Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

Classical simulation of quantum dynamics plays an important role in our understanding of
quantum complexity, and in the development of quantum technologies. Compared to other …

We have generalized the well-known statement that the Clifford group is a unitary 3-design
into symmetric cases by extending the notion of unitary design. Concretely, we have proven …

Quantum computing has potential to provide exponential speedups over classical
computing for many important applications. However, today's quantum computers are in …

Parameterized quantum circuits used as variational ansatzes are emerging as promising
tools to tackle complex problems ranging from quantum chemistry to combinatorial …

Given their potential to demonstrate near-term quantum advantage, variational quantum
algorithms (VQAs) have been extensively studied. Although numerous techniques have …

The overheads of classical decoding for quantum error correction in cryogenic quantum
systems grow rapidly with the number of logical qubits and their correction code distance …

In recent years, quantum computing has emerged as a transformative force in the field of
combinatorial optimization, offering novel approaches to tackling complex problems that …

We consider the question of how correlated the system hardness is between classical
algorithms of electronic structure theory in ground state estimation and quantum algorithms …

The variational quantum eigensolver (VQE) framework has been instrumental in advancing
near-term quantum algorithms. However, parameter optimization remains a significant …