Does provable absence of barren plateaus imply classical simulability?
Los Alamos National Laboratory · Los Alamos National Security (United States) · +9 more institutions
Abstract
A large amount of effort has recently been put into understanding the barren plateau phenomenon. In this perspective article, we face the increasingly loud elephant in the room and ask a question that has been hinted at by many but not explicitly addressed: Can the structure that allows one to avoid barren plateaus also be leveraged to efficiently simulate the loss classically? We collect evidence-on a case-by-case basis-that many commonly used models whose loss landscapes avoid barren plateaus can also admit classical simulation, provided that one can collect some classical data from quantum devices during an initial data acquisition phase. This follows from the observation that barren plateaus result from a…
Citation impact
- FWCI
- 112.37
- Percentile
- 100%
- References
- 162
Authors
12- MCM. CerezoCorresponding
Los Alamos National Laboratory, Los Alamos National Security (United States), Quantum Science Center
- MLMartín Larocca
Los Alamos National Laboratory
- DGDiego García-Martín
Los Alamos National Laboratory
- NLN. L. Diaz
Los Alamos National Laboratory, Instituto de Física La Plata
- PBPaolo Braccia
Los Alamos National Laboratory
Topics & keywords
- Computer science
- Quantum
- Plateau (mathematics)
- Perspective (graphical)
- Curse of dimensionality
- Theoretical computer science
- Quantum computer
- Artificial intelligence
Funding
- UDU.S. Department of Energy
- CICalifornia Institute of Technology
- CUChulalongkorn University
- CNConsejo Nacional de Investigaciones Científicas y Técnicas
- NRNational Research Council of Thailand
- OOOffice of Science
- WBWalter Burke Institute for Theoretical Physics
- EAEngineering and Physical Sciences Research CouncilAward: EP/T517665/1
- NPNational Physical Laboratory
- ASAdvanced Scientific Computing Research
- LDLaboratory Directed Research and DevelopmentAwards: 20230527ECR, 20230049DR
- LALos Alamos National LaboratoryAwards: 20230049DR, 20230527ECR