We present a method for accurate determination of atomic transition matrix elements at the 10 −3 level. Measurements of the ac Stark (light) shift around "magic-zero" wavelengths, where the light shift vanishes, provide precise constraints on the matrix elements. We make the first measurement of the 5s-6p matrix elements in rubidium by measuring the light shift around the 421 nm and 423 nm zeros with a sequence of standing wave pulses. In conjunction with existing theoretical and experimental data, we find 0.3236(9) ea0 and 0.5230(8) ea0 for the 5s-6p 1/2 and 5s-6p 3/2 elements, respectively, an order of magnitude more accurate than the best theoretical values. This technique can provide needed, accurate matrix elements for many atoms, including those used in atomic clocks, tests of fundamental symmetries, and quantum information.

We demonstrate universal quantum control over chains of ions in a surface-electrode ion trap, including all the fundamental operations necessary to perform algorithms in a one-dimensional, nearest-neighbor quantum computing architecture. We realize both single-qubit operations and nearest-neighbor entangling gates with Raman laser beams, and we interleave the two gate types. We report average single-qubit gate fidelities as high as 0.970(1) for two-, three-, and four-ion chains, characterized with randomized benchmarking. We generate Bell states between the nearest-neighbor pairs of a three-ion chain, with fidelity up to 0.84(2). We combine one-and two-qubit gates to perform quantum process tomography of a CNOTgate in a two-ion chain, and we report an overall fidelity of 0.76(3). System overviewThe experimental system is shown schematically in figure 1(a). We trap chains of 171 Yb + ions 60 μm above the surface-electrode ion trap described in [19]. This trap features through-chip vias instead of wirebonds. The

We study the Quantum Approximate Optimization Algorithm (QAOA) in the context of the Max-Cut problem. Near-term (noisy) quantum devices are only able to (accurately) execute QAOA at low circuit depths while QAOA requires a relatively high circuit-depth in order to "see" the whole graph [FGG20]. We introduce a classical pre-processing step that initializes QAOA with a biased superposition of all possible cuts in the graph, referred to as a warm-start. In particular, our initialization informs QAOA by a solution to a low-rank semidefinite programming relaxation of the Max-Cut problem. Our experimental results show that this variant of QAOA, called QAOAwarm, is able to outperform standard QAOA on lower circuit depths with less training time (in the optimization stage for QAOA's variational parameters). We provide experimental evidence as well as theoretical intuition on performance of the proposed framework.

Using trapped ion quantum bits in a scalable microfabricated surface trap, we perform the Bernstein-Vazirani algorithm. Our architecture relies upon ion transport and can readily be expanded to larger systems. The algorithm is demonstrated using two-and three-ion chains. For three ions, an improvement is achieved compared to a classical system using the same number of oracle queries. For two ions and one query, we correctly determine an unknown bit string with probability 97.6(8)%. For three ions, we succeed with probability 80.9(3)%.

We study the Quantum Approximate Optimization Algorithm ( QAOA ) in the context of the Max-Cut problem. Noisy quantum devices are only able to accurately execute QAOA at low circuit depths, while classically-challenging problem instances may call for a relatively high circuit-depth. This is due to the need to build correlations between reachable pairs of vertices in potentially large graphs [16]. To enhance the solving power of low-depth QAOA, we introduce a classical pre-processing step that initializes QAOA with a biased superposition of possible cuts in the graph, referred to as a warm-start . In particular, we initialize QAOA with a solution to a low-rank semidefinite programming relaxation of the Max-Cut problem. Our experimental results show that this variant of QAOA , called QAOA-warm , is able to outperform standard QAOA on lower circuit depths in solution quality and training time. While this improvement is partly due to the classical warm-start, we find strong evidence of further improvement using QAOA circuit at small depth. We provide experimental evidence of improved performance as well as theoretical properties of the proposed framework.

The Robust Phase Estimation (RPE) protocol was designed to be an efficient and robust way to calibrate quantum operations. The robustness of RPE refers to its ability to estimate a single parameter, usually gate amplitude, even when other parameters are poorly calibrated or when the gate experiences significant errors. Here we demonstrate the robustness of RPE to errors that affect initialization, measurement, and gates. In each case, the error threshold at which RPE begins to fail matches quantitatively with theoretical bounds. We conclude that RPE is an effective and reliable tool for calibration of one-qubit rotations and that it is particularly useful for automated calibration routines and sensor tasks.

No abstract

No abstract