Yilun Xu
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View article: Trigonometric gradient microstructures in additively manufactured single crystals enable strength-ductility synergy and programmable performance
Trigonometric gradient microstructures in additively manufactured single crystals enable strength-ductility synergy and programmable performance Open
Additively manufactured (AM) single crystals (SXs) show great promise for extreme-environment applications. AM process enhances gradient microstructures around dendrites, including dislocation densities, matrix channel width, precipitate a…
View article: CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise
CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise Open
Quantum Neural Networks (QNNs) have shown significant value across domains, with well-trained QNNs representing critical intellectual property often deployed via cloud-based QNN-as-a-Service (QNNaaS) platforms. Recent work has examined QNN…
View article: First-principle crosstalk dynamics and Hamiltonian learning via Rabi experiments
First-principle crosstalk dynamics and Hamiltonian learning via Rabi experiments Open
Coherent errors constitute a significant barrier to successful large-scale quantum computation. One such error mechanism is crosstalk, which violates spatial locality or the independence of operations. We present a description of crosstalk…
View article: Manipulating spectral windings and skin modes through nonconservative couplings
Manipulating spectral windings and skin modes through nonconservative couplings Open
The discovery of the non-Hermitian skin effect (NHSE) has revolutionized our\nunderstanding of wave propagation in non-Hermitian systems, highlighting\nunexpected localization effects beyond conventional theories. Here, we discover\nthat N…
View article: Energy-Based Diffusion Language Models for Text Generation
Energy-Based Diffusion Language Models for Text Generation Open
Despite remarkable progress in autoregressive language models, alternative generative paradigms beyond left-to-right generation are still being actively explored. Discrete diffusion models, with the capacity for parallel generation, have r…
View article: Hamiltonian Score Matching and Generative Flows
Hamiltonian Score Matching and Generative Flows Open
Classical Hamiltonian mechanics has been widely used in machine learning in the form of Hamiltonian Monte Carlo for applications with predetermined force fields. In this work, we explore the potential of deliberately designing force fields…
View article: Heavy-Tailed Diffusion Models
Heavy-Tailed Diffusion Models Open
Diffusion models achieve state-of-the-art generation quality across many applications, but their ability to capture rare or extreme events in heavy-tailed distributions remains unclear. In this work, we show that traditional diffusion and …
View article: Think While You Generate: Discrete Diffusion with Planned Denoising
Think While You Generate: Discrete Diffusion with Planned Denoising Open
Discrete diffusion has achieved state-of-the-art performance, outperforming or approaching autoregressive models on standard benchmarks. In this work, we introduce Discrete Diffusion with Planned Denoising (DDPD), a novel framework that se…
View article: Quantum phase transition in a quantum Rabi square with next-nearest-neighbor hopping
Quantum phase transition in a quantum Rabi square with next-nearest-neighbor hopping Open
We propose a quantum Rabi square model where both the nearest-neighbor and the next-nearest-neighbor photon hopping are allowed among four quantum Rabi systems located at the vertices of a square. By tuning the next-nearest hopping strengt…
View article: DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents Open
Diffusion models (DMs) have revolutionized generative learning. They utilize a diffusion process to encode data into a simple Gaussian distribution. However, encoding a complex, potentially multimodal data distribution into a single contin…
View article: Phase transition and multistability in Dicke dimer
Phase transition and multistability in Dicke dimer Open
The exotic phase transitions and multistabilities in atom-cavity coupled systems have attracted tremendous interests recently. In this work, we investigate the effect of photon hopping between two Dicke cavities, which induces rich quantum…
View article: Mechanistic understanding of microstructural effects on the thermal fatigue resistance of solder joints
Mechanistic understanding of microstructural effects on the thermal fatigue resistance of solder joints Open
This paper uses a multi-scale crystal plasticity modelling approach to investigate the role of microstructure in the damage of Sn-3Ag-0.5Cu (wt%, SAC305) solder joints subject to thermal cycling. Faithful microstructure modelling has been …
View article: Temperature-dependent, multi-mechanism crystal plasticity reveals the deformation and failure behaviour of multi-principal element alloys
Temperature-dependent, multi-mechanism crystal plasticity reveals the deformation and failure behaviour of multi-principal element alloys Open
In this work, we have developed a temperature-dependent, multi-mechanism crystal plasticity (CP) model aimed at unravelling the deformation and failure resistance of Cantor alloy-like multi-principal element alloys (MPEA) under both uniaxi…
View article: Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling
Quasi-Probabilistic Readout Correction of Mid-Circuit Measurements for Adaptive Feedback via Measurement Randomized Compiling Open
Quantum measurements are a fundamental component of quantum computing. However, on modern-day quantum computers, measurements can be more error prone than quantum gates, and are susceptible to non-unital errors as well as non-local correla…
View article: The role of microstructure in the thermal fatigue of solder joints
The role of microstructure in the thermal fatigue of solder joints Open
Thermal fatigue is a common failure mode in electronic solder joints, yet the role of microstructure is incompletely understood. Here, we quantify the evolution of microstructure and damage in Sn-3Ag-0.5Cu joints throughout a ball grid arr…
View article: Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models Open
In light of the widespread success of generative models, a significant amount of research has gone into speeding up their sampling time. However, generative models are often sampled multiple times to obtain a diverse set incurring a cost t…
View article: Microstructurally-sensitive fatigue crack nucleation in a Zircaloy-4 alloy
Microstructurally-sensitive fatigue crack nucleation in a Zircaloy-4 alloy Open
Microstructurally-sensitive fatigue crack nucleation and subsequently short crack growth were observed at an edge-notch in a textured Zircaloy-4 sample with the c-axis aligned perpendicular to the viewing surface. To understand the competi…
View article: Slip intermittency and dwell fatigue in titanium alloys: a discrete dislocation plasticity analysis
Slip intermittency and dwell fatigue in titanium alloys: a discrete dislocation plasticity analysis Open
Slip intermittency and stress oscillations in titanium alloy Ti–7Al–O that were observed using in-situ far-field high energy X-ray diffraction microscopy (ff-HEDM) are investigated using a discrete dislocation plasticity (DDP) model. The m…
View article: Slip intermittency and dwell fatigue in titanium alloys: a discrete dislocation plasticity analysis
Slip intermittency and dwell fatigue in titanium alloys: a discrete dislocation plasticity analysis Open
Slip intermittency and stress oscillations in titanium alloy Ti-7Al-O that were observed using in-situ far-field high energy X-ray diffraction microscopy (ff-HEDM) are investigated using a discrete dislocation plasticity (DDP) model. The m…
View article: Restart Sampling for Improving Generative Processes
Restart Sampling for Improving Generative Processes Open
Generative processes that involve solving differential equations, such as diffusion models, frequently necessitate balancing speed and quality. ODE-based samplers are fast but plateau in performance while SDE-based samplers deliver higher …
View article: GenPhys: From Physical Processes to Generative Models
GenPhys: From Physical Processes to Generative Models Open
Since diffusion models (DM) and the more recent Poisson flow generative models (PFGM) are inspired by physical processes, it is reasonable to ask: Can physical processes offer additional new generative models? We show that the answer is ye…
View article: PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models Open
We introduce a new family of physics-inspired generative models termed PFGM++ that unifies diffusion models and Poisson Flow Generative Models (PFGM). These models realize generative trajectories for $N$ dimensional data by embedding paths…
View article: Stable Target Field for Reduced Variance Score Estimation in Diffusion Models
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models Open
Diffusion models generate samples by reversing a fixed forward diffusion process. Despite already providing impressive empirical results, these diffusion models algorithms can be further improved by reducing the variance of the training ta…