Droplet impact on a surface is practically relevant to a variety of fields in nature and industry, while a complete control of its outcomes remains challenging due to various unmanageable factors. In this work, we propose the quantum simulation of droplet impact outcomes in the platform of ultracold atoms. Specifically, we study the quantum-fluctuation-driven dynamics (QFDD) of two-dimensional Bose-Bose mixtures from an initial Townes soliton towards the formation of a quantum droplet. By tuning the fluctuation energy of the initial Townes state through its size and number, the subsequent QFDD can produce various outcomes including splashing, recoiling, and deposition, similar to those in droplet impact dynamics. We have utilized the Weber number to identify the thresholds of splashing and recoiling, and further established a universal scaling law between the maximum spreading factor and the Weber number in the recoiling regime. In addition, we show that the residual QFDD in the deposition regime can be used to probe the collective breathing modes of a quantum droplet. Our results reveal a mechanism for the droplet impact outcomes, which can be directly tested in cold-atom experiments and can pave the way for exploring intriguing droplet dynamics in a clean and fully controlled quantum setting.

We report the observation of graphene doped up to the Lifshitz transition obtained solely by the intercalation of Erbium atoms. ARPES measurements show that a wide flat band is generated around the $M$ point of the Brillouin zone. We propose that this is the effect of an induced spin-orbit coupling. Scanning Tunneling Microscopy (STM) experiments reveal a longrange ordered hexagonal superstructure: we argue that this reflects the ordering of the intercalated Er atoms acting as impurities. This system provides a playground to study the interaction between a magnetic order and a divergent density of states at the Fermi level.

We perform nonperturbative calculations of light-field driven valley-polarization process in monolayer ${\mathrm{MoS}}_2$ which has additional Rashba spin-orbit couplings (SOCs). The ultrafast electron dynamics is simulated within the independent particle picture by solving density-matrix equations in the basis of linear combination of atomic orbitals, where tight-binding (TB) models including both intrinsic atomic and Rashba SOCs are used to calculate relevant matrix elements. We demonstrate that the Rashba-type SOCs can be manifested by suboptical-cycle control of valley selectivity excitations, in particular necessary via using few-cycle linearly polarized pulse with controlled carrier-envelope phase (CEP). This procedure will lead to a CEP-dependent valley Hall conductivity (VHC), which exhibits an important phase shift among different Rashba coupling strengths. The additional analysis shows that this phase shift is mainly determined by the $d_z^2$-orbital TB Rashba parameter from Mo atom and originates from contribution of conduction bands to VHC, where the Berry curvature modified by Rashba SOC plays a crucial role. Moreover, we also provide a qualitative interpretation on the Rashba-dependent VHC in terms of suboptical-cycle Landau-Zener-Stückelberg interference. Our results suggest a feasible approach for probing Rashba SOCs in hexagonal two-dimensional materials, and might pave the way of achieving more controls in the future valleytronics application.

Computationally intractable tasks are often encountered in physics and optimization. They usually comprise a cost function to be optimized over a so-called feasible set, which is specified by a set of constraints. This may yield, in general, to difficult and nonconvex optimization tasks. A number of standard methods are used to tackle such problems: variational approaches focus on parametrizing a subclass of solutions within the feasible set. In contrast, relaxation techniques have been proposed to approximate it from outside, thus complementing the variational approach to provide ultimate bounds to the global optimal solution. In this paper, we propose a novel approach combining the power of relaxation techniques with deep reinforcement learning in order to find the best possible bounds within a limited computational budget. We illustrate the viability of the method in two paradigmatic problems in quantum physics and quantum information processing: finding the ground state energy of many-body quantum systems, and building energy-based entanglement witnesses of quantum local Hamiltonians. We benchmark our approach against other classical optimization algorithms such as breadth-first search or Monte Carlo, and we characterize the effect of transfer learning. We find the latter may be indicative of phase transitions with a completely autonomous approach. Finally, we provide tools to tackle other common applications in the field of quantum information processing with our method.

Emerging accelerator concepts increasingly rely on the combination of high-frequency electromagnetic radiation with electron beams, enabling longitudinal phase space manipulation which supports a variety of advanced applications. The handshake between electron beams and radiation is conventionally provided by magnetic undulators which unfortunately require a balance between the electron beam energy, undulator parameters, and laser wavelength. Here we propose a scheme using laser-driven large-core antiresonant optical fibers to manipulate electron beams. We explore two general cases using ${\mathrm{TM}}_{01}$ and ${\mathrm{HE}}_{11}$ modes. In the former, we show that large energy modulations $O$(100 keV). can be achieved while maintaining the overall electron beam quality. Further, we show that by using larger field strengths $O$(100 MV/m) the resulting transverse forces can be exploited with beam-matching conditions to filter arbitrary phases from the modulated electron bunch, leading to the production of $\approx 100$ attosecond FWHM microbunches. Finally, we also investigate the application of the transverse dipole ${\mathrm{HE}}_{11}$ mode and find it suitable for supporting time-resolved electron beam measurements with sub-attosecond resolution. We expect the findings to be widely appealing to high-charge pump-probe experiments, metrology, and accelerator science.

The contextual subspace variational quantum eigensolver (CS-VQE) is a hybrid quantum-classical algorithm that approximates the ground-state energy of a given qubit Hamiltonian. It achieves this by separating the Hamiltonian into contextual and noncontextual parts. The ground-state energy is approximated by classically solving the noncontextual problem, followed by solving the contextual problem using VQE, constrained by the noncontextual solution. In general, computation of the contextual correction needs fewer qubits and measurements compared with solving the full Hamiltonian via traditional VQE. We simulate CS-VQE on different tapered molecular Hamiltonians and apply the unitary partitioning measurement reduction strategy to further reduce the number of measurements required to obtain the contextual correction. Our results indicate that CS-VQE combined with measurement reduction is a promising approach to allow feasible eigenvalue computations on noisy intermediate-scale quantum devices. We also provide a modification to the CS-VQE algorithm; the CS-VQE algorithm previously could cause an exponential increase in Hamiltonian terms but with this modification now at worst will scale quadratically.

The fate of many-body localization in long-range interacting systems is not fully settled. For instance, the phase boundary between ergodic and many-body localized regimes is still under debate. Here, we use Floquet dynamics which can induce many-body localization in a clean long-range interacting system through spatio-temporal disorder, which are realized by regular operation of random local rotations. The phase diagram has been determined for two types of uniform and nonuniform long-range couplings. Our Floquet mechanism shows more localizing power than conventional static disorder methods as it pushes the phase boundary in favor of the localized phase. Moreover, our comprehensive long-time simulations provide strong support for obtained results based on static analysis.

Population bottlenecks involve steep declines in population size as well as changes to composition; they are an important aspect of contemporary evolution, and have been implicated across a wide range of taxa. However, the precise mechanisms by which such bottlenecks translate into altered evolutionary outcomes remain poorly understood. Here, we demonstrate how the fixation probabilities associated with such outcomes can depend nontrivially on the rates of post-bottleneck growth and mutation as a population recovers. Notably, increased population growth can invert naive expectations, driving fixation to attractors that are different to those from within whose basin the bottleneck constrained the population, initially, despite more rapidly suppressing the intrinsic fluctuations that are ostensibly required to switch between basins of attraction. Such behavior moreover only occurs beneath a critical threshold of mutation, which is itself a function of the rate of population growth. We explain our results in terms of statistically distinct regimes of demographic behavior, drawing parallels with the notion of nonequilibrium phase transitions. These regimes are delimited by sharp transitions in time, as a population grows, and ultimately result from a time-dependent antagonism between mutation and the stochastically induced effects of frequency-dependent birth. Recast in this context, the rates of population growth and mutation are seen to control long-term fixation probabilities by altering the duration and character of post-bottleneck dynamical demographic regimes.

Cell signaling is essential for individual cells to execute various tasks and respond to changes in their environment. It is carried out via diffusing molecules, whose transport is often aided by directional advection. How diffusion and advection together impact the accuracy of information transmission during signaling remains poorly understood. Here, we study this problem using a simplified model of signal transport in the presence and absence of crowding. Mutual information, our measure of accuracy, shows three distinct regimes characterized by power-law decay. Surprisingly, crowding has no measurable effect on information transmission. Our results provide several important insights into the role of transport in cell signaling.

Ordered atomic arrays with subwavelength lattice spacing emit light collectively. For fully inverted atomic arrays, this results in an initial burst of radiation and a fast buildup of coherences between the atoms at initial times. Based on a cumulant expansion of the equations of motion, we derive exact analytical expressions for the emission properties and numerically analyze the full many-body problem resulting in the collective decay process for unprecedented system sizes of up to a few hundred atoms. We benchmark the cumulant expansion approach and show that it correctly captures the cooperative dynamics resulting in superradiance. For fully inverted arrays, this allows us to extract the scaling of the superradiant peak with particle number. For partially excited arrays where no coherences are shared among atoms, we also determine the critical number of excitations required for the emergence of superradiance in one- and two-dimensional geometries. In addition, we study the robustness of superradiance in the case of non-unit filling and position disorder.

Neural networks with recurrent asymmetric couplings are important to understand how episodic memories are encoded in the brain. Here, we integrate the experimental observation of wide synaptic integration window into our model of sequence retrieval in the continuous time dynamics. The model with non-normal neuron interactions is theoretically studied by deriving a random matrix theory of the Jacobian matrix in neural dynamics. The spectra bears several distinct features, such as breaking rotational symmetry about the origin, and the emergence of nested voids within the spectrum boundary. The spectral density is thus highly nonuniformly distributed in the complex plane. The random matrix theory also predicts a transition to chaos. In particular, the edge of chaos provides computational benefits for the sequential retrieval of memories. Our paper provides a systematic study of time-lagged correlations with arbitrary time delays, and thus can inspire future studies of a broad class of memory models, and even big data analysis of biological time series.

Macroscopic and microscopic properties of dense granular layers flowing down inclined planes are obtained from Discrete-Element-Method simulations for both frictionless and frictional grains. Three fundamental observations for dense granular flows are recovered, namely the occurrence of a critical stress, the Bagnold velocity profile, as well as well-defined friction and dilatancy laws. The microscopic aspects of the grain motion highlight the formation of transient clusters. From this microscopic picture, we derive a theoretical scaling model without any empirical input that explains quantitatively the fundamental laws of dense granular flows in incline plane and shear geometries. The adequacy between the model and the observed results suggests that granular flows can be viewed as flows from thermal fluids of hard spheres.

We study a minimal quantum Otto heat engine, where the working medium consists of an interacting few-body system in a harmonic trap. This allows us to consider the interaction strength as an additional tunable parameter during the work strokes. We calculate the figures of merit of this engine as a function of the temperature and show clearly in which parameter regimes the interactions assist in engine performance. We also study the finite-time dynamics and the subsequent tradeoff between the efficiency and the power, comparing the interaction-enhanced cycle with the case where the system remains scale-invariant.

Quantum phase transitions universally exist in the ground and excited states of quantum many-body systems, and they have a close relationship with the nonequilibrium dynamical phase transitions, which however are challenging to identify. In the system of spin-1 Bose-Einstein condensates, though dynamical phase transitions with correspondence to equilibrium phase transitions in the ground state and uppermost excited state have been probed, those taking place in intermediate excited states remain untouched in experiments thus far. Here we unravel that both the ground- and excited-state quantum phase transitions in spinor condensates can be diagnosed with dynamical phase transitions. A connection between equilibrium phase transitions and nonequilibrium behaviors of the system is disclosed in terms of the quantum Fisher information. We also demonstrate that near the critical points parameter estimation beyond the standard quantum limit can be implemented. This work not only advances the exploration of excited-state quantum phase transitions via a scheme that can immediately be applied to a broad class of few-mode quantum systems, but also provides a new perspective on the relationship between quantum criticality and quantum enhanced sensing.

We study a three-dimensional (3D) classical Ising model that is exactly solvable when some coupling constants take certain imaginary values. The solution combines and generalizes the Onsager-Kaufman solution [L. Onsager, Phys. Rev. 65, 117 (1944); B. Kaufman, Phys. Rev. 76, 1232 (1949)] of the 2D Ising model and the solution of Kitaev's honeycomb model [A. Kitaev, Ann. Phys, 321, 2 (2006)], leading to a three-parameter phase diagram with a third-order phase transition between two distinct phases. Interestingly, the phases of this model are distinguished by topological features: the expectation value of a certain family of loop observables depend only on the topology of the loop (whether the loop is contractible), and are quantized at rational values that differ in the two phases. We show that a related exactly solvable 3D classical statistical model with real coupling constants also shows the topological features of one of these phases. Furthermore, even in the model with complex parameters, the partition function has some physical relevance, as it can be interpreted as the transition amplitude of a quantum dynamical process and may shed light on dynamical quantum phase transitions.