Lev S. Bishop

We consider the problem of mapping a logical quantum circuit onto a given hardware with limited 2-qubit connectivity. We model this problem as an integer linear program, using a network flow formulation with binary variables that includes the initial allocation of qubits and their routing. We consider several cost functions: an approximation of the fidelity of the circuit, its total depth, and a measure of cross-talk, all of which can be incorporated in the model. Numerical experiments on synthetic data and different hardware topologies indicate that the error rate and depth can be optimized simultaneously without significant loss. We test our algorithm on a large number of quantum volume circuits, optimizing for error rate and depth; our algorithm significantly reduces the number of CNOTs compared to Qiskit’s default transpiler SABRE [ 19 ] and produces circuits that, when executed on hardware, exhibit higher fidelity.

Quantum assembly languages are machine-independent languages that traditionally describe quantum computation in the circuit model. Open quantum assembly language (OpenQASM 2) was proposed as an imperative programming language for quantum circuits based on earlier QASM dialects. In principle, any quantum computation could be described using OpenQASM 2, but there is a need to describe a broader set of circuits beyond the language of qubits and gates. By examining interactive use cases, we recognize two different timescales of quantum-classical interactions: real-time classical computations that must be performed within the coherence times of the qubits, and near-time computations with less stringent timing. Since the near-time domain is adequately described by existing programming frameworks, we choose in OpenQASM 3 to focus on the real-time domain, which must be more tightly coupled to the execution of quantum operations. We add support for arbitrary control flow as well as calling external classical functions. In addition, we recognize the need to describe circuits at multiple levels of specificity, and therefore we extend the language to include timing, pulse control, and gate modifiers. These new language features create a multi-level intermediate representation for circuit development and optimization, as well as control sequence implementation for calibration, characterization, and error mitigation.

Using a circuit QED device, we demonstrate a simple qubit-measurement pulse shape that yields fast ring-up and ring-down of the readout resonator regardless of the qubit state. The pulse differs from a square pulse only by the inclusion of additional constant-amplitude segments designed to effect a rapid transition from one steady-state population to another. Using a Ramsey experiment performed shortly after the measurement pulse to quantify the residual population, we find that compared to a square pulse followed by a delay, this pulse shape reduces the time scale for cavity ring-down by more than twice the cavity time constant. At low drive powers, this performance is achieved using pulse parameters calculated from a linear cavity model; at higher powers, empirical optimization of the pulse parameters leads to similar performance.

We report on the spectrum of a superconducting transmon device coupled to a planar superconducting resonator in the strong dispersive limit where discrete peaks, each corresponding to a different number of photons, are resolved. A thermal population of 5.474 GHz photons at an effective resonator temperature of T = 120 mK results in a weak n = 1 photon peak along with the n = 0 photon peak in the qubit spectrum in the absence of a coherent drive on the resonator. Two-tone spectroscopy using independent coupler and probe tones reveals an Autler–Townes splitting in the thermal n = 1 photon peak. The observed effect is explained accurately using the four lowest levels of the dispersively dressed qubit–resonator system and compared to results from numerical simulations of the steady-state master equation for the coupled system.