We describe tensor network algorithms to optimize quantum circuits for adiabatic quantum
computing. To suppress diabatic transitions, we include counterdiabatic driving in the …

Quantum optimization, both for classical and quantum functions, is one of the most well-
studied applications of quantum computing, but recent trends have relied on hybrid methods …

Recently, feedback-based quantum algorithms have been introduced to calculate the
ground states of Hamiltonians, inspired by quantum Lyapunov control theory. This paper …

Combinatorial optimization problems are one of the areas where near-term noisy quantum
computers may have practical advantage against classical computers. Recently a novel …

We investigate the efficiency of approximate counterdiabatic driving (CD) in accelerating
adiabatic passage through a first-order quantum phase transition. Specifically, we analyze a …

We explore a non-variational quantum state preparation approach combined with the
ADAPT operator selection strategy in the application of preparing the ground state of a …

In recent years, quantum computing has drawn significant interest within the field of high-
energy physics. We explore the potential of quantum algorithms to resolve the combinatorial …

The feedback-based algorithm for quantum optimization\\(FALQON) has recently been
proposed to solve quadratic unconstrained binary optimization problems. This paper …