Qubits made from superconducting materials are a mature platform for quantum information science application such as quantum computing. However, materials-based losses are now a limitingfactor in reaching the coherence times needed for applications. In particular, knowledge of the atomistic structure and properties of the circuit materials is needed to identify, understand, and mitigate materials-based decoherence channels. In this work we characterize the atomic structure of the native oxide film formed on Nb resonators by comparing fluctuation electron microscopy experiments to density functional theory calculations, finding that an amorphous layer consistent with an Nb2O5 stoichiometry. Comparing X-ray absorption measurements at the Oxygen K edge with first-principles calculations, we find evidence of d-type magnetic impurities in our sample, known to cause impedance in proximal superconductors. This work identifies the structural and chemical composition of the oxide layer grown on Nb superconductors, and shows that soft X-ray absorption can fingerprint magnetic impurities in these superconducting systems.
We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identity bit-flip errors from continuous noisysyndrome measurements. The algorithm is designed to operate on measurement signals deviating from the ideal behavior in which the mean value corresponds to a code syndrome value and the measurement has white noise. We analyze continuous measurements taken from a superconducting architecture using three transmon qubits to identify three significant practical examples of non-ideal behavior, namely auto-correlation at temporal short lags, transient syndrome dynamics after each bit-flip, and drift in the steady-state syndrome values over the course of many experiments. Based on these real-world imperfections, we generate synthetic measurement signals from which to train the recurrent neural network, and then test its proficiency when implementing active error correction, comparing this with a traditional double threshold scheme and a discrete Bayesian classifier. The results show that our machine learning protocol is able to outperform the double threshold protocol across all tests, achieving a final state fidelity comparable to the discrete Bayesian classifier.
The development of noisy intermediate-scale quantum (NISQ) devices has extended the scope of executable quantum circuits with high-fidelity single- and two-qubit gates. Equipping NISQdevices with three-qubit gates will enable the realization of more complex quantum algorithms and efficient quantum error correction protocols with reduced circuit depth. Several three-qubit gates have been implemented for superconducting qubits, but their use in gate synthesis has been limited due to their low fidelity. Here, using fixed-frequency superconducting qubits, we demonstrate a high-fidelity iToffoli gate based on two-qubit interactions, the so-called cross-resonance effect. As with the Toffoli gate, this three-qubit gate can be used to perform universal quantum computation. The iToffoli gate is implemented by simultaneously applying microwave pulses to a linear chain of three qubits, revealing a process fidelity as high as 98.26(2)%. Moreover, we numerically show that our gate scheme can produce additional three-qubit gates which provide more efficient gate synthesis than the Toffoli and Toffoli gates. Our work not only brings a high-fidelity iToffoli gate to current superconducting quantum processors but also opens a pathway for developing multi-qubit gates based on two-qubit interactions.
The storage and processing of quantum information are susceptible to external noise, resulting in computational errors that are inherently continuous A powerful method to suppress theseeffects is to use quantum error correction. Typically, quantum error correction is executed in discrete rounds where errors are digitized and detected by projective multi-qubit parity measurements. These stabilizer measurements are traditionally realized with entangling gates and projective measurement on ancillary qubits to complete a round of error correction. However, their gate structure makes them vulnerable to errors occurring at specific times in the code and errors on the ancilla qubits. Here we use direct parity measurements to implement a continuous quantum bit-flip correction code in a resource-efficient manner, eliminating entangling gates, ancilla qubits, and their associated errors. The continuous measurements are monitored by an FPGA controller that actively corrects errors as they are detected. Using this method, we achieve an average bit-flip detection efficiency of up to 91%. Furthermore, we use the protocol to increase the relaxation time of the protected logical qubit by a factor of 2.7 over the relaxation times of the bare comprising qubits. Our results showcase resource-efficient stabilizer measurements in a multi-qubit architecture and demonstrate how continuous error correction codes can address challenges in realizing a fault-tolerant system.
and quantum information"]processors [arXiv:1109.3743]. As in conventional computing, key attributes of such memories are high storage density and, crucially, random access, or the ability to read from or write to an arbitrarily chosen register. However, achieving such random access with quantum memories [arXiv:1904.09643] in a dense, hardware-efficient manner remains a challenge, for example requiring dedicated cavities per qubit [arXiv:1109.3743] or pulsed field gradients [arXiv:0908.0101]. Here we introduce a protocol using chirped pulses to encode qubits within an ensemble of quantum two-level systems, offering both random access and naturally supporting dynamical decoupling to enhance the memory lifetime. We demonstrate the protocol in the microwave regime using donor spins in silicon coupled to a superconducting cavity, storing up to four multi-photon microwave pulses and retrieving them on-demand up to 2~ms later. A further advantage is the natural suppression of superradiant echo emission, which we show is critical when approaching unit cooperativity. This approach offers the potential for microwave random access quantum memories with lifetimes exceeding seconds [arXiv:1301.6567, arXiv:2005.09275], while the chirped pulse phase encoding could also be applied in the optical regime to enhance quantum repeaters and networks.
Crosstalk is a leading source of failure in multiqubit quantum information processors. It can arise from a wide range of disparate physical phenomena, and can introduce subtle correlationsin the errors experienced by a device. Several hardware characterization protocols are able to detect the presence of crosstalk, but few provide sufficient information to distinguish various crosstalk errors from one another. In this article we describe how gate set tomography, a protocol for detailed characterization of quantum operations, can be used to identify and characterize crosstalk errors in quantum information processors. We demonstrate our methods on a two-qubit trapped-ion processor and a two-qubit subsystem of a superconducting transmon processor.
As the number of qubits in nascent quantum processing units increases, the connectorized RF (radio frequency) analog circuits used in first generation experiments become exceedinglycomplex. The physical size, cost and electrical failure rate all become limiting factors in the extensibility of control systems. We have developed a series of compact RF mixing boards to adresss this challenge by integrating I/Q quadrature mixing, IF(intermediate frequency)/LO(local oscillator)/RF power level adjustments, and DC (direct current) bias fine tuning on a 40 mm × 80 mm 4-layer PCB (printed circuit board) board with EMI (electromagnetic interference) shielding. The RF mixing module is designed to work with RF and LO frequencies between 2.5 and 8.5 GHz. The typical image rejection and adjacent channel isolation are measured to be ∼27 dBc and ∼50 dB. By scanning the drive phase in a loopback test, the module short-term amplitude and phase stability are typically measured to be 5×10−4 (Vpp/Vmean) and 1×10−3 radian (pk-pk). The operation of RF mixing board was validated by integrating it into the room temperature control system of a superconducting quantum processor and executing randomized benchmarking characterization of single and two qubit gates. We measured a single-qubit process infidelity of 0.0020±0.0001 and a two-qubit process infidelity of 0.052±0.004.
As quantum information processors grow in quantum bit (qubit) count and functionality, the control and measurement system becomes a limiting factor to large scale extensibility. Totackle this challenge and keep pace with rapidly evolving classical control requirements, full control stack access is essential to system level optimization. We design a modular FPGA (field-programmable gate array) based system called QubiC to control and measure a superconducting quantum processing unit. The system includes room temperature electronics hardware, FPGA gateware, and engineering software. A prototype hardware module is assembled from several commercial off-the-shelf evaluation boards and in-house developed circuit boards. Gateware and software are designed to implement basic qubit control and measurement protocols. System functionality and performance are demonstrated by performing qubit chip characterization, gate optimization, and randomized benchmarking sequences on a superconducting quantum processor operating at the Advanced Quantum Testbed at Lawrence Berkeley National Laboratory. The single-qubit and two-qubit process fidelities are measured to be 0.9980±0.0001 and 0.948±0.004 by randomized benchmarking. With fast circuit sequence loading capability, the QubiC performs randomized compiling experiments efficiently and improves the feasibility of executing more complex algorithms.
Quantum sensing and computation can be realized with superconducting microwave circuits. Qubits are engineered quantum systems of capacitors and inductors with non-linear Josephsonjunctions. They operate in the single-excitation quantum regime, photons of 27μeV at 6.5 GHz. Quantum coherence is fundamentally limited by materials defects, in particular atomic-scale parasitic two-level systems (TLS) in amorphous dielectrics at circuit interfaces.[1] The electric fields driving oscillating charges in quantum circuits resonantly couple to TLS, producing phase noise and dissipation. We use coplanar niobium-on-silicon superconducting resonators to probe decoherence in quantum circuits. By selectively modifying interface dielectrics, we show that most TLS losses come from the silicon surface oxide, and most non-TLS losses are distributed throughout the niobium surface oxide. Through post-fabrication interface modification we reduced TLS losses by 85% and non-TLS losses by 72%, obtaining record single-photon resonator quality factors above 5 million and approaching a regime where non-TLS losses are dominant.
[1]Müller, C., Cole, J. H. & Lisenfeld, J. Towards understanding two-level-systems in amorphous solids: insights from quantum circuits. Rep. Prog. Phys. 82, 124501 (2019)
The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy intermediate-scalequantum (NISQ) computing, systematic miscalibrations, drift, and crosstalk in the control of qubits can lead to a coherent form of error which has no classical analog. Coherent errors severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable quantum computations. Moreover, the average error rates measured by randomized benchmarking and related protocols are not sensitive to the full impact of coherent errors, and therefore do not reliably predict the global performance of quantum algorithms, leaving us unprepared to validate the accuracy of future large-scale quantum computations. Randomized compiling is a protocol designed to overcome these performance limitations by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of algorithmic performance from error rates measured via cycle benchmarking. In this work, we demonstrate significant performance gains under randomized compiling for the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. Additionally, we accurately predict algorithm performance using experimentally-measured error rates. Our results demonstrate that randomized compiling can be utilized to maximally-leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing.