One way of solving 3sat instances on a quantum computer is to transform the 3sat instances
into instances of Quadratic Unconstrained Binary Optimizations (QUBOs), which can be …

Quantum computers leverage the principles of quantum mechanics to do computation with a
potential advantage over classical computers. Though a single classical computer …

Benchmarking the performance of quantum optimization algorithms is crucial for identifying
utility for industry-relevant use cases. Benchmarking processes vary between optimization …

Reinforcement Learning (RL) policies are designed to predict actions based on current
observations to maximize cumulative future rewards. In real-world applications (ie, non …

Hardware accelerators like quantum annealers or neuromorphic chips are capable of
finding the ground state of a Hamiltonian. A promising route in utilizing these devices is via …

A common way of solving satisfiability instances with quantum methods is to transform these
instances into instances of QUBO. State-of-the-art transformations from MAX-3SAT to QUBO …

We aim to advance the state-of-the-art in Quadratic Unconstrained Binary Optimization
formulation with a focus on cryptography algorithms. As the minimal QUBO encoding of the …

Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are
prominent approaches for solving combinatorial optimization problems, such as those …

As contemporary quantum computers do not possess error correction, any calculation
performed by these devices can be considered an involuntary approximation. To solve a …

In this paper, we present an open-source Python framework, called satqubolib. This
framework aims to provide all necessary tools for solving (MAX)-3SAT problems on quantum …