Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …

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 …

Using tools from the representation theory of compact Lie groups we formulate a theory of
Barren Plateaus (BPs) for parameterized quantum circuits where the observable lies in the …

In recent years, research in quantum computing has largely focused on two approaches:
near-term intermediate-scale quantum (NISQ) computing and future fault-tolerant quantum …

Combinatorial optimization is a broadly attractive area for potential quantum advantage, but
no quantum algorithm has yet made the leap. Noise in quantum hardware remains a …

We introduce a comprehensive quantum solver for binary combinatorial optimization
problems on gate-model quantum computers that outperforms any published alternative and …

We show that the quantum approximate optimization algorithm (QAOA) for higher-order,
random coefficient, heavy-hex compatible spin glass Ising models has strong parameter …

We develop a hardware-efficient ansatz for variational optimization, derived from existing
ansatzes in the literature, that parametrizes subsets of all interactions in the cost Hamiltonian …

Constrained optimization problems are ubiquitous in science and industry. Quantum
algorithms have shown promise in solving optimization problems, yet none of the current …

Quantum alternating operator ansatz (QAOA) has a strong connection to the adiabatic
algorithm, which it can approximate with sufficient depth. However, it is unclear to what …