Poincar\'e invariance of spinning binary dynamics in the post-Minkowskian Hamiltonian approach

We initiate the construction of the global Poincar\'e algebra generators in the context of the post-Minkowskian Hamiltonian formulation of gravitating binary dynamics in isotropic coordinates that is partly inspired by scattering amplitudes. At the first post-Minkowskian (1PM) order, we write down the Hamiltonian in a form valid in an arbitrary inertial frame. Then we construct the boost generator at the same order which uniquely solves all the equations required by the Poincar\'e algebra. Our results are linear in Newton's constant but exact in velocities and spins, including all spin multiple moments. We also compute the generators of canonical transformations that proves the equivalence between our new generators and the corresponding generators in the ADM coordinates up to the second post-Newtonian (2PN) order.Comment: 33 pages; v2. references added, minor correction

Classical observables from partial wave amplitudes

We study the formalism of Kosower-Maybee-O'Connell (KMOC) to extract classical impulse from quantum amplitude in the context of the partial wave expansion of a 2-to-2 elastic scattering. We take two complementary approaches to establish the connection. The first one takes advantage of Clebsch-Gordan relations for the base amplitudes of the partial wave expansion. The second one is a novel adaptation of the traditional saddle point approximation in the semi-classical limit. In the former, an interference between the S-matrix and its conjugate leads to a large degree of cancellation such that the saddle point approximation to handle a rapidly oscillating integral is no longer needed. As an example with a non-orbital angular momentum, we apply our methods to the charge-monopole scattering problem in the probe limit and reproduce both of the two angles characterizing the classical scattering. A spinor basis for the partial wave expansion, a non-relativistic avatar of the spinor-helicity variables, plays a crucial role throughout our computations.Comment: 48 pages, 3 figure

Controlled Text Generation for Black-box Language Models via Score-based Progressive Editor

Despite recent progress in language models, generating constrained text for specific domains remains a challenge, particularly when utilizing black-box models that lack domain-specific knowledge. In this paper, we introduce ScoPE (Score-based Progressive Editor) generation, a novel approach for controlled text generation for black-box language models. We employ ScoPE to facilitate text generation in the target domain by integrating it with language models through a cascading approach. Trained to enhance the target domain score of the edited text, ScoPE progressively edits intermediate output discrete tokens to align with the target attributes throughout the auto-regressive generation process of the language model. This iterative process guides subsequent steps to produce desired output texts for the target domain. Our experimental results on diverse controlled generations demonstrate that ScoPE effectively facilitates controlled text generation for black-box language models in both in-domain and out-of-domain conditions, which is challenging for existing methods

Learning-based Uncertainty-aware Navigation in 3D Off-Road Terrains

This paper presents a safe, efficient, and agile ground vehicle navigation algorithm for 3D off-road terrain environments. Off-road navigation is subject to uncertain vehicle-terrain interactions caused by different terrain conditions on top of 3D terrain topology. The existing works are limited to adopt overly simplified vehicle-terrain models. The proposed algorithm learns the terrain-induced uncertainties from driving data and encodes the learned uncertainty distribution into the traversability cost for path evaluation. The navigation path is then designed to optimize the uncertainty-aware traversability cost, resulting in a safe and agile vehicle maneuver. Assuring real-time execution, the algorithm is further implemented within parallel computation architecture running on Graphics Processing Units (GPU).Comment: 6 pages, 6 figures, submitted to International Conference on Robotics and Automation (ICRA 2023

Learning Terrain-Aware Kinodynamic Model for Autonomous Off-Road Rally Driving With Model Predictive Path Integral Control

High-speed autonomous driving in off-road environments has immense potential for various applications, but it also presents challenges due to the complexity of vehicle-terrain interactions. In such environments, it is crucial for the vehicle to predict its motion and adjust its controls proactively in response to environmental changes, such as variations in terrain elevation. To this end, we propose a method for learning terrain-aware kinodynamic model which is conditioned on both proprioceptive and exteroceptive information. The proposed model generates reliable predictions of 6-degree-of-freedom motion and can even estimate contact interactions without requiring ground truth force data during training. This enables the design of a safe and robust model predictive controller through appropriate cost function design which penalizes sampled trajectories with unstable motion, unsafe interactions, and high levels of uncertainty derived from the model. We demonstrate the effectiveness of our approach through experiments on a simulated off-road track, showing that our proposed model-controller pair outperforms the baseline and ensures robust high-speed driving performance without control failure.Comment: Accepted to IEEE Robotics and Automation Letters (and ICRA 2024). Our video can be found at https://youtu.be/VXf_prNQnJo Project page : https://sites.google.com/view/terrainawarekinody

Offline-to-Online Knowledge Distillation for Video Instance Segmentation

In this paper, we present offline-to-online knowledge distillation (OOKD) for video instance segmentation (VIS), which transfers a wealth of video knowledge from an offline model to an online model for consistent prediction. Unlike previous methods that having adopting either an online or offline model, our single online model takes advantage of both models by distilling offline knowledge. To transfer knowledge correctly, we propose query filtering and association (QFA), which filters irrelevant queries to exact instances. Our KD with QFA increases the robustness of feature matching by encoding object-centric features from a single frame supplemented by long-range global information. We also propose a simple data augmentation scheme for knowledge distillation in the VIS task that fairly transfers the knowledge of all classes into the online model. Extensive experiments show that our method significantly improves the performance in video instance segmentation, especially for challenging datasets including long, dynamic sequences. Our method also achieves state-of-the-art performance on YTVIS-21, YTVIS-22, and OVIS datasets, with mAP scores of 46.1%, 43.6%, and 31.1%, respectively

Finger-triggered portable PDMS suction cup for equipment-free microfluidic pumping

This study presents a finger-triggered portable polydimethylsiloxane suction cup that enables equipment-free microfluidic pumping. The key feature of this method is that its operation only involves a “pressing-and-releasing” action for the cup placed at the outlet of a microfluidic device, which transports the fluid at the inlet toward the outlet through a microchannel. This method is simple, but effective and powerful. The cup is portable and can easily be fabricated from a three-dimensional printed mold, used without any pre-treatment, reversibly bonded to microfluidic devices without leakage, and applied to various material-based microfluidic devices. The effect of the suction cup geometry and fabrication conditions on the pumping performance was investigated. Furthermore, we demonstrated the practical applications of the suction cup by conducting an equipment-free pumping of thermoplastic-based microfluidic devices and water-in-oil droplet generation.11Yscopu

Active Matrix Organic Light-Emitting Displays: Novel Amorphous Silicon Thin-Film Transistors and Pixel Electrode Circuits.

Today active-matrix organic light-emitting displays (AM-OLEDs) are considered as next generation flat panel display. In this thesis, several hydrogenated amorphous silicon (a-Si:H) thin-film transistor (TFT) technologies have been developed to accelerate the AM-OLED development. Among others to address the charging time delay issue of the conventional current-driven a-Si:H TFT pixel electrode circuit, a non-linear current scaling-function by cascaded-capacitors connected to the driving TFT was investigated. To enhance the performance of fabricated pixel electrode circuit, novel design of a-Si:H pixel circuit with cascaded storage capacitors was investigated based on the current-mirror structure. The electrical and thermal stability of the proposed a-Si:H TFT pixel electrode circuits were also explored in comparison to the conventional current-driven circuit. To address the inherent electrical stability issue of the a-Si:H TFT, two novel a-Si:H TFT structures were proposed: Corbino and Hexagonal TFTs. It was shown that both a-Si:H TFT structures have the asymmetric electrical characteristics under different drain bias conditions. To extract the electrical device parameters, asymmetric geometric factors were developed for different drain bias conditions. By using multiple Hexagonal TFT structure, the output current of Hexagonal a-Si:H TFT connected in parallel increases linearly with their number within a given pixel circuit. Current-voltage measurements indicate that a high ON-OFF current ratio and a low sub-threshold slope can be maintained for multiple Hexagonal TFTs connected in parallel while the field-effect mobility and threshold voltage remain identical to a single HEX a-Si:H TFT. Due to a unique device geometry, enhanced electrical stability and larger pixel aperture ratio can be achieved in the multiple a-Si:H HEX-TFT in comparison to standard single a-Si:H TFT having same channel width. Lastly, the dynamic responses of different a-Si:H TFT structures with various storage capacitor size were explored for AM-OLEDs. The effect of dofferent storage capacitors and overlap capacitors of TFTs on the charging time and feed-through voltage characteristics of the a-Si:H switching TFT were explored. Feed-through voltage behavior of Corbino a-Si:H TFT was also discussed in comparison to normal rectangular a-Si:H TFT as a switching TFT for AM-OLEDs.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58418/1/hojinny_1.pd