6 citations · 6 across the 6 of their papers we have counts for
6 papers
Artificial Entanglement in the Fine-Tuning of Large Language Models
Min Chen, Zihan Wang, Canyu Chen +3
Large language models (LLMs) can be adapted to new tasks using parameter-efficient fine-tuning (PEFT) methods that modify only a small number of trainable parameters, often through…
Provably Efficient Quantum Algorithms for Solving Nonlinear Differential Equations Using Multiple Bosonic Modes Coupled with Qubits
Yu Gan, Hirad Alipanah, Jinglei Cheng +7
Quantum computers have long been expected to efficiently solve complex classical differential equations. Most digital, fault-tolerant approaches use Carleman linearization to map n…
PEGNet: A Physics-Embedded Graph Network for Long-Term Stable Multiphysics Simulation
Can Yang, Zhenzhong Wang, Junyuan Liu +2
Accurate and efficient simulations of physical phenomena governed by partial differential equations (PDEs) are important for scientific and engineering progress. While traditional…
A parity obstruction to degree-optimal syndrome extraction in bivariate bicycle codes
Guangyi Li, Yu Gan, Zeguan Wu +3
Syndrome extraction for a CSS code has depth at least the Tanner-graph degree , attained by edge colouring if gate order is ignored; correctness adds a parity constraint. We pro…
Quantum Dynamics Simulation of the Advection-Diffusion Equation
Hirad Alipanah, Feng Zhang, Yongxin Yao +6
The advection-diffusion equation is simulated on a superconducting quantum computer via several quantum algorithms. Three formulations are considered: (1) Trotterization, (2) varia…
Polyhedral Discretizations for Elliptic PDEs
Junyu Liu, Daniele Panozzo, Mario Botsch +1
We study the use of polyhedral discretizations for the solution of heat diffusion and elastodynamic problems in computer graphics. Polyhedral meshes are more natural for certain ap…