Large Trajectory Models are Scalable Motion Predictors and Planners

Motion prediction and planning are vital tasks in autonomous driving, and recent efforts have shifted to machine learning-based approaches. The challenges include understanding diverse road topologies, reasoning traffic dynamics over a long time horizon, interpreting heterogeneous behaviors, and generating policies in a large continuous state space. Inspired by the success of large language models in addressing similar complexities through model scaling, we introduce a scalable trajectory model called State Transformer (STR). STR reformulates the motion prediction and motion planning problems by arranging observations, states, and actions into one unified sequence modeling task. With a simple model design, STR consistently outperforms baseline approaches in both problems. Remarkably, experimental results reveal that large trajectory models (LTMs), such as STR, adhere to the scaling laws by presenting outstanding adaptability and learning efficiency. Qualitative results further demonstrate that LTMs are capable of making plausible predictions in scenarios that diverge significantly from the training data distribution. LTMs also learn to make complex reasonings for long-term planning, without explicit loss designs or costly high-level annotations

The Early Cretaceous extensional deformation in the southeastern Beishan Range, central Asia: Constrains from 2D seismic reflection profile interpretation and apatite fission track thermochronology

Objective  The Beishan Range occupies a key position in Central Asia. This study aims to deepen the understanding of the timing, intracontinental deformation processes, and their dynamic mechanisms in the Late Mesozoic on the southern margin of the Central Asian Orogenic Belt (CAOB).   Methods  We conducted detailed analyses of the Early Cretaceous extensional and earlier compressional structures in the southeastern Beishan Range through field geological observations, interpretation of 2D reflection seismic profiles, and apatite fission track thermochronology.   Conclusion  Field observations show that Lower–Middle Jurassic strata have been strongly deformed by numerous thrusts and folds. 2D seismic reflection profiles reveal two NE- to NEE-striking normal faults. The Suosuojing fault is a SE-dipping low-angle listric normal fault, while the Wudaoming fault is a NW-dipping high-angle normal fault. These normal faults cut through the early-formed fold-thrust system, indicating a transition from contraction to extension. The Suosuojing and Wudaoming faults, respectively, define the northwestern and southeastern boundaries of the Early Cretaceous Zongkouzi basin. The Zongkouzi basin exhibits a graben geometry, with Lower Cretaceous strata displaying typical growth-strata relationships, suggesting that the normal faults were active during the late Early Cretaceous. Thermal history modeling results from apatite fission track data indicate that the footwall of the Suosuojing fault experienced rapid cooling between 132 and 110 Ma. This rapid cooling phase was closely related to the footwall exhumation during the normal slip of the Suosuojing fault. We argue that the Late Mesozoic intracontinental contraction–extension transition in the southeastern Beishan Range likely occurred between ~133 Ma and ~129 Ma in the late Early Cretaceous. The collapse of the thickened crust and coupled mantle upwelling triggered the Early Cretaceous extensional deformation in the southern CAOB

Preliminary Test Results for the MICE Spectrometer Superconducting Solenoids

This report describes the MICE spectrometer solenoids as built. Each magnet consists of five superconducting coils. Two coils are used to tune the beam going from or to the MICE spectrometer from the rest of the MICE cooling channel. Three spectrometer coils (two end coils and a long center coil) are used to create a uniform 4 T field (to {+-}0.3 percent) over a length of 1.0 m within a diameter of 0.3 m. The three-coil spectrometer set is connected in series. The two end coils use small power supplies to tune the uniform field region where the scintillating fiber tracker is located. This paper will present the results of the preliminary testing of the first spectrometer solenoid

Design and Construction of a Prototype Solenoid Coil for MICE Coupling Magnets

A superconducting coupling solenoid mounted around four conventional RF cavities, which produces up to 2.6 T central magnetic field to keep the muons within the cavities, is to be used for the Muon Ionization Cooling Experiment (MICE). The coupling coil made from copper matrix NbTi conductors is the largest of three types of magnets in MICE both in terms of 1.5 m inner diameter and about 13MJ stored magnetic energy at full operation current of 210A. The stress induced inside the coil assembly during cool down and magnet charging is relatively high. In order to validate the design method and develop the coil winding technique with inside-wound SC splices required for the coupling coil, a prototype coil made from the same conductor and with the same diameter and thickness but only one-fourth long as the coupling coil was designed and fabricated by ICST. The prototype coil was designed to be charged to strain conditions that are equivalent or greater than would be encountered in the coupling coil. This paper presents detailed design of the prototype coil as well as developed coil winding skills. The analyses on stress in the coil assembly and quench process were carried out

Status of Muon Collider Research and Development and Future Plans

The status of the research on muon colliders is discussed and plans are outlined for future theoretical and experimental studies. Besides continued work on the parameters of a 3-4 and 0.5 TeV center-of-mass (CoM) energy collider, many studies are now concentrating on a machine near 0.1 TeV (CoM) that could be a factory for the s-channel production of Higgs particles. We discuss the research on the various components in such muon colliders, starting from the proton accelerator needed to generate pions from a heavy-Z target and proceeding through the phase rotation and decay ($\pi \to \mu \nu_{\mu}$) channel, muon cooling, acceleration, storage in a collider ring and the collider detector. We also present theoretical and experimental R & D plans for the next several years that should lead to a better understanding of the design and feasibility issues for all of the components. This report is an update of the progress on the R & D since the Feasibility Study of Muon Colliders presented at the Snowmass'96 Workshop [R. B. Palmer, A. Sessler and A. Tollestrup, Proceedings of the 1996 DPF/DPB Summer Study on High-Energy Physics (Stanford Linear Accelerator Center, Menlo Park, CA, 1997)].Comment: 95 pages, 75 figures. Submitted to Physical Review Special Topics, Accelerators and Beam

Stabilization of the 81-channel coherent beam combination using machine learning.

We develop a rapidly converging algorithm for stabilizing a large channel-count diffractive optical coherent beam combination. An 81-beam combiner is controlled by a novel, machine-learning based, iterative method to correct the optical phases, operating on an experimentally calibrated numerical model. A neural-network is trained to detect phase errors based on interference pattern recognition of uncombined beams adjacent to the combined one. Due to the non-uniqueness of solutions in the full space of possible phases, the network is trained within a limited phase perturbation/error range. This also reduces the number of samples needed for training. Simulations have proven that the network can converge in one step for small phase perturbations. When the trained neural-network is applied to a realistic case of 360 degree full range, an iterative scheme exploits random walking at the beginning, with the accuracy of prediction on phase feedback direction, to allow the neural-network to step into the training range for fast convergence. This neural-network-based iterative method of phase detection works tens of times faster than the commonly used stochastic parallel gradient descent approach (SPGD) using a single-detector and random dither when both are tested with random phase perturbations

81-beam coherent combination using a programmable array generator.

We have generated 81 independently controllable beams using a spatial light modulator and combined them on a diffractive combiner, to characterize the combiner and develop a fast phase error detection scheme. A key parameter of the diffractive combiner is measured in a new way, enabling an efficient combination when programming calibrated phases of each beam. This testbed provides a platform for development of advanced feedback phase control of high channel-count beam combination