Ivano Tavernelli

Gate-efficient simulation of molecular eigenstates on a quantum computer

  1. Marc Ganzhorn,
  2. Daniel J. Egger,
  3. Panagiotis Kl. Barkoutsos,
  4. Pauline Ollitrault,
  5. Gian Salis,
  6. Nikolaj Moll,
  7. Andreas Fuhrer,
  8. Peter Müller,
  9. Stefan Woerner,
  10. Ivano Tavernelli,
  11. and Stefan Filipp
A key requirement to perform simulations of large quantum systems on near-term quantum hardware is the design of quantum algorithms with short circuit depth that finish within the available
coherence time. A way to stay within the limits of coherence is to reduce the number of gates by implementing a gate set that matches the requirements of the specific algorithm of interest directly in hardware. Here, we show that exchange-type gates are a promising choice for simulating molecular eigenstates on near-term quantum devices since these gates preserve the number of excitations in the system. Complementing the theoretical work by Barkoutsos et al. [PRA 98, 022322 (2018)], we report on the experimental implementation of a variational algorithm on a superconducting qubit platform to compute the eigenstate energies of molecular hydrogen. We utilize a parametrically driven tunable coupler to realize exchange-type gates that are configurable in amplitude and phase on two fixed-frequency superconducting qubits. With gate fidelities around 95% we are able to compute the eigenstates within an accuracy of 50 mHartree on average, a limit set by the coherence time of the tunable coupler.
arxiv pdf

Quantum optimization using variational algorithms on near-term quantum devices

  1. Nikolaj Moll,
  2. Panagiotis Barkoutsos,
  3. Lev S. Bishop,
  4. Jerry M. Chow,
  5. Andrew Cross,
  6. Daniel J. Egger,
  7. Stefan Filipp,
  8. Andreas Fuhrer,
  9. Jay M. Gambetta,
  10. Marc Ganzhorn,
  11. Abhinav Kandala,
  12. Antonio Mezzacapo,
  13. Peter Müller,
  14. Walter Riess,
  15. Gian Salis,
  16. John Smolin,
  17. Ivano Tavernelli,
  18. and Kristan Temme
Universal fault-tolerant quantum computers will require error-free execution of long sequences of quantum gate operations, which is expected to involve millions of physical qubits.
Before the full power of such machines will be available, near-term quantum devices will provide several hundred qubits and limited error correction. Still, there is a realistic prospect to run useful algorithms within the limited circuit depth of such devices. Particularly promising are optimization algorithms that follow a hybrid approach: the aim is to steer a highly entangled state on a quantum system to a target state that minimizes a cost function via variation of some gate parameters. This variational approach can be used both for classical optimization problems as well as for problems in quantum chemistry. The challenge is to converge to the target state given the limited coherence time and connectivity of the qubits. In this context, the quantum volume as a metric to compare the power of near-term quantum devices is discussed. With focus on chemistry applications, a general description of variational algorithms is provided and the mapping from fermions to qubits is explained. Coupled-cluster and heuristic trial wave-functions are considered for efficiently finding molecular ground states. Furthermore, simple error-mitigation schemes are introduced that could improve the accuracy of determining ground-state energies. Advancing these techniques may lead to near-term demonstrations of useful quantum computation with systems containing several hundred qubits.
arxiv pdf