Just Another Quantum Assembly Language (Jaqal(TM))
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Physical Review Letters
We demonstrate an experimental implementation of robust phase estimation (RPE) to learn the phase of a single-qubit rotation on a trapped Yb+ ion qubit. We show this phase can be estimated with an uncertainty below 4×10-4 rad using as few as 176 total experimental samples, and our estimates exhibit Heisenberg scaling. Unlike standard phase estimation protocols, RPE neither assumes perfect state preparation and measurement, nor requires access to ancillae. We crossvalidate the results of RPE with the more resource-intensive protocol of gate set tomography.
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Nature Communications
Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone, they will depend on fault-tolerant quantum error correction (FTQEC) to compute reliably. Quantum error correction can protect against general noise if - and only if - the error in each physical qubit operation is smaller than a certain threshold. The threshold for general errors is quantified by their diamond norm. Until now, qubits have been assessed primarily by randomized benchmarking, which reports a different error rate that is not sensitive to all errors, and cannot be compared directly to diamond norm thresholds. Here we use gate set tomography to completely characterize operations on a trapped-Yb+-ion qubit and demonstrate with greater than 95% confidence that they satisfy a rigorous threshold for FTQEC (diamond norm ≤6.7 × 10-4).
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In recent years, advanced network analytics have become increasingly important to na- tional security with applications ranging from cyber security to detection and disruption of ter- rorist networks. While classical computing solutions have received considerable investment, the development of quantum algorithms to address problems, such as data mining of attributed relational graphs, is a largely unexplored space. Recent theoretical work has shown that quan- tum algorithms for graph analysis can be more efficient than their classical counterparts. Here, we have implemented a trapped-ion-based two-qubit quantum information proces- sor to address these goals. Building on Sandia's microfabricated silicon surface ion traps, we have designed, realized and characterized a quantum information processor using the hyperfine qubits encoded in two 171 Yb + ions. We have implemented single qubit gates using resonant microwave radiation and have employed Gate set tomography (GST) to characterize the quan- tum process. For the first time, we were able to prove that the quantum process surpasses the fault tolerance thresholds of some quantum codes by demonstrating a diamond norm distance of less than 1 . 9 x 10 [?] 4 . We used Raman transitions in order to manipulate the trapped ions' motion and realize two-qubit gates. We characterized the implemented motion sensitive and insensitive single qubit processes and achieved a maximal process infidelity of 6 . 5 x 10 [?] 5 . We implemented the two-qubit gate proposed by Molmer and Sorensen and achieved a fidelity of more than 97 . 7%.
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Quantum tomography is used to characterize quantum operations implemented in quantum information processing (QIP) hardware. Traditionally, state tomography has been used to characterize the quantum state prepared in an initialization procedure, while quantum process tomography is used to characterize dynamical operations on a QIP system. As such, tomography is critical to the development of QIP hardware (since it is necessary both for debugging and validating as-built devices, and its results are used to influence the next generation of devices). But tomography suffers from several critical drawbacks. In this report, we present new research that resolves several of these flaws. We describe a new form of tomography called gate set tomography (GST), which unifies state and process tomography, avoids prior methods critical reliance on precalibrated operations that are not generally available, and can achieve unprecedented accuracies. We report on theory and experimental development of adaptive tomography protocols that achieve far higher fidelity in state reconstruction than non-adaptive methods. Finally, we present a new theoretical and experimental analysis of process tomography on multispin systems, and demonstrate how to more effectively detect and characterize quantum noise using carefully tailored ensembles of input states.
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Nature Physics
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