We study collisions of ultracold CaF molecules in strong static electric fields. These fields allow the creation of long-range barriers in the interaction potential, effectively preventing the molecules from reaching the short-range region where inelastic and other loss processes are likely to occur. We carry out coupled-channel calculations of rate coefficients for elastic scattering and loss. We develop an efficient procedure for including energetically well-separated rotor functions in the basis set via a Van Vleck transformation. We show that shielding is particularly efficient for CaF and allows the rate of two-body loss processes to be reduced by a factor of ${10}^7$ or more at a field of 23 kV/cm. The loss rates remain low over a substantial range of fields. Electron and nuclear spins cause strong additional loss in some small ranges of field, but have little effect elsewhere. These results pave the way for evaporative cooling of CaF towards quantum degeneracy.

In this paper, we demonstrate the capability to establish spin-polarized currents in doped $\mathrm{SrTi}{\mathrm{O}}_3$ (STO). The results are based on the study of charge and spin transport in STO layers doped by the reversible electromigration of oxygen atoms in resistive-switching ${\mathrm{La}}_{0.7}{\mathrm{Sr}}_{0.3}\mathrm{Mn}{\mathrm{O}}_3/\mathrm{STO}/\mathrm{Co}$ vertical stacks. The formation of oxygen vacancies inside STO results in a metallic conductivity at temperatures $<200–250$ K, above which a transition to an insulatinglike behavior is detected. A detailed theoretical analysis shows that the behavior of the metallic phase in our samples corresponds to the well-known state of the thermodynamically doped STO featuring the so-called bad metal behavior. Thus, our findings introduce this class of unconventional materials as valuable candidates for innovative spintronic devices.

We study the current-voltage characteristics of a superconducting junction with particle losses at the contacts. We adopt the Keldysh formalism to compute the steady-state current for varying transmission of the contact. In the low-transmission regime, the dissipation leads to an enhancement of the current at low bias, a nonmonotonic dependence of current on dissipation, and the emergence of new structures in the current-voltage curves. The effect of dissipation by particle loss is found to be qualitatively different from that of a finite temperature and a finite inelastic scattering rate in the reservoirs.

We present experimental data on the strong field tunnel ionization of argon in a counter-rotating two-color (CRTC) laser field. We find that the initial momentum component along the tunneling direction changes sign comparing the rising and the falling edge of the CRTC field. If the initial momentum at the tunnel exit points in the direction of the ion at the instant of tunneling, this manifests as an enhanced Coulomb interaction of the outgoing electron with its parent ion. Our conclusions are in accordance with predictions based on strong field approximation.

Laser cooling of single atoms in optical tweezers is a prerequisite for neutral atom quantum computing and simulation. Resolved sideband cooling comprises a well-established method for efficient motional ground-state preparation, but typically requires careful cancellation of light shifts in so-called magic traps. Here, we study a novel laser cooling scheme which overcomes such constraints, and applies when the ground state of a narrow cooling transition is trapped stronger than the excited state. We demonstrate our scheme, which exploits sequential addressing of red sideband transitions via frequency chirping of the cooling light, at the example of ${}^{88}\mathrm{Sr}$ atoms and report ground-state populations compatible with recent experiments in magic tweezers. The scheme also induces light-assisted collisions, which are key to the assembly of large atom arrays. Our work enriches the toolbox for tweezer-based quantum technology, also enabling applications for tweezer-trapped molecules and ions that are incompatible with resolved sideband cooling conditions.

In one dimension, quantum fluctuations prevent the appearance of long-range order in a supersolid, and only quasi-long-range order can survive. We derive this quantum critical behavior and study its influence on the superfluid response and properties of the solid. The analysis is based on an effective low-energy description accounting for the two coupled Goldstone modes. We find that the quantum phase transition from the superfluid to the supersolid is shifted by quantum fluctuations from the position where the local formation of a solid structure takes place. For current experimental parameters with dipolar atomic gases, this shift is extremely small and cannot be resolved yet, i.e., current observations in experiments are expected to be in agreement with predictions from mean-field theory based on the extended Gross-Pitaevskii formalism.

Global quenches of quantum many-body models can give rise to periodic dynamical quantum phase transitions (DQPTs) directly connected to the zeros of a Landau order parameter (OP). The associated dynamics has been argued to bear a close resemblance to Rabi oscillations characteristic of two-level systems. Here, we address the question of whether this DQPT behavior is merely a manifestation of the limit of an effective two-level system or if it can arise as part of a more complex dynamics. We focus on quantum many-body scarring as a useful toy model allowing us to naturally study state transfer in an otherwise chaotic system. We find that a DQPT signals a change in the dominant contribution to the wave function in the degenerate initial-state manifold, with a direct relation to an OP zero only in the special case of occurring at the midpoint of an evenly degenerate manifold. Our work generalizes previous results and reveals that, in general, periodic DQPTs comprise complex many-body dynamics fundamentally beyond that of two-level systems.

We study a quantum walk of a single particle that is subject to stroboscopic projective measurements on a graph with two sites. This two-level system is the minimal model of a measurement-induced quantum walk. The mean first detected transition and return time are computed on an IBM quantum computer as a function of the hopping matrix element between the sites and the on-site potential. The experimentally monitored quantum walk reveals the theoretically predicted behavior, such as the quantization of the first detected return time and the strong increase of the mean first detected transition time near degenerate points, with high accuracy.

We use the configuration model to generate random networks having a degree distribution that follows a $q$-exponential, $P_q\left(k\right)=(2-q)\lambda {[1-(1-q)\lambda k]}^{-1/(q-1)}$, for arbitrary values of the parameters $q$ and $\lambda$. Typically, for small values of $\lambda$, this distribution crosses over from a plateau at small $k$'s to a power-law decay at large values of the node degrees. Furthermore, by sufficiently increasing $\lambda$, we can continuously narrow this plateau, getting closer and closer to a pure power-law degree distribution. As a generalization of the pure scale-free networks, therefore, $q$-exponentials display a rich variety of behavior in terms of their topological and transport properties. This is substantiated here by investigating their average degree, assortativity, small-world behavior, resilience to random and malicious attacks, and $k$-core decomposition. Our results show that the more the degree distribution resembles a pure power law, the less well connected the networks. As a consequence, their average degree follows $\langle k\rangle \sim {\lambda }^{-1}$ for $\lambda <1$, and the expected average degree $k_{\text{nn}}$ of the nearest neighbors of a given node with degree $k$ generally decreases with $\lambda$. Moreover, random $q$-exponential networks exhibit small-world behavior for any $\lambda$, but with an average shortest path that becomes smaller as $\lambda$ decreases and $q$ increases. Finally, $q$ exponentials become more resilient to random and malicious attacks as their degree distribution systematically deviates from the pure power law. Being at the same time well-connected and robust, networks with $q$-exponential degree distribution exhibit scale-free and small-world properties, making them a particularly suitable model for applications in several systems.

Being the backbone of many human-made systems, networks require both pruning and growth to adapt to changing demand. We develop a message passing-based framework for analyzing and addressing the two-level optimization problem of edge removal/addition for indirectly dependent objectives. As exemplar problem we use routing in optical communication networks to minimize capability loss (removal) or maximize capacity (addition). The methods developed result in lower path lengths and higher capacity topologies with respect to existing ones and are suitable for a broad range of network design tasks.

By machine learning, specifically the convolutional neural network (CNN) technology, the screening parameter $\kappa$ is determined from single particle dynamics in two-dimensional (2D) dusty plasma simulations and also in an experiment. Independent Langevin simulation runs are performed with different $\kappa$ values to obtain individual particle dynamical data to train, validate, and test CNNs. By adjusting the training dataset to mimic the application with the experimental data, three different CNNs are designed. From the analyzed results with the test dataset of simulations, all three CNNs have excellent performance in determining the $\kappa$ value, with the resulting root-mean-square error of the determined $\kappa$ value of 0.081, 0.279, and 0.155, respectively. While using these trained CNNs with the 2D dusty plasma experimental data, the distribution of the determined $\kappa$ values has a prominent peak at the $\kappa$ value, agreeing well with that determined from the phonon spectra. The results presented here clearly demonstrate the feasibility of determining the global property of dusty plasmas purely from single particle dynamics using machine learning, which may be developed further to diagnose more complicated plasma environment conditions in the future.

Krylov complexity is a measure of operator complexity that exhibits universal behavior and bounds a large class of other measures. In this paper, we generalize Krylov complexity from a closed system to an open system coupled to a Markovian bath, where Lindbladian evolution replaces Hamiltonian evolution. We show that Krylov complexity in open systems can be mapped to a non-Hermitian tight-binding model in a half-infinite chain. We discuss the properties of the non-Hermitian terms and show that the strengths of the non-Hermitian terms increase linearly with the increase of the Krylov basis index $n$. Such a non-Hermitian tight-binding model can exhibit localized edge modes that determine the long-time behavior of Krylov complexity. Hence, the growth of Krylov complexity is suppressed by dissipation, and at long times, Krylov complexity saturates at a finite value much smaller than that of a closed system with the same Hamiltonian. Our conclusions are supported by numerical results on several models, such as the Sachdev-Ye-Kitaev model and the interacting fermion model. Our work provides insights for discussing complexity, chaos, and holography for open quantum systems.

Anomaly detection algorithms are a valuable tool in network science for identifying unusual patterns in a network. These algorithms have numerous practical applications, including detecting fraud, identifying network security threats, and uncovering significant interactions within a data set. In this project, we propose a probabilistic generative approach that incorporates community membership and reciprocity as key factors driving regular behavior in a network, which can be used to identify potential anomalies that deviate from expected patterns. We model pairs of edges in a network with exact two-edge joint distributions. As a result, our approach captures the exact relationship between pairs of edges and provides a more comprehensive view of social networks. Additionally, our study highlights the role of reciprocity in network analysis and can inform the design of future models and algorithms. We also develop an efficient algorithmic implementation that takes advantage of the sparsity of the network.

In recently published papers [M. J. J. Vrakking, Phys. Rev. Lett. 126, 113203 (2021); J. Phys. B 55, 134001 (2022)], Vrakking proposed an inventive scheme to control the entanglement or coherence of the vibrational states in a hydrogen molecular ion and a continuum electron, both of which were generated via the photoionization of a hydrogen molecule irradiated by a coherent pair of extreme ultraviolet (XUV) attosecond pulses and a few-femtosecond ultraviolet (UV) pulse. He clarified, for the first time to our knowledge, how the coherence of the XUV attosecond pulse pair is transferred to the molecular ion system accompanying a detached continuum electron by numerically solving a time-dependent Schrödinger equation (TDSE) governing the evolution of the ion and the electron in a rigorous manner. Nevertheless, it was not straightforwardly resolved how and why the specific characteristics of the resultant joint energy spectrogram emerged and how the entanglement or coherence was altered with the irradiation of the UV pulse. In this paper, we present an analytical solution of the TDSE using time-dependent perturbation theory, and we utilize the resultant solution to explain what causes the particular features in the entanglement or coherence between the electron and the ion spectra.

The analysis of symmetry in quantum systems is of utmost theoretical importance, useful in a variety of applications and experimental settings, and difficult to accomplish in general. Symmetries imply conservation laws, which partition Hilbert space into invariant subspaces of the time-evolution operator, each of which is demarcated according to its conserved quantity. We show that, starting from a chosen basis, any invariant, symmetry-protected subspaces which are diagonal in that basis are discoverable using transitive closure on graphs representing state-to-state transitions under $k$-local unitary operations. Importantly, the discovery of these subspaces relies neither upon the explicit identification of a symmetry operator or its eigenvalues nor upon the construction of matrices of the full Hilbert space dimension. We introduce two classical algorithms, which efficiently compute and elucidate features of these subspaces. The first algorithm explores the entire symmetry-protected subspace of an initial state in time complexity linear to the size of the subspace by closing local basis state-to-basis state transitions. The second algorithm determines, with bounded error, if a given measurement outcome of a dynamically generated state is within the symmetry-protected subspace of the state in which the dynamical system is initialized. We demonstrate the applicability of these algorithms by performing postselection on data generated from emulated noisy quantum simulations of three different dynamical systems: the Heisenberg-XXX model and the $T_6$ and $F_4$ quantum cellular automata. Due to their efficient computability and indifference to identifying the underlying symmetry, these algorithms lend themselves to the postselection of quantum computer data, optimized classical simulation of quantum systems, and discovery of previously hidden symmetries in quantum mechanical systems.

Quantum measurements can produce unpredictable randomness arising from the uncertainty principle. When measuring a state with von Neumann measurements, the intrinsic randomness can be quantified by the quantum coherence of the state on the measurement basis. Unlike projection measurements, there are additional and possibly hidden degrees of freedom in an apparatus for generic measurements. We propose an adversary scenario to characterize the intrinsic randomness of general measurements with arbitrary input states. Interestingly, we discover that certain measurements, including symmetric and information-complete ones, generate nonzero randomness for all states, which suggests a new approach for designing source-independent random number generators without state characterization. Furthermore, our results reveal that intrinsic randomness can quantify coherence under general measurements, which generalizes the result in the standard resource theory of state coherence.