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Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extends to technical challenges within science and engineering, including the nascent field of quantum computing (QC). The counterintuitive nature and high-dimensional mathematics of QC make it a prime candidate for AI's data-driven learning capabilities, and in fact, many of QC's biggest scaling challenges may ultimately rest on developments in AI. However, bringing leading techniques from AI to QC requires drawing on disparate expertise from arguably two of the most advanced and esoteric areas of computer science. Here we aim to encourage this cross-pollination by reviewing how state-of-the-art AI techniques are already advancing challenges across the hardware and software stack needed to develop useful QC - from device design to applications. We then close by examining its future opportunities and obstacles in this space., Comment: 42 pages, 7 figures, 2 tables

Cohesive particles form agglomerates that are usually very porous. Their geometry, particularly their fractal dimension, depends on the agglomeration process (diffusion-limited or ballistic growth by adding single particles or cluster-cluster aggregation). However, in practice, the packing structure depends not only on the initial formation but also on the mechanical processing of the agglomerate after it has grown. Surprisingly, the packing converges to a statistically invariant structure under certain process conditions, independent of the initial growth process. We consider the repeated fragmentation on a given length scale, followed by ballistic agglomeration. Examples of fragmentation are sieving with a given mesh size or dispersion in a turbulent fluid. We model the agglomeration by gravitational sedimentation. The asymptotic structure is fractal up to the fragmentation length scale, and the fragments have a power-law size distribution. A scaling relation connects the power law and the fractal dimension., Comment: 13 pages, 12 figures

Biomineralizing organisms are widely noted and extensively studied due to their ability to generate structures exhibiting exceptional crystallographic control. Primarily, it is the organisms, such as sea-urchins or bivalves, that generate nearly single-crystalline biocrystals that have attracted attention. In contrast, biomineralizing organisms with seemingly disordered polycrystalline bio-armor have been left relatively unstudied. However, the crystalline ordering in the black-lipped pearl oyster, Pinctada margaritifera, reveals that biominerals with varying crystal textures are an unrecognized class of functionally graded materials. Changing crystal textures inevitably cause a variation in Young modulus due to the orientation-dependent mechanical properties of crystals. The case of Pinctada margaritifera demonstrates that bioceramics with such crystallographical gradients are toughened by stress delocalization and reduced stress intensity factors, outperforming non-graded counterparts. These findings suggest that a multitude of biominerals, which are perceived as poorly ordered because of their polycrystallinity and changing crystal textures, may be considered as graded materials with hitherto unidentified emergent mechanical properties. The underlying design principle is remarkably simple and applicable to a wide range of crystalline material classes and may thus serve as a blueprint for future bioinspired functional materials.

We report on the evaporation of hexane from porous alumina and silicon membranes. These membranes contain billions of independent nanopores tailored to an ink-bottle shape, where a cavity several tens of nanometers in diameter is separated from the bulk vapor by a constriction. For alumina membranes with narrow enough constrictions, we demonstrate that cavity evaporation proceeds by cavitation. Measurements of the pressure dependence of the cavitation rate follow the predictions of the bulk, homogeneous, classical nucleation theory, definitively establishing the relevance of homogeneous cavitation as an evaporation mechanism in mesoporous materials. Our results imply that porous alumina membranes are a promising new system to study liquids in a deeply metastable state., Comment: 14 pages , 4 figures. Source files also contain Supplemental Material (Doebele_HomogeneousCavitationMembranes_SM.pdf)

The combination of soft nanoscale organic components with inorganic nanograins hierarchically designed by natural organisms results in highly ductile structural materials that can withstand mechanical impact and exhibit high resilience on the macro- and nano-scale. Our investigation of nacre deformation reveals the underlying nanomechanics that govern the structural resilience and absorption of mechanical energy. Using high-resolution scanning/transmission electron microscopy (S/TEM) combined with in situ indentation, we observe nanoscale recovery of heavily deformed nacre that restores its mechanical strength on external stimuli up to 80% of its yield strength. Under compression, nacre undergoes deformation of nanograins and non-destructive locking across organic interfaces such that adjacent inorganic tablets structurally join. The locked tablets respond to strain as a continuous material, yet the organic boundaries between them still restrict crack propagation. Remarkably, the completely locked interface recovers its original morphology without any noticeable deformation after compressive contact stresses as large as 1.2 GPa., Comment: 4 figures

A new statistical model for the combined effects of decoherence, energy redistribution and dissipation on electron transport in large quantum systems is introduced. The essential idea is to consider the electron phase information to be lost only at randomly chosen regions with an average distance corresponding to the decoherence length. In these regions the electron's energy can be unchanged or redistributed within the electron system or dissipated to a heat bath. The different types of scattering and the decoherence leave distinct fingerprints in the energy distribution functions. They can be interpreted as a mixture of unthermalized and thermalized electrons. In the case of weak decoherence, the fraction of thermalized electrons show electrical and thermal contact resistances. In the regime of incoherent transport the proposed model is equivalent to a Boltzmann equation. The model is applied to experiments with carbon nanotubes. The excellent agreement of the model with the experimental data allows to determine the scattering lengths of the system., Comment: 19 pages, 11 figures

The thermal boundary resistance (Kapitza resistance) of (001) twist grain boundaries in silicon nanowires depends on the mismatch angle. This dependence is systematically investigated by means of nonequilibrium molecular dynamics simulations. Grain boundary systems with and without coincidence site lattice are compared. The Kapitza resistance increases with twist angle up to 40{\deg}. For larger angles, it varies only little around 1.56 $\pm$ 0.05 K m^2/GW, except for a drop by 30% near the 90{\deg} {\Sigma} 1 grain boundary. Finite size effects due to the fixed outer boundary conditions of the nanowire are negligible for diameters larger than 25 nm., Comment: The following article has been submitted to the Journal of Applied Physics (JAP). After it is published, it will be found at http://aip.scitation.org/journal/jap

The Onsager-de Groot-Callen transport theory, implemented as a network model, is used to simulate the transient Harman method, which is widely used experimentally to determine all thermoelectric transport coefficients in a single measurement setup. It is shown that this method systematically overestimates the Seebeck coefficient for samples composed of two different materials. As a consequence, the figure of merit is also overestimated, if the thermal coupling of the measurement setup to the environment is weak. For a mixture of metal and semiconductor particles near metal percolation the figure of merit obtained by the Harman method is more than 100 \% too large. For a correct interpretation of the experimental data, information on composition and microstructure of the sample are indispensable.

Intricate biomineralization processes in molluscs engineer hierarchical structures with meso-, nano-, and atomic architectures that give the final composite material exceptional mechanical strength and optical iridescence on the macroscale. This multiscale biological assembly inspires new synthetic routes to complex materials. Our investigation of the prism-nacre interface reveals nanoscale details governing the onset of nacre formation using high-resolution scanning transmission electron microscopy. A wedge polishing technique provides unprecedented, large-area specimens required to span the entire interface. Within this region, we find a transition from nanofibrillar aggregation to irregular early-nacre layers, to well-ordered mature nacre suggesting the assembly process is driven by aggregation of nanoparticles (~50-80 nm) within an organic matrix that arrange in fiber-like polycrystalline configurations. The particle number increases successively and, when critical packing is reached, they merge into early-nacre platelets. These results give new insights into nacre formation and particle-accretion mechanisms that may be common to many calcareous biominerals., Comment: 5 Figures

In this numerical study, measurements of the contact forces inside a periodic two-dimensional sheared system of soft frictional particles are reported. The distribution of normalized normal forces exhibits a gradual broadening with increasing the pure shear deformation, leading to a slower decay for large forces. The process however slows down and the distribution approaches an invariant shape at high shear deformations. By introducing the joint probability distribution in sheared configurations, it is shown that for a fixed direction, the force distribution decays faster than exponentially even in a sheared system. The overall broadening can be attributed to the averaging over different directions in the presence of shear-induced stress anisotropy. The distribution of normalized tangential forces almost preserves its shape for arbitrary applied strain., Comment: 5 pages, 7 figures

A substantial number of algorithms exists for the simulation of moving particles suspended in fluids. However, finding the best method to address a particular physical problem is often highly non-trivial and depends on the properties of the particles and the involved fluid(s) together. In this report we provide a short overview on a number of existing simulation methods and provide two state of the art examples in more detail. In both cases, the particles are described using a Discrete Element Method (DEM). The DEM solver is usually coupled to a fluid-solver, which can be classified as grid-based or mesh-free (one example for each is given). Fluid solvers feature different resolutions relative to the particle size and separation. First, a multicomponent lattice Boltzmann algorithm (mesh-based and with rather fine resolution) is presented to study the behavior of particle stabilized fluid interfaces and second, a Smoothed Particle Hydrodynamics implementation (mesh-free, meso-scale resolution, similar to the particle size) is introduced to highlight a new player in the field, which is expected to be particularly suited for flows including free surfaces., Comment: 16 pages, 4 figures

An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.

We report experiments on slow granular flows in a split-bottom Couette cell that show novel strain localization features. Nontrivial flow profiles have been observed which are shown to be the consequence of simultaneous formation of shear zones in the bulk and at the boundaries. The fluctuating band model based on a minimization principle can be fitted to the experiments over a large variation of morphology and filling height with one single fit parameter, the relative friction coefficient between wall and bulk. The possibility of multiple shear zone formation is controlled by the relative friction. Moreover, we observe that the symmetry of an initial state, with coexisting shear zones at both side walls, breaks spontaneously below a threshold value of the shear velocity. A dynamical transition between two asymmetric flow states happens over a characteristic time scale which depends on the shear strength., Comment: 5 pages, 5 figures, to appear in Phys. Rev. Lett. (2013)

We study the long-range spatial correlations in the nonequilibrium steady state of a randomly driven granular fluid with the emphasis on obtaining the explicit form of the static structure factors. The presence of immobile particles immersed in such a fluidized bed of fine particles leads to the confinement of the fluctuation spectrum of the hydrodynamic fields, which results in effective long-range interactions between the intruders. The analytical predictions are in agreement with the results of discrete element method simulations. By changing the shape and orientation of the intruders, we address how the effective force is affected by small changes in the boundary conditions., Comment: 9 pages, 7 figures

Electron transport through disordered quasi one-dimensional quantum systems is studied. Decoherence is taken into account by a spatial distribution of virtual reservoirs, which represent local interactions of the conduction electrons with their environment. We show that the decoherence distribution has observable effects on the transport. If the decoherence reservoirs are distributed randomly without spatial correlations, a minimal degree of decoherence is necessary to obtain Ohmic conduction. Below this threshold the system is localized and thus, a decoherence driven metal-insulator transition is found. In contrast, for homogenously distributed decoherence, any finite degree of decoherence is sufficient to destroy localization. Thus, the presence or absence of localization in a disordered one-dimensional system may give important insight about how the electron phase is randomized., Comment: 8 pages, 5 figures

The evolution of the force distributions during the isotropic compression of two dimensional packings of soft frictional particles is investigated numerically. Regardless of the applied deformation, the normal contact force distribution can be fitted by the product of a power-law, and a stretched exponential, while the tangential force distribution is fitted well by a Gaussian. With increasing strain, the asymptotic behavior at large forces does not change, but both normal and tangential distributions exhibit a broadening, even though, when scaled with the average forces, their widths decrease. Furthermore, the distribution of friction mobilization is a decreasing function of the mobilization, except for an increased probability of fully mobilized contacts. The excess coordination number of the packings increases with the applied strain, indicating that the more a packing is compressed the more stable it becomes., Comment: 5 pages, 5 figures

While the self-learning kinetic Monte Carlo (SLKMC) method enables the calculation of transition rates from a realistic potential, implementations of it were usually limited to one specific surface orientation. An example is the fcc (111) surface in Latz et al. 2012, J. Phys.: Condens. Matter 24, 485005. This work provides an extension by means of detecting the local orientation, and thus allows for the accurate simulation of arbitrarily shaped surfaces. We applied the model to the diffusion of Ag monolayer islands and voids on a Ag(111) and Ag(001) surface, as well as the relaxation of a three-dimensional spherical particle.

We study theoretically how electrons, coherently injected at one point on the boundary of a two-dimensional electron system, are focused by a perpendicular magnetic field $B$ onto another point on the boundary. Using the non-equilibrium Green's function approach, we calculate the generalized 4-point Hall resistance $R_{xy}$ as a function of B. In weak fields, $R_{xy}$ shows the characteristic equidistant peaks observed in the experiment and explained by classical cyclotron motion along the boundary. In strong fields, $R_{xy}$ shows a single extended plateau reflecting the quantum Hall effect. In intermediate fields, we find superimposed upon the lower Hall plateaus anomalous oscillations, which are neither periodic in 1/B (quantum Hall effect) nor in $B$ (classical cyclotron motion). The oscillations are explained by the interference between the occupied edge channels, which causes beatings in $R_{xy}$. In the case of two occupied edge channels, these beatings constitute a new commensurability between the magnetic flux enclosed within the edge channels and the flux quantum. Introducing decoherence and a partially specular boundary shows that this new effect is quite robust., Comment: 7 pages, 8 figures

The reliability of kinetic Monte Carlo (KMC) simulations depends on accurate transition rates. The self-learning KMC method (Trushin et al 2005 Phys. Rev. B 72 115401) combines the accuracy of rates calculated from a realistic potential with the efficiency of a rate catalog, using a pattern recognition scheme. This work expands the original two-dimensional method to three dimensions. The concomitant huge increase in the number of rate calculations on the fly needed can be avoided by setting up an initial database, containing exact activation energies calculated for processes gathered from a simpler KMC model. To provide two representative examples, the model is applied to the diffusion of Ag monolayer islands on Ag(111), and the homoepitaxial growth of Ag on Ag(111) at low temperatures.