A Diffusion-Model of Joint Interactive Navigation

Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios in simulation ensures realism but the rarity of safety critical events makes large scale collection of driving scenarios expensive. In this paper, we present DJINN - a diffusion based method of generating traffic scenarios. Our approach jointly diffuses the trajectories of all agents, conditioned on a flexible set of state observations from the past, present, or future. On popular trajectory forecasting datasets, we report state of the art performance on joint trajectory metrics. In addition, we demonstrate how DJINN flexibly enables direct test-time sampling from a variety of valuable conditional distributions including goal-based sampling, behavior-class sampling, and scenario editing.Comment: 10 pages, 4 figure

Video Killed the HD-Map: Predicting Driving Behavior Directly From Drone Images

The development of algorithms that learn behavioral driving models using human demonstrations has led to increasingly realistic simulations. In general, such models learn to jointly predict trajectories for all controlled agents by exploiting road context information such as drivable lanes obtained from manually annotated high-definition (HD) maps. Recent studies show that these models can greatly benefit from increasing the amount of human data available for training. However, the manual annotation of HD maps which is necessary for every new location puts a bottleneck on efficiently scaling up human traffic datasets. We propose a drone birdview image-based map (DBM) representation that requires minimal annotation and provides rich road context information. We evaluate multi-agent trajectory prediction using the DBM by incorporating it into a differentiable driving simulator as an image-texture-based differentiable rendering module. Our results demonstrate competitive multi-agent trajectory prediction performance when using our DBM representation as compared to models trained with rasterized HD maps

Establishing non-thermal regimes in pump-probe electron-relaxation dynamics

Time- and angle-resolved photoemission spectroscopy (TR-ARPES) accesses the electronic structure of solids under optical excitation, and is a powerful technique for studying the coupling between electrons and collective modes. One approach to infer electron-boson coupling is through the relaxation dynamics of optically-excited electrons, and the characteristic timescales of energy redistribution. A common description of electron relaxation dynamics is through the effective electronic temperature. Such a description requires that thermodynamic quantities are well-defined, an assumption that is generally violated at early delays. Additionally, precise estimation of the non-thermal window -- within which effective temperature models may not be applied -- is challenging. We perform TR-ARPES on graphite and show that Boltzmann rate equations can be used to calculate the time-dependent electronic occupation function, and reproduce experimental features given by non-thermal electron occupation. Using this model, we define a quantitative measure of non-thermal electron occupation and use it to define distinct phases of electron relaxation in the fluence-delay phase space. More generally, this approach can be used to inform the non-thermal-to-thermal crossover in pump-probe experiments.Comment: 18 pages, 10 figure

Dirac states with knobs on: interplay of external parameters and the surface electronic properties of 3D topological insulators

Topological insulators are a novel materials platform with high applications potential in fields ranging from spintronics to quantum computation. In the ongoing scientific effort to demonstrate controlled manipulation of their electronic structure by external means, stoichiometric variation and surface decoration are two effective approaches that have been followed. In ARPES experiments, both approaches are seen to lead to electronic band structure changes. Such approaches result in variations of the energy position of bulk and surface-related features and the creation of two-dimensional electron gases.The data presented here demonstrate that a third manipulation handle is accessible by utilizing the amount of illumination a topological insulator surface has been exposed to under typical experimental ARPES conditions. Our results show that this new, third, knob acts on an equal footing with stoichiometry and surface decoration as a modifier of the electronic band structure, and that it is in continuous competition with the latter. The data clearly point towards surface photovoltage and photo-induced desorption as the physical phenomena behind modifications of the electronic band structure under exposure to high-flux photons. We show that the interplay of these phenomena can minimize and even eliminate the adsorbate-related surface band bending on typical binary, ternary and quaternary Bi-based topological insulators. Including the influence of the sample temperature, these data set up a framework for the external control of the electronic band structure in topological insulator compounds in an ARPES setting. Four external knobs are available: bulk stoichiometry, surface decoration, temperature and photon exposure. These knobs can be used in conjunction to tune the band energies near the surface and consequently influence the topological properties of the relevant electronic states.Comment: 16 pages, 8 figure

Nature of the current-induced insulator-to-metal transition in Ca2_2RuO4_4 as revealed by transport-ARPES

The Mott insulator Ca$_2$RuO$_4$ exhibits a rare insulator-to-metal transition (IMT) induced by DC current. While structural changes associated with this transition have been tracked by neutron diffraction, Raman scattering, and x-ray spectroscopy, work on elucidating the response of the electronic degrees of freedom is still in progress. Here we unveil the current-induced modifications of the electronic states of Ca$_2$RuO$_4$ by employing angle-resolved photoemission spectroscopy (ARPES) in conjunction with four-probe transport. Two main effects emerge: a clear reduction of the Mott gap and a modification in the dispersion of the Ru-bands. The changes in dispersion occur exclusively along the $XM$ high-symmetry direction, parallel to the $b$-axis where the greatest in-plane lattice change occurs. These experimental observations are reflected in dynamical mean-field theory (DMFT) calculations simulated exclusively from the current-induced lattice constants, indicating a current driven structural transition as the primary mechanism of the IMT. Furthermore, we demonstrate this phase is distinct from the high-temperature zero-current metallic phase. Our results provide insight into the elusive nature of the current-induced IMT of Ca$_2$RuO$_4$ and advance the challenging, yet powerful, technique of transport-ARPES.Comment: 8 pages, 4 figure

Spin-orbit coupling in iridates

Transition-metal oxides (TMOs) are a widely studied class of materials with fascinating electronic properties and a great potential for applications. Sr₂IrO₄ is such a TMO, with a partially filled 5d t₂g shell. Given the reduced Coulomb interactions in these extended 5d orbitals, the insulating state in Sr₂IrO₄ is quite unexpected. To explain this state, it has been proposed that SOC entangles the t₂g states into a filled jeff = 3/2 state and a half-filled jeff = 1/2 state, in which a smaller Coulomb interaction can open a gap. This new scheme extends filling and bandwidth, the canonical control parameters for metal-insulator transitions, to the relativistic domain. Naturally the question arises whether in this case, SOC can in fact drive such a transition. In order to address this question, we have studied the behaviour of Sr₂IrO₄ when substituting Ir for Ru or Rh. Both of these elements change the electronic structure and drive the system into a metallic state. A careful analysis of filling, bandwidth, and SOC, demonstrates that only SOC can satisfactorily explain the transition. This establishes the importance of SOC in the description of metal-insulator transitions and stabilizing the insulating state in Sr₂IrO₄. It has furthermore been proposed that the jeff = 1/2 model in Sr₂IrO₄ is an analogue to the superconducting cuprates, realizing a two-dimensional pseudo-spin 1/2 model. We test this directly by measuring the spin-orbital entanglement using circularly polarized spin-ARPES. Our results indicate that there is a drastic change in the spin-orbital entanglement throughout the Brillouin zone, implying that Sr₂IrO₄ can not simply be described as a pseudo-spin 1/2 insulator, casting doubt on direct comparisons to the cuprate superconductors. We thus find that the insulating ground state in Sr₂IrO₄ is mediated by SOC, however, SOC is not strong enough to fully disentangle the jeff = 1/2 state, requiring that Sr₂IrO₄ is described as a multi-orbital relativistic Mott insulator.Science, Faculty ofPhysics and Astronomy, Department ofGraduat

Critic Sequential Monte Carlo

We introduce CriticSMC, a new algorithm for planning as inference built from a novel composition of sequential Monte Carlo with learned soft-Q function heuristic factors. This algorithm is structured so as to allow using large numbers of putative particles leading to efficient utilization of computational resource and effective discovery of high reward trajectories even in environments with difficult reward surfaces such as those arising from hard constraints. Relative to prior art our approach is notably still compatible with model-free reinforcement learning in the sense that the implicit policy we produce can be used at test time in the absence of a world model. Our experiments on self-driving car collision avoidance in simulation demonstrate improvements against baselines in terms of infraction minimization relative to computational effort while maintaining diversity and realism of found trajectories.Comment: 20 pages, 3 figure