We present a detailed theoretical and experimental study of the rotation of the plane of polarization of light traveling through a gas of fast-spinning molecules. This effect is similar to the polarization drag phenomenon predicted by Fermi a century ago and it is a mechanical analog of the Faraday effect. In our experiments, molecules were spun up by an optical centrifuge and brought to the super-rotor state that retains its rotation for a relatively long time. Polarizability properties of fast-rotating molecules were analyzed considering the rotational Doppler effect and Coriolis forces. We used molecular dynamics simulations to account for intermolecular collisions. We found, both experimentally and theoretically, a nontrivial nonmonotonic time dependence of the polarization rotation angle. This time dependence reflects the transfer of the angular momentum from rotating molecules to the macroscopic gas flow, which may lead to the birth of gas vortices. Moreover, we show that the long-term behavior of the polarization rotation is sensitive to the details of the intermolecular potential. Thus, the polarization drag effect appears as a novel diagnostic tool for the characterization of intermolecular interaction potentials and studies of collisional processes in gases.

Recent studies have revealed that slip on clay-rich fault planes, which develop in the shallow crust and can cause huge earthquakes, is controlled by their flow properties rather than their frictional properties. Here, we simulate a seismogenic crustal fault and show that such a fault plane may behave as a thixotropic yield stress fluid. We then conduct numerical experiments using a simple spring-slider model that incorporates this thixotropic property, and we successfully reproduce spontaneous stick-slip behaviors that correspond to a variety of seismogenic processes, ranging from regular earthquakes with high slip rates to slow earthquakes with lower slip rates. This finding suggests that the seismic activity on a shallow clay-rich crustal fault may be governed by the time-evolving microstructure of the clay-water system that exists along the fault plane.

The bulk photovoltaic effect (BPVE) converts light into a coherent dc current at zero bias, through what is commonly known as the shift current. This current has previously been attributed to the displacement of the electronic wave function center in real space, when the sample is excited by light. We reveal that materials like twisted bilayer graphene (TBG) with a flatband dispersion are uniquely suited to maximize the BPVE because they lead to an enhanced shift in the momentum space, unlike any previously known shift current mechanism. We identify properties of quantum geometry, which go beyond the quantum geometric tensor, and are unrelated to Berry charges, as the physical origin of the large BPVE we observe in TBG. Our calculations show that TBG with a band gap of several meV exhibits a giant BPVE in a range of 0.2–1 THz, which represents the strongest BPVE reported so far at this frequency in a two-dimensional material and partially persists even a room temperature. Our paper provides a design principle for shift current generation, which applies to a broad range of twisted heterostructures with the potential to overcome the so-called “terahertz gap” in THz sensing.

The study of thermodynamic fluctuations allows one to relate the free energy difference between two equilibrium states with the work done on a system through processes far from equilibrium. This finding plays a crucial role in the quantum regime, where the definition of work becomes nontrivial. Based on these relations, here we develop a simple interferometric method allowing a direct estimation of the work distribution and the average dissipative work during a driven thermodynamic process by superposing the forward and time-reversal evolutions of the process. We show that our scheme provides useful upper bounds on the average dissipative work even without full control over the thermodynamic process, and we propose methodological variations depending on the possible experimental limitations encountered. Finally, we exemplify its applicability by an experimental proposal for implementing our method on a quantum photonics system, on which the thermodynamic process is performed through polarization rotations induced by liquid crystals acting in a discrete temporal regime.

Hybrid quantum systems involving cold atoms and microwave resonators can enable cavity-mediated infinite-range interactions between atomic spin systems and realize atomic quantum memories and transducers for microwave-to-optical conversion. To achieve strong coupling of atoms to on-chip microwave resonators, it was suggested to use atomic Rydberg states with strong electric-dipole transitions. Here we report on the experimental realization of coherent coupling of a Rydberg transition of ultracold atoms, trapped on an integrated superconducting atom chip, to the microwave field of an on-chip coplanar waveguide resonator. Close to the chip surface, stray electric fields lead to inhomogeneous Rydberg level shifts, which would hinder coherent interactions of atoms in a cloud with the Rydberg excitation lasers and the microwave cavity field. We, however, use optical excitation of a Rydberg state of atoms in a narrow layer with nearly constant electric field, which allows for resonant coupling of the atoms to the cavity microwave field on an appropriate Rydberg transition. We also achieve state-selective detection of the energetically close Rydberg states. We then observe and characterize cavity-driven Rabi oscillations between a pair of atomic Rydberg states. The residual damping of the oscillations is dominated by the spread of Rabi frequencies of atoms in different positions of the resonant cavity mode, as revealed by our model. Despite the technical challenges, our studies demonstrate the feasibility of coherent-state manipulation of Rydberg atoms interacting with superconducting circuits, paving the way for realization of capable hybrid quantum systems.

We introduce a method for reconstructing macroscopic models of one-dimensional stochastic processes with long-range correlations from sparsely sampled time series by combining fractional calculus and discrete-time Langevin equations. The method is illustrated for the ARFIMA(1,d,0) process and a nonlinear autoregressive toy model with multiplicative noise. We reconstruct a model for daily mean temperature data recorded at Potsdam, Germany and use it to predict the first-frost date by computing the mean first passage time of the reconstructed process and the $0{}^{\circ }\mathrm{C}$ temperature line, illustrating the potential of long-memory models for predictions in the subseasonal-to-seasonal range.

Recently, there has been a renewed interest in properties of the higher-spin Kitaev models, especially their low-dimensional analogs with additional interactions. These quasi-one-dimensional systems exhibit rich phase diagrams with symmetry-protected topological phases, Luttinger liquids, hidden order, and higher-rank magnetism. However, the nature of the pure spin-$S$ Kitaev chains is not yet fully understood. Earlier works found a unique ground state with short-ranged correlations for $S=1$ and an intriguing double-peak structure in the heat capacity associated with an entropy plateau. To understand the low-energy excitations and thermodynamics for general $S$, we study the anisotropic spin-$S$ Kitaev chain. Starting from the dimerized limit, we derive an effective low-energy Hamiltonian at finite anisotropy. For half-integer spins we find a trivial effective model, reflecting a nonlocal symmetry protecting the degeneracy, while for integer $S$ we find interactions among the flux degrees of freedom that select a unique ground state. The effective model for integer spins is used to predict the low-energy excitations and thermodynamics, and we make a comparison with the semiclassical limit through linear spin wave theory. Finally, we speculate on the nature of the isotropic limit.

Language is an outcome of our complex and dynamic human-interactions and the technique of natural language processing (NLP) is hence built on human linguistic activities. Along with generative pretrained transformer (GPT), bidirectional encoder representations from transformers (bert) has recently gained its popularity, owing to its outstanding NLP capabilities, by establishing the state-of-the-art scores in several NLP benchmarks. A lite bert (albert) is literally characterized as a lightweight version of bert, in which the number of bert parameters is reduced by repeatedly applying the same neural network called transformer's encoder layer. By pretraining the parameters with a massive amount of natural language data, albert can convert input sentences into versatile high-dimensional vectors potentially capable of solving multiple NLP tasks. In that sense, albert can be regarded as a well-designed high-dimensional dynamical system whose operator is the transformer's encoder, and essential structures of human language are thus expected to be encapsulated in its dynamics. In this study, we investigated the embedded properties of pretrained albert to reveal how NLP tasks are effectively solved by exploiting its dynamics. We thereby aimed to explore the nature of human language from the dynamical expressions of the NLP model. Our analysis consists of two parts, namely, short- and long-term analyses, according to timescale differences to capture the dynamics. Our short-term analysis clarified that the pretrained model stably yields trajectories with higher dimensionality in a certain time range, which would enhance the expressive capacity required for NLP tasks. Also, our long-term analysis revealed that albert intrinsically shows transient chaos, a typical nonlinear phenomenon showing chaotic dynamics only in its transient, and the pretrained albert model tends to produce the chaotic trajectory for a significantly longer time period compared to a randomly initialized one. Our results imply that local chaoticity would contribute to improving NLP performance, uncovering a novel aspect in the role of chaotic dynamics in human language behaviors.

The Bell inequality can provide a useful witness for device-independent applications with quantum (or postquantum) eavesdroppers. This feature holds only for single entangled systems. Our goal is to explore a device-independent model for quantum networks. We first propose a Bell inequality to verify the genuinely multipartite nonlocality of connected quantum networks including cyclic networks and universal quantum computational resources for a measurement-based computation model. This is further used to construct a monogamy relation in a fully device-independent model with multisource quantum resources. It is finally applied for multiparty quantum key distribution, blind quantum computation, and quantum secret sharing. The present model can inspire various large-scale applications on quantum networks in a device-independent manner.

Single-shot measurement of ultrashort time with a dispersive temporal interferometer (DTI) paves the way for exploring intracavity dynamics in ultrafast lasers. Here, we report observations of pulse evolution dynamics after mode-locking buildup in ultrafast lasers. We observe the roundtrip time and phase evolution of the mode-locked pulses after buildup, and we unveil that the pulse experiences three different stages before stabilization, i.e., the soliton breathing stage, the relaxation oscillation stage, and the long-term relaxation stage. We find that the gain depletion effect makes the pulse move forward but does not shift its phase, and it can be distinguished by a DTI from the refractive index change. With this, the dynamics of the three stages is analyzed. Moreover, it is unveiled that the gain relaxation dynamics can intensively affect a laser's stability. These results provide additional perspectives on the intracavity dynamics of mode-locked lasers and of complex nonlinear systems, and they can help to improve the laser stability, which may impact laser design, ultrafast diagnostics, and nonlinear optics.

To describe the nonclassicality of quantum channels, it is necessary to quantify their properties. In the framework of resource theory of quantum channel, we present three new entanglement measures of channels for a quantum system of arbitrary finite dimension, based on the Choi relative entropy of channels, concurrence, and $k$-ME concurrence, respectively. Rigorous proofs show that these proposed measures fulfill all the requirements dictated by the resource theory of quantum channels, including non-negativity, weak monotonicity, strong monotone, convexity, additivity, and subadditivity. By using the measure, we describe the probability that the initial hypothesis is true in the hypothesis testing of channels. Compared with other known measures of the quantum channels, these measures have an obvious advantage in computability. According to the power of generating entanglement, we give a classification of quantum channels. Moreover, we provide several examples that characterize the properties of quantum channels and the conversions between quantum coherence states and entangled states and between fully separable states and multipartite entangled states.

We introduce a Bayesian method for the estimation of single-qubit errors in quantum devices, and use it to characterize these errors on three superconducting 27-qubit devices. We self-consistently estimate up to seven parameters of each qubit's state preparation, readout, and gate errors, analyze the stability of these errors as a function of time, and demonstrate easily implemented approaches for mitigating different errors before a quantum computation experiment. On the investigated devices we find non-negligible qubit reset errors that cannot be parametrized as a diagonal mixed state, but manifest as a coherent phase in a superposition with a small contribution from the qubit's excited state. We are able to mitigate such errors by applying prerotations on the initialized qubits, which we demonstrate with multiqubit entangled states. Our results show that Bayesian estimation can resolve small parameters—including those pertaining to quantum gate errors—with a high relative accuracy, at a lower measurement cost as compared with standard characterization approaches.

Gate-tunable Josephson junctions embedded in a microwave environment provide a promising platform to in situ engineer and optimize novel superconducting quantum circuits. The key quantity for the circuit design is the phase-dependent complex admittance of the junction, which can be probed by sensing a radio frequency SQUID with a tank circuit. Here, we investigate a graphene-based Josephson junction as a prototype gate-tunable element enclosed in a SQUID loop that is inductively coupled to a superconducting resonator operating at 3 GHz. With a concise circuit model that describes the dispersive and dissipative response of the coupled system, we extract the phase-dependent junction admittance corrected for self-screening of the SQUID loop. We decompose the admittance into the current-phase relation and the phase-dependent loss, and as these quantities are dictated by the spectrum and population dynamics of the supercurrent-carrying Andreev bound states, we gain insight to the underlying microscopic transport mechanisms in the junction. We theoretically reproduce the experimental results by considering a short, diffusive junction model that takes into account the interaction between the Andreev spectrum and the electromagnetic environment, from which we estimate lifetimes on the order of $\sim 10$ ps for nonequilibrium populations.