Graham J. Norris

Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets

  1. Nathan Lacroix,
  2. Christoph Hellings,
  3. Christian Kraglund Andersen,
  4. Agustin Di Paolo,
  5. Ants Remm,
  6. Stefania Lazar,
  7. Sebastian Krinner,
  8. Graham J. Norris,
  9. Mihai Gabureac,
  10. Alexandre Blais,
  11. Christopher Eichler,
  12. and Andreas Wallraff
Variational quantum algorithms are believed to be promising for solving computationally hard problems and are often comprised of repeated layers of quantum gates. An example thereof
is the quantum approximate optimization algorithm (QAOA), an approach to solve combinatorial optimization problems on noisy intermediate-scale quantum (NISQ) systems. Gaining computational power from QAOA critically relies on the mitigation of errors during the execution of the algorithm, which for coherence-limited operations is achievable by reducing the gate count. Here, we demonstrate an improvement of up to a factor of 3 in algorithmic performance as measured by the success probability, by implementing a continuous hardware-efficient gate set using superconducting quantum circuits. This gate set allows us to perform the phase separation step in QAOA with a single physical gate for each pair of qubits instead of decomposing it into two CZ-gates and single-qubit gates. With this reduced number of physical gates, which scales with the number of layers employed in the algorithm, we experimentally investigate the circuit-depth-dependent performance of QAOA applied to exact-cover problem instances mapped onto three and seven qubits, using up to a total of 399 operations and up to 9 layers. Our results demonstrate that the use of continuous gate sets may be a key component in extending the impact of near-term quantum computers.
arxiv pdf

Repeated Quantum Error Detection in a Surface Code

  1. Christian Kraglund Andersen,
  2. Ants Remm,
  3. Stefania Lazar,
  4. Sebastian Krinner,
  5. Nathan Lacroix,
  6. Graham J. Norris,
  7. Mihai Gabureac,
  8. Christopher Eichler,
  9. and Andreas Wallraff
The realization of quantum error correction is an essential ingredient for reaching the full potential of fault-tolerant universal quantum computation. Using a range of different schemes,
logical qubits can be redundantly encoded in a set of physical qubits. One such scalable approach is based on the surface code. Here we experimentally implement its smallest viable instance, capable of repeatedly detecting any single error using seven superconducting qubits, four data qubits and three ancilla qubits. Using high-fidelity ancilla-based stabilizer measurements we initialize the cardinal states of the encoded logical qubit with an average logical fidelity of 96.1%. We then repeatedly check for errors using the stabilizer readout and observe that the logical quantum state is preserved with a lifetime and coherence time longer than those of any of the constituent qubits when no errors are detected. Our demonstration of error detection with its resulting enhancement of the conditioned logical qubit coherence times in a 7-qubit surface code is an important step indicating a promising route towards the realization of quantum error correction in the surface code.
arxiv pdf