Beating Random Assignment for Approximating Quantum 2-Local Hamiltonian Problems
Ojas Parekh, Kevin Thompson

TL;DR
This paper introduces the first classical approximation algorithms that outperform the trivial random assignment for quantum 2-Local Hamiltonian problems, achieving better approximation ratios and connecting quantum problems to classical CSP techniques.
Contribution
It presents novel classical approximation algorithms for quantum 2-Local Hamiltonian problems that beat previous bounds, including for maximally entangled instances and special bipartite cases.
Findings
First polynomial-time 0.764-approximation for Max 2-Local Hamiltonian with rank 3 projectors
Numerical evidence suggests a 0.821-approximation for strictly quadratic instances
Improved classical approximation for bipartite strictly quadratic traceless 2-Local Hamiltonians
Abstract
The quantum k-Local Hamiltonian problem is a natural generalization of classical constraint satisfaction problems (k-CSP) and is complete for QMA, a quantum analog of NP. Although the complexity of k-Local Hamiltonian problems has been well studied, only a handful of approximation results are known. For Max 2-Local Hamiltonian where each term is a rank 3 projector, a natural quantum generalization of classical Max 2-SAT, the best known approximation algorithm was the trivial random assignment, yielding a 0.75-approximation. We present the first approximation algorithm beating this bound, a classical polynomial-time 0.764-approximation. For strictly quadratic instances, which are maximally entangled instances, we provide a 0.801 approximation algorithm, and numerically demonstrate that our algorithm is likely a 0.821-approximation. We conjecture these are the hardest instances to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
