwave and optical entanglement generator, provides a practical way to coherently connect optical communication channels and microwave quantum processors. Recent experiments on a quantum transducer verifying entanglement between the microwave and optical photons show the promise of approaching that goal. While flying optical photons can be efficiently controlled or detected, the microwave photon needs to be stored in a cavity or converted to the excitation of a superconducting qubit for further quantum operations. However, it remains challenging to efficiently capture or detect a single microwave photon with an arbitrary time profile. This work focuses on this challenge in the setting of an entanglement-based quantum transducer and proposes a solution by shaping the optical pump pulse. By Schmidt decomposing the output entangled state, we show that the microwave-optical photon pair takes a specific temporal profile that is controlled by the optical pump. The microwave photon from the transducer can be nearly perfectly absorbed by a receiving cavity with tunable coupling and is ready to be converted to the excitation of superconducting qubits, enabling further quantum operations.

Quantum state preparation (QSP) is an essential step in many quantum information processing tasks and has been deeply studied in a closed system. However, environmental noise inevitably destroys the quantumness of the system, resulting in decreased fidelity. In this work, we investigate the enhancement of fidelity by pulse control for arbitrary single or two-qubit QSP in a noisy environment. The control pulses are designed by leveraging supervised learning. The environment is modeled as a collection of bosons, and we use the quantum state diffusion equation technique to deal with the dynamics of the system. We consider two types of noise: quasistatic noise and dynamic noise. We propose active and adaptive denoising schemes for the quasistatic and dynamic noise, respectively. The environmental parameters are required to construct the dataset when training the neural network (NN) in adaptive denoising, while they are not needed in active denoising. The adaptive denoising scheme is universal in that it can be effectively applied to both quasistatic and dynamic noises. High-fidelity QSP has been obtained by the well-trained NN. Our work demonstrates that machine learning has great potential in optimal pulse design in a dynamic environment.

Anticipating a tipping point, a transition from one stable steady state to another, is a problem of broad relevance due to the ubiquity of the phenomenon in diverse fields. The steady-state nature of the dynamics about a tipping point makes its prediction significantly more challenging than predicting other types of critical transitions from oscillatory or chaotic dynamics. Exploiting the benefits of noise, we develop a general data-driven and machine-learning approach to predicting potential future tipping in nonautonomous dynamical systems and validate the framework using examples from different fields. As an application, we address the problem of predicting the potential collapse of the Atlantic meridional overturning circulation, possibly driven by climate-induced changes in the freshwater input to the North Atlantic. Our predictions based on synthetic and currently available empirical data place a potential collapse window spanning from 2040 to 2065, in consistency with the results in the current literature.

Neutrinoless double beta decay is one of the most sensitive probes for new physics beyond the Standard Model of particle physics. One of the isotopes under investigation is ${}^{136}\mathrm{Xe}$, which would double beta decay into ${}^{136}\mathrm{Ba}$. Detecting the single ${}^{136}\mathrm{Ba}$ daughter provides a sort of ultimate tool in the discrimination against backgrounds. Previous work demonstrated the ability to perform single atom imaging of Ba atoms in a single-vacancy site of a solid xenon matrix. In this paper, the effort to identify signal from individual barium atoms is extended to Ba atoms in a hexa-vacancy site in the matrix and is achieved despite increased photobleaching in this site. Abrupt fluorescence turn-off of a single Ba atom is also observed. Significant recovery of fluorescence signal lost through photobleaching is demonstrated upon annealing of Ba deposits in the Xe ice. Following annealing, it is observed that Ba atoms in the hexa-vacancy site exhibit antibleaching while Ba atoms in the tetra-vacancy site exhibit bleaching. This may be evidence for a matrix site transfer upon laser excitation. Our findings offer a path of continued research toward tagging of Ba daughters in all significant sites in solid xenon.

The search for objects that yield maximum electromagnetic chirality in their emitted wave field has gathered significant attention in recent years. However, achieving such maximum chirality is challenging, as it typically requires complex chiral metamaterials. Here, we demonstrate that chiral spheres can yield maximum chirality in their emitted wave field. Specifically, we analytically find the spectral trajectories at which chiral spheres become optically transparent to a given helicity of the incident field, while for its opposite helicity, they behave as dual objects, i.e., on scattering, they preserve helicity. Since chiral spheres behave as dual objects at the first Kerker condition of zero backscattering, we significantly simplify this condition in terms of a Riccati-Bessel function. Our analytical findings suggest the creation of spherical building blocks for designing metasurfaces or metamaterials with maximum electromagnetic chirality properties.

In this paper, we investigate a design approach of reinforcement learning to engineer a gyroscope in an optical lattice for the inertial sensing of rotations. Our methodology is not based on traditional atom interferometry, that is, splitting, reflecting, and recombining wavefunction components. Instead, the learning agent is assigned the task of generating lattice shaking sequences that optimize the sensitivity of the gyroscope to rotational signals in an end-to-end design philosophy. What results is an interference device that is completely distinct from the familiar Mach-Zehnder-type interferometer. For the same total interrogation time, the end-to-end design leads to a twentyfold improvement in sensitivity over traditional Bragg interferometry.

The formation of germanene on Ag(111) has been extensively studied and confirmed. However, the nature of the transition stage between the initial $\mathrm{A}{\mathrm{g}}_2\mathrm{Ge}$ alloy phase at 1/3 monolayer (ML) and the final quasifreestanding phase germanene phase at coverage $\ge 1$ ML still remains elusive. Using angle-resolved photoemission spectroscopy, scanning-tunneling microscopy (STM), and low-energy electron diffraction, we confirm the existence of striped-phase (SP) germanene in the transition stage. Along the armchair direction of SP, the period of higher-order coincidence corresponds to $11a_{\mathrm{AC}}=31a_{\mathrm{Ag}\left(111\right)}$, which accommodates four stripes on the bridge sites of the underlying Ag(111) lattice, as manifested in STM topography. On the electronic-structure side, the splitlike surface band of $\mathrm{A}{\mathrm{g}}_2\mathrm{Ge}$ centered at the surface zone boundary ${\overline{M}}_{\mathrm{Ag}\left(111\right)}$ evidently evolves to a steep, $\mathsf{V}$-shaped interfacial-state band, characteristic of SP germanene. Moreover, an anomalous broad Ag bulk-state band was observed to fully develop upon formation of SP germanene. The bulk-state band originates from the direct transition to the final-state bands of originally $d$ character at $\sim 22–23\mathrm{eV}$ above the Fermi level. Because of the strong hybridization between germanene π and Ag $d$ orbitals, the unoccupied Ag bulk final-state $d$ bands near the interface take on $p_z$ character, inducing the direct transition from the Ag bulk occupied $p_z$-valence band, following the selection rule for the photoemission cross section. A germanene identity of SP is thus confirmed. Our result indicates a very important missing segment of the evolution from the initial surface alloy phase to the final Xene layer, which is the coexistence of both in a common stripe lattice during a continuous transition.

Distinct from familiar $s$-, $p$-, or $d$-wave pairings, the monopole superconducting order represents a novel class of pairing order arising from nontrivial monopole charge of the Cooper pair. In the weak-coupling regime, this order can emerge when pairing occurs between Fermi surfaces with different Chern numbers in, for example, doped Weyl semimetal systems. However, the phase of monopole pairing order is not well-defined over an entire Fermi surface, making it challenging to design experiments sensitive to both its symmetry and topology. To address this, we propose a scheme based on symmetry and topological principles to identify this elusive pairing order through a set of phase-sensitive Josephson experiments. By examining the discrepancy between global and local angular momentum of the pairing order, we can unveil the monopole charge of the pairing order, including for models with higher pair monopole charge $|q_p|=1,2$, and 3. We demonstrate the proposed probe of monopole pairing order through analytic and numerical studies of Josephson coupling in models of monopole superconductor junctions. This work opens a promising avenue to uncover the unique topological properties of monopole pairing orders and to distinguish them from known pairing orders based on spherical harmonic symmetry.

Semantic information theory (SIT) offers an alternative approach to evaluating the information architecture of complex systems. In this paper, we describe the steps required to operationalize SIT via its application to dynamical problems. Our road map has four steps: (1) separating the dynamical system into agent-environment subsystems, (2) choosing an appropriate coarse graining and quantifying correlations, (3) identifying a measure of viability, and (4) implementing a scrambling protocol and measuring the semantic content. We apply the road map to a model inspired by the neural dynamics of epileptic seizures whereby an agent (a control process) attempts to maintain an environment (a base process) in a desynchronized state. The synchronization dynamics is studied through the well-known Kuramoto model of phase synchronization. Our application of SIT to this problem reveals features of both semantic information and the Kuramoto model. For the latter, we find articulating the correlational structure for agent and environment (the oscillators) allows us to cast the model from a computational (information theoretic) perspective, where the agent-environment dynamics form a communication channel. For the former, we find a topological dependence of whether information can be considered semantic or not.

In this paper, the optical response to a terahertz pulse was investigated in the transition metal chalcogenide $\mathrm{T}{\mathrm{a}}_2\mathrm{NiS}{\mathrm{e}}_5$, a candidate excitonic insulator. First, by irradiating a terahertz pulse with a relatively weak electric field (0.3 MV/cm), the spectral changes in reflectivity near the absorption edge due to third-order optical nonlinearity were measured, and the absorption peak characteristic of the excitonic phase just below the interband transition was identified. Next, by irradiating a strong terahertz pulse with a strong electric field of 1.65 MV/cm, the absorption of the excitonic phase was found to be reduced, and a Drude-like response appeared in the mid-infrared region. These responses can be interpreted as carrier generation by exciton dissociation induced by the electric field, resulting in the partial melting of the excitonic phase and metallization. The presence of a distinct threshold electric field for carrier generation indicates exciton dissociation via quantum-tunneling processes. The spectral change due to metallization by the electric field is significantly different from that due to the strong optical excitation across the gap, which can be explained by the different melting mechanisms of the excitonic phase in the two types of excitations.

We propose a method for constructing PREPARE circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of quantum circuits solely on classical computers. The PREPARE circuit generates a quantum state which encodes the coefficients of the terms in the Hamiltonian as probability amplitudes and plays a crucial role in the state-of-the-art efficient implementations of quantum phase estimation. We employ the automatic quantum circuit encoding algorithm [Shirakawa et al., Phys. Rev. Res. 6, 043008 (2024)] to construct PREPARE circuits, which requires classical simulations of quantum circuits of $O(logN)$ qubits with $N$ being the number of qubits of the Hamiltonian. The generated PREPARE circuits do not need any ancillary qubit. We demonstrate our method by investigating the number of $T$-gates of the obtained PREPARE circuits for quantum chemistry Hamiltonians of various molecules, which shows a constant-factor reduction compared to previous approaches that do not use ancillary qubits. Since the number of available logical qubits and $T$ gates will be limited at the early stage of the fault-tolerant quantum computing, the proposed method is particularly of use for performing the quantum phase estimation with such limited capability.

Unusual magnetotransport behaviors, such as temperature-dependent negative magnetoresistance (MR) and bowtie-shaped MR, have puzzled us for a long time. Although several mechanisms have been proposed to explain these phenomena, the absence of comprehensive quantitative calculations has made these explanations less convincing. In our work, we introduce a methodology to study magnetotransport behaviors in magnetic materials. This approach integrates the anomalous Hall conductivity induced by the Berry curvature, with a multiband ordinary conductivity tensor, employing a combination of first-principles calculations and semiclassical Boltzmann transport theory. Our method also incorporates the temperature dependence of the relaxation time and the anomalous Hall conductivity, as well as the field dependence of the anomalous Hall conductivity. We initially test this approach on models, obtaining distinct behaviors of magnetoresistance and Hall resistivity across several types of magnetic materials, and then apply it to a Weyl semimetal ${\mathrm{Co}}_3{\mathrm{Sn}}_2{\mathrm{S}}_2$. The results, which align well with experimental observations in terms of magnetic field and temperature dependencies, demonstrate the efficacy of our approach. This methodology provides a comprehensive and efficient means to understand the underlying mechanisms of the unusual complex behaviors observed in magnetotransport measurements in magnetic materials.

Estimating many-body effects that deviate from an independent particle approach has long been a key research interest in condensed matter physics. Layered cuprates are prototypical systems, where electron-electron interactions are found to strongly affect the dynamics of single-particle excitations. It is, however, still unclear how the electron correlations influence charge excitations, such as plasmons, which have been variously treated with either weak or strong correlation models. In this work, we demonstrate the hybridized nature of collective valence charge fluctuations leading to dispersing acoustic-like plasmons in hole-doped ${\mathrm{La}}_{1.84}{\mathrm{Sr}}_{0.16}{\mathrm{CuO}}_4$ and electron-doped ${\mathrm{La}}_{1.84}{\mathrm{Ce}}_{0.16}{\mathrm{CuO}}_4$ using the two-particle probe, resonant inelastic x-ray scattering. We then describe the plasmon dispersions in both systems, within both the weak-coupling mean-field random phase approximation (RPA) and strong-coupling $t\text{−}J\text{−}V$ model in a large-$N$ scheme. The $t\text{−}J\text{−}V$ model, which includes the correlation effects implicitly, accurately describes the plasmon dispersions as resonant excitations outside the single-particle intraband continuum. In comparison, a quantitative description of the plasmon dispersion in the RPA approach is obtained only upon explicit consideration of renormalized electronic band parameters. Our comparative analysis shows that electron correlations significantly impact the low-energy plasmon excitations across the cuprate doping phase diagram, even at long wavelengths. Thus, complementary information on the evolution of electron correlations, influenced by the rich electronic phases in condensed matter systems, can be extracted through the study of two-particle charge response.

Deducing the states of spatiotemporally chaotic systems (SCSs) as they evolve in time is crucial for various applications. However, generally achieving this is a dramatic challenge due to the complexity of nonperiodic dynamics and the hardness of obtaining robust solutions. In recent years, there has been a growing interest in approaching the problem using both classical and quantum machine learning methods. Although effective for predicting SCSs within a relatively short time, the current schemes are not capable of providing robust solutions for longer times than the training time. Here we propose an approach for advancing the prediction of chaotic behavior. Our approach can be viewed as a unique quantum reservoir computing scheme, which can simultaneously capture the linear and the nonlinear features of input data and evolve under a modified Hamiltonian. Our work presents an alternative approach to handling SCSs.

Understanding the dynamics of open quantum many-body systems is a major problem in quantum matter. Specifically, efficiently solving the spectrum of the Liouvillian superoperator governing such dynamics remains a critical open challenge. Here, we put forward a method for solving the many-body Liouvillian spectrum and dynamics based on the non-Hermitian kernel polynomial method and tensor-network techniques. We demonstrate the faithfulness of our method by computing the dynamics of the dephasing quantum compass model with a gradient magnetic field and comparing it with exact results. In particular, we show that our method allows us to characterize the quantum Zeno crossover and the reduction of relaxation rate due to Stark localization in this model. We further demonstrate the ability of our method to go beyond exact results by exploring nearest-neighbor interaction effects on the Liouvillian dynamics, elucidating the interplay between Stark localization and many-body interactions. Our method provides an efficient solution to many-body Liouvillian spectrum and dynamics, establishing a methodology to explore large open quantum many-body systems.

Forty years ago, measurements of enrichments in ${}^{18}\mathrm{O}$ in stratospheric ozone ${\text{O}}_3$ revealed a value significantly greater than statistically expected and roughly equal in heavy isotopes ${}^{17}\mathrm{O}$ and ${}^{18}\mathrm{O}$. Despite numerous experimental and theoretical studies, this mass-independent fractionation (MIF) still remains unexplained. However, it is now accepted that its origin comes from isotopic effects found in the recombination reaction $\mathrm{O}+{\text{O}}_2+M\to {\text{O}}_3 + M$ where $M$ is a stabilizer, even if the theoretical origin of the isotope effects found in this reaction is still not known. Here we study the first of the two steps involved in this reaction, namely, the rapid quasiequilibrium $\mathrm{O}+{\mathrm{O}}_2 \rightleftharpoons {\mathrm{O}}_3^{*}$ process where ${\mathrm{O}}_3^{*}$ is metastable ozone. The quasiequilibrium constant for this process is obtained from a full quantum dynamical approach. These high-level calculations yield the most accurate value of this quantity to date for ${}^{48}\mathrm{O}_3$ and ${}^{50}\mathrm{O}_3$. These reference results constitute a crucial stage for a better understanding of the ozone formation reaction, and could therefore help to unravel the mystery of MIF.