We introduce a general framework called neural-network- (NN) encoded variational quantum algorithms (VQAs), or NNVQA for short, to address the challenges of implementing VQAs on noisy intermediate-scale quantum (NISQ) computers. Specifically, NNVQA feeds input (such as parameters of a Hamiltonian) from a given problem to a neural network and uses its outputs to parameterize an ansatz circuit for the standard VQA. Combining the strengths of NN and parameterized quantum circuits, NNVQA can accelerate the training process of VQAs and handle a broad family of related problems with varying input parameters with the pretrained NN. To concretely illustrate the merits of NNVQA, we present results on a NN variational quantum eigensolver (VQE) for solving the ground state of parameterized $XXZ$ spin models in one and two dimensions. Our results demonstrate that NNVQE is able to estimate the ground-state energies of parameterized Hamiltonians with high precision without fine tuning, and significantly reduce the overall training cost to estimate ground-state properties across the phases of the given Hamiltonian. We also employ an active learning strategy to further increase the training efficiency while maintaining prediction accuracy. These encouraging results demonstrate that NNVQAs offer an alternative hybrid quantum-classical paradigm to utilize NISQ resources for solving more realistic and challenging computational problems.

We present an experimental realization of a noise-free and high-bandwidth quantum memory scheme using a rubidium vapor that is confined within the hollow core of a photonic crystal fiber. We achieve the same internal efficiencies as similar free-space experiments (30%) for 4.5-ns-long optical pulses but with a 100-fold reduction in the control-field power required. Modeling indicates that this efficiency could be improved to 88% with higher control powers and the implementation of techniques such as light-induced atomic desorption to increase the optical depth. The compactness, robustness, and low drive power of this approach lends itself to direct integration into large-scale fiber-based quantum processors.

Preserving qubit coherence and maintaining high-fidelity qubit control under complex noise environment is an enduring challenge for scalable quantum computing. Here we demonstrate an addressable fault-tolerant single spin qubit with an average control fidelity of 99.12% via randomized benchmarking on a silicon quantum dot device with an integrated micromagnet. Its dephasing time $T_2^{\ast }$ is $1.025\text{μ}\mathrm{s}$, and can be enlarged to $264\text{μ}\mathrm{s}$ by using the Hahn-echo technique, reflecting strong low-frequency noise in our system. To break through the noise limitation, we introduce geometric quantum computing to obtain high control fidelity by exploiting its noise-resilient feature. However, the control fidelities of the geometric quantum gates are lower than 99%. According to our simulation, the noise-resilient feature of geometric quantum gates is masked by the heating effect. With further optimization to alleviate the heating effect, geometric quantum computing can be a potential approach to reproducibly achieving high-fidelity qubit control in a complex noise environment.

As quantum technology rapidly advances, the need for efficient scalable methods to characterize quantum systems intensifies. Quantum state tomography and Hamiltonian learning are essential for interpreting and optimizing quantum systems, yet a unified approach remains elusive. Such an integration could enhance our understanding of the complex relationship between quantum states and Hamiltonians, contributing to the development of more efficient methodologies. In this paper, we present a method that integrates quantum state tomography and Hamiltonian learning, drawing inspiration from machine translation in the field of natural language processing (NLP). We demonstrate the effectiveness of our approach across a variety of quantum systems, successfully learning the complex relationships between quantum states and Hamiltonians. Furthermore, the scalability and few-shot learning capabilities of our method could potentially minimize the resources required for characterizing and optimizing quantum systems. Our research provides valuable insights into the relationship between quantum states and Hamiltonians, paving the way for further studies on quantum systems and advancing quantum computation and related technologies.

A sending-or-not-sending (SNS) protocol is a very promising variant in twin-field quantum key distribution (TFQKD) for its advantages at the regime of long distance and the robustness against large optical misalignment. The actively odd-parity pairing (AOPP) method can significantly enhance the key-rate performance of the original SNS TFQKD, which forms the AOPP SNS TFQKD protocol. In this paper, we introduce the advantage distillation (AD) method to further improve the communication distance for AOPP SNS TFQKD. We also prove the composable security against coherent attacks for the AOPP SNS TFQKD with AD in the finite-key regime for bit blocks with a size of 2 in the AD process. Our AD method for AOPP SNS TFQKD protocol is expected to improve the key-rate performance in practice without changing the SNS TFQKD experimental system.

Efficient generation, guiding, and detection of phonons, or mechanical vibrations, are of interest in various fields, including radio-frequency communication, sensing, and quantum information. Diamond is a useful platform for phononics because of the presence of strain-sensitive spin qubits, and its high Young’s modulus, which allows for low-loss gigahertz devices. We demonstrate a diamond phononic waveguide platform for generating, guiding, and detecting gigahertz-frequency surface acoustic wave (SAW) phonons. We generate SAWs using interdigital transducers integrated on $\mathrm{Al}\mathrm{N}$/diamond and observe SAW transmission at 4–5 GHz through both ridge and suspended waveguides, with wavelength-scale cross sections (approximately 1 ${\mathrm{m}}^2$) to maximize spin-phonon interaction. This work is a crucial step for developing acoustic components for quantum phononic circuits with strain-sensitive color centers in diamond.

Kerr cat qubits are a promising candidate for fault-tolerant quantum computers owing to the biased nature of their errors. The $ZZ$ coupling between the qubits can be utilized for a two-qubit entangling gate, but the residual coupling called $ZZ$ crosstalk is detrimental to precise computing. In order to resolve this problem, we propose a tunable $ZZ$-coupling scheme using two transmon couplers. By setting the detunings of the two couplers at opposite values, the residual $ZZ$ couplings via the two couplers cancel each other out. We also apply our scheme to the $R_{ZZ}(\mathrm{\Theta })$ gate ($ZZ$ rotation with angle $\mathrm{\Theta }$), one of the two-qubit entangling gates. We numerically show that the fidelity of the $R_{ZZ}(-\pi /2)$ gate is higher than 99.9% in a case of 16-ns gate time and without decoherence.

Parametric down-conversion is a widely exploited technique in optics to produce entangled states of photons for quantum information processing and quantum sensing. In the microwave domain, devices based on Josephson junctions, such as Josephson parametric amplifiers and voltage-biased Josephson junctions, have been successfully utilized to generate such states. However, their high susceptibility to magnetic fields has posed challenges in many applications. Here we demonstrate the generation of two-mode squeezed states via four-wave mixing in a superconducting nanowire resonator patterned from $\mathrm{Nb}\mathrm{N}$. The $\mathrm{Nb}\mathrm{N}$ nanowire exhibits a strong Kerr nonlinearity, resulting in the emission of a signal-idler pair with a cross-correlation of $g^{(2)}(0)=11.9$. Owing to the magnetic resilience and high critical temperature ($T_c$) of $\mathrm{Nb}\mathrm{N}$, our microwave parametric sources based on kinetic inductance promise an expanded range of potential applications.

Unauthorized light injection has always been a vital threat to the practical security of a quantum-key-distribution (QKD) system. An optical-power limiter (OPL) based on the thermo-optical defocusing effect has been proposed and implemented, limiting the injected hacking light. As a hardware countermeasure, the performance of the OPL under various light-injection attacks will be tested to clarify the security boundary before it is widely deployed. To investigate the security boundary of the OPL in quantum cryptography, we comprehensively test and analyze the behavior of the OPL under continuous-wave (cw) light-injection attacks and pulse-illumination attacks with pulse repetition rates of $0.5$ Hz, $40$ MHz, and $1$ GHz. The test results illuminate the security boundary of the OPL, which allows one to properly employ the OPL in use cases. The methodology of testing and analysis proposed here is applicable to other power-limitation components in a QKD system.

Distributing quantum information between remote systems will necessitate the integration of emerging quantum components with existing communication infrastructure. This requires understanding the channel-induced degradations of the transmitted quantum signals, beyond the typical characterization methods for classical communication systems. Here we report on a comprehensive characterization of a Boston-Area Quantum Network (BARQNET) telecom fiber testbed, measuring the time-of-flight, polarization, and phase noise imparted on transmitted signals. We further design and demonstrate a compensation system that is both resilient to these noise sources and compatible with integration of emerging quantum memory components on the deployed link. These results have utility for future work on the BARQNET as well as other quantum network testbeds in development, enabling near-term quantum networking demonstrations and informing what areas of technology development will be most impactful in advancing future system capabilities.

We present a way to achieve fully directional, quantum-limited phase-preserving amplification in a four-port, four-mode superconducting Josephson circuit by utilizing interference between six parametric processes that couple all four modes. Full directionality, defined as the reverse isolation surpassing forward gain between the matched input and output ports of the amplifier, ensures its robustness against impedance mismatch that might be present at its output port during applications. Unlike existing directional phase-preserving amplifiers, both the minimal backaction and the quantum-limited added noise of this amplifier remains unaffected by noise incident on its output port. In addition, the matched input and output ports allow direct on-chip integration of these amplifiers with other circuit QED components, facilitating scaling up of superconducting quantum processors.

Spin-photon coupling presents an enticing opportunity for the long-range coupling of spin qubits. The spin-photon coupling rate, $g_s$, is proportional to the charge-photon coupling rate, $g_c$. To move deeper into the strong-coupling regime, $g_c$ can be enhanced by fabricating high-impedance cavities using high-kinetic-inductance films. Here, we report dc transport and microwave response investigations of niobium nitride ($\mathrm{Nb}\mathrm{N}$) films of different thicknesses. The kinetic inductance increases rapidly as the film thickness is reduced below 50 nm and for 15-nm $\mathrm{Nb}\mathrm{N}$ films we measure a sheet kinetic inductance $L_{k,S}=41.2\text{pH}/◻$. As an application of the high-kinetic-inductance films, we fabricate compact $LC$ filters that are commonly used to reduce microwave leakage in circuit quantum electrodynamics (cQED) devices. These filters feature up to 60 dB of attenuation near typical cavity resonance frequencies of $f_c=8$ GHz.

The passive approach to quantum key distribution (QKD) eliminates all optical modulators and random number generators from QKD systems reaching an enhanced simplicity, immunity to modulator side channels, and potentially higher repetition rates. In this work, we provide finite-key security bounds for a fully passive decoy-state Bennett-Brassard 1984 (BB84) protocol, considering a recently presented passive QKD source. With our analysis, the attainable secret-key rate is comparable to that of the perfect parameter-estimation limit, in fact differing from the key rate of the active approach by less than one order of magnitude. This demonstrates the practicality of fully passive QKD solutions.

In the field of quantum computation and communication, there is a compelling need for quantum coherent frequency conversion between microwave electronics and infrared optics. A promising platform for this is an optomechanical crystal resonator that uses simultaneous photonic and phononic crystals to create a colocalized cavity coupling an electromagnetic mode to an acoustic mode, which then via electromechanical interactions can undergo direct transduction to electronics. The majority of the work in this area has been on one-dimensional nanobeam resonators, which provide strong optomechanical couplings but, due to their geometry, suffer from an inability to dissipate heat produced by the laser pumping required for operation. Recently, a quasi-two-dimensional optomechanical crystal cavity has been developed in silicon, exhibiting similarly strong coupling with better thermalization but at a mechanical frequency above optimal qubit operating frequencies. Here, we adapt this design to gallium arsenide, a natural thin-film single-crystal piezoelectric that can incorporate electromechanical interactions, obtaining a mechanical resonant mode at $f_{\mathrm{m}}\approx 4.5\mathrm{GHz}$ that is ideal for superconducting qubits and demonstrating optomechanical coupling of $g_{\mathrm{om}}/(2\pi )\approx 650\mathrm{kHz}$.

Identifying and calibrating quantitative dynamical models for physical quantum systems is important for a variety of applications. Here we present a closed-loop Bayesian learning algorithm for estimating multiple unknown parameters in a dynamical model, using optimized experimental “probe” controls and measurement. The estimation algorithm is based on a Bayesian particle filter, and is designed to autonomously choose informationally optimized probe experiments with which to compare to model predictions. We demonstrate the performance of the algorithm in both simulated calibration tasks and in an experimental single-qubit ion-trap system. Experimentally, we find that, with $60$ times fewer samples, we exceed the precision of conventional calibration methods, delivering an approximately $93$ times improvement in efficiency (as quantified by the reduction of measurements and resets required to achieve a target residual uncertainty and multiplied by the increase in accuracy). In simulated and experimental demonstrations, we see that successively longer pulses are selected as the posterior uncertainty iteratively decreases, leading to an exponential improvement in the accuracy of model parameters with the number of experimental queries, and a commensurate increase in the per-query time.

Because of their small size, low loss, and compatibility with magnetic fields, and elevated temperatures, surface acoustic wave (SAW) resonators hold significant potential as future quantum interconnects. Here, we design, fabricate, and characterize gigahertz-frequency SAW resonators with the potential for strong capacitive coupling to nanoscale solid-state quantum systems, including semiconductor quantum dots. Strong capacitive coupling to such systems requires a large characteristic impedance, and the resonators we fabricate have impedance values above $100\mathrm{\Omega }$. We achieve such high impedance values by tightly confining a Gaussian acoustic mode. At the same time, the resonators have low loss, with quality factors of several thousand at millikelvin temperatures. These high-impedance resonators are expected to exhibit large vacuum electric field fluctuations and have the potential for strong coupling to a variety of solid-state quantum systems.