Tianshu Wang
We explore, using a state-of-the-art simulation code in 3D and to late enough times to witness final observables, the dependence of core-collapse supernova explosions on the nuclear equation of state. Going beyond questions of…
In this work, we explore in a consistent fashion the effects of fast flavor conversion (FFC) in 1D and 2D core-collapse supernova (CCSN) simulations. In addition, we investigate the impact of various angular reconstruction methods and…
We present the first three-dimensional study of the asymptotic ejecta distributions for a suite of theoretical Type IIp supernovae originating from red supergiant progenitors. We simulate using the radiation-hydrodynamic code F{\sc{ornax}}…
We explore the effects of the neutrino collisional flavor instability (CFI) based on 1D and 2D core-collapse supernova (CCSN) simulations done using the sophisticated radiation-hydrodynamic code Fornax. We compare the growth rates of…
Large language models (LLMs) have demonstrated impressive capabilities and are receiving increasing attention to enhance their reasoning through scaling test--time compute. However, their application in open--ended, knowledge--intensive,…
On the basis of a large collection of detailed 3D core-collapse supernova simulations carried to late times, we identify four channels of stellar mass black hole formation. Our examples for Channel 1 involve the formation of lower-gap and…
Merging our supernova code F{\sc{ornax}} with the Box3D fast-flavor neutrino oscillation formalism, we explore the effects of fast-flavor conversion (FFC) in state-of-the-art 1D and 2D core-collapse supernova simulations. We find that after…
In order to better connect core-collapse supernovae (CCSN) theory with its observational signatures, we have developed a simulation pipeline from the onset of core collapse to beyond shock breakout. Using this framework, we present a…
The development of Natural Language Interfaces to Databases (NLIDBs) has been greatly advanced by the advent of large language models (LLMs), which provide an intuitive way to translate natural language (NL) questions into Structured Query…
Recent advances in Large Language Models (LLMs) have demonstrated significant potential in the field of Recommendation Systems (RSs). Most existing studies have focused on converting user behavior logs into textual prompts and leveraging…
Entity matching (EM) is a critical step in entity resolution (ER). Recently, entity matching based on large language models (LLMs) has shown great promise. However, current LLM-based entity matching approaches typically follow a binary…
We report nucleosynthetic results for both $^{44}$Ti and nickel isotopes for eighteen three-dimensional (3D) core-collapse supernova (CCSN) simulations extended to $\sim$20 seconds after bounce. We find that many of our long-term models are…
The practice of Retrieval-Augmented Generation (RAG), which integrates Large Language Models (LLMs) with retrieval systems, has become increasingly prevalent. However, the repercussions of LLM-derived content infiltrating the web and…
We here focus on the behavior of supernovae that technically explode in 1D (spherical symmetry). When simulated in 3D, however, the outcomes of representative progenitors of this class are quite different in almost all relevant quantities.…
Guidance commands of flight vehicles are a series of data sets with fixed time intervals, thus guidance design constitutes a sequential decision problem and satisfies the basic conditions for using deep reinforcement learning (DRL). In this…
Linking a claim to grounded references is a critical ability to fulfill human demands for authentic and reliable information. Current studies are limited to specific tasks like information retrieval or semantic matching, where the…
Blocking is a critical step in entity resolution, and the emergence of neural network-based representation models has led to the development of dense blocking as a promising approach for exploring deep semantics in blocking. However,…
In this paper, we derive correlations between core-collapse supernova observables and progenitor core structures that emerge from our suite of twenty state-of-the-art 3D core-collapse supernova simulations carried to late times. This is the…
Memory is one of the most essential cognitive functions serving as a repository of world knowledge and episodes of activities. In recent years, large-scale pre-trained language models have shown remarkable memorizing ability. On the…
Using twenty long-term 3D core-collapse supernova simulations, we find that lower compactness progenitors that explode quasi-spherically due to the short delay to explosion experience smaller neutron star recoil kicks in the $\sim$100$-$200…