On training variational quantum circuits

ORAL

Abstract

We consider certain training phenomena including under versus over parameterisation and noise effects in variational quantum circuits. Particularly we contrast abrupt training transitions, reachability deficits, parameter concentrations and parameter saturations.

Publication: Quantum machine learning
J Biamonte, P Wittek, N Pancotti, P Rebentrost, N Wiebe, and S Lloyd
Nature 549, 195–202 (2017) 10.1038/nature23474

Ion-native variational ansatz for quantum approximate optimization
D Rabinovich, S Adhikary, E Campos, V Akshay, E Anikin, R Sengupta, O Lakhmanskaya, K Lakhmanskiy, and J Biamonte
Physical Review A 106, 032418 (2022) 10.1103/PhysRevA.106.032418

Progress towards analytically optimal angles in quantum approximate optimisation
D Rabinovich, R Sengupta, E Campos, V Akshay, and J Biamonte
Mathematics 10, 2601 (2022) 10.3390/math10152601

Reachability deficits implicit in quantum approximate optimization of graph problems
V Akshay, H Philathong, I Zacharov, and J Biamonte
Quantum 5, 532 (2021) 10.22331/q-2021-08-30-532

Parameter concentrations in quantum approximate optimization
V Akshay, D Rabinovich, E Campos, and J Biamonte
(Letter) Physical Review A 104, L010401 (2021) 10.1103/PhysRevA.104.L010401

Universal variational quantum computation
J Biamonte
(Letter) Physical Review A 103, L030401 (2021) 10.1103/PhysRevA.103.L030401

Quantum machine learning tensor network states
A Kardashin, A Uvarov, and J Biamonte
Frontiers in Physics 8, 586374 (2021) 10.3389/fphy.2020.586374

Variational simulation of Schwinger's Hamiltonian with polarization qubits
O Borzenkova, G Struchalin, A Kardashin, V Krasnikov, N Skryabin, S Straupe, S Kulik, and J Biamonte
Applied Physics Letters 118, 144002 (2021) 10.1063/5.0043322

Abrupt transitions in variational quantum circuit training
E Campos, A Nasrallah, and J Biamonte
Physical Review A 103, 032607 (2021) 10.1103/PhysRevA.103.032607

Training saturation in layerwise quantum approximate optimisation
E Campos, D Rabinovich, V Akshay, and J Biamonte
(Letter) Physical Review A 104, L030401 (2021) 10.1103/PhysRevA.104.L030401

On barren plateaus and cost function locality in variational quantum algorithms
A Uvarov and J Biamonte
Journal of Physics A: Mathematical and Theoretical 54, 245–301 (2021) 10.1088/1751-8121/abfac7

Reachability deficits in quantum approximate optimization
V Akshay, H Philathong, M Morales, and J Biamonte
Physical Review Letters 124, 090504 (2020) 10.1103/PhysRevLett.124.090504

On the universality of the quantum approximate optimization algorithm
M Morales, J Biamonte, and Z Zimborás
Quantum Information Processing 19, 291 (2020) 10.1007/s11128-020-02748-9

Variational quantum eigensolver for frustrated quantum systems
A Uvarov, J Biamonte, and D Yudin
Physical Review B 102, 075104 (2020) 10.1103/PhysRevB.102.075104

Machine learning phase transitions with a quantum processor
A Uvarov, A Kardashin, and J Biamonte
Physical Review A 102, 012415 (2020) 10.1103/PhysRevA.102.012415

Variational learning of Grover's quantum search algorithm
M Morales, T Tlyachev, and J Biamonte
Physical Review A 98, 062333 (2018) 10.1103/PhysRevA.98.062333

Presenters

  • Jacob Biamonte

    Beijing Institute of Mathematical Sciences and Applications

Authors

  • Jacob Biamonte

    Beijing Institute of Mathematical Sciences and Applications