Abstract Interfacing light from solid-state single-photon sources with scalable and robust room-temperature quantum memories has been a long-standing challenge in photonic quantum information technologies due to inherent noise processes and time-scale mismatches between the operating conditions of solid-state and atomic systems. Here, we demonstrate storage of single photons from a semiconductor quantum dot (QD) device in a room-temperature atomic vapor memory and their on-demand retrieval. A deterministically fabricated InGaAs QD light source emits single photons at the wavelength of the cesium D1 line at 895 nm which exhibit an inhomogeneously broadened linewidth of 5.1(7) GHz and are subsequently stored in a low-noise ladder-type cesium vapor memory. We show control over the interaction between the single photons and the atomic vapor, allowing for variable retrieval times of up to 19.8(3) ns. A maximum internal efficiency of η int = 0.6 ( 1 ) % is achieved. Our results expand the application space of both room-temperature vapor memories and semiconductor QDs in future quantum network architectures.

Abstract In quantum information, device-independent protocols offer a new approach to information processing tasks, making minimal assumptions about the devices used. Typically, since these protocols draw conclusions directly from the data collected in a meaningful Bell test, the no-signaling conditions, and often even Born’s rule for local measurements, are taken as premises of the protocol. Here, we demonstrate how to test such premises in an (almost) device-independent setting, i.e., directly from the raw data and with minimal assumptions. In particular, for IBM’s quantum computing cloud services, we implement the prediction-based ratio protocol to characterize how well the qubits can be accessed locally and independently. More precisely, by performing a variety of Clauser-Horne-Shimony-Holt-type experiments on these systems and carrying out rigorous hypothesis tests on the collected data, we provide compelling evidence showing that some of these qubits suffer from measurement cross-talks, i.e., their measurement statistics are affected by the choice of measurement bases on another qubit. Unlike standard randomized benchmarking, our approach does not rely on assumptions such as gate-independent Markovian noise. Moreover, despite the relatively small number of experimental trials, the direction of “signaling” may also be identified in some cases. Our approach thus serves as a complementary tool for benchmarking the local addressability of quantum computing devices.

Abstract Exponentially small spectral gaps are known to be the crucial bottleneck for traditional Quantum Annealing (QA) based on interpolating between two Hamiltonians, a simple driving term and the complex problem to be solved, with a linear schedule in time. One of the simplest models exhibiting exponentially small spectral gaps is a ferromagnetic Ising ring with a single antiferromagnetic bond introducing frustration. Previous studies of this model have explored continuous-time diabatic QA, where optimized non-adiabatic annealing schedules provided good solutions, avoiding exponentially large annealing times. In our work, we move to a digital framework of Variational Quantum Algorithms, and present two main results: (1) we show that the model is digitally controllable with a scaling of resources that grows quadratically with the system size, achieving the exact solution using the Quantum Approximate Optimization Algorithm; (2) We combine a technique of quantum control—the Chopped RAndom Basis method—and digitized quantum annealing to construct smooth digital schedules yielding optimal solutions with very high accuracy.

Abstract Achieving unit fidelity in quantum state preparation is often impossible in the presence of environmental decoherence. While continuous monitoring and feedback control can improve fidelity, perfect state preparation remains elusive in many scenarios. Inspired by quantum speed limits, we derive a fundamental bound on the steady-state average fidelity achievable via continuous monitoring and feedback control. This bound depends only on the unconditional Lindblad dynamics, the Hamiltonian variance, and the target state. We also adapt the bound to the case of Markovian feedback strategies. We then focus on preparing Dicke states in an atomic ensemble subject to collective damping and dispersive coupling. By imposing additional constraints on control Hamiltonians and monitoring strategies, we derive tighter fidelity bounds. Finally, we propose specific control strategies and validate them using reinforcement learning. Benchmarking their performance against our theoretical bounds highlights the relevance and usefulness of these bounds in characterizing quantum feedback control strategies.

Abstract Quantum machine learning is a rapidly advancing discipline that leverages the features of quantum mechanics to enhance the performance of computational tasks. Quantum reservoir processing (QRP), which allows efficient optimization of a single output layer without precise control over the quantum system, stands out as one of the most versatile and practical quantum machine learning techniques. Here we experimentally demonstrate a QRP approach for continuous-variable state reconstruction on a bosonic circuit quantum electrodynamics platform. The scheme learns the true dynamical process through a minimum set of measurement outcomes of a known set of initial states. We show that the map learnt this way achieves high reconstruction fidelity for several test states, offering significantly enhanced performance over using a map calculated based on an idealized model of the system. This is due to a key feature of reservoir processing which accurately accounts for physical non-idealities such as decoherence, spurious dynamics, and systematic errors. Our results present a valuable tool for robust bosonic state and process reconstruction, concretely demonstrating the power of QRP in enhancing real-world applications.

Abstract We review concepts and recent work related to creating light–matter interfaces for future quantum networks based on rare-earth ion-doped crystals. More precisely, we explore their unique suitability for creating photon sources, optical quantum memories for light, and qubits that allow quantum information processing. In addition, we review the state-of-the-art of elementary quantum repeater links, and provide suggestions for future research.

Abstract As quantum computing development advances closer toward achieving fault-tolerant error-corrected realisation, debates on applications, impacts, risks, and benefits of quantum computing are timely and due. While there is awareness of the potential power and complexity of quantum computers, there has been relatively little attention on the social impacts and ethical implications of this technology. In grappling with the social impacts of quantum computing, some stakeholders have turned to applied ethics, specifically (classical) computer and Artificial Intelligence (AI) ethics, for guidance. While computer and AI ethics are useful starting points for evaluating the ethical issues posed by quantum computing, uncritically applying existing sets of ethical principles risks overlooking how quantum computing differs from these technologies. We argue that borrowing of ethical principles and guidelines from AI and computing is inappropriate for several reasons: (1) quantum computing, classical computing, and AI are different technologies with significant material differences; (2) unlike AI and classical computers which have become established, quantum computing is an emerging technology, which has implications on the levels of accessibility and immediate impact in society; and (3) there are significant differences in the way AI and quantum computing have been developed and by whom. We also briefly summarise some of the unique risks and societ al impacts posed by quantum computing. We posit that these reasons support the argument for a new sub-field of quantum computing ethics, which would allow a relevant scholarship to develop and provide guidance as quantum computing technology continues to mature.

Abstract We consider a quantum battery (QB) composed of a pair of qubits coupled with an Ising interaction in the usual NMR framework, where the longitudinal applied field is constant and the time-dependent variables controlling the system are the amplitude and phase of the transverse field, and use optimal control to derive fast charging protocols. We study both the cases where the Ising coupling is weaker and stronger than the longitudinal field. In the first case, where the lowest-energy state of the system is the spin-down state, the optimal charging protocol stipulates the transverse field amplitude to be constant and equal to its maximum allowed value, while the minimum time for full charging of the battery tends to zero as this maximum bound increases. In the second case, where the lowest-energy state is a maximally entangled Bell state, the optimal charging protocol includes a time interval where the transverse field amplitude is zero and its phase is immaterial, corresponding to singular control. In this case, the QB can be charged with higher levels of stored energy, while the minimum time for full charging tends to a nonzero limit proportional to the inverse Ising interaction, as the maximum bound of the control amplitude increases. We analyze intuitively and quantitatively the distinct behavior of the two cases and additionally use the dynamical Lie algebra of the system to elucidate the presence of a singular arc in the optimal pulse-sequence in the second case. The discovered interplay between the QB parameters, the stored energy and the minimum time for full charging, provides great flexibility for optimizing the performance of the device according to the operating constraints. The valuable insights gained regarding the design of QBs is expected to find immediate applications in modern quantum science and technology, while we aim to extend the proposed methods to larger spin chains.

Abstract The entanglement distribution networks with various topologies are mainly implemented by active wavelength multiplexing routing strategies, which directly transmit entangled photons between quantum network nodes. However, designing an entanglement routing scheme, which achieves the maximized network connections and the optimal overall network efficiency simultaneously, remains a huge challenge for quantum networks. In this article, we propose a differentiated service entanglement routing (DSER) scheme, which firstly finds out the lowest loss paths and supported wavelength channels with the tensor-based path searching algorithm, and then allocates the paired channels with the differentiated routing strategies. The evaluation results show that the proposed DSER scheme can be performed for constructing various large scale quantum networks.

Abstract To achieve the entangling gate fidelity above the quantum error correction threshold, it is critical to suppress errors due to experimental imperfection. We consider the Mølmer-Sørensen gates in trapped-ion systems, and develop a general approach to suppress a family of noise sources that appeared as either symmetric or asymmetric errors. Using the time-average displacement minimization technique, both symmetric error and displacement-dependent part of the asymmetric errors are eliminated. Then, by analyzing the tangent space of displacement- independent errors, we obtain the analytic form of the generators of the correction operator to the remaining error terms. We then develop a compensation pulse to fully suppress the remaining displacement-independent errors. The effectiveness of our scheme is further verified by numerical analysis, through which we observe a significant reduction of entangling gate infidelity. Our findings enhance gate fidelity and robustness to noise for ion trap quantum computing.