1 citations · 2 across the 15 of their papers we have counts for
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Domain-Aware Quantum Circuit for QML
Gurinder Singh, Thaddeus Pellegrini, Kenneth M. Merz
Designing parameterized quantum circuits (PQCs) that are expressive, trainable, and robust to hardware noise is a central challenge for quantum machine learning (QML) on noisy inte…
Improved parameter initialization for the (local) unitary cluster Jastrow ansatz
Wan-Hsuan Lin, Fangchun Liang, Mario Motta +3
The unitary cluster Jastrow (UCJ) ansatz and its variant known as local UCJ (LUCJ) are promising choices for variational quantum algorithms for chemistry due to their combination o…
Quantum Algorithm for Protein Structure Prediction Using the Face-Centered Cubic Lattice
Rui-Hao Li, Hakan Doga, Bryan Raubenolt +16
In this work, we present the first implementation of the face-centered cubic (FCC) lattice model for protein structure prediction with a quantum algorithm. Our motivation to encode…
Improving GANs by leveraging the quantum noise from real hardware
Hongni Jin, Kenneth M. Merz
We propose a novel approach to generative adversarial networks (GANs) in which the standard i.i.d. Gaussian latent prior is replaced or hybridized with a quantum-correlated prior d…
Quantum-Centric Alchemical Free Energy Calculations
Milana Bazayeva, Zhen Li, Danil Kaliakin +4
In the present work, we present a hybrid quantum-classical workflow aimed at improving the accuracy of alchemical free energy (AFE) predictions by incorporating configuration inter…
QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representations
Hongni Jin, Gurinder Singh, Kenneth M. Merz
Implicit neural representations have shown potential in various applications. However, accurately reconstructing the image or providing clear details via image super-resolution rem…
Benchmarking MedMNIST dataset on real quantum hardware
Gurinder Singh, Hongni Jin, Kenneth M. Merz
Quantum machine learning (QML) has emerged as a promising domain to leverage the computational capabilities of quantum systems to solve complex classification tasks. In this work,…