We consider mediated interactions in an array of floating transmons, where each qubit capacitor consists of two superconducting pads galvanically isolated from ground. Each such pair contributes two quantum degrees of freedom, one of which is used as a qubit, while the other remains fixed. However, these extraneous modes can generate coupling between the qubit modes that extends beyond the nearest neighbor. We present a general formalism describing the formation of this coupling and calculate it for a one-dimensional chain of transmons. We show that the strength of coupling and its range (that is, the exponential falloff) can be tuned independently via circuit design to realize a continuum from nearest-neighbor-only interactions to interactions that extend across the length of the chain. We discuss how this coupling breaks integrability, allowing the system to locally equilibrate, and so enables exploration of quantum thermalization. We present designs with capacitance and microwave simulations showing that various interaction configurations can be achieved in realistic circuits. Such a coupling could be used in analog simulation of different quantum regimes or to increase connectivity in digital quantum systems. Thus the mechanism must also be taken into account in other types of qubits with extraneous modes.

Adiabatic quantum-control schemes are widely used in the areas of quantum-information processing and quantum sensing. The very requirement of adiabaticity in these schemes often leads to problems of low efficiency and being sensitive to decoherence. To address such issues, various methods have been developed for accelerating adiabatic processes, but they often need to be designed on an $adhoc$ basis. Here we propose and experimentally demonstrate an inverse-engineering approach, where a parameterized state of the Schrödinger equation is employed for constructing desired evolutions. Within a single and simple frame, the user-defined passages can be flexibly customized for different objectives and systems. To experimentally benchmark its performance, we implement this approach in a task of coherent state transfer in a superconducting Xmon device. We find that our method completed the transfer with the fastest speed and highest efficiency (>99.5%) among all recent experiments performed in similar configurations.

Defect spin qubits in silicon carbide have recently drawn widespread attention. Extraction of spin information in the presence of noise always requires multiple repeated measurements, which consumes a large amount of time resources. In this paper, we propose a deep-learning-enhanced method to extract effective parameters from continuous-wave optically detected magnetic resonance (ODMR) spectra and Rabi oscillations with less time consumption. Even if the signal-to-noise ratio is reasonably low, a well-trained convolutional neural network (CNN) can predict the resonance peaks of ODMR spectra or the period of Rabi oscillations. Because of the fast output of predictions by the CNN, this method can be used to sense the magnetic field in the environment and microwave intensities in real time.

Scattering of light by cloud, haze, and fog decreases the transmission efficiency of communication channels in quantum key distribution (QKD), reduces the system’s practical security, and thus constrains the deployment of free-space QKD. Here, we employ wave-front shaping technology to compensate distorted optical signals in high-loss scattering quantum channels and fulfill a polarization-encoded BB84 QKD experiment. With this quantum-channel compensation technology, we achieve a typical enhancement of about 250 in transmission efficiency and build a secure communication link even considering finite key length effect, while the link is impossible to share secure keys before optimization. The method applied in the QKD system shows the potential to expand the application range of QKD systems from lossless channels to highly scattered ones and therefore enhances the deployment ability of a global quantum communication network.

Realistic modeling of qubit systems including noise and constraints imposed by control hardware is required for performance prediction and control optimization of quantum processors. We introduce qopt, a software framework for simulating qubit dynamics and robust quantum optimal control considering common experimental situations. To this end, we model open and closed qubit systems with a focus on the simulation of realistic noise characteristics and experimental constraints. Specifically, the influence of noise can be calculated using Monte Carlo methods, effective master equations or with the efficient filter function formalism, which enables the investigation and mitigation of autocorrelated noise. In addition, limitations of control electronics, including finite bandwidth effects as well as nonlinear transfer functions and drive-dependent noise, can be considered. The calculation of gradients based on analytic results is implemented to facilitate the efficient optimization of control pulses. The software easily interfaces with QuTiP, is published under an open-source license, is well tested, and features a detailed documentation.

Magnetic-field-resilient superconducting circuits enable sensing applications and hybrid quantum computing architectures involving spin or topological qubits and electromechanical elements, as well as studying flux noise and quasiparticle loss. We investigate the effect of in-plane magnetic fields up to 1 T on the spectrum and coherence times of thin-film three-dimensional aluminum transmons. Using a copper cavity, unaffected by strong magnetic fields, we can probe solely the effect of magnetic fields on the transmons. We present data on a single-junction and a superconducting-quantum-interference-device (SQUID) transmon that are cooled down in the same cavity. As expected, the transmon frequencies decrease with increasing field, due to suppression of the superconducting gap and a geometric Fraunhofer-like contribution. Nevertheless, the thin-film transmons show strong magnetic field resilience: both transmons display microsecond coherence up to at least 0.65 T, and $T_1$ remains above $1\mu \text{s}$ over the entire measurable range. SQUID spectroscopy is feasible up to 1 T, the limit of our magnet. We conclude that thin-film aluminum Josephson junctions are suitable hardware for superconducting circuits in the high-magnetic-field regime.

Quantum two-level systems (TLSs) are present in the materials of qubits and are considered defects because they limit qubit coherence. For superconducting qubits, the quintessential Josephson junction barrier is made of amorphous alumina, which hosts TLSs. However, TLSs are not generally understood, either structurally or in atomic composition. In this study, we greatly extend the quantitative data available on TLSs by reporting on the physical dipole moment in two alumina types: polycrystalline $\gamma$-${\mathrm{Al}}_2{\mathrm{O}}_3$ and amorphous a-$\mathrm{Al}{\mathrm{O}}_x$. To obtain the dipole moments $p_z$, rather than the less-structural coupling parameter $g$, we tune individual TLSs with a known external electric field in a cavity quantum electrodynamic system. We find a clear difference in the dipole moment distribution from the film types, indicating a difference in TLS structures. A large sample of approximately 400 individual TLSs are analyzed from the polycrystalline film type. Their dipoles along the growth direction $p_z$ have a mean value of $2.6\pm 0.3$ debye (D) ($0.54\pm 0.06e$ Å) and standard deviation $\sigma =1.6\pm 0.2\mathrm{D}$ ($0.33\pm 0.03e$ Å). The material distribution fits well to a single Gaussian function. Approximately 200 individual TLSs are analyzed from amorphous films. Both the mean $p_z=4.6\pm 0.5\mathrm{D}$ ($0.96\pm 0.1e$ Å) and $\sigma =2.5\pm 0.3\mathrm{D}$ ($0.52\pm 0.05e$ Å) are larger. Amorphous alumina also has very large $p_z$, greater than $8.6\mathrm{D}$ ($1.8e$ Å), in contrast to polycrystalline which has none of this moment. These large moments agree only with oxygen-based TLS models. Based on data and the candidate models (delocalized O and hydrogen-based TLSs), we find polycrystalline alumina has smaller ratio of O-based to H-based TLS than amorphous alumina.

Nonadiabatic holonomic quantum computation (NHQC) has attracted significant attention due to its fast evolution and the geometric nature-induced resilience to local noises. However, its long operation time and complex physical implementation make it hard to surpass the dynamical scheme, and thus hindering its wide application. Here, we present to implement NHQC with the shortest path under some conditions, through the inverse Hamiltonian engineering technique, which posseses higher fidelity and stronger robustness than previous NHQC schemes. Meanwhile, the gate performance in our scheme can be further improved by using the proposed composite dynamical decoupling pulses, which can efficiently improve both the gate fidelity and robustness, making our scheme outperform the optimal dynamical scheme in a certain parameter range. Remarkably, our scheme can be readily implemented with Rydberg atoms, and a simplified implementation of the controlled-not gate in the Rydberg blockade regime can be achieved. Therefore, our scheme represents a promising progress towards future fault-tolerant quantum computation in atomic systems.

We show a concept of optical frequency tweezers for tweezing light in the optical frequency domain with a high resolution, which is the frequency version of optical tweezers for the spatial manipulation of microscopic objects. We report a proof-of-principle experiment via frequency conversion inside a cavity only for the converted light. Owing to the atypical configuration, the experiment successfully achieves the tweezing operation in the frequency domain, which picks light at a target frequency from the frequency-multiplexed input light and converts it to a different frequency, without touching any other light sitting in different frequency positions and shaking the frequency by the pump light.

Quantum entanglement represents an ideal resource to guarantee the security of random numbers employed in many scientific and cryptographic applications. However, entanglement-based certified random number generators are particularly challenging to implement. Here, we demonstrate a certified quantum random number generator based on momentum-polarization entangled single-photon states. The use of single-photon entanglement allows an attenuated laser source to be employed and a simple setup where only linear optical components are utilized. For the latter, a semi-device-independent modeling of the photonic quantum random number generator is developed, which certifies a minimum entropy of $(2.5\pm 0.5)\mathrm{\%}$, corresponding to a generation rate of 4.4 kHz. At the expenses of a higher level of trust in the system, the certified minimum entropy can be increased to $(30.1\pm 0.5)\mathrm{\%}$, implying a generation rate of 52.7 kHz. Our results show that a simple optical implementation combined with an accurate modeling provide an entanglement-based high-security quantum random number generator using imperfect devices.

The faithful distribution of entanglement over noisy channels is a vital prerequisite for many quantum technological applications. Quantum information can be encoded in different degrees of freedom (DOF) of photons, where each encoding comes with its own advantages and disadvantages with respect to noise resilience and practicality in manipulation. In this work, we experimentally implement a deterministic entanglement purification protocol that allows us to faithfully distribute entanglement in one DOF over a noisy channel and then remotely transfer it to another DOF for manipulation. In particular, we distribute robust energy-time entanglement and transfer it to polarization entanglement at the communicating parties. The remotely obtained polarization state is independent of the polarization noise during distribution and reaches fidelities to a Bell state of up to $97.6\mathrm{\%}$. Our scheme enables robust and efficient polarization entanglement distribution in the presence of arbitrary polarization noise, which is relevant for future large-scale quantum networks.

We explore the implementation of hybridly protected quantum operations combining the merits of geometry and holonomy, dynamical decoupling approach, and dephasing-free feature based on a simple and experimentally achievable spin model. The implementation of the quantum operations can be achieved in different physical systems with controllable parameters. The protected quantum operations are hence controllable and well suited for resolving various quantum-computation tasks, such as executing quantum error-correction codes or quantum error mitigation. Our scheme is based on an experimentally achievable Hamiltonian with reduced requirement of computational resources and thus, it brings us closer towards realizing protected quantum operations for resolving quantum-computation tasks in near-term quantum devices.

An optical unitary converter (OUC) that can convert a set of $N$ mutually orthogonal optical modes into another set of arbitrary $N$ orthogonal modes is expected to be a key device in diverse applications, including optical communication, deep learning, and quantum computing. While various types of OUC have been demonstrated on photonic integration platforms, the sensitivity against a slight deviation in waveguide dimensions has been the crucial issue in scaling $N$. Here, we demonstrate that an OUC based on the concept of multiplane light conversion (MPLC) shows outstanding robustness against waveguide deviations. Moreover, it becomes more and more insensitive to fabrication errors as we increase $N$, which is in clear contrast to the conventional OUC architecture, composed of $2\times 2$ Mach-Zehnder interferometers. The physical origin behind this unique robustness and scalability is studied by considering a generalized OUC configuration. As a result, we reveal that the number of coupled modes in each stage plays an essential role in determining the sensitivity of the entire OUC. The maximal robustness is attained when all-to-all-coupled interferometers are employed, which are naturally implemented in a MPLC-based OUC.

Impurities in silicon are fundamental to a variety of modern nanoscale technologies working in both classical and quantum regimes of operation. The aggressive miniaturization of electronic devices has reduced their size to the nanometer scale, where the exact count and positioning of a few impurity atoms dictates their overall operation and performance. In the emerging area of quantum hardware development, single-impurity spins in silicon form excellent qubits and identifying their exact locations is important to engineer two-qubit interactions for high-fidelity quantum operations and the associated quantum control systems. This work reports a theoretical framework for the spatial metrology of single-impurity atoms in silicon with exact atomic precision for impurity depths approaching the bulk limit. The application of a carefully designed electric field pulls the impurity wave functions toward the surface, leading to spatially resolved scanning tunneling microscope images of electronic states exhibiting features that distinctly depend on the exact locations of the impurity atoms beneath the silicon surface. After verification of the developed metrology technique for individual atom positions, we train a machine-learning algorithm that can autonomously perform the metrology with high throughput in the presence of noise commensurate with experimental measurements. A future experimental implementation of the established capability for impurity-atom characterization is anticipated to play an important role in the design of a wide range of electronic and quantum devices.

The current autotuning approaches for quantum dot (QD) devices, while showing some success, lack an assessment of data reliability. This leads to unexpected failures when noisy or otherwise low-quality data is processed by an autonomous system. In this work, we propose a framework for robust autotuning of QD devices that combines a machine learning (ML) state classifier with a data quality control module. The data quality control module acts as a “gatekeeper” system, ensuring that only reliable data are processed by the state classifier. Lower data quality results in either device recalibration or termination. To train both ML systems, we enhance the QD simulation by incorporating synthetic noise typical of QD experiments. We confirm that the inclusion of synthetic noise in the training of the state classifier significantly improves the performance, resulting in an accuracy of $95.0(9)\mathrm{\%}$ when tested on experimental data. We then validate the functionality of the data quality control module by showing that the state classifier performance deteriorates with decreasing data quality, as expected. Our results establish a robust and flexible ML framework for autonomous tuning of noisy QD devices.

Multipartite entanglement is one of the core concepts in quantum information science with broad applications that span from condensed matter physics to quantum physics foundation tests. Although its most studied and tested forms encompass two-dimensional systems, current quantum platforms technically allow the manipulation of additional quantum levels. We report the experimental demonstration and certification of a high-dimensional multipartite entangled state in a superconducting quantum processor. We generate the three-qutrit Greenberger-Horne-Zeilinger state by designing the necessary pulses to perform high-dimensional quantum operations. We obtain the fidelity of $76\mathrm{\%}\pm 1\mathrm{\%}$, proving the generation of a genuine three-partite and three-dimensional entangled state. To this date, only photonic devices have been able to create and certify the entanglement of these high-dimensional states. Our work demonstrates that another platform, superconducting systems, is ready to exploit genuine high-dimensional entanglement and that a programmable quantum device accessed on the cloud can be used to design and execute experiments beyond binary quantum computation.

Understanding and suppressing sources of decoherence is a leading challenge in building practical quantum computers. In superconducting qubits, low-frequency charge noise is a well-known decoherence mechanism that is effectively suppressed in the transmon qubit. Devices with multiple charge-sensitive modes can exhibit more complex behaviors, which can be exploited to study charge fluctuations in superconducting qubits. Here we characterize charge sensitivity in a superconducting qubit with two transmonlike modes, each of which is sensitive to multiple charge-parity configurations and charge-offset biases. Using Ramsey interferometry, we observe sensitivity to four charge-parity configurations and track two independent charge-offset drifts over hour time-scales. We provide a predictive theory for charge sensitivity in such multimode qubits which agrees with our results. Finally, we demonstrate the utility of a multimode qubit as a charge detector by spatially tracking local-charge drift.