Insights from the Quantum Era - April 2023

Here are some scientific papers that caught our eye this month:

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Quantum Enhanced Greedy Solver for Optimization Problems

Scientists from Rigetti, NASA Ames, and USRA have developed a quantum-enhanced greedy solver for combinatorial optimization problems, a field that remains of high promise for quantum advantage. The team’s iterative quantum heuristic optimization algorithm's worst-case average performance - in the presence of depolarizing quantum noise - is on par with a classical greedy algorithm. In general, the quantum-classical algorithm outperformed its classical counterpart, demonstrating quantum enhancement in output quality, although better-quality quantum hardware remains a necessity to achieve quantum advantage!

Read on ArXiv

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Fermionic quantum processing with programmable neutral atom arrays

Quantum chemistry is expected to be one of the main applications of quantum computing; yet, deploying quantum algorithms for fermions on qubits requires a large qubit and gate encoding cost. In this work, the authors explore what an architecture for tweezer-trapped fermionic register could look like, how gates and operations should be deployed, and what potential advantages could come about. This is quite a visionary work, with a detailed analysis of the experimental hurdles that need to be overcome for the creation of a very relevant type of quantum computing architecture.

Read on ArXiv

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Mid-circuit measurements on a neutral atom quantum processor

Mid-circuit readout: no quantum error correction scheme can be done without it and it remains a topic of active research and development for neutral-atom architectures. Here, the authors demonstrate an approach to mid-circuit readout in neutral-atom computers based on shelving data in protected hyperfine-Zeeman sub-states, tied to a non-destructive measurement of an ancilla qubit. The measurement scheme performance achieves fidelities of ~95%.

Read on ArXiv

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