Symmetry considerations are key to our understanding of the fundamental laws of nature. The presence of a symmetry implies that a physical system is invariant under specific transformations, and this invariance may have deep consequences. For instance, symmetry arguments state that a system will remain in its initial state if incentives to actions are equally balanced. Here, we apply this principle to a chain of qubits and show that it is possible to engineer the symmetries of its Hamiltonian in order to keep quantum information intrinsically protected from both relaxation and decoherence. We show that the coherence properties of this system are strongly enhanced relative to those of its individual components. Such a qubit chain can be realized using a simple architecture consisting of a relatively small number of superconducting Josephson junctions.

Information processing and storage by the same physical system is emerging as a promising alternative to traditional computing platforms. In turn, this requires the realization of elementary units the memory content of which can be easily tuned and controlled. Here, we introduce a polariton-based quantum memristor where the memristive nature arises from the intercavity polariton exchange and is controlled by a time-varying atom-cavity detuning. A dynamical hysteresis is characterized by the fluctuations in the instantaneous polariton number, where the history information is encoded into a dynamical phase. Using a Lindblad master-equation approach, we find that features of the quantum memristor dynamics, such as the area and circulation of the hysteresis loop, showcase a kind of “plasticity” controlled by quantum state initialization. This makes this quantum memristor very versatile for a wide range of applications.

As we are approaching actual application of quantum technology, it is essential to exploit the current quantum resources in the best possible way. With this in mind, it might not be beneficial to use the usual standard gate sets, inspired by classical logic gates, while compiling quantum algorithms when other less standardized gates currently perform better. We, therefore, consider a promising native gate, which occurs naturally in superconducting circuits, known as the diamond gate. We show how the diamond gate can be decomposed into standard gates and, using single-qubit gates, can work as a controlled-not swap (cns) gate. We then show how this cns gate can create a controlled-phase gate. Controlled-phase gates are the backbone of the quantum Fourier-transform algorithm and we, therefore, show how to use the diamond gate to perform this algorithm. We also show how to use the diamond gate in quantum machine learning; namely, we use it to approximate nonlinear functions and classify two-dimensional data.

With the advent of quantum technology, nitrogen vacancy ($\mathrm{N}$-$V$) centers in diamond turn out to be a frontier that provides an efficient platform for quantum computation, communication, and sensing applications. Due to the coupled spin-charge dynamics of the $\mathrm{N}$-$V$ system, knowledge of $\mathrm{N}$-$V$ charge-state dynamics can help to formulate efficient spin-control sequences strategically. Here, we report two spectroscopy-based deconvolution methods to create charge-state mapping images of ensembles of $\mathrm{N}$-$V$ centers in diamond. First, relying on the fact that an off-axis external magnetic field mixes the electronic spins and selectively modifies the photoluminescence (PL) of $\mathrm{N}$-$V^{-}$, we perform decomposition of the optical spectrum for an ensemble of $\mathrm{N}$-$V$ and extract the spectra for $\mathrm{N}$-$V^{-}$ and $\mathrm{N}$-$V^0$ states. Next, we introduce an optical-filter-based decomposition protocol and perform PL imaging for $\mathrm{N}$-$V^{-}$ and $\mathrm{N}$-$V^0$. Previously obtained spectra for $\mathrm{N}$-$V^{-}$ and $\mathrm{N}$-$V^0$ states are used to calculate their transmissivities through a long-pass optical filter. These results help us to determine the spatial distribution of the $\mathrm{N}$-$V$ charge states in a diamond sample.

In measurement-device-independent quantum key distribution (MDI QKD), the setup of Bell state measurement (BSM) usually requires that the photons sent by different users should be frequency degenerate. It increases the complexity to implement MDI QKD since a complicated feedback system is usually required to calibrate photons’ frequencies in different users. It also limits the development of MDI QKD networks since wavelength division multiplexing (WDM) technology is not compatible with this requirement. In this work, we propose a MDI QKD scheme of frequency-nondegenerate photons, in which the users send photons with different frequencies. It is based on a BSM setup with a frequency-domain beam splitter (FBS), which is realized by a phase modulator (PM). A proof-of-principle experiment is realized, showing that the BSM of frequency-nondegenerate photons could select specific users to realize MDI QKD by adjusting the modulation frequency of the PM to match the frequency difference of photons sent by the users. The results manifest that our scheme has great potential for simplifying the implementation and realizing MDI QKD networks combined with WDM.

Crystal-strain variation imposes significant limitations on many quantum sensing and information applications for solid-state defect qubits in diamond. Thus, the precision measurement and control of diamond crystal strain is a key challenge. Here, we report diamond strain measurements with a unique set of capabilities, including micron-scale spatial resolution, a millimeter-scale field of view, and a 2-order-of-magnitude improvement in volume-normalized sensitivity over previous work, reaching $5(2)\times {10}^{-8}/\sqrt{\mathrm{Hz}\mu {\mathrm{m}}^{-3}}$ (with spin-strain coupling coefficients representing the dominant systematic uncertainty). We use strain-sensitive spin-state interferometry on ensembles of nitrogen-vacancy ($\mathrm{N}$-$V$) color centers in single-crystal bulk diamond with low strain gradients. This quantum interferometry technique provides insensitivity to magnetic-field inhomogeneity from the electronic and nuclear spin bath, thereby enabling long $\mathrm{N}$-$V$–ensemble electronic spin dephasing times and enhanced strain sensitivity, as well as broadening the potential applications of the technique beyond isotopically enriched or high-purity diamond. We demonstrate the strain-sensitive measurement protocol first on a confocal scanning laser microscope, providing quantitative measurement of sensitivity as well as three-dimensional strain mapping; and second on a wide-field-imaging quantum diamond microscope. Our strain-microscopy technique enables fast, sensitive characterization for diamond material engineering and nanofabrication; as well as diamond-based sensing of strains applied externally, as in diamond anvil cells or embedded diamond stress sensors, or internally, as by crystal damage due to particle-induced nuclear recoils.

Disorder in condensed matter and atomic physics is responsible for a great variety of fascinating quantum phenomena, which are still challenging for understanding, not to mention the relevant dynamical control. Here we introduce proof of the concept and analyze a neural-network-based machine-learning algorithm for achieving feasible high-fidelity quantum control of a particle in random environment. To explicitly demonstrate its capabilities, we show that convolutional neural networks are able to solve this problem as they can recognize the disorder and, by supervised learning, further produce the policy for the efficient low-energy cost control of a quantum particle in a time-dependent random potential. We show that the accuracy of the proposed algorithm is enhanced by a higher-dimensional mapping of the disorder pattern and using two neural networks, each properly trained for the given task. The designed method, being computationally more efficient than the gradient-descent optimization, can be applicable to identify and control various noisy quantum systems on a heuristic basis.

In order to assess whether quantum resources can provide an advantage over classical computation, it is necessary to characterize and benchmark the nonclassical properties of quantum algorithms in a practical manner. In this paper, we show that using measurements in no more than three out of the possible $3^N$ bases, one can not only reconstruct the single-qubit reduced density matrices and measure the ability to create coherent superpositions, but also possibly verify entanglement across all $N$ qubits participating in the algorithm. We introduce a family of generalized Bell-type observables for which we establish an upper bound to the expectation values in fully separable states by proving a generalization of the Cauchy-Schwarz inequality, which may serve of independent interest. We demonstrate that a subset of such observables can serve as entanglement witnesses for states of the quantum-approximate-optimization algorithm for the MaxCut problem (QAOA MaxCut), and further argue that they are especially well tailored for this purpose by defining and computing an entanglement potency metric on witnesses. A subset of these observables also certifies, in a weaker sense, the entanglement in GHZ states, which share the ${\mathbb{Z}}_2$ symmetry of QAOA MaxCut. The construction of such witnesses follows directly from the cost Hamiltonian to be optimized, and not through the standard technique of using the projector of the state being certified. It may thus provide insights to construct similar witnesses for other variational algorithms prevalent in the noisy intermediate-scale quantum era. We demonstrate our ideas with proof-of-concept experiments on the Rigetti Aspen-9 chip for ansatz containing up to 24 qubits.

Semiconductor spin qubits may show significant device-to-device variability in the presence of spin-orbit coupling mechanisms. Interface roughness, charge traps, layout, or process inhomogeneities indeed shape the real-space wave functions, and hence the spin properties. It is, therefore, necessary to understand how reproducible the qubits can be, in order to assess strategies to cope with variability, and to set constraints on the quality of materials and fabrication. Here we model the variability of single-qubit properties (Larmor and Rabi frequencies) due to disorder at the $\mathrm{Si}/{\mathrm{Si}\mathrm{O}}_2$ interface (roughness, charge traps) in metal-oxide-semiconductor devices. We consider both electron qubits (with synthetic spin-orbit coupling fields created by micromagnets) and hole qubits (with intrinsic spin-orbit coupling). We show that charge traps are much more limiting than interface roughness, and can scatter Rabi frequencies over one order of magnitude. We discuss the implications for the design of spin qubits and for the choice of materials.

Fewer-qubit quantum logic gate, serving as a basic unit for constructing universal multiqubit gates, has been widely applied in quantum computing and quantum information. However, traditional constructions for fewer-qubit gates often utilize a multipulse protocol, which inevitably suffers from serious intrinsic errors during the gate execution. In this paper, we report an optimal model about universal two- and three-qubit cnot gates mediated by excitation to Rydberg states with easily accessible van der Waals interactions. This gate depends on a global optimization to implement amplitude- and phase-modulated pulses via genetic algorithm, which can facilitate the gate operation with fewer optical pulses. Compared to conventional multipulse piecewise schemes, our gate can be realized by simultaneous excitation of atoms to the Rydberg states, saving the time for multipulse switching at different spatial locations. Our numerical simulations show that a single-pulse two- (three-) qubit cnot gate is possibly achieved with a fidelity of 99.23% (90.39%) for two qubits separated by $7.10\mu \mathrm{m}$ when the fluctuation of Rydberg interactions is excluded. Our work is promising for achieving fast and convenient multiqubit quantum computing in the study of neutral-atom quantum technology.

Spin echo can be used to refocus random dynamical phases caused by inhomogeneities in control fields and thereby retain the purity of a spatial distribution of quantum spins. This technique for accurate spin control is an essential ingredient in many applications, such as nuclear magnetic resonance, magnetic resonance imaging, and quantum information processing. Here, we show how all the elements of a spin echo sequence can be performed at high speed by means of transitionless quantum driving. This technique promises accurate control of rapid quantum spin evolution. We apply the scheme to universal nonadiabatic geometric single- and two-qubit gates in a nuclear magnetic resonance setting.

We propose how to achieve strong phonon blockade (PB) in a hybrid spin-mechanical system in the weak-coupling regime. We demonstrate the implementation of magnetically induced two-phonon interactions between a mechanical cantilever resonator and an embedded nitrogen-vacancy center, which, when combined with parametric amplification of the mechanical motion, produces significantly enlarged anharmonicity in the eigenenergy spectrum. In the weak-driving regime, we show that strong PB appears in the hybrid system along with a large mean phonon number, even in the presence of strong mechanical dissipation. We also show flexible tunability of phonon statistics by controlling the strength of mechanical parametric amplification. Our work opens up prospects for the implementation of an efficient single-phonon source, with potential applications in quantum phononics and phononic quantum networks.

Autocorrelated noise appears in many solid-state qubit systems and hence needs to be taken into account when developing gate operations for quantum information processing. However, explicitly simulating this kind of noise is often less efficient than approximate methods. Here, we focus on the filter function formalism, which allows the computation of gate fidelities in the presence of autocorrelated classical noise. Hence, this formalism can be combined with optimal control algorithms to design control pulses, which optimally implement quantum gates. To enable the use of gradient-based algorithms with fast convergence, we present analytically derived filter function gradients with respect to control pulse amplitudes, and analyze the computational complexity of our results. When comparing pulse optimization using our derivatives to a gradient-free approach, we find that the gradient-based method is roughly 2 orders of magnitude faster for our test cases. We also provide a modular computational implementation compatible with quantum optimal control packages.

Noisy intermediate-scale quantum (NISQ) devices are nowadays starting to become available to the final user, hence potentially allowing the quantum speedups predicted by quantum-information theory to be shown. However, before implementing any quantum algorithm, it is crucial to have at least a partial or possibly full knowledge on the type and amount of noise affecting the quantum machine. Here, by generalizing quantum generative adversarial learning from quantum states (QGANs) to quantum operations, superoperators, and channels (here named super QGANs), we propose a very promising framework to characterize noise in a realistic quantum device, even in the case of spatially and temporally correlated noise (memory channels) affecting quantum circuits. The key idea is to learn about the noise by mimicking it in a way that one cannot distinguish between the real (to be sensed) and the fake (generated) one. We find that, when applied to the benchmarking case of Pauli channels, the super-QGAN protocol is able to learn the associated error rates even in the case of spatially and temporally correlated noise. Moreover, we also show how to employ it for quantum metrology applications. We believe our super QGANs pave the way for the development of hybrid quantum-classical machine-learning protocols for a better characterization and control of the current and future unavoidably noisy quantum devices.

The ability to engineer high-fidelity gates on quantum processors in the presence of systematic errors remains the primary barrier to achieving quantum advantage. Quantum optimal control methods have proven effective in experimentally realizing high-fidelity gates, but they require exquisite calibration to be performant. We apply robust trajectory optimization techniques to suppress gate errors arising from system parameter uncertainty. We propose a derivative-based approach that maintains computational efficiency by using forward-mode differentiation. Additionally, the effect of depolarization on a gate is typically modeled by integrating the Lindblad master equation, which is computationally expensive. We employ a computationally efficient model and utilize time-optimal control to achieve high-fidelity gates in the presence of depolarization. We apply these techniques to a fluxonium qubit and suppress simulated gate errors due to parameter uncertainty below ${10}^{-7}$ for static parameter deviations of the order of 1%.

A flux qubit can interact strongly when it is capacitively coupled to other circuit elements. This interaction can be separated into two parts, one acting on the qubit subspaces and one in which excited states mediate the interaction. The first term dominates the interaction between the flux qubit and an $LC$ resonator, leading to ultrastrong couplings of the form ${\sigma }^y(a+a^{†})$, which complement the inductive ${\sigma }^{x}i(a^{†}-a)$ coupling. However, when coupling two flux qubits capacitively, all terms need to be taken into account, leading to complex nonstoquastic ultrastrong interaction of types ${\sigma }_1^y{\sigma }_2^y$, ${\sigma }_1^z{\sigma }_2^z$, and ${\sigma }_1^x{\sigma }_2^x$. Our theory explains all these interactions, describing them in terms of general circuit properties—coupling capacitances, qubit gaps, inductive, Josephson and capacitive energies—that apply to a wide variety of circuits and flux qubit designs.

Demonstrating a quantum computational advantage will require high-fidelity control and readout of multiqubit systems. As system size increases, multiplexed qubit readout becomes a practical necessity to limit the growth of resource overhead. Many contemporary qubit-state discriminators presume single-qubit operating conditions or require considerable computational effort, limiting their potential extensibility. Here, we present multiqubit readout using neural networks as state discriminators. We compare our approach to contemporary methods employed on a quantum device with five superconducting qubits and frequency-multiplexed readout. We find that fully connected feedforward neural networks increase the qubit-state-assignment fidelity for our system. Relative to contemporary discriminators, the assignment error rate is reduced by up to 25% due to the compensation of system-dependent nonidealities such as readout crosstalk, which is reduced by up to one order of magnitude. Our work demonstrates a potentially extensible building block for high-fidelity readout relevant to both near-term devices and future fault-tolerant systems.

Absorption spectroscopy has long been hailed as an absolute necessity for detecting the properties of complex chemical and biological samples. While conventional spectroscopy using classical light is severely limited by shot noise and lacks robustness against experimental imperfections, quantum light offers an avenue to perform absorption spectroscopy with provable advantages in the technical operations and the measurement precision. Here, we present an experimental approach to implement entanglement-based absorption spectroscopy with the assistance of Hong-Ou-Mandel interference. Since the temporal interference fringe is determined by the spectrum pattern, a maximum-likelihood decision is sufficient for revealing the relevant quantum information about the absorptive properties of the test samples. These experimental results may significantly facilitate the use of quantum interferometric spectroscopy to practical applications, which may be particularly relevant for photon-sensitive biological and chemical samples.