Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …

Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …

Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …

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

We introduce parity quantum optimization with the aim of solving optimization problems
consisting of arbitrary $ k $-body interactions and side conditions using planar quantum chip …

We show that universal parity quantum computing employing a recently introduced constant
depth decoding procedure is equivalent to measurement-based quantum computation …

We present benchmarks of the parity transformation for the Quantum Approximate
Optimization Algorithm (QAOA). We analyse the gate resources required to implement a …

We review encoding and hardware-independent formulations of optimization problems for
quantum computing. Using this generalized approach, an extensive library of optimization …

Parity compilation is the challenge of laying out the required constraints for the parity
mapping in a local way. We present the first constructive compilation algorithm for the parity …

We show how to efficiently decompose a parameterized multi-qubit Pauli (PMQP) gate into
native parameterized two-qubit Pauli (P2QP) gates minimizing both the circuit depth and the …