53 citations · 167 across the 9 of their papers we have counts for
9 papers
Stabilizer ground states for simulating quantum many-body physics: theory, algorithms, and applications
Jiace Sun, Lixue Cheng, Shi-Xin Zhang
Stabilizer states, which are also known as the Clifford states, have been commonly utilized in quantum information, quantum error correction, and quantum circuit simulation due to…
Towards chemical accuracy with shallow quantum circuits: A Clifford-based Hamiltonian engineering approach
Jiace Sun, Lixue Cheng, Weitang Li
Achieving chemical accuracy with shallow quantum circuits is a significant challenge in quantum computational chemistry, particularly for near-term quantum devices. In this work, w…
Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression
Lixue Cheng, Jiace Sun, J. Emiliano Deustua +2
We introduce a novel machine learning strategy, kernel addition Gaussian process regression (KA-GPR), in molecular-orbital-based machine learning (MOB-ML) to learn the total correl…
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning
Jiace Sun, Lixue Cheng, Thomas F. Miller
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments a…
New Stable and Fast Ring-Polymer Molecular Dynamics for Calculating Bimolecular Rate Coefficients with Example of OH + CH_4
Xiongfei Gui, Wenbin Fan, Jiace Sun +1
The accurate and efficient calculation of the rate coefficients of chemical reactions is a key issue in the research of chemical dynamics. In this work, by applying the dimension-f…
Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space
Lixue Cheng, Jiace Sun, Thomas F. Miller
We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This w…
Molecular Energy Learning Using Alternative Blackbox Matrix-Matrix Multiplication Algorithm for Exact Gaussian Process
Jiace Sun, Lixue Cheng, Thomas F. Miller
We present an application of the blackbox matrix-matrix multiplication (BBMM) algorithm to scale up the Gaussian Process (GP) training of molecular energies in the molecular-orbita…
A generalized class of strongly stable and dimension-free T-RPMD integrators
Jorge L. Rosa-Raíces, Jiace Sun, Nawaf Bou-Rabee +1
Recent work shows that strong stability and dimensionality freedom are essential for robust numerical integration of thermostatted ring-polymer molecular dynamics (T-RPMD) and path…
Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states
Tamara Husch, Jiace Sun, Lixue Cheng +2
Molecular-orbital-based machine learning (MOB-ML) provides a general framework for the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. We d…