Quantum 7, 956 (2023). https://doi.org/10.22331/q-2023-03-20-956 As a cornerstone for many quantum linear algebraic and quantum machine learning algorithms, controlled quantum state preparation (CQSP) aims to provide the transformation of $|irangle |0^nrangle to |irangle |psi_irangle $ […]
Quantum 7, 955 (2023). https://doi.org/10.22331/q-2023-03-20-955 The time-marching strategy, which propagates the solution from one time step to the next, is a natural strategy for solving time-dependent differential equations on classical computers, as well as for […]
Quantum 7, 954 (2023). https://doi.org/10.22331/q-2023-03-20-954 Entanglement is the key resource for quantum technologies and is at the root of exciting many-body phenomena. However, quantifying the entanglement between two parts of a real-world quantum system is […]
Quantum 7, 953 (2023). https://doi.org/10.22331/q-2023-03-17-953 Quantum contextual sets have been recognized as resources for universal quantum computation, quantum steering and quantum communication. Therefore, we focus on engineering the sets that support those resources and on […]
Quantum 7, 952 (2023). https://doi.org/10.22331/q-2023-03-17-952 We present benchmarks of the parity transformation for the Quantum Approximate Optimization Algorithm (QAOA). We analyse the gate resources required to implement a single QAOA cycle for real-world scenarios. In […]
Quantum 7, 951 (2023). https://doi.org/10.22331/q-2023-03-17-951 Constraints make hard optimization problems even harder to solve on quantum devices because they are implemented with large energy penalties and additional qubit overhead. The parity mapping, which has been […]
Quantum 7, 950 (2023). https://doi.org/10.22331/q-2023-03-17-950 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 architectures. The method introduces a decomposition […]
Quantum 7, 949 (2023). https://doi.org/10.22331/q-2023-03-16-949 Variational quantum algorithms, which have risen to prominence in the noisy intermediate-scale quantum setting, require the implementation of a stochastic optimizer on classical hardware. To date, most research has employed […]
Quantum 7, 948 (2023). https://doi.org/10.22331/q-2023-03-16-948 In the framework of ontological models, the inherently nonclassical features of quantum theory always seem to involve properties that are fine tuned, i.e. properties that hold at the operational level […]
Quantum 7, 947 (2023). https://doi.org/10.22331/q-2023-03-16-947 In the minimal scenario of quantum correlations, two parties can choose from two observables with two possible outcomes each. Probabilities are specified by four marginals and four correlations. The resulting […]
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