A number of commercially available quantum computers, such as those based on trapped-
ion or superconducting qubits, can now perform mid-circuit measurements and resets. In …

The design of fast algorithms for combinatorial optimization greatly contributes to a plethora
of domains such as logistics, finance, and chemistry. Quantum approximate optimization …

We present a direct comparison between QAOA (Quantum Alternating Operator Ansatz), and
QA (Quantum Annealing) on 127 qubit problem instances. QAOA with p= 1, 2 rounds is …

As combinatorial optimization is one of the main quantum computing applications, many
methods based on parameterized quantum circuits are being developed. In general, a set of …

Noisy intermediate-scale quantum (NISQ) devices are restricted by their limited number of
qubits and their short decoherence times. An approach addressing these problems is …

In this paper we consider the scalability of multi-angle QAOA with respect to the number of
QAOA layers. We found that MA-QAOA is able to significantly reduce the depth of QAOA …

The K-nearest neighbors (KNNs) algorithm is one of Top-10 data mining algorithms and is
widely used in various fields of artificial intelligence. This leads to that quantum KNN …

Quantum Approximate Optimization Algorithm (QAOA) is one of the leading candidates for
demonstrating the quantum advantage using near-term quantum computers. Unfortunately …

Quantum computers are devices, which allow more efficient solutions of problems as
compared to their classical counterparts. As the timeline to developing a quantum-error …

Feature selection plays a significant role in computer science; nevertheless, this task is
intractable since its search space scales exponentially with the number of dimensions …