Quantum 6, 879 (2022). https://doi.org/10.22331/q-2022-12-19-879 The effective quantum field theory description of gravity, despite its non-renormalizability, allows for predictions beyond classical general relativity. As we enter the age of gravitational wave astronomy, an important and […]
Quantum 6, 878 (2022). https://doi.org/10.22331/q-2022-12-19-878 Realizations of gauge theories in setups of quantum synthetic matter open up the possibility of probing salient exotic phenomena in condensed matter and high-energy physics, along with potential applications in […]
Quantum 6, 877 (2022). https://doi.org/10.22331/q-2022-12-19-877 The permanent is pivotal to both complexity theory and combinatorics. In quantum computing, the permanent appears in the expression of output amplitudes of linear optical computations, such as in the […]
Quantum 6, 876 (2022). https://doi.org/10.22331/q-2022-12-13-876 Many quantum algorithms for numerical linear algebra assume black-box access to a block-encoding of the matrix of interest, which is a strong assumption when the matrix is not sparse. Kernel […]
Quantum 6, 875 (2022). https://doi.org/10.22331/q-2022-12-13-875 Here we argue that the probability that a given source produces exactly a single photon is a natural quantity to benchmark single-photon sources as it certifies the absence of multi-photon […]
Quantum 6, 874 (2022). https://doi.org/10.22331/q-2022-12-13-874 We introduce a hybrid quantum-classical variational algorithm to simulate ground-state phase diagrams of frustrated quantum spin models in the thermodynamic limit. The method is based on a cluster-Gutzwiller ansatz where […]
Quantum 6, 873 (2022). https://doi.org/10.22331/q-2022-12-07-873 Topological data analysis (TDA) is an emergent field of data analysis. The critical step of TDA is computing the persistent Betti numbers. Existing classical algorithms for TDA are limited if […]
Quantum 6, 872 (2022). https://doi.org/10.22331/q-2022-12-07-872 The quantum Fourier transform (QFT) is a key primitive for quantum computing that is typically used as a subroutine within a larger computation, for instance for phase estimation. As such, […]
Quantum 6, 871 (2022). https://doi.org/10.22331/q-2022-12-07-871 We develop a framework of “semi-automatic differentiation” that combines existing gradient-based methods of quantum optimal control with automatic differentiation. The approach allows to optimize practically any computable functional and is […]
Quantum 6, 870 (2022). https://doi.org/10.22331/q-2022-12-07-870 Quantum computers may provide good solutions to combinatorial optimization problems by leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often presented as an algorithm for noisy hardware. However, […]
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