Quick Navigation
Topics
Quantum Simulation
Quantum Annealing with Antiferromagnetic Transverse Interactions for the Hopfield Model
arXiv
Authors: Yuya Seki, Hidetoshi Nishimori
Year
2014
Paper ID
47202
Status
Preprint
Abstract Read
~2 min
Abstract Words
169
Citations
N/A
Abstract
We investigate quantum annealing with antiferromagnetic transverse interactions for the generalized Hopfield model with k-body interactions. The goal is to study the effectiveness of antiferromagnetic interactions, which were shown to help us avoid problematic first-order quantum phase transitions in pure ferromagnetic systems, in random systems. We estimate the efficiency of quantum annealing by analyzing phase diagrams for two cases where the number of embedded patterns is finite or extensively large. The phase diagrams of the model with finite patterns show that there exist annealing paths that avoid first-order transitions at least for 5 le k le 21. The same is true for the extensive case with k=4 and 5. In contrast, it is impossible to avoid first-order transitions for the case of finite patterns with k=3 and the case of extensive number of patterns with k=2 and 3. The spin-glass phase hampers the quantum annealing process in the case of k=2 and extensive patterns. These results indicate that quantum annealing with antiferromagnetic transverse interactions is efficient also for certain random spin systems.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2014 reference point for readers tracking recent quantum research.
- We investigate quantum annealing with antiferromagnetic transverse interactions for the generalized Hopfield model with k-body interactions.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.