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We are motivated by the problem of autonomous vehicle performance validation. A key challenge is that an autonomous vehicle requires testing in every kind of driving scenario it could encounter, including rare events, to provide a strong case for safety and show there is no edge-case pathological behavior. Autonomous vehicle companies rely on potentially millions of miles driven in realistic simulation to expose the driving stack to enough miles to estimate rates and severity of collisions. To address scalability and coverage, we propose the use of a behavior foundation model, specifically a masked autoencoder (MAE), trained to reconstruct driving scenarios. We leverage the foundation model in two complementary ways: we (i) use the learned embedding space to group qualitatively similar scenarios together and (ii) fine-tune the model to label scenario difficulty based on the likelihood of a collision upon re-simulation. We use the difficulty scoring as importance weighting for the groups of scenarios. The result is an approach which can more rapidly estimate the rates and severity of collisions by prioritizing hard scenarios while ensuring exposure to every kind of driving scenario.

We employ a particle-in-cell Monte Carlo collision/particle-particle particle-mesh (PIC-MCC/PPPM) simulation to study the plasma flow around and the charge distribution of a three-dimensional dust cluster in the sheath of a low-pressure rf argon discharge. The geometry of the cluster and its position in the sheath are fixed to the experimental values, prohibiting a mechanical response of the cluster. Electrically, however, the cluster and the plasma environment, mimicking also the experimental situation, are coupled self-consistently. We find a broad distribution of the charges collected by the grains. The ion flux shows on the scale of the Debye length strong focusing and shadowing inside and outside the cluster due to the attraction of the ions to the negatively charged grains whereas the electron flux is characterized on this scale only by a weak spatial modulation of its magnitude depending on the rf phase. On the scale of the individual dust potentials, however, the electron flux deviates in the vicinity of the cluster strongly from the laminar flow associated with the plasma sheath. It develops convection patterns to compensate for the depletion of electrons inside the dust cluster., Comment: revised version, 14 pages, 13 figures

X-ray phase-contrast imaging has recently led to a revolution in resolving power and tissue contrast in biomedical imaging, microscopy and materials science. The necessary high spatial coherence is currently provided by either large-scale synchrotron facilities with limited beamtime access or by microfocus X-ray tubes with rather limited flux. X-rays radiated by relativistic electrons driven by well-controlled high-power lasers offer a promising route to a proliferation of this powerful imaging technology. A laser-driven plasma wave accelerates and wiggles electrons, giving rise to brilliant keV X-ray emission. This so-called Betatron radiation is emitted in a collimated beam with excellent spatial coherence and remarkable spectral stability. Here we present the first phase-contrast micro-tomogram revealing quantitative electron density values of a biological sample using betatron X-rays, and a comprehensive source characterization. Our results suggest that laser-based X-ray technology offers the potential for filling the large performance gap between synchrotron- and current X-ray tube-based sources., Comment: 16 pages, 5 figures, submitted to Nature Communication

We investigate exciton bound-state formation and crystallization effects in two-dimensional electron-hole bilayers. Performing unbiased path integral Monte Carlo simulations all quantum and Coulomb correlation effects are treated on first principles. We analyze diverse pair distribution functions in dependence on the layer separation, particle density and hole-to-electron mass ratio and derive a schematic phase diagram for the neutral mass-asymmetric bilayer system. Our simulations reveal a great variety of possible phases namely an exciton gas, an exciton crystal, an electron-hole liquid and a hole crystal embedded in an electron gas.

We comment on a recent letter by Amini et al. (EPL 87, 37002 (2009)) concerning the existence of a mobility edge in disordered graphene., Comment: 3 pages, 3 figures

Numerical approaches to Anderson localization face the problem of having to treat large localization lengths while being restricted to finite system sizes. We show that by finite-size scaling of the probability distribution of the local density of states (LDOS) this long-standing problem can be overcome. To this end we reexamine the approach, propose numerical refinements, and apply it to study the dependence of the distribution of the LDOS on the dimensionality and coordination number of the lattice. Particular attention is given to the graphene lattice. We show that the system-size dependence of the LDOS distribution is indeed an unambiguous sign of Anderson localization, irrespective of the dimension and lattice structure. The numerically exact LDOS data obtained by us agree with a log-normal distribution over up to ten orders of magnitude and thereby fulfill a nontrivial symmetry relation previously derived for the non-linear $\sigma$-model., Comment: extended version, new appendix A added, 9 pages, 8 figures

We examine several numerical techniques for the calculation of the dynamics of quantum systems. In particular, we single out an iterative method which is based on expanding the time evolution operator into a finite series of Chebyshev polynomials. The Chebyshev approach benefits from two advantages over the standard time-integration Crank-Nicholson scheme: speedup and efficiency. Potential competitors are semiclassical methods such as the Wigner-Moyal or quantum tomographic approaches. We outline the basic concepts of these techniques and benchmark their performance against the Chebyshev approach by monitoring the time evolution of a Gaussian wave packet in restricted one-dimensional (1D) geometries. Thereby the focus is on tunnelling processes and the motion in anharmonic potentials. Finally we apply the prominent Chebyshev technique to two highly non-trivial problems of current interest: (i) the injection of a particle in a disordered 2D graphene nanoribbon and (ii) the spatiotemporal evolution of polaron states in finite quantum systems. Here, depending on the disorder/electron-phonon coupling strength and the device dimensions, we observe transmission or localisation of the matter wave., Comment: 8 pages, 3 figures

Disorder effects strongly influence the transport properties of graphene based nanodevices even to the point of Anderson localization. Focusing on the local density of states and its distribution function, we analyze the localization properties of actual size graphene nanoribbons. In particular we determine the time evolution and localization length of the single particle wave function in dependence on the ribbon extension and edge geometry, as well as on the disorder type and strength., Comment: final version, 5 pages, 5 figures