Quantum information processing is likely to have a far-reaching impact in the field of artificial intelligence. Noisy, intermediate-scale quantum devices provide a platform for exploring the possibility of attaining a quantum advantage through hybrid quantum-classical machine-learning algorithms. One example of such a hybrid algorithm is “quantum kitchen sinks,” which builds upon a classical algorithm known as “random kitchen sinks” to leverage a gate model quantum computer for machine-learning applications. We propose an alternative algorithm called “analog-quantum kitchen sinks” (AQKSs), which employs an analog-quantum computer for mapping data features into new features in a nonlinear manner. The new features can then be used by a classical algorithm to perform machine-learning tasks. We show the effectiveness of our algorithm for performing binary classification on both a synthetic dataset and a real-world dataset by simulating the operations of a quantum annealer. We demonstrate that the AQKS algorithm reduces the classification error of a linear classifier from $50\mathrm{\%}$ to $0.6\mathrm{\%}$ for the synthetic dataset and from $4.4\mathrm{\%}$ to $1.6\mathrm{\%}$ for the other dataset. Our proposed AQKS algorithm presents the possibility to use current quantum annealers for solving practical machine-learning problems.

Nanostructured and bulk silicon carbide ($\mathrm{Si}\mathrm{C}$) materials are relevant for electronics, nano- and micromechanical systems, and biosensing applications. $\mathrm{Si}\mathrm{C}$ has recently emerged as an alternative platform for nanophotonics and quantum applications due to its intra-band-gap point defects, emitting from the visible to the near-infrared, which are ideal for photoluminescent probes. Here, we use a single-molecule localization microscope to study the photoluminescence (PL) properties of $\mathrm{Si}\mathrm{C}$ point defects in bulk, quantum dots, and nanoparticles of different sizes in the 3C and $4H\text{−}\mathrm{Si}\mathrm{C}$ polytypes using intra-band-gap excitation. We study the PL dynamics by using different excitation wavelengths, and we use the point-defect PL intermittency to achieve superresolved images, with a resolution of 20 nm and a minimum distance between emitters of 40 nm. We observe that, while 561 nm is an ideal excitation wavelength to obtain a sufficient blinking behavior, 638 nm is mostly quenching the PL. We further incubate $4H\text{−}\mathrm{Si}\mathrm{C}$ nanoparticles with MCF10A cells in vitro and observe superresolved images of the nanoparticles in cells by combining 561 and 638 nm excitation. This approach is very promising for the application of $\mathrm{Si}\mathrm{C}$ fluorescent nanocrystals and their quantum dots, hosting a combination of intra-band-gap color centers and surface defects, for quantum nanophotonics, magnetic sensing, and biomedical imaging, paving the way for single-particle tracking combined with spin sensing within a cellular environment using near-infrared emission.

Solid-state quantum emitters are excellent sources of on-demand indistinguishable or entangled photons and can host long-lived spin memories, crucial resources for photonic quantum-information applications. However, their scalability remains an outstanding challenge. Here, we present a scalable technique to multiplex streams of photons from multiple independent quantum dots, on chip, into a fiber network for use “off chip.” Multiplexing is achieved by incorporating a multicore fiber into a confocal microscope and spatially matching the multiple foci, seven in this case, to quantum dots in an array of deterministically positioned nanowires. As a proof-of-principle demonstration, we perform parallel spectroscopy on the nanowire array to identify two nearly identical quantum dots at different positions, which are subsequently tuned into resonance with an external magnetic field. Multiplexing of background-free single photons from these two quantum dots is then achieved. Our approach, applicable to all types of quantum emitters, can readily be integrated into scalable photonic based quantum technologies.

Present-day, noisy, small or intermediate-scale quantum processors—although far from fault tolerant—support the execution of heuristic quantum algorithms, which might enable a quantum advantage, for example, when applied to combinatorial optimization problems. On small-scale quantum processors, validations of such algorithms serve as important technology demonstrators. We implement the quantum approximate optimization algorithm on our hardware platform, consisting of two superconducting transmon qubits and one parametrically modulated coupler. We solve small instances of the NP (nondeterministic polynomial time)-complete exact-cover problem, with 96.6% success probability, by iterating the algorithm up to level two.

Airlines today are faced with a number of large-scale scheduling problems. One such problem is the tail-assignment problem, which is the task of assigning individual aircraft to a given set of flights, minimizing the overall cost. Each aircraft is identified by the registration number on its tail fin. In this paper, we simulate the quantum approximate optimization algorithm (QAOA) applied to instances of this problem derived from real-world data. The QAOA is a variational hybrid quantum-classical algorithm recently introduced and likely to run on near-term quantum devices. The instances are reduced to fit on quantum devices with 8, 15, and 25 qubits. The reduction procedure leaves only one feasible solution per instance, which allows us to map the tail-assignment problem onto the exact-cover problem. We find that repeated runs of the QAOA identify the feasible solution with close to unit probability for all instances. Furthermore, we observe patterns in the variational parameters such that an interpolation strategy can be employed, which significantly simplifies the classical optimization part of the QAOA. Finally, we empirically find a relation between the connectivity of the problem graph and the single-shot success probability of the algorithm.

Non-Abelian geometric phases acquired in cyclic quantum evolution can be utilized as natural resources for constructing robust holonomic gates for quantum-information processing. Recently, an extensible holonomic quantum computation (HQC) was proposed and demonstrated in a recent superconducting experiment [Yan et al., Phys. Rev. Lett. 122, 080501 (2019)]. However, for the weakly anharmonic system, this HQC was given of low gate fidelity due to leakage to states outside of the computational subspace. Here, we propose a scheme to construct nonadiabatic holonomic gates via a dynamical invariant using resonant interaction of three-level superconducting quantum systems. Furthermore, the proposed scheme can be compatible with optimal control technology for maximizing the gate fidelity against leakage error. For benchmarking, we provide a thorough analysis on the performance of our scheme under experimental conditions, which shows that the gate error can be reduced by as much as 91.7% compared with the conventional HQC. Moreover, the leakage rates can be reduced to the ${10}^{-3}$ level by numerically choosing a suitable control parameter. Therefore, our scheme provides a promising way towards fault-tolerant quantum computation in a weakly anharmonic solid-state system.

Characterization of microstructures in living tissues is one of the keys to diagnosing early stages of pathology and understanding disease mechanisms. However, the extraction of reliable information on biomarkers based on microstructure details is still a challenge, as the size of features that can be resolved with noninvasive magnetic resonance imaging (MRI) is orders of magnitude larger than the relevant structures. Here we derive from quantum information theory the ultimate precision limits for obtaining such details by MRI probing of water-molecule diffusion. We show that currently available MRI pulse sequences can be optimized to attain the ultimate precision limits by choosing control parameters that are uniquely determined by the expected size, the diffusion coefficient, and the spin relaxation time $T_2$. By attaining the ultimate precision limit per measurement, the number of measurements and the total acquisition time may be drastically reduced compared to the present state of the art. These results are expected to open alternative avenues towards unraveling diagnostic information by quantitative MRI.

Controllable interaction between superconducting qubits is desirable for large-scale quantum computation and simulation. Here, based on a theoretical proposal by Yan et al. [Phys. Rev. Appl. 10, 054061 (2018)] we experimentally demonstrate a simply designed and flux-controlled tunable coupler with a continuous tunability by adjusting the coupler frequency, which can completely turn off adjacent superconducting qubit coupling. Utilizing the tunable interaction between two qubits via the coupler, we implement a different type of controlled-phase (cz) gate with “dynamically decoupled regime,” which allows the qubit-qubit coupling to be only “on” at the usual operating point while dynamically “off” during the tuning process of one qubit frequency into and out of the operating point. This scheme not only efficiently suppresses the leakage out of the computational subspace, but also allows for the acquired two-qubit phase being geometric at the operating point. We achieve an average cz gate fidelity of $98.3\pm 0.6\mathrm{\%}$, which is dominantly limited by qubit decoherence. The demonstrated tunable coupler provides a desirable tool to suppress adjacent qubit coupling and is suitable for large-scale quantum computation and simulation.

Superconducting quantum circuits are typically housed in conducting enclosures in order to control their electromagnetic environment. As devices grow in physical size, the electromagnetic modes of the enclosure come down in frequency and can introduce unwanted long-range cross-talk between distant elements of the enclosed circuit. Incorporating arrays of inductive shunts such as through-substrate vias or machined pillars can suppress these effects by raising these mode frequencies. Here, we derive simple, accurate models for the modes of enclosures that incorporate such inductive-shunt arrays. We use these models to predict that cavity-mediated interqubit couplings and drive-line cross-talk are exponentially suppressed with distance for arbitrarily large quantum circuits housed in such enclosures, indicating the promise of this approach for quantum computing. We find good agreement with a finite-element simulation of an example device containing more than 400 qubits.

The theory of quantum cryptography aims to guarantee unconditional information-theoretic security against an omnipotent eavesdropper. In many practical scenarios, however, the assumption of an all-powerful adversary is excessive and can be relaxed considerably. In this paper we study secret-key distillation across a lossy and noisy quantum wiretap channel between Alice and Bob, with a separately parameterized realistically lossy quantum channel to the eavesdropper Eve. We show that under such restricted eavesdropping, the key rates achievable can exceed the secret-key-distillation capacity against an unrestricted eavesdropper in the quantum wiretap channel. Furthermore, we show upper bounds on the key rates based on the relative entropy of entanglement. This simple restricted eavesdropping model is widely applicable, for example, to free-space quantum optical communication, where realistic collection of light by Eve is limited by the finite size of her optical aperture. Future work will include calculating bounds on the amount of light Eve can collect under various realistic scenarios.

Quantum key distribution (QKD) is one of the most important aspects of quantum cryptography. Using laws of quantum mechanics as the basis for security, the key-distribution process makes information theoretically secure in QKD. With the advancement and commercialization of QKD, an end-to-end QKD simulation software is required that can include experimental imperfections. Software of this kind will ensure that resources are invested only after prior performance analysis, and is faithful to experimental capacities and limitations. In this work, we introduce our QKD simulation toolkit qkdSim, which is ultimately aimed at being developed into such a software package that can precisely model and analyze any generic QKD protocol. We present the design, implementation, and testing of a prototype of qkdSim that can accurately simulate our own experimental demonstration of the B92 protocol. The simulation results match well with experiment; a representative key rate and the quantum bit error rate from experiment is $51\pm 0.5$ kbit/sec and $4.79\mathrm{\%}\pm 0.01\mathrm{\%}$ respectively, wherein the simulation yields $52.83\pm 0.36$ kbit/sec and $4.79\mathrm{\%}\pm 0.01\mathrm{\%}$, respectively.

We develop a form of nondestructive optical thermometry to deterministically measure the temperature of the selected segment of a cold-atom ensemble. The essence is to monitor the thermal expansion of the targeted cold atoms after their labeling through manipulation of the internal states, and the nondestructive property relies on nearly lossless detection via the driving of a cycling transition. The temperature information is extracted from the change of densities via a bucket detector without the necessity of a complicated imaging setup. We also focus on the application of this method to isotropic laser cooling, and it has the capability of addressing only the atoms on the optical detection axis within the enclosure, which is readily compatible with typical configurations of atomic clocks or quantum sensing. Our results confirm the sub-Doppler-cooling features of isotropic laser cooling, and we further investigate the relevant cooling properties. Furthermore, we demonstrate the recently developed optical configuration with injection of cooling-laser light in the form of hollow beams, which helps to enhance the cooling performance and accumulate more cold atoms in the central regions.

Precise measurement of the angular deviation of an object is a common task in science and technology. Many methods use light for this purpose. Some of these exploit interference effects to achieve technological advantages, such as amplification effects, or simplified measurement devices. However, all of these schemes require phase stability to be useful. Here we show theoretically and experimentally that this drawback can be lifted by utilizing two-photon interference, which is known to be less sensitive to phase fluctuations. Our results show that nonclassical interference can provide a path towards robust interferometric sensing, allowing for increased metrological precision in the presence of phase noise.

A simple and flexible scheme for high-dimensional linear quantum operations is demonstrated on optical discrete spatial modes in the transverse plane. Quantum-state tomography via symmetric informationally complete positive-operator-valued measures and quantum Fourier transformation are implemented with dimensionality of 15. The statistical fidelity of symmetric informationally complete positive-operator-valued measures and the fidelity of quantum-state tomography are approximately 0.97 and up to 0.853, respectively, while the matrix fidelity of quantum Fourier transformation is 0.85. We believe that our approach has the potential for further exploration of high-dimensional spatial entanglement provided by spontaneous parametric down-conversion in nonlinear crystals.

We demonstrate the local control of up to eight two-level systems interacting strongly with a microwave cavity. Following calibration, the frequency of each individual two-level system (qubit) is tunable without influencing the others. Bringing the qubits one by one on resonance with the cavity, we observe the collective coupling strength of the qubit ensemble. The splitting scales up with the square root of the number of the qubits, which is the hallmark of the Tavis-Cummings model. The local control circuitry causes a bypass shunting the resonator, and a Fano interference in the microwave readout, whose contribution can be calibrated away to recover the pure cavity spectrum. The simulator’s attainable size of dressed states with up to five qubits is limited by reduced signal visibility, and—if uncalibrated—by off-resonance shifts of subcomponents. Our work demonstrates control and readout of a quantum coherent mesoscopic multiqubit system of intermediate scale under conditions of noise.

The fragility of quantum systems makes them ideally suited for sensing applications at the nanoscale. However, interpreting the output signal of a qubit-based sensor is generally complicated by background clutter due to out-of-band spectral leakage, as well as ambiguity in signal origin when the sensor is operated with noisy hardware. We present a sensing protocol based on optimally band-limited “Slepian functions” that can overcome these challenges, by providing narrowband sensing of ambient dephasing noise, coupling additively to the sensor along the $z$ axis, while permitting isolation of the target noise spectrum from other contributions coupling along a different axis. This is achieved by introducing a finite-difference control modulation, which linearizes the sensor’s response and affords tunable band-limited “windowing” in frequency. Building on these techniques, we experimentally demonstrate two spectral estimation capabilities using a trapped-ion qubit sensor. We first perform efficient experimental reconstruction of a “mixed” dephasing spectrum, composed of a broadband $1/f$-type spectrum with discrete spurs. We then demonstrate the simultaneous reconstruction of overlapping dephasing and control noise spectra from a single set of measurements, in a setting where the two noise sources contribute equally to the sensor’s response. Our approach provides a direct means to augment quantum-sensor performance in the presence of both complex broadband noise environments and imperfect control signals, by optimally complying with realistic time-bandwidth constraints.

How to achieve the maximal entanglement, for given finite entanglement resources? In this paper, we propose a two-port feedback optical parametric amplifier (TFPA) consisting of a nondegenerate optical parametric amplifier (NOPA) and two linear beam splitters. The former is an entanglement resource, and the latter serve as feedback controllers that feed the two entangled beams generated from the NOPA back into its input ports. By manipulating the reflectivity of the beam splitters and the phase delays introduced by the feedback paths, an entanglement enhancement can be achieved by the TFPA. Furthermore, we demonstrate that such entanglement enhancement can happen at all phase points for the ideal case, and the maximal entanglement can be infinitely large. For the lossy case, our TFPA also has its unique advantages in the robustness of the losses of the system.