Generating and distributing encryption keys via chaos synchronization of optical systems is a promising method for achieving secure and fast real-time encryption of large data volumes. However, current state-of-the-art systems based on lasers subjected to time-delayed feedback have exhibited serious limitations in regard to stability and speed due to their inherent phase sensitivity and their fundamental bandwidth limitation by the laser relaxation oscillation frequency. Here, we propose, simulate, and build a fundamentally different concept based on optoelectronic oscillators (OEOs) to generate and distribute encryption keys. We demonstrate both theoretically and experimentally that by injecting chaotic OEOs with a common external chaotic signal, chaos synchronization can be achieved. The key distribution signal shared between sender and receiver is in the optical domain and can thus be transmitted over a standard fiber-optic network. As the optoelectronic feedback is phase insensitive, stable synchronization becomes possible without any need for active stabilization, resulting in a compact and inexpensive setup. From the chaotic time traces, identical random bit sequences can be generated on the sender’s and receiver’s sides at rates of up to 6 GBit/s, which is comparable to current state-of-the-art systems of the same bandwidth. Since OEOs are not bandwidth limited by relaxation oscillations, the key generation can be further increased compared to laser-based systems by increasing the OEO bandwidth, thus presenting a promising platform for achieving fast and secure real-time encryption.

Teleportation is a fundamental concept of quantum mechanics with an important application in extending the range of quantum communication channels via quantum relay nodes. To be compatible with real-world technology such as secure quantum key distribution over fiber networks, such a relay node should ideally operate at gigahertz clock rates and accept time-bin-encoded qubits in the low-loss telecom band around 1550 nm. Here, we show that $\mathrm{In}\mathrm{As}$-$\mathrm{In}\mathrm{P}$ droplet-epitaxy quantum dots, with their sub-Poissonian emission near 1550 nm, are ideally suited for the realization of this technology. To create the necessary on-demand photon emission at gigahertz clock rates, we develop a flexible-pulsed optical-excitation scheme and demonstrate that the fast driving conditions are compatible with a low multiphoton emission rate. We show further that, even under these driving conditions, photon pairs obtained from the biexciton cascade show an entanglement fidelity close to 90%, comparable to the value obtained under continuous-wave excitation. Using asymmetric Mach-Zehnder interferometers and our photon source, we finally construct a time-bin qubit quantum relay able to receive and send time-bin-encoded photons and demonstrate mean teleportation fidelities of $0.82\pm 0.01$, exceeding the classical limit by more than ten standard deviations.

Experimentally quantifying entanglement and coherence are extremely important for quantum resource theory. However, because the quantum state tomography requires exponentially growing measurements with the number of qubits, it is hard to quantify entanglement and coherence based on the full information of the experimentally realized multipartite states. Fortunately, other methods have been found to directly measure the fidelity of experimental states without quantum state tomography. Here we present a fidelity-based method to derive experimentally accessible lower bounds for measures of genuine multipartite entanglement and coherence. On the one hand, the method works for genuine multipartite entanglement measures including the convex-roof extended negativity, the concurrence, the G-concurrence, and the geometric measure for genuine multipartite entanglement. On the other hand, the method also delivers observable lower bounds for the convex roof of the $l_1$-norm of coherence, the geometric measure of coherence, and the coherence of formation. Furthermore, all the lower bounds are based on the fidelity between the chosen pure state and the target state, and we obtain the lower bounds of several real experimental states as examples of our results.

While quantum dots are at the forefront of quantum-device technology, the tuning of multidot systems requires a lengthy experimental process as multiple parameters need to be accurately controlled. This process becomes increasingly time-consuming and difficult to perform manually as the devices become more complex and the number of tuning parameters grows. In this work, we present a crucial step toward automated tuning of quantum-dot qubits. We introduce an algorithm driven by machine learning that uses a small number of coarse-grained measurements as its input and tunes the quantum-dot system into a preselected charge state. We train and test our algorithm on a $\mathrm{Ga}\mathrm{As}$ double-quantum-dot device and we consistently arrive at the desired state or its immediate neighborhood.

Defining quantum dots in semiconductor-based heterostructures is an essential step in initializing solid-state qubits. With growing device complexity and increasing number of functional devices required for measurements, a manual approach to finding suitable gate voltages to confine electrons electrostatically is impractical. Here, we implement a two-stage device characterization and dot-tuning process, which first determines whether devices are functional and then attempts to tune the functional devices to the single or double quantum-dot regime. We show that automating well-established manual-tuning procedures and replacing the experimenter’s decisions by supervised machine learning is sufficient to tune double quantum dots in multiple devices without premeasured input or manual intervention. The quality of measurement results and charge states are assessed by four binary classifiers trained with experimental data, reflecting real device behavior. We compare and optimize eight models and different data preprocessing techniques for each of the classifiers to achieve reliable autonomous tuning, an essential step towards scalable quantum systems in quantum-dot-based qubit architectures.

The construction of a photon-photon quantum phase gate based on photonic nonlinearity has long been a fundamental issue, and is vital for deterministic and scalable photonic quantum-information processing. It requires not only strong nonlinear interaction at the single-photon level but also suppressed phase noise and spectral entanglement for high gate fidelity. In this paper, we propose that a high-quality-factor microcavity with strong ${\chi }^{(2)}$ nonlinearity can be quantized to anharmonic energy levels and can be effectively treated as an artificial atom. Such an artificial atom has a size much larger than the photon wavelength, which enables passive and active ultrastrong coupling to traveling photons. A high-fidelity quantum control phase gate is realized by our mediating the phase between photons with an intermediate artificial atom in a photonic molecule structure. The scheme avoids two-photon emission and thus eliminates spectral entanglement and quantum phase noise. Experimental realization of the artificial atom can be envisioned on an integrated photonic chip and holds great potential for single-emitter-free, room-temperature quantum-information processing.

The current practice of manually tuning quantum dots (QDs) for qubit operation is a relatively time-consuming procedure that is inherently impractical for scaling up and applications. In this work, we report on the in situ implementation of a recently proposed autotuning protocol that combines machine learning (ML) with an optimization routine to navigate the parameter space. In particular, we show that a ML algorithm trained using exclusively simulated data to quantitatively classify the state of a double-QD device can be used to replace human heuristics in the tuning of gate voltages in real devices. We demonstrate active feedback of a functional double-dot device operated at millikelvin temperatures and discuss success rates as a function of the initial conditions and the device performance. Modifications to the training network, fitness function, and optimizer are discussed as a path toward further improvement in the success rate when starting both near and far detuned from the target double-dot range.

Hamiltonian-based quantum computation is a class of quantum algorithms in which the problem is encoded in a Hamiltonian and the evolution is performed by a continuous transformation of the Hamiltonian. Universal adiabatic quantum computing, quantum simulation, and quantum annealing are examples of such algorithms. Up to now, all implementations of this approach have been limited to qubits coupled via a single degree of freedom. This gives rise to a stoquastic Hamiltonian that has no sign problem in quantum Monte Carlo simulations. In this paper, we report implementation and measurements of two superconducting flux qubits coupled via two canonically conjugate degrees of freedom—charge and flux—to achieve a nonstoquastic Hamiltonian. We perform microwave spectroscopy to extract circuit parameters and show that the charge coupling manifests itself as a ${\sigma }^y{\sigma }^y$ interaction in the computational basis. We observe destructive interference in quantum coherent oscillations between the computational-basis states of the two-qubit system. Finally, we show that the extracted Hamiltonian is nonstoquastic over a wide range of parameters.

Quantum communication schemes such as quantum key distribution (QKD) and superdense teleportation provide unique opportunities to communicate information securely. Increasingly, optical communication is being extended to free-space channels, but atmospheric turbulence in free-space channels requires optical receivers and measurement infrastructure to support many spatial modes. Here, we present a multimode Michelson-type time-delay interferometer using a field-widened design for the measurement of phase-encoded states in free-space communication schemes. The interferometer is constructed using glass beam paths to provide thermal stability, a field-widened angular tolerance, and a compact footprint. The performance of the interferometer is highlighted by measured visibilities of $99.02\pm 0.05\mathrm{\%}$ and $98.38\pm 0.01\mathrm{\%}$ for single- and multimode inputs, respectively. Additionally, high-quality multimode interference is demonstrated for arbitrary spatial-mode structures and for temperature changes of $\pm 1.0{}^{\circ }\mathrm{C}$. The interferometer has a measured optical-path-length drift of $130\mathrm{nm}/{}^{\circ }\mathrm{C}$ near room temperature. With this setup, we demonstrate the measurement of a two-peaked multimode single-photon state used in time-phase QKD with a visibility of $97.37\pm 0.01\mathrm{\%}$.

Entangling operations are among the most important primitive gates employed in quantum computing, and it is crucial to ensure high-fidelity implementations as systems are scaled up. We experimentally realize and characterize a simple scheme to minimize errors in entangling operations related to the residual excitation of mediating bosonic oscillator modes that both improves gate robustness and provides scaling benefits in larger systems. The technique employs discrete phase shifts in the control field driving the gate operation, determined either analytically or numerically, to ensure all modes are de-excited at arbitrary user-defined times. We demonstrate an average gate fidelity of 99.4(2)% across a wide range of parameters in a system of ${{}^{171}\mathrm{Yb}}^{+}$ trapped ion qubits, and observe a reduction of gate error in the presence of common experimental error sources. Our approach provides a unified framework to achieve robustness against both static and time-varying laser amplitude and frequency detuning errors. We verify these capabilities through system-identification experiments revealing improvements in error susceptibility achieved in phase-modulated gates.

A common impediment to qubit performance is imperfect state initialization. In the case of the diamond nitrogen-vacancy (N-$V$) center, the initialization fidelity is limited by fluctuations in the defect’s charge state during optical pumping. Here we use real-time control to deterministically initialize the N-$V$ center’s charge state at room temperature. We demonstrate a maximum charge initialization fidelity of $(99.4\pm 0.1)\mathrm{\%}$ and present a quantitative model of the initialization process that allows system-level optimization of the spin-readout signal-to-noise ratio. Even when the overhead associated with the initialization sequence is accounted for, increasing the charge initialization fidelity from the steady-state value of 75% to nearly 100% allows a factor-of-2 speedup in experiments while maintaining the same signal-to-noise-ratio. In combination with high-fidelity readout based on spin-to-charge conversion, real-time initialization enables a factor-of-20 speedup over traditional methods, resulting in an estimated ac magnetic sensitivity of $1.3\mathrm{nT}/{\mathrm{Hz}}^{1/2}$ for our single-N-$V$-center spin. The real-time control method is immediately beneficial for quantum-sensing applications with N-$V$ centers as well as for probing charge-dependent physics, and it will facilitate protocols for quantum feedback control over multiqubit systems.

Computational reversibility is necessary for quantum computation and inspires the development of computing systems, in which information carriers are conserved as they flow through a circuit. While conservative logic provides an exciting vision for reversible computing with no energy dissipation, the large dimensions of information carriers in previous realizations detract from the system efficiency, and nanoscale conservative logic remains elusive. We therefore propose a nonvolatile reversible computing system in which the information carriers are magnetic skyrmions, topologically-stable magnetic whirls. These nanoscale quasiparticles interact with one another via the spin Hall and skyrmion Hall effects as they propagate through ferromagnetic nanowires structured to form cascaded conservative logic gates. These logic gates can be directly cascaded in large-scale systems that perform complex logic functions, with signal integrity provided by clocked synchronization structures. The feasibility of the proposed system is demonstrated through micromagnetic simulations of Boolean logic gates, a Fredkin gate, and a cascaded full adder. As skyrmions can be transported in a pipelined and nonvolatile manner at room temperature without the motion of any physical particles, this skyrmion logic system has the potential to deliver scalable high-speed low-power reversible Boolean and quantum computing.

We present measurements of the capacitive coupling energy and the interdot capacitances in a linear quadruple-quantum-dot array in undoped $\mathrm{Si}$/$\mathrm{Si}\mathrm{Ge}$. With the device tuned to a regime of strong ($>1\mathrm{GHz}$) intra-double-dot tunnel coupling, as is typical for double-dot qubits, we measure a capacitive coupling energy of $20.9\pm 0.3\mathrm{GHz}$. In this regime, we demonstrate a fitting procedure to extract all the parameters in the four-dimensional Hamiltonian for two capacitively coupled charge qubits from a two-dimensional slice through the quadruple-dot charge-stability diagram. We also investigate the tunability of the capacitive coupling energy, using interdot barrier gate voltages to tune the inter- and intra-double-dot capacitances, and change the capacitive coupling energy of the double dots over a range of 15–32 GHz. We provide a model for the capacitive coupling energy based on the electrostatics of a network of charge nodes joined by capacitors, which shows how the coupling energy should depend on inter-double-dot and intra-double-dot capacitances in the network, and find that the expected trends agree well with the measurements of coupling energy.

Parasitic crosstalk in superconducting quantum devices is a leading limitation for quantum gates. We demonstrate the suppression of static ZZ crosstalk in a two-qubit, two-coupler superconducting circuit, where the frequency of a tunable coupler can be adjusted such that the ZZ interactions from each coupler destructively interfere. We verify the crosstalk elimination with simultaneous randomized benchmarking, and use a parametrically activated iswap interaction to achieve a Bell-state preparation fidelity of 98.5% and a $\sqrt{\mathrm{i}\mathrm{swap}}$-gate fidelity of 94.8% obtained via quantum-process tomography.

A transducer capable of converting quantum information stored as microwaves into telecom-wavelength signals is a critical piece of future quantum technology as it promises to enable the networking of quantum processors. Cavity optomechanical devices that are simultaneously coupled to microwave fields and optical resonances are being pursued in this regard. Yet even in the classical regime, developing optical modulators based on cavity optomechanics could provide alternatives to current technology. Here we demonstrate a magnetically mediated wavelength-conversion technique based on mixing high-frequency tones with an optomechanical torsional resonator. This process can act either as an optical phase modulator or an amplitude modulator depending on the experimental configuration, and the carrier modulation is always coherent with the input tone. Such coherence allows classical information transduction and transmission via the technique of phase-shift keying. We demonstrate that we can encode up to eight bins of information, corresponding to three bits, simultaneously and demonstrate the transmission of a 52 500-pixel image over 6 km of optical fiber with just 0.67% error. Furthermore, we show that magneto-optomechanical transduction can be described in a fully quantum manner, implying that this is a possible approach to signal transduction in the quantum regime.

The Hodgkin-Huxley model describes the behavior of the cell membrane in neurons, treating each part of it as an electric circuit element; namely, capacitors, memristors, and voltage sources. We focus on the activation channel of potassium ions, due to its simplicity, while keeping most of the features displayed by the original model. This reduced version is essentially a classical memristor, a resistor whose resistance depends on the history of electric signals that have crossed it, coupled to a voltage source and a capacitor. We consider a quantized Hodgkin-Huxley model based on a quantum-memristor formalism. We compare the behavior of the membrane voltage and the potassium-channel conductance when the circuit is subjected to ac sources, in both the classical realm and the quantum realm. Numerical simulations show an expected adaptation of the considered channel conductance depending on the signal history in all regimes. Remarkably, the computation of higher moments of the voltage shows purely quantum features related to the circuit zero-point energy. Finally, we study the implementation of the Hodgkin-Huxley quantum memristor as an asymmetric rf superconducting quantum-interference device in superconducting circuits. This study may allow the construction of quantum neuron networks inspired by the brain function, as well as the design of neuromorphic quantum architectures for quantum machine learning.

There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum-annealing machines, has the potential to outperform current classical optimization algorithms implemented on CMOS technologies. The benchmarking of these devices has been controversial. Initially, random spin-glass problems were used, however, these were quickly shown to be not well suited to detect any quantum speedup. Subsequently, benchmarking shifted to carefully crafted synthetic problems designed to highlight the quantum nature of the hardware while (often) ensuring that classical optimization techniques do not perform well on them. Even worse, to date a true sign of improved scaling with the number of problem variables remains elusive when compared to classical optimization techniques. Here, we analyze the readiness of quantum-annealing machines for real-world application problems. These are typically not random and have an underlying structure that is hard to capture in synthetic benchmarks, thus posing unexpected challenges for optimization techniques, both classical and quantum alike. We present a comprehensive computational scaling analysis of fault diagnosis in digital circuits, considering architectures beyond D-Wave quantum annealers. We find that the instances generated from real data in multiplier circuits are harder than other representative random spin-glass benchmarks with a comparable number of variables. Although our results show that transverse-field quantum annealing is outperformed by state-of-the-art classical optimization algorithms, these benchmark instances are hard and small in the size of the input, therefore representing the first industrial application ideally suited for testing near-term quantum annealers and other quantum algorithmic strategies for optimization problems.

Silicon spin qubits are a promising quantum-computing platform offering long coherence times, small device sizes, and compatibility with industry-backed device-fabrication techniques. In recent years, high-fidelity single-qubit and two-qubit operations have been demonstrated in $\mathrm{Si}$. Here we demonstrate coherent spin control in a quadruple quantum dot fabricated from isotopically enriched ${}^{28}\mathrm{Si}$. We tune the ground-state charge configuration of the quadruple dot down to the single-electron regime and demonstrate tunable interdot tunnel couplings as large as 20 GHz, which enables exchange-based two-qubit gate operations. Site-selective single spin rotations are achieved with the use of electric dipole spin resonance in a magnetic field gradient. We execute a resonant controlled-not gate between two adjacent spins in 270 ns.

A key requirement to perform simulations of large quantum systems on near-term quantum hardware is the design of quantum algorithms with a short circuit depth that finish within the available coherence time. A way to stay within the limits of coherence is to reduce the number of gates by implementing a gate set that matches the requirements of the specific algorithm of interest directly in the hardware. Here, we show that exchange-type gates are a promising choice for simulating molecular eigenstates on near-term quantum devices since these gates preserve the number of excitations in the system. We report on the experimental implementation of a variational algorithm on a superconducting qubit platform to compute the eigenstate energies of molecular hydrogen. We utilize a parametrically driven tunable coupler to realize exchange-type gates that are configurable in amplitude and phase on two fixed-frequency superconducting qubits. With gate fidelities around 95%, we are able to compute the eigenstates to within an accuracy of 50 mHa (milliHartree) on average, a limit set by the coherence time of the tunable coupler.

Dispersive sensing is a powerful technique that enables scalable and high-fidelity readout of solid-state quantum bits. In particular, gate-based dispersive sensing has been proposed as the readout mechanism for future topological qubits, which can be measured by single electrons tunneling through zero-energy modes. The development of such a readout requires resolving the coherent charge tunneling amplitude from a quantum dot in a Majorana-zero-mode host system faithfully on short time scales. Here, we demonstrate rapid single-shot detection of a coherent single-electron tunneling amplitude between $\mathrm{In}\mathrm{As}$ nanowire quantum dots. We realize a sensitive dispersive detection circuit by connecting a sub-GHz, lumped-element microwave resonator to a high-lever arm gate on one of the dots. The resulting large dot-resonator coupling leads to an observed dispersive shift that is of the order of the resonator linewidth at charge degeneracy. This shift enables us to differentiate between Coulomb blockade and resonance—corresponding to the scenarios expected for qubit-state readout—with a signal-to-noise ratio exceeding 2 for an integration time of $1\mu \mathrm{s}$. Our result paves the way for single-shot measurements of fermion parity on microsecond time scales in topological qubits.