Until high-fidelity quantum computers with a large number of qubits become widely
available, classical simulation remains a vital tool for algorithm design, tuning, and …

In this study, we introduce an innovative Quantum-enhanced Support Vector Machine
(QSVM) approach for stellar classification problems. The QSVM algorithm in our work shows …

Quantum field theory in the presence of strong background fields contains interesting
problems where quantum computers may someday provide a valuable computational …

High performance computing (HPC) is renowned for its capacity to tackle complex problems.
Meanwhile, quantum computing (QC) provides a potential way to accurately and efficiently …

Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing
ansatz into density-functional theory via density-based basis-set corrections to obtain …

The fragment molecular orbital (FMO) scheme is one of the popular fragmentation‐based
methods and has the potential advantage of making the circuit shallow for quantum …

This paper presents techniques for theoretically and practically efficient and scalable
Schrödinger-style quantum circuit simulation. Our approach partitions a quantum circuit into …

Deep learning hardware achieves high throughput and low power consumption by reducing
computing precision and specializing in matrix multiplication. For machine learning …

We describe a matrix product state (MPS) extension for the Fermionic Quantum Emulator
(FQE) software library. We discuss the theory behind symmetry-adapted MPSs for …

This paper introduces a noise-aware distributed Quantum Approximate Optimization
Algorithm (QAOA) tailored for execution on near-term quantum hardware. Leveraging a …