Our study aims to increase the spatial resolution of high-sensitivity magnetometry based on singlet-transition infrared (IR) absorption using nitrogen-vacancy ($\mathrm{N}$-$V$) centers in diamond in monolithic cavities, with potential applications in biomagnetic field detection. We develop a master-equation treatment of optically detected magnetic resonance, incorporating IR light saturation effects. This master equation provides the singlet population, which is then utilized to calculate the reflectivity and ultimately derive the magnetic field sensitivity taking into account photon and spin shot noise. We further show that our model is compatible with experiments of IR-based $\mathrm{N}$-$V$-center magnetometry. Through optimization in a high-parameter space, we uncover the potential to achieve sensitivities in the order of subpicotesla, even for submillimeter scales.

We introduce a quantum-inspired algorithm for graph coloring problems (GCPs) that utilizes qudits in a product state, with each qudit representing a node in the graph and parameterized by $d$-dimensional spherical coordinates. We propose and benchmark two optimization strategies: qudit gradient descent, initiating qudits in random states and employing gradient descent to minimize a cost function; and qudit local quantum annealing, which adapts the local quantum annealing method to optimize an adiabatic transition from a tractable initial function to a problem-specific cost function. Our approaches are benchmarked against established solutions for standard GCPs, showing that our methods not only rival but frequently surpass the performance of recent state-of-the-art algorithms in terms of solution quality and computational efficiency. The adaptability of our algorithm and its high-quality solutions, achieved with minimal computational resources, point to an advancement in the field of quantum-inspired optimization, with potential applications extending to a broad spectrum of optimization problems.

We theoretically propose how to achieve nonreciprocal enhancement of bipartite and tripartite entanglement using an optomechanical resonator coupled to a nonlinear optical resonator. We find that by our pumping the nonlinear resonator, directional optical squeezing can occur along the pump direction, resulting in an asymmetric detuning and chiral photon interaction between the two resonators. As a result, nonreciprocal enhancement of bipartite and tripartite entanglement can be achieved, exhibiting robustness regarding bath temperature. Specifically, in one direction, bipartite entanglement can be enhanced by about 2 times and tripartite entanglement can be enhanced by about 3.5 times compared with the opposite direction. Our work provides a route to manipulate and enhance nonreciprocal bipartite and tripartite entanglement using directional quantum squeezing, which may find potential applications in constructing chiral quantum networks.

Local local oscillator (LLO) continuous-variable quantum key distribution (CVQKD) systems have gained prominence due to their security advantages with LO generated locally. However, the nonsynchronization of two lasers leads to phase drift, a detrimental phenomenon that restricts excess noise suppression. Prevailing solutions, such as pilot-multiplexing schemes, offer better recovery results than pilot-sequential schemes, but at the expense of increased system complexity and demanding technical requirements. In this work, we introduce an innovative carrier-recovery strategy employing the long-short-term memory (LSTM) neural network, aiming to optimize the recovery performance in the simple self-referenced CVQKD systems with the pilot-sequential scheme. Through temporal modeling, the LSTM network proficiently predicts and compensates for the rapid phase drifts. Experimental validations conducted in both fiber and free-space channels underscore the effectiveness of our method for carrier recovery. In practical CVQKD experiments, our LSTM-based approach yields a near 50% reduction in excess noise, leading to a significant increase in secret key rates when compared with the traditional pilot-sequential method. The simplicity of hardware and operation positions our scheme as a superior alternative for current mainstream pilot-multiplexing CVQKD systems, particularly appealing for on-chip implementation and satellite-to-ground quantum communication applications.

Current quantum computers suffer from noise that stems from interactions between the quantum system that constitutes the quantum device and its environment. These interactions can be suppressed through dynamical decoupling to reduce computational errors. However, the performance of dynamical decoupling depends on the type of system-environment interactions that are present, which often lack an accurate model in quantum devices. We show that the performance of dynamical decoupling can be improved by optimizing its rotational gates to tailor them to the quantum hardware. We find that, compared to canonical decoupling sequences, such as CPMG, XY4, and UR6, the optimized dynamical decoupling sequences yield the best performance in suppressing noise in superconducting qubits. Our work thus enhances existing error suppression methods, which helps increase the circuit depth and result quality on noisy hardware.

Quantum memories play a key role in facilitating tasks within quantum networks and quantum information processing, including secure communications, advanced quantum sensing, and distributed quantum computing. Progress in characterizing large nuclear-spin registers coupled to defect electronic spins has been significant, but selecting memory qubits remains challenging due to the multitude of possible assignments. Numerical simulations for evaluating entangling gate fidelities encounter obstacles, restricting research to small registers, while experimental investigations are time-consuming and often limited to well-understood samples. Here we present an efficient methodology for systematically assessing the controllability of defect systems coupled to nuclear-spin registers. We showcase the approach by investigating the generation of entanglement links between silicon monovacancy or divacancy centers in $\mathrm{Si}\mathrm{C}$ and randomly selected sets of nuclear spins within the two-species (${}^{13}\mathrm{C}$ and ${}^{29}\mathrm{Si}$) nuclear register. We quantify the performance of entangling gate operations and present the achievable gate fidelities, considering both the size of the register and the presence of unwanted nuclear spins. We find that some control sequences perform better than others depending on the number of target versus bath nuclei. This efficient approach is a guide for both experimental investigation and engineering, facilitating the high-throughput exploration of suitable defect systems for quantum memories.

Gaussian channel simulation is an essential paradigm in understanding the evolution of bosonic quantum states. It allows us to investigate how such states are influenced by the environment and how they transmit quantum information. This makes it an essential tool for understanding the properties of Gaussian quantum communication. Quantum teleportation provides an avenue to effectively simulate Gaussian channels, such as amplifier channels, loss channels, and classically additive noise channels. However, implementations of these channels, particularly quantum amplifier channels and channels capable of performing Gaussian noise suppression, are limited by experimental imperfections and nonideal entanglement resources. In this work, we overcome these difficulties using a heralded quantum teleportation scheme that is empowered by a measurement-based noiseless linear amplifier. The noiseless linear amplification enables us to simulate a range of Gaussian channels that were previously inaccessible. In particular, we demonstrate the simulation of nonphysical Gaussian channels otherwise inaccessible using conventional means. We report Gaussian noise suppression, effectively converting an imperfect quantum channel into a near-identity channel. The performance of Gaussian noise suppression is quantified by calculating the transmitted entanglement.

High-power measurement-induced cavity response is investigated in the $|g⟩$, $|e⟩$, and $|f⟩$ states of a transmon. All the states exhibit photon blockades above a certain critical value, a phenomenon that has previously been understood based on the bistability of semiclassical Duffing oscillators. The measurement-induced state transition (MIST) to high-level transmon states is expected to be one contributor to the bistability; however, the critical values measured in the $|e⟩$ and $|f⟩$ states are not coincident with the MIST. To understand this discrepancy, we utilize the recently developed semiclassical dynamics model of a cavity photon state. The appearance of dim and bright cavity states obtained from the model’s steady-state solution leads to the photon blockades at lower critical photon numbers, and this can explain the response of the bistable region in the $|e⟩$ and $|f⟩$ states.

The paper describes the means to reveal and characterize slow periodic modulation of the qubit frequency. Such modulation can come from different sources and can impact qubit stability. We show that the modulation leads to very sharp peaks in the power spectrum of outcomes of periodically repeated Ramsey measurements. The positions and shapes of the peaks allow us to find both the frequency and the amplitude of the modulation. We also explore how additional slow fluctuations of the qubit frequency and fluctuations of the modulation frequency affect the spectrum. The analytical results are in excellent agreement with extensive simulations.

High-dimensional entanglement has been shown to provide significant advantages in quantum communication. One of its most promising implementations is available in the time domain routinely produced in spontaneous parametric down-conversion . While advantageous in the sense that only a single detector channel is needed locally, it is notoriously hard to analyze, especially in an assumption-free manner as required for quantum key distribution (QKD) applications. We develop a complete analysis of high-dimensional entanglement in the polarization-time domain and show how to efficiently certify relevant density matrix elements and security parameters for QKD. In addition to putting past experiments on rigorous footing, we also develop a physical noise model and propose a setup that can further enhance the noise resistance of free-space quantum communication.

Spin selection is explored for a quantum dot spin qubit with spin accumulations $\mathrm{\Delta }{\mu }_S$ and $\mathrm{\Delta }{\mu }_D$ in the source and drain reservoir, created by ferromagnetic contacts. If $\mathrm{\Delta }{\mu }_S$ and $\mathrm{\Delta }{\mu }_D$ have opposite signs, a single electron can be trapped on the quantum dot in two opposite spin states, depending on the source-drain voltage. The selected spin is then electrically reversible and with low error rates for temperatures up to above 4 K. If $\mathrm{\Delta }{\mu }_S$ and $\mathrm{\Delta }{\mu }_D$ have the same sign, the spin selectivity is enhanced and persists up to even higher temperature than for a spin qubit with spin accumulation in only one of the reservoirs. These results offer opportunities to improve and electrically control spin qubit initialization and readout at elevated temperature.

The rapid advancement of quantum information technology has spurred the need for establishing hybrid quantum systems (HQSs) capable of providing complementary functionalities and multitasking capabilities. Recently, there has been growing interest in HQSs that leverage magnons and other discrete quantum systems. However, the realization of high-fidelity quantum logic on an HQS incorporating both a single spin and coherent magnons has remained elusive at room temperature. In this study, we successfully demonstrate the high-fidelity quantum control of a single spin’s state and present the experimental implementation of a quantum game on an HQS through flexible coherent magnon driving. This accomplishment is made possible through the use of nitrogen-vacancy centers and yttrium-iron-garnet film. Our findings not only underscore the advantages of single-spin coherence for implementing high-fidelity quantum logic but also highlight the absence of heat generation of magnon driving resulting from reducing the energy cost by two orders of magnitude. This, in turn, opens up exciting avenues for further research focused on entangling spin qubits with a quantum data bus of magnons within the context of quantum networks.

The assessment of channel resources is critical in the implementation of quantum teleportation (QT), however, an accurate evaluation approach remains elusive in high-dimensional systems. In this paper, we present a general approach for achieving the optimal $d$-dimensional QT fidelity of arbitrary mixed-channel states, and perform an experimental verification of three-dimensional QT to demonstrate its validity. Compared with the previous method, our approach is more precise in determining the optimal QT fidelity with a wider range, which improves the identification of channel resource effectiveness, and eliminates the divergence between different estimation methods for high-dimensional fully entangled fraction (FEF, which has a close connection with the optimal QT fidelity). Our approach can be further applied in the resource design and allocation in high-dimensional quantum networks.

We propose a faster digital quantum algorithm for portfolio optimization using the digitized counterdiabatic quantum optimization paradigm in the impulse regime, that is, where the counterdiabatic terms are dominant. Our approach notably reduces the circuit depth requirement of the algorithm and enhances the solution accuracy, making it suitable for current quantum processors. We apply this protocol to a real-case scenario of portfolio optimization with 20 assets, using purely quantum and hybrid classical-quantum paradigms. We demonstrate the advantages of our protocol using up to 20 qubits on an IonQ trapped-ion quantum computer. By benchmarking our method against the standard quantum approximate optimization algorithm and finite-time digitized adiabatic algorithms, we obtain a significant reduction in the circuit depth by factors of 2.5 to 40, while minimizing the dependence on the classical optimization subroutine. Besides portfolio optimization, the proposed method is applicable to a large class of combinatorial optimization problems.

Converting quantum information from stationary qubits to traveling photons enables both fast qubit initialization and efficient generation of flying qubits for redistribution of quantum information. This conversion can be performed using cavity-sideband transitions. In the fluxonium, however, direct cavity-sideband transitions are forbidden due to parity symmetry. Here we circumvent this parity selection rule by using a three-wave mixing element to couple the fluxonium to a resonator. We experimentally demonstrate a scheme for interfacing the fluxonium with traveling photons through microwave-induced parametric conversion. We perform fast reset on the fluxonium qubit, initializing it with $>95\mathrm{\%}$ ground-state population. We then implement controlled release and temporal shaping of a flying photon, useful for quantum state transfer and remote entanglement. The simplicity and flexibility of our demonstrated scheme enables fluxonium-based remote entanglement architectures.

We investigate the effect of the magnetic field on a photonic crystal Josephson traveling-wave parametric amplifier (TWPA). We show that the observed change in the photonic band gap and plasma frequency of the TWPA can be modeled by considering the suppression of the critical current in the Josephson junctions (JJs) of the TWPA due to the Fraunhofer effect and closing of the superconducting gap. Accounting for the JJ geometry is crucial for understanding the field dependence. In one in-plane direction, the TWPA band gap can be shifted by 2 GHz using up to 60 mT of field, without losing gain or bandwidth, showing that TWPAs without superconducting quantum interference devices (SQUID) can be field tunable. In the other in-plane direction, the magnetic field is perpendicular to the larger side of the Josephson junctions, so the Fraunhofer effect has a smaller period. This larger side of the JJs is modulated to create the band gap. The field interacts more strongly with the larger junctions, and as a result, the TWPA band gap closes and reopens as the field increases, causing the TWPA to become severely compromised already at 2 mT. A slightly higher operating limit of 5 mT is found in the out-of-plane field, for which the TWPA’s response is hysteretic. These measurements reveal the requirements for magnetic shielding needed to use TWPAs in experiments where high fields at the sample are required. With magnetic shields and at a distance from a sample at the magnet center, we can operate the TWPA while applying over 2 T to the sample.

The growing maturity of photonic integrated circuit (PIC) fabrication technology enables the high integration of an increasing number of optical components onto a single chip. With the incremental circuit complexity, the calibration of active phase shifters in a large-scale PIC becomes a crucial issue. The traditional one-by-one calibration techniques encounter significant hurdles with the propagation of calibration errors, and achieving the decoupling of all phase shifters for independent calibration is not straightforward. To address this issue, we propose a global calibration approach for large-scale PIC. Our method utilizes a custom network to simultaneously learn the nonlinear phase-current relations for all thermo-optic phase shifters on the PIC by minimizing the negative likelihood of the measurement datasets. Moreover, the reflectivities of all static beam splitter components can also be synchronizedly extracted using this calibration method. As an example, a quantum walk PIC with a circuit depth of 12 is calibrated, and a programmable discrete-time quantum walk is experimentally demonstrated. These results will greatly benefit the applications of large-scale PICs in photonic quantum information processing.

With great interest from the quantum computing community, an immense amount of R&D effort has been invested into improving superconducting qubits. The technologies developed for the design and fabrication of these qubits can be directly applied to applications for ultralow-threshold particle detectors, e.g., low-mass dark matter and far-infrared photon sensing. We propose a novel energy-resolving sensor based on the transmon qubit architecture combined with a signal-enhancing superconducting quasiparticle amplification stage. We refer to these sensors as SQUATs: superconducting quasiparticle-amplifying transmons. We detail the operating principle and design of this new sensor and predict that, with minimal R&D effort, solid-state-based detectors patterned with these sensors can achieve sensitivity to single terahertz photons, and sensitivity to $1\mathrm{meV}$ phonons in the detector absorber substrate on the microsecond timescale.

Parameterized quantum circuits (PQCs) have been widely used as a machine learning model to explore the potential of achieving quantum advantages for various tasks. However, training PQCs is notoriously challenging owing to the phenomenon of plateaus and/or the existence of (exponentially) many spurious local minima. To enhance trainability, in this work we propose an efficient parameter initialization strategy with theoretical guarantees. We prove that, by reducing the initial domain of each parameter inversely proportional to the square root of the circuit depth, the magnitude of the cost gradient decays at most polynomially with respect to the qubit count and circuit depth. Our theoretical results are substantiated through numerical simulations of variational quantum eigensolver tasks. Moreover, we demonstrate that the reduced-domain initialization strategy can protect specific quantum neural networks from exponentially many spurious local minima. Our results highlight the significance of an appropriate parameter initialization strategy, offering insights to enhance the trainability and convergence of variational quantum algorithms.