With superconducting transmon qubits — a promising platform for quantum information processing — two-qubit gates can be performed using AC signals to modulate a tunabletransmon’s frequency via magnetic flux through its SQUID loop. However, frequency tunablity introduces an additional dephasing mechanism from magnetic fluctuations. In this work, we experimentally study the contribution of instrumentation noise to flux instability and the resulting error rate of parametrically activated two-qubit gates. Specifically, we measure the qubit coherence time under flux modulation while injecting broadband noise through the flux control channel. We model the noise’s effect using a dephasing rate model that matches well to the measured rates, and use it to prescribe a noise floor required to achieve a desired two-qubit gate infidelity. Finally, we demonstrate that low-pass filtering the AC signal used to drive two-qubit gates between the first and second harmonic frequencies can reduce qubit sensitivity to flux noise at the AC sweet spot (ACSS), confirming an earlier theoretical prediction. The framework we present to determine instrumentation noise floors required for high entangling two-qubit gate fidelity should be extensible to other quantum information processing systems.
In state-of-the-art quantum computing platforms, including superconducting qubits and trapped ions, imperfections in the 2-qubit entangling gates are the dominant contributions of errorto system-wide performance. Recently, a novel 2-qubit parametric gate was proposed and demonstrated with superconducting transmon qubits. This gate is activated through RF modulation of the transmon frequency and can be operated at an amplitude where the performance is first-order insensitive to flux-noise. In this work we experimentally validate the existence of this AC sweet spot and demonstrate its dependence on white noise power from room temperature electronics. With these factors in place, we measure coherence-limited entangling-gate fidelities as high as 99.2 ± 0.15%.
The ubiquitous presence of 1/f flux noise was a significant barrier to long-coherence in superconducting qubits until the development of qubits that could operate in static, flux noiseinsensitive configurations commonly referred to as `sweet-spots‘. Several proposals for entangling gates in superconducting qubits tune the flux bias away from these spots, thus reintroducing the dephasing problem to varying degrees. Here we revisit one such proposal, where interactions are parametrically activated by rapidly modulating the flux bias of the qubits around these sweet-spots, and study the effect of modulation on the sensitivity to flux noise. We explicitly calculate how dephasing rates depend on different components of the flux-noise spectrum, and show that, while these parametric gates are insensitive to 1/f flux noise, dephasing rates are increased under modulation, and dominated by white noise. Remarkably, we find that simple filtering of the flux control signal allows for entangling gates to operate in a novel sweet-spot for dephasing under flux modulation. This sweet spot, which we dub the AC sweet spot, is insensitive to 1/f flux noise, and much less sensitive to white noise in the control electronics, allowing for interactions of quality that is limited only by higher order effects and other sources of noise.
The realization of quantum computing’s promise despite noisy imperfect qubits relies, at its core, on the ability to scale cheaply through error correction and fault-tolerance.While fault-tolerance requires relatively mild assumptions about the nature of the errors, the overhead associated with coherent and non-Markovian errors can be orders of magnitude larger than the overhead associated with purely stochastic Markovian errors. One proposal, known as Pauli frame randomization, addresses this challenge by randomizing the circuits so that the errors are rendered incoherent, while the computation remains unaffected. Similarly, randomization can suppress couplings to slow degrees of freedom associated with non-Markovian evolution. Here we demonstrate the implementation of circuit randomization in a superconducting circuit system, exploiting a flexible programming and control infrastructure to achieve this with low effort. We use high-accuracy gate-set tomography to demonstrate that without randomization the natural errors experienced by our experiment have coherent character, and that with randomization these errors are rendered incoherent. We also demonstrate that randomization suppresses signatures of non-Markovianity evolution to statistically insignificant levels. This demonstrates how noise models can be shaped into more benign forms for improved performance.
Scaling up quantum machines requires developing appropriate models to understand and verify their complex quantum dynamics. We focus on superconducting quantum processors based on transmonsfor which full numerical simulations are already challenging at the level of qubytes. It is thus highly desirable to develop accurate methods of modeling qubit networks that do not rely solely on numerical computations. Using systematic perturbation theory to large orders in the transmon regime, we derive precise analytic expressions of the transmon parameters. We apply our results to the case of parametrically-modulated transmons to study recently-implemented parametrically-activated entangling gates.
The main promise of quantum computing is to efficiently solve certain problems that are prohibitively expensive for a classical computer. Most problems with a proven quantum advantageinvolve the repeated use of a black box, or oracle, whose structure encodes the solution. One measure of the algorithmic performance is the query complexity, i.e., the scaling of the number of oracle calls needed to find the solution with a given probability. Few-qubit demonstrations of quantum algorithms, such as Deutsch-Jozsa and Grover, have been implemented across diverse physical systems such as nuclear magnetic resonance, trapped ions, optical systems, and superconducting circuits. However, at the small scale, these problems can already be solved classically with a few oracle queries, and the attainable quantum advantage is modest. Here we solve an oracle-based problem, known as learning parity with noise, using a five-qubit superconducting processor. Running classical and quantum algorithms on the same oracle, we observe a large gap in query count in favor of quantum processing. We find that this gap grows by orders of magnitude as a function of the error rates and the problem size. This result demonstrates that, while complex fault-tolerant architectures will be required for universal quantum computing, a quantum advantage already emerges in existing noisy systems
Typical quantum gate tomography protocols struggle with a self-consistency problem: the gate operation cannot be reconstructed without knowledge of the initial state and final measurement,but such knowledge cannot be obtained without well-characterized gates. A recently proposed technique, known as randomized benchmarking tomography (RBT), sidesteps this self-consistency problem by designing experiments to be insensitive to preparation and measurement imperfections. We implement this proposal in a superconducting qubit system, using a number of experimental improvements including implementing each of the elements of the Clifford group in single `atomic‘ pulses and custom control hardware to enable large overhead protocols. We show a robust reconstruction of several single-qubit quantum gates, including a unitary outside the Clifford group. We demonstrate that RBT yields physical gate reconstructions that are consistent with fidelities obtained by randomized benchmarking.
We present methods and results of shot-by-shot correlation of noisy measurements to extract entangled state and process tomography in a superconducting qubit architecture. We show thataveraging continuous values, rather than counting discrete thresholded values, is a valid tomographic strategy and is in fact the better choice in the low signal-to-noise regime. We show that the effort to measure N-body correlations from individual measurements scales exponentially with N, but with sufficient signal-to-noise the approach remains viable for few-body correlations. We provide a new protocol to optimally account for the transient behavior of pulsed measurements. Despite single-shot measurement fidelity that is less than perfect, we demonstrate appropriate processing to extract and verify entangled states and processes.
Sideband transitions have been shown to generate controllable interaction
between superconducting qubits and microwave resonators. Up to now, these
transitions have been implementedwith voltage drives on the qubit or the
resonator, with the significant disadvantage that such implementations only
lead to second-order sideband transitions. Here we propose an approach to
achieve first-order sideband transitions by relying on controlled oscillations
of the qubit frequency using a flux-bias line. Not only can first-order
transitions be significantly faster, but the same technique can be employed to
implement other tunable qubit-resonator and qubit-qubit interactions. We
discuss in detail how such first-order sideband transitions can be used to
implement a high fidelity controlled-NOT operation between two transmons
coupled to the same resonator.