It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the
US decadal particle-physics community planning, and in fact until recently, this was not …

Hybrid quantum-classical algorithms are central to much of the current research in quantum
computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era …

We use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model
to examine the likely performance of variational quantum eigensolvers in nuclear-structure …

Measuring quantum observables by grou** terms that can be rotated to sums of only
products of Pauli ẑ operators (Ising form) is proven to be efficient in near term quantum …

Quantum computer provides new opportunities for quantum chemistry. In this article, we
present a versatile, extensible, and efficient software package, named Q $^ 2$ Chemistry, for …

We study variational quantum algorithms from the perspective of free fermions. By deriving
the explicit structure of the associated Lie algebras, we show that the Quantum Approximate …

One of the major problems of most quantum computing applications is that the required
number of qubits to solve a practical problem is much larger than that of today's quantum …

Quantum machine learning is one of the many potential applications of quantum computing,
each of which is hoped to provide some novel computational advantage. However, quantum …

Variational algorithms have received significant attention in recent years due to their
potential to solve practical problems using noisy intermediate-scale quantum (NISQ) …

We propose a quantum algorithm to compute low-energy expectation values of a quantum
Hamiltonian by sampling a partition function associated with the average energy of that …