Quantum 7, 945 (2023). https://doi.org/10.22331/q-2023-03-09-945 The quantum switch is a quantum computational primitive that provides computational advantage by applying operations in a superposition of orders. In particular, it can reduce the number of gate queries […]
Quantum 7, 944 (2023). https://doi.org/10.22331/q-2023-03-09-944 A proof of work (PoW) is an important cryptographic construct enabling a party to convince others that they invested some effort in solving a computational task. Arguably, its main impact […]
Quantum 7, 943 (2023). https://doi.org/10.22331/q-2023-03-09-943 We consider a nonlinearly coupled electromechanical system, and develop a quantitative theory for two-phonon cooling. In the presence of two-phonon cooling, the mechanical Hilbert space is effectively reduced to its […]
Quantum 7, 942 (2023). https://doi.org/10.22331/q-2023-03-09-942 Active quantum error correction is a central ingredient to achieve robust quantum processors. In this paper we investigate the potential of quantum machine learning for quantum error correction in a […]
Quantum 7, 941 (2023). https://doi.org/10.22331/q-2023-03-09-941 A simple scheme is presented for realizing robust optically controlled quantum gates for scalable atomic quantum processors by driving the qubits with optical standing waves. Atoms localized close to the […]
Quantum 7, 940 (2023). https://doi.org/10.22331/q-2023-03-09-940 Self-correcting quantum memories demonstrate robust properties that can be exploited to improve active quantum error-correction protocols. Here we propose a cellular automaton decoder for a variation of the color code […]
Quantum 7, 939 (2023). https://doi.org/10.22331/q-2023-03-06-939 Quantum capacity, as the key figure of merit for a given quantum channel, upper bounds the channel’s ability in transmitting quantum information. Identifying different types of channels, evaluating the corresponding […]
Quantum 7, 938 (2023). https://doi.org/10.22331/q-2023-03-02-938 Neural Network Quantum States (NQS) represent quantum wavefunctions by artificial neural networks. Here we study the wavefunction access provided by NQS defined in [Science, 355, 6325, pp. 602-606 (2017)] and […]
Quantum 7, 937 (2023). https://doi.org/10.22331/q-2023-03-02-937 Amplitude estimation algorithms are based on Grover’s algorithm: alternating reflections about the input state and the desired outcome. But what if we are given the ability to perform arbitrary rotations, […]
Quantum 7, 936 (2023). https://doi.org/10.22331/q-2023-03-02-936 The ability to extract relevant information is critical to learning. An ingenious approach as such is the information bottleneck, an optimisation problem whose solution corresponds to a faithful and memory-efficient […]
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