DiscoverThe New Quantum EraQuantum reservoir computing with Susanne Yelin
Quantum reservoir computing with Susanne Yelin

Quantum reservoir computing with Susanne Yelin

Update: 2024-08-151
Share

Description

Sebastian is joined by Susanne Yelin, Professor of Physics in Residence at Harvard University and the University of Connecticut.
Susanne's Background:

  • Fellow at the American Physical Society and Optica (formerly the American Optics Society)
  • Background in theoretical AMO (Atomic, Molecular, and Optical) physics and quantum optics
  • Transition to quantum machine learning and quantum computing applications

Quantum Machine Learning Challenges

  • Limited to simulating small systems (6-10 qubits) due to lack of working quantum computers
  • Barren plateau problem: the more quantum and entangled the system, the worse the problem
  • Moved towards analog systems and away from universal quantum computers

Quantum Reservoir Computing

  • Subclass of recurrent neural networks where connections between nodes are fixed
  • Learning occurs through a filter function on the outputs
  • Suitable for analog quantum systems like ensembles of atoms with interactions
  • Advantages: redundancy in learning, quantum effects (interference, non-commuting bases, true randomness)
  • Potential for fault tolerance and automatic error correction

Quantum Chemistry Application

  • Goal: leverage classical chemistry knowledge and identify problems hard for classical computers
  • Collaboration with quantum chemists Anna Krylov (USC) and Martin Head-Gordon (UC Berkeley)
  • Focused on effective input-output between classical and quantum computers
  • Simulating a biochemical catalyst molecule with high spin correlation using a combination of analog time evolution and logical gates
  • Demonstrating higher fidelity simulation at low energy scales compared to classical methods

Future Directions

  • Exploring fault-tolerant and robust approaches as an alternative to full error correction
  • Optimizing pulses tailored for specific quantum chemistry calculations
  • Investigating dynamics of chemical reactions
  • Calculating potential energy surfaces for molecules
  • Implementing multi-qubit analog ideas on the Rydberg atom array machine at Harvard
  • Dr. Yelin's work combines the strengths of analog quantum systems and avoids some limitations of purely digital approaches, aiming to advance quantum chemistry simulations beyond current classical capabilities.
Comments 
loading
00:00
00:00
1.0x

0.5x

0.8x

1.0x

1.25x

1.5x

2.0x

3.0x

Sleep Timer

Off

End of Episode

5 Minutes

10 Minutes

15 Minutes

30 Minutes

45 Minutes

60 Minutes

120 Minutes

Quantum reservoir computing with Susanne Yelin

Quantum reservoir computing with Susanne Yelin

Sebastian Hassinger & Kevin Rowney