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

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

We present a scalable architecture for solving higher-order constrained binary optimization
(HCBO) problems on current neutral-atom hardware operating in the Rydberg blockade …

We propose a universal gate set for quantum computing with all-to-all connectivity and
intrinsic robustness to bit-flip errors based on parity encoding. We show that logical …

Solving optimization problems on near term quantum devices requires developing error
mitigation techniques to cope with hardware decoherence and dephasing processes. We …

Current state-of-the-art quantum optimization algorithms require representing the original
problem as a binary optimization problem, which is then converted into an equivalent Ising …

Collateral optimization refers to the systematic allocation of financial assets to satisfy
obligations or secure transactions while simultaneously minimizing costs and optimizing the …

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 present a protocol to encode and decode arbitrary quantum states in the parity
architecture with constant circuit depth using measurements, local nearest-neighbor and …