One of the demanding frontiers in ultracold quantum science is identifying laser cooling schemes for complex atoms and molecules out of their vast spectra of internal states. Motivated by the prospect of expanding the set of available ultracold molecules for applications in fundamental physics, chemistry, astrochemistry, and quantum simulation, we propose and demonstrate an automated graph-based search approach for viable laser cooling schemes. The method is time efficient, reproduces the results of previous manual searches, and reveals a plethora of new potential laser cooling schemes. We discover laser cooling schemes for YO, ${\mathrm{C}}_2, {\mathrm{OH}}^{+}$, CN, and ${\mathrm{CO}}_2$, including surprising schemes that start from highly excited states or do not rely on a strong main transition. A central insight of this work is that the reinterpretation of quantum states and transitions between them as a graph can dramatically enhance the ability to identify new quantum control schemes for complex quantum systems. As such, this approach will also apply to complex atoms and, in fact, any complex many-body quantum system with a discrete spectrum of internal states.

To determine the precise link between anatomical structure and function, brain studies primarily concentrate on the anatomical wiring of the brain and its topological properties. In this work, we investigate the weighted degree and connection length distributions of the KKI-113 and KKI-18 human connectomes, the fruit fly, and the mouse retina. We find that the node strength (weighted degree) distribution behavior differs depending on the considered scale. On the global scale, the distributions are found to follow a power-law behavior, with a roughly universal exponent close to 3. However, this behavior breaks at the local scale as the node strength distributions of the KKI-18 follow a stretched exponential, and the fly and mouse retina follow the log-normal distribution, respectively, which are indicative of underlying random multiplicative processes and underpins nonlocality of learning in a brain close to the critical state. However, for the case of the KKI-113 and the H01 human $(1{\mathrm{mm}}^3$) datasets, the local weighted degree distributions follow an exponentially truncated power law, which may hint at the fact that the critical learning mechanism may have manifested at the node level too.

Superradiance, in which the collective behavior of emitters can generate enhanced radiative decay, was first predicted by a model, now known as the Dicke model, that contains a collection of two-level systems (the emitters) all interacting with the same photonic mode. In this article, we extend the original Dicke model to elucidate the influence of nuclear motion on superradiant emission. Our dynamical simulations of the combined electronic, nuclear, and photonic system reveal a new time scale attributed to the population leakage of the dark, subradiant states. Furthermore, this dark-state emission pathway can be controlled by tuning the nuclear potential energy landscape. These findings impact how superradiant states and molecular degrees of freedom can be leveraged and utilized in quantum optical systems.

The interaction of matter with short light pulses is relevant in optical traps, optical tweezers, and many other applications. The theoretical description of such polychromatic light-matter interaction is challenging, and more so when the object is moving with respect to the light source, albeit with constant speed. Light sails are futuristic examples where such speed should reach the relativistic regime. In here, we provide a methodology for the theoretical and numerical analysis of the interaction of light pulses with objects moving with constant speed. The methodology allows one, in particular, to readily compute the transfer of fundamental quantities such as energy and momentum from the light pulse to the object. As an example, we compute the transfer of energy and momentum between a given pulse and a silicon sphere moving at relativistic speeds. The methodology, however, is valid for generic pulses and objects. Particularizing the equations to the case of zero speed allows one to treat static or quasistatic objects. The method is based on the polychromatic T-matrix (transition matrix) formalism, which leverages the many publicly available resources for computing T matrices.

An important tool in studying the subfemtoscale spacetime structure of matter in ultrarelativistic heavy-ion collisions is Hanbury Brown–Twiss (HBT) intensity interferometry of identical particles in the final state of the collisions. We propose that a variant of the entanglement enabled intensity interferometry ($E^2{I}^2$) framework introduced by Cotler and Wilczek can provide a powerful alternative to HBT interferometry in extracting fundamental nonperturbative features of quantum chromodynamics at high energies. We apply this framework to demonstrate that the spatial distributions of color singlet (pomeron) configurations in nuclei are sensitive to measurements of exclusive resonant decays of $\rho$ mesons into ${\pi }^{\pm }$ pairs in ultrarelativistic ultraperipheral nuclear collisions (UPCs) at the Relativistic Heavy Ion Collider and the Large Hadron Collider. A preliminary analysis suggests that the model-independent extraction of pomeron distributions will require careful treatment of the interplay of $E^2{I}^2$ in the vector meson exclusive decay with the incoherent cross section for exclusive vector meson production. The $E^2{I}^2$ framework developed here is quite general. It can also be employed as a tool to extract information on the spin structure of pomeron couplings as well as enhance the discovery potential for rare odderon configurations from exclusive vector meson decays into few-particle final states both in UPCs and at the Electron-Ion Collider.

High-quality squeezed light is an important resource for a variety of applications. Multiple methods for generating squeezed light are known, having been demonstrated theoretically and experimentally. However, the effectiveness of these methods—in particular, the inherent limitations to the signals that can be produced—has received little consideration. Here we present a comparative theoretical analysis for generating a highly displaced squeezed light from a linear optical method—a beamsplitter mixing a squeezed vacuum and a strong coherent state—and well-studied parametric amplification methods including an optical parametric oscillator, an optical parametric amplifier, and a dissipative optomechanical squeezer seeded with coherent states. We show that the quality of highly displaced squeezed states that can be generated using these methods is limited on a fundamental level by the physical mechanism utilized; across all methods there are significant trade-offs between displacement, squeezing, and overall uncertainty. We explore the nature and extent of these trade-offs specific to each mechanism and identify the optimal operation modes for each. Finally, we identify the conditions for minimum-uncertainty squeezing in arbitrary parametric amplifying systems and show that displacing the output signal will in general violate these conditions, adding noise and degrading squeezing.

We present a method to approximately solve general instances of combinatorial optimization problems using the physical dynamics of three-dimensional (3D) rotors obeying Landau-Lifshitz-Gilbert dynamics. Conventional techniques to solve discrete optimization problems that use simple continuous relaxation of the objective function followed by gradient-descent minimization are inherently unable to avoid local optima, thus producing poor-quality solutions. Our method considers the physical dynamics of macrospins capable of escaping from local minima, thus facilitating the discovery of high-quality, nearly optimal solutions, as supported by extensive numerical simulations on a prototypical quadratic unconstrained binary optimization (QUBO) problem. Our method produces solutions that compare favorably with those obtained using state-of-the-art minimization algorithms (such as simulated annealing) while offering the advantage of being physically realizable by means of arrays of stochastic magnetic tunnel-junction devices.

The CDF II experiment at the Fermilab Tevatron used a drift chamber to measure the momenta of charged particles. We present a model for the response of the drift chamber to the curvature of a charged particle's trajectory. Constraints on the model parameters are obtained from cosmic-ray data and from information published by CDF in the context of the $W$ boson mass measurement. Implications for the calibration of the drift chamber measurement of momentum are discussed. The robustness of the CDF calibration procedure is demonstrated. The model provides a framework for the analysis of precision magnetic trackers of high-momentum particles.

The integrated Berry curvature is a geometric property that has dramatic implications for material properties. This study investigates the integrated Berry curvature and other contributions to the anomalous Hall effect in ${\mathrm{CrGeTe}}_3$ as a function of pressure. The anomalous Hall effect is absent in the insulating phase of ${\mathrm{CrGeTe}}_3$ and evolves with pressure in a domelike fashion as pressure is applied. The dome's edges are characterized by Fermi surface deformations, manifested as mixed electron and hole transport. We corroborate the presence of bipolar transport using ab initio calculations, which also predict a nonmonotonic behavior of the Berry curvature as a function of pressure. Quantitative discrepancies between our calculations and experimental results indicate that additional scattering mechanisms, which are also strongly tuned by pressure, contribute to the anomalous Hall effect in ${\mathrm{CrGeTe}}_3$.

We explore the dynamics of active elements performing persistent random motion with fluctuating active speed and in the presence of translational noise in a $d$-dimensional harmonic trap, modeling active speed generation through an Ornstein-Uhlenbeck process. Our approach employs an exact analytic method based on the Fokker-Planck equation to compute time-dependent moments of any dynamical variable of interest across arbitrary dimensions. We analyze dynamical crossovers in particle displacement before reaching the steady state, focusing on three key timescales: speed relaxation, persistence, and dynamical relaxation in the trap. Notably, for slow active speed relaxation, we observe an intermediate-time metastable saturation in the mean-squared displacement before reaching the final steady state. The steady-state distributions of particle positions exhibit two types of non-Gaussian departures based on control parameters: bimodal distributions with negative excess kurtosis and heavy-tailed unimodal distributions with positive excess kurtosis. We obtain detailed steady-state phase diagrams using the exact calculation of excess kurtosis, identifying Gaussian and non-Gaussian regions and potential re-entrant transitions.

We study the dynamical phase transitions (DPTs) appearing for a single Brownian particle without drift. We first explore how first-order DPTs in large deviations can be found even for a single Brownian particle without any force upon raising the dimension to higher than 4. The DPTs accompany temporal phase separations in their dynamical paths, which we numerically confirm by fitting to scaling functions. We next investigate how second-order DPTs can appear in one-dimensional free Brownian motion by choosing the observable, which essentially captures the localization transition of the trajectories. We discuss and confirm that the DPTs predicted for high dimensions can also be found when considering many Brownian particles at lower dimensions.

The spin-vector Monte Carlo model is widely used as a benchmark for the classicality of quantum annealers but severely restricts the time evolution. The spin-vector Langevin (SVL) model has been proposed and tested as an alternative, closely reproducing the real-time dynamics of physical quantum annealers such as D-Wave machines in the dissipative regime. We investigate the SVL annealing dynamics of classical $O\left(2\right)$ rotors on regular graphs, identifying universal features in the nonequilibrium dynamics when changing the range of interactions and the topology of the graph. Regular graphs with low connectance or edge density exhibit universal scaling dynamics consistent with the Kibble-Zurek mechanism, which leads to a power-law dependence of the density of defects and the residual energy as a function of the annealing time. As the interaction range is increased, the power-law scaling is suppressed, and an exponential scaling with the annealing time sets in. Our results establish a universal breakdown of the Kibble-Zurek mechanism in classical systems characterized by long-range interactions, in sharp contrast with previous findings in the quantum domain.

Neural quantum states (NQSs) have emerged as a powerful ansatz for variational quantum Monte Carlo studies of strongly correlated systems. Here, we apply recurrent neural networks (RNNs) and autoregressive transformer neural networks to the Fermi-Hubbard and the (non-Hermitian) Hatano-Nelson-Hubbard models in one and two dimensions. In both cases, we observe that the convergence of the RNN ansatz is challenged when increasing the interaction strength. We present a physically motivated and easy-to-implement strategy for improving the optimization, namely, by ramping of the model parameters. Furthermore, we investigate the advantages and disadvantages of the autoregressive sampling property of both network architectures. For the Hatano-Nelson-Hubbard model, we identify convergence issues that stem from the autoregressive sampling scheme in combination with the non-Hermitian nature of the model. Our findings provide insights into the challenges of the NQS approach and make the first step towards exploring strongly correlated electrons using this ansatz.

Turbulent diffusion causes particles placed in proximity to separate. We investigate the required swimming efforts to maintain an active particle close to its passively advected counterpart. We explore optimally balancing these efforts by developing a novel physics-informed reinforcement learning strategy and comparing it with prescribed control and physics-agnostic reinforcement learning strategies. Our scheme, coined the actor-physicist, is an adaptation of the actor-critic algorithm in which the neural network parameterized critic is replaced with an analytically derived physical heuristic function, the physicist. We validate the proposed physics-informed reinforcement learning approach through extensive numerical experiments in both synthetic Batchelor-Kraichnan and more realistic Arnold-Beltrami-Childress flow environments, demonstrating its superiority in controlling particle dynamics when compared to standard reinforcement learning methods.

Modulating macroscopic parameters of materials in time offers innovative avenues for manipulating electromagnetic waves. Due to such enticing prospects, the general research subject of time-varying systems is expanding today in different branches of electromagnetism and optics. However, compared with the research efforts and progresses that have taken place in the realm of classical electrodynamics, the quantum aspects of this emerging subject have been less explored. Here, through the lens of quantum optics, we study the scattering of electromagnetic fields from an isotropic and nondispersive material with a suddenly changing refractive index, creating a time interface. We revisit the transformation of the bosonic mode operators and corresponding quantum states due to this interface, governed by the two-mode squeeze operator. Building on this foundation, at the core of the investigation, our analysis focuses on the quantum state engineering and photon statistics of the scattered light. Notably, such an analysis reveals and connects various quantum optical phenomena and opportunities arising from the time interface, including photon-pair production and destruction, photon bunching and antibunching, vacuum generation, quantum state discrimination, and quantum state freezing. To bridge theory and experiment, we propose a possible circuit quantum electrodynamics approach for validating our theoretical predictions. We hope that our work inspires experimental investigations of such quantum state engineering and photon statistics phenomena, as well as further quantum optical explorations of electromagnetic field interaction with photonic time crystals or with dispersive time-varying materials.