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At least 487 records · Page 27

Energy barriers for Dy and H penetrating graphene on 6 H -SiC(0001) and freestanding bilayer graphene from first-principles calculations

Currently, intercalation of foreign guest atoms into two-dimensional (2D) layered van der Waals materials is an active research area motivated in part by the development of next-generation energy-storage technologies and optoelectronic devices. One such extensively studied 2D material is the graphene-on-SiC system. To realize and control the desired intercalated structures, it is fundamentally important to understand the kinetic process of intercalation. For the intercalation of a guest atom into graphene layers on SiC substrate, a critical kinetic parameter is the energy barrier of a guest atom penetrating the perfect graphene top layer into the gallery under it. However, accurate theoretical calculations for such penetration barriers are unavailable in literature. From our first-principles density functional theory calculations, we obtain the global energy barriers of 3.47 and 1.80 eV for single Dy and H atoms penetrating the graphene top layer on a graphene buffer layer supported by a Si-terminated 6H-SiC(0001) substrate, respectively. Furthermore, for comparison as well as for examining the lateral strain effects, we also obtain the global barriers of 5.05 and 1.50 eV for single Dy and H atoms penetrating freestanding bilayer graphene with a tensile strain of about 8.8% to match our model for supported graphene, as well as the global barriers of 7.21 and 4.18 eV for penetrating unstrained freestanding bilayer graphene, respectively. From corresponding minimum energy paths with multiple energy minima and saddle points, we can also obtain various local energy barriers and the global backward barrier from the graphene gallery back to the top surface.

2D materials↗

Unveiling hidden physics at the LHC

The field of particle physics is at the crossroads. The discovery of a Higgs-like boson completed the Standard Model (SM), but the lacking observation of convincing resonances Beyond the SM (BSM) offers no guidance for the future of particle physics. On the other hand, the motivation for New Physics has not diminished and is, in fact, reinforced by several striking anomalous results in many experiments. Here we summarise the status of the most significant anomalies, including the most recent results for the flavour anomalies, the multi-lepton anomalies at the LHC, the Higgs-like excess at around 96 GeV, and anomalies in neutrino physics, astrophysics, cosmology, and cosmic rays. While the LHC promises up to 4 ab –1 of integrated luminosity and far-reaching physics programmes to unveil BSM physics, we consider the possibility that the latter could be tested with present data, but that systemic shortcomings of the experiments and their search strategies may preclude their discovery for several reasons, including: final states consisting in soft particles only, associated production processes, QCD-like final states, close-by SM resonances, and SUSY scenarios where no missing energy is produced. New search strategies could help to unveil the hidden BSM signatures, devised by making use of the CERN open data as a new testing ground. We discuss the CERN open data with its policies, challenges, and potential usefulness for the community. We showcase the example of the CMS collaboration, which is the only collaboration regularly releasing some of its data. We find it important to stress that individuals using public data for their own research does not imply competition with experimental efforts, but rather provides unique opportunities to give guidance for further BSM searches by the collaborations. Wide access to open data is paramount to fully exploit the LHCs potential.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Encoding an Oscillator into Many Oscillators

An outstanding challenge for quantum information processing using bosonic systems is Gaussian errors such as excitation loss and added thermal noise errors. Thus, bosonic quantum error correction is essential. Most bosonic quantum error correction schemes encode a finite-dimensional logical qubit or qudit into noisy bosonic oscillator modes. In this case, however, the infinite-dimensional bosonic nature of the physical system is lost at the error-corrected logical level. On the other hand, there are several proposals for encoding an oscillator mode into many noisy oscillator modes. However, these oscillator-into-oscillators encoding schemes are in the class of Gaussian quantum error correction. Therefore, these codes cannot correct practically relevant Gaussian errors due to the established no-go theorems that state that Gaussian errors cannot be corrected by using only Gaussian resources. Here, we circumvent these no-go results and show that it is possible to correct Gaussian errors by using Gottesman-Kitaev-Preskill (GKP) states as non-Gaussian resources. In particular, we propose a non-Gaussian oscillator-into-oscillators code, namely the GKP two-mode squeezing code, and demonstrate that it can quadratically suppress additive Gaussian noise errors in both the position and momentum quadratures except for a small sublogarithmic correction. Furthermore, we demonstrate that our GKP two-mode squeezing code is near optimal in the weak noise limit by proving via quantum information theoretic tools that quadratic noise suppression is optimal when we use two physical oscillator modes. Lastly, in this work we show that our non-Gaussian oscillator encoding scheme can also be used to correct excitation loss and thermal noise errors, which are dominant error sources in many realistic bosonic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impact of dynamics, entanglement and Markovian noise on the fidelity of few-qubit digital quantum simulation

Quantum algorithms have been proposed to accelerate the simulation of the chaotic dynamical systems that are ubiquitous in the physics of plasmas. Quantum computers without error correction might even use noise to their advantage to calculate the Lyapunov exponent by measuring the Loschmidt echo fidelity decay rate. For the first time, digital Hamiltonian simulations of the quantum sawtooth map, performed on the IBM-Q quantum hardware platform, show that the fidelity decay rate of a digital quantum simulation increases during the transition from dynamical localization to chaotic diffusion in the map. The observed error per CNOT gate increases by $1.5{\times }$ as the dynamics varies from localized to diffusive, while only changing the phases of virtual RZ gates and keeping the overall gate count constant. A gate-based Lindblad noise model that captures the effective change in relaxation and dephasing errors during gate operation qualitatively explains the effect of dynamics on fidelity as being due to the localization and entanglement of the states created. Specifically, highly delocalized states that are entangled with random phases show an increased sensitivity to dephasing and, on average, a similar sensitivity to relaxation as localized states. In contrast, delocalized unentangled states show an increased sensitivity to dephasing but a lower sensitivity to relaxation. This gate-based Lindblad model is shown to be a useful benchmarking tool by estimating the effective Lindblad coherence times during CNOT gates and finding a consistent $2\unicode{x2013}3{\times }$ shorter $T_2$ time than reported for idle qubits. Thus, the interplay of the dynamics of a simulation with the noise processes that are active can strongly influence the overall fidelity decay rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The matrix product approximation for the dynamic cavity method

Stochastic dynamics of classical degrees of freedom, defined on vertices of locally tree-like graphs, can be studied in the framework of the dynamic cavity method which is exact for tree graphs. Such models correspond for example to spin-glass systems, Boolean networks, neural networks, and other technical, biological, and social networks. The central objects in the cavity method are edge messages—conditional probabilities of two vertex variable trajectories. In this paper, we discuss a rather pedagogical derivation for the dynamic cavity method, give a detailed account of the novel matrix product edge message (MPEM) algorithm for the solution of the dynamic cavity equation as introduced, and present optimizations and extensions. Matrix product approximations of the edge messages are constructed recursively in an iteration over time. Computation costs and precision can be tuned by controlling the matrix dimensions of the MPEM in truncations. Without truncations, the dynamics is exact. Data for Glauber–Ising dynamics shows a linear growth of computation costs in time. In contrast to Monte Carlo simulations, the approach has a much better error scaling. Hence, it gives for example access to low probability events and decaying observables like temporal correlations. Here, we discuss optimized truncation schemes and an extension that allows to capture models which have a continuum time limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Role of Electron Correlation beyond the Active Space in Achieving Quantitative Predictions of Spin-Phonon Relaxation

Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as temperature rises, interactions between electronic states and lattice vibrations accelerate spin relaxation, significantly limiting their practical applications. Recently, ab initio simulations have made it possible to advance our understanding of phonon-induced magnetic relaxation, but significant deviations from experiments have often been observed. The description of molecules’ electronic structure has been mostly based on complete active space self-consistent field (CASSCF) calculations, and the impact of electron correlation beyond the active space remains largely unexplored. In this study, we provide the first systematic investigation of spin-phonon relaxation in SMMs with post-CASSCF multiconfigurational methods, specifically CAS followed by second-order perturbation theory and multiconfiguration pair-density functional theory. Taking Co(II)- and Dy(III)-based SMMs as case studies, we analyze how electron correlation influences spin-phonon relaxation rates across a range of temperatures, comparing theoretical predictions with experimental observations. Our findings demonstrate that post-CASSCF treatments make it possible to achieve quantitative predictions for Co(II)-based SMMs. For Dy(III)-based systems, however, accurate predictions require consideration of additional effects, underscoring the urgent necessity of further advancing the study of the effects of electronic correlation in these complex systems.

Energy↗

Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2

In the Energy Exascale Earth System Model (E3SM) Multi-scale Modeling Framework (MMF), where parameterizations of convection and turbulence are replaced by a 2-D cloud-resolving model (CRM), there are multiple options to represent land–atmosphere interactions. Here, we propose three different coupling strategies, namely the (1) coupling of a single land surface model to the global grid (MMF), (2) coupling a single land copy directly to the embedded CRM (SFLX2CRM), and (3) coupling a single copy of land model to each column of the CRM grid (MAML). In the MAML (Multi-Atmosphere Multi-Land) framework, a land model is coupled to CRM at the CRM-grid scale by coupling an individual copy of a land model to each CRM grid. Therefore, we can represent intra-CRM heterogeneity in the land–atmosphere interaction processes. There are 5-year global simulations run using these three coupling strategies, and we find some regional differences but overall small changes with respect to whether a land model is coupled to CRM or a global atmosphere. In MAML, the spatial heterogeneity within CRM induces stronger turbulence, which leads to the changes in soil moisture, surface heat fluxes, and precipitation. However, the differences in the MAML from the other two cases are rather weak, suggesting that the impact of using MAML does not justify the increase in cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Pass-efficient methods for compression of high-dimensional turbulent flow data

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential equation (PDE) systems. Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory. To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored. Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., or the execution of the PDE solver is expensive, the number of passes made over the data must be minimized. In the interest of addressing this problem, this work focuses on the utility of pass-efficient, parallelizable, low-rank, matrix decomposition methods in compressing high-dimensional simulation data from turbulent flows. Additionally, a particular emphasis is placed on using coarse representation of the data – compatible with the PDE discretization grid – to accelerate the construction of the low-rank factorization. This includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition. The methods are described extensively and numerical experiments on two turbulent channel flow data are performed. In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics. In the particle-laden case, compression factors of 100 are achieved and the compressed data is used to recover particle velocities. These results show that these compression methods can enable efficient computation of various quantities of interest in both the carrier and disperse phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

OSSOS. XXI. Collision Probabilities in the Edgeworth–Kuiper Belt

Here, we present results on the intrinsic collision probabilities, P {sub I}, and range of collision speeds, V {sub I}, as a function of the heliocentric distance, r, in the trans-Neptunian region. The collision speed is one of the parameters that serves as a proxy for a collisional outcome (e.g., disruption and scattering of fragments, or formation of a crater, as both processes are related to the impact energy). We utilize an improved and debiased model of the trans-Neptunian object (TNO) region from the “Outer Solar System Origins Survey” (OSSOS). It provides a well-defined model of TNO orbital distribution, based on multiple opposition observations of more than 1000 bodies. We compute collisional probabilities for the OSSOS models of the main classical, resonant, detached+outer, and scattering TNO populations. The intrinsic collision probabilities and collision speeds are computed using Öpik’s approach, as revised and modified by Wetherill for noncircular and inclined orbits. The calculations are carried out for each of the dynamical TNO groups, allowing for inter-population collisions as well as collisions within each TNO population, resulting in 28 combinations in total. Our results indicate that collisions in the trans-Neptunian region are possible over a wide range in (r, V {sub I}) phase space. Although collisions are calculated to happen within r ∼ 20–200 au and V {sub I} ∼ 0.1 km s{sup −1} to as high as V {sub I} ∼ 9 km s{sup −1}, most of the collisions are likely to happen at low relative velocities V {sub I} < 1 km s{sup −1} and are dominated by the main classical belt.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Electrically controlling and optically observing the membrane potential of supported lipid bilayers

Supported lipid bilayers are a well-developed model system for the study of membranes and their associated proteins, such as membrane channels, enzymes, and receptors. These versatile model membranes can be made from various components, ranging from simple synthetic phospholipids to complex mixtures of constituents, mimicking the cell membrane with its relevant physiochemical and molecular phenomena. In addition, the high stability of supported lipid bilayers allows for their study via a wide array of experimental probes. In this work, we describe a platform for supported lipid bilayers that is accessible both electrically and optically, and demonstrate direct optical observation of the transmembrane potential of supported lipid bilayers. We show that the polarization of the supported membrane can be electrically controlled and optically probed using voltage-sensitive dyes. Membrane polarization dynamics is understood through electrochemical impedance spectroscopy and the analysis of an equivalent electrical circuit model. In addition, we describe the effect of the conducting electrode layer on the fluorescence of the optical probe through metal-induced energy transfer, and show that while this energy transfer has an adverse effect on the voltage sensitivity of the fluorescent probe, its strong distance dependency allows for axial localization of fluorescent emitters with ultrahigh accuracy. We conclude with a discussion on possible applications of this platform for the study of voltage-dependent membrane proteins and other processes in membrane biology and surface science.

59 BASIC BIOLOGICAL SCIENCES↗

Recovery of release cloud from laser shock-loaded graphite and hydrocarbon targets: in search of diamonds

Abstract This work presents first insights into the dynamics of free-surface release clouds from dynamically compressed polystyrene and pyrolytic graphite at pressures up to 200 GPa, where they transform into diamond or lonsdaleite, respectively. These ejecta clouds are released into either vacuum or various types of catcher systems, and are monitored with high-speed recordings (frame rates up to 10 MHz). Molecular dynamics simulations are used to give insights to the rate of diamond preservation throughout the free expansion and the catcher impact process, highlighting the challenges of diamond retrieval. Raman spectroscopy data show graphitic signatures on a catcher plate confirming that the shock-compressed PS is transformed. First electron microscopy analyses of solid catcher plates yield an outstanding number of different spherical-like objects in the size range between ten(s) up to hundreds of nanometres, which are one type of two potential diamond candidates identified. The origin of some objects can unambiguously be assigned, while the history of others remains speculative.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical Investigation of the Spark Discharge Process in a Crossflow

The present study numerically investigates the spark discharge process under crossflow conditions using a thermal equilibrium plasma solver that fully couples the electromagnetic physics and fluid dynamics in a computational framework. Numerical results are validated by the comparison with experimental data. Here, the spark discharge experiment is performed in a constant volume vessel using an inductive coil ignition system for automotive applications, and the evolution of the spark channel is measured using high-speed imaging. The crossflow in the gap between the spark-plug electrodes is generated by a rotating fan with two different fan speeds, and the flow velocity across the gap is characterized by particle image velocimetry (PIV) measurement. A computational fluid dynamics (CFD) solver is employed to simulate the crossflow and provide the flow field variables (velocity, pressure, temperature) to the plasma solver. The crossflow velocity predicted in the flow simulation agrees well with the PIV data in that the non-uniform velocity profiles at monitoring points are reproduced by the CFD code. With the crossflow initialization in the plasma solver, the simulated spark discharge process from the breakdown to spark discharge matches the experimental data, including the voltage and circuit waveforms and the high-speed images of the spark channel evolution. The stretch of spark channel captured by plasma simulations agrees with the measured data. The plasma simulation reveals that the mean temperature of the spark channel is maintained at 5000 K during the discharge phase, and the temperature varies along the spark channel so that the highest value is obtained at the spark root on the center electrode. Overall, the results presented in this paper are meant to provide valuable information about the properties of the plasma generated by the spark discharge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Magnon-magnon coupling in an all-oxide insulator garnet Y 3 ⁢Fe 5 ⁢O 12 /Tm 3 ⁢Fe 5⁢ O 12 heterostructure

Hybrid magnonic systems have recently attracted significant attention due to their intriguing physics and potential applications in coherent information processing. In this regard, we have investigated magnon-magnon coupling in the all-oxide insulator garnet Y 3⁢ Fe 5⁢ O 12 (YIG)/Tm 3 ⁢Fe 5 ⁢O 12 (TmIG) heterostructure. The presence of an avoided mode crossing region between the ferromagnetic resonance modes of YIG and TmIG indicates interfacial exchange coupling. This all-insulator system enables interfacial coupling via magnon-magnon interactions. The mode crossing occurs at 𝑓 𝑐 = 6.88 GHz, corresponding to the minimal resonance separation between the two hybrid modes. The coupling strength is determined to be 78 MHz (or 2.8 mT), providing clear evidence of magnon-magnon coupling between the two Kittel modes in the YIG/TmIG insulator system at 200 K. As a result, these findings pave the way for engineering magnonic band structures, tunable coherent magnonic interactions, and nonreciprocal spin transport, which are crucial for advancing ultralow-power magnonic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Monitoring Redox Processes in Lithium-Ion Batteries by Laboratory-Scale Operando X-ray Emission Spectroscopy

Tracking changes in the chemical state of transition metals in alkali-ion batteries is crucial to understanding the redox chemistry during operation. X-ray absorption spectroscopy (XAS) is often used to follow the chemistry through observed changes in the chemical state and local atomic structure as a function of the state-of-charge (SoC) in batteries. In this study, we utilize an operando X-ray emission spectroscopy (XES) method to observe changes in the chemical state of active elements in batteries during operation. Operando XES and XAS were compared by using a laboratory-scale setup for four different battery systems: LiCoO 2 (LCO), Li[Ni 1/3 Co 1/3 Mn 1/3 ]O 2 (NMC111), Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 (NMC811), and LiFePO 4 (LFP) under a constant current charging the battery in 10 h (C/10 charge rate). We show that XES, despite narrower chemical shifts in comparison to XAS, allows us to fingerprint the battery SOC in real time. We further demonstrate that XES can be used to track the change in net spin of the probed atoms by analyzing changes in the emission peak shape. As a test case, the connection between net spin and the local chemical and structural environment was investigated by using XES and XAS in the case of electrochemically delithiated LCO in the range of 2–10% lithium removal.

25 ENERGY STORAGE↗

Measurement Uncertainty in One-Of-A-Kind Event Data Analysis

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable, have unavoidable built-in differences resulting in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates over the measurement uncertainty. Range of true values depends on built-in differences in physics of the experiment. Stochastic physical processes result typically in a broader range of true values than non-stochastic processes do. Measurement uncertainty depends on a measurement method (properties of the detector not of the experiment). Modern measurement methods, including digital ones, frequently make the measurement uncertainty very small. When data from one–of –a kind experiment are analyzed, only the measurement uncertainty is reported. It provides no information about the range of true experimental values, neither about reliability of a reported data point. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable. Methods for data analysis from an experiment repeated statistically significant number of times are very well developed. They do not require a detailed expertise in physics of an experiment, nor in the properties of the measurement system used, and meaning of the reported uncertainty is well understood in any scientific community. It all changes when data from one-of-a-kind experiment is analyzed. Analyst’s expertise is required both in the physics of the experiment and in all aspects of the measurement system, all possible malfunctions. Data users must remember that only measurement uncertainty is reported from any one-of-a-kind experiment. Theory with simulations may provide estimation of expected built-in differences in the experiment, and by this of expected range of true values for a given experiment; yet measurement uncertainty can never be used in place of the range of true experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Staircases of passive and active scalar concentration in cellular flow

This paper develops a unified model for staircase formation in both passive and active scalar systems, building upon prior numerical studies by offering new heuristic and physical insights. While prior studies primarily reported numerical results, they did not explore the underlying unifying physics that governs both types of scalar transport; this work addresses that gap by identifying shared mechanisms across both cases. Results of studies of passive and active scalar staircase formation in cellular flows are presented. Staircase formation in cellular flows occurs due to the interplay of fast mixing within cells and slow transport across the inter-cell boundary. The cell boundary emerges as a de facto transport barrier. Special attention is focused on the effects of cellular fluctuations and noise upon staircase structure. A forced, fluctuating vortex array model is used to drive the underlying flow structure. Cellular Peclet number and staircase profile curvature are identified as figures-of-merit to quantify the resiliency of layering. These are related to simple, multi-scatterer scalar random walk models. Results for Peclet number and curvature scaling with flow excitation are presented. We also study staircases of magnetic potential evolving in two-dimensional magnetohydrodynamics as examples of layering of active scalar concentration. Formation of magnetic potential staircases is indeed observed. Flux expulsion inhibits the intercellular transport of magnetic potential and strengthens staircase barriers. Magnetic staircases can be supported against resistive decay by magnetic potential noise forcing. Implications for staircase formation in magnetic confinement experiments are discussed.

Control theory↗

Photon pumping in a weakly-driven quantum cavity–spin system

Highlights: • We study photon frequency conversion in a driven spin coupled to a cavity mode. • Quantized frequency conversion is excpected in the strong-drive adiabatic limit. • A new photon pumping effect is established in the accessible weak drive regime. • Pumping is linked to the delocalization of the corresponding Floquet states. • Quantum coherence is preserved in both the strong and ultraweak-drive limits. We investigate the photon pumping effect in a topological model consisting of a periodically driven spin-1/2 coupled to a quantum cavity mode out of the adiabatic limit. In the strong-drive adiabatic limit, a quantized frequency conversion of photons is expected as the temporal analog of the Hall current. We numerically establish a novel photon pumping phenomenon in the experimentally accessible nonadiabatic driving regime for a broad region of the parameter space. The photon frequency conversion efficiency exhibits strong fluctuations and high efficiency that can reach up 80% of the quantized value for commensurate frequency combinations. We link the pumping properties to the delocalization of the corresponding Floquet states which display multifractal behavior as the result of hybridization between localized and delocalized sectors. Finally we demonstrate that the quantum coherence properties of the initial state are preserved during the frequency conversion process in both the strong and ultra-weak-drive limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗