Quantum 7, 1137 (2023). https://doi.org/10.22331/q-2023-10-12-1137 We construct Pauli topological subsystem codes characterized by arbitrary two-dimensional Abelian anyon theories–this includes anyon theories with degenerate braiding relations and those without a gapped boundary to the vacuum. Our […]
Quantum 7, 1136 (2023). https://doi.org/10.22331/q-2023-10-11-1136 We introduce a multi-modal, multi-level quantum complex exponential least squares (MM-QCELS) method to simultaneously estimate multiple eigenvalues of a quantum Hamiltonian on early fault-tolerant quantum computers. Our theoretical analysis demonstrates […]
Quantum 7, 1135 (2023). https://doi.org/10.22331/q-2023-10-11-1135 One of the most puzzling consequences of interpreting quantum mechanics in terms of concepts borrowed from classical physics, is the so-called wave-particle duality. Usually, wave-particle duality is illustrated in terms […]
Quantum 7, 1134 (2023). https://doi.org/10.22331/q-2023-10-10-1134 When two parties, Alice and Bob, share correlated quantum systems and Alice performs local measurements, Alice’s updated description of Bob’s state can provide evidence of nonclassical correlations. This simple scenario, […]
Quantum 7, 1133 (2023). https://doi.org/10.22331/q-2023-10-10-1133 Run-times of quantum algorithms are often studied via an asymptotic, worst-case analysis. Whilst useful, such a comparison can often fall short: it is not uncommon for algorithms with a large […]
Quantum 7, 1132 (2023). https://doi.org/10.22331/q-2023-10-10-1132 A promising avenue for the preparation of Gibbs states on a quantum computer is to simulate the physical thermalization process. The Davies generator describes the dynamics of an open quantum […]
Quantum 7, 1131 (2023). https://doi.org/10.22331/q-2023-10-10-1131 We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the dynamics of many-body quantum systems classically. By systematically studying the relevant stochastic estimators, we are […]
Quantum 7, 1130 (2023). https://doi.org/10.22331/q-2023-10-09-1130 Quantum machine learning algorithms based on parameterized quantum circuits are promising candidates for near-term quantum advantage. Although these algorithms are compatible with the current generation of quantum processors, device noise […]
Quantum 7, 1129 (2023). https://doi.org/10.22331/q-2023-10-09-1129 Recently, tremendous progress has been made in the field of quantum science and technologies: different platforms for quantum simulation as well as quantum computing, ranging from superconducting qubits to neutral […]
Quantum 7, 1128 (2023). https://doi.org/10.22331/q-2023-10-09-1128 Recent work has revealed the central role played by the Kirkwood-Dirac quasiprobability (KDQ) as a tool to properly account for non-classical features in the context of condensed matter physics (scrambling, […]
Recent Comments