DeepAI AI Chat
Log In Sign Up

2-Local Hamiltonian with Low Complexity is QCMA

by   Ying-hao Chen, et al.
The University of Texas at Austin

We prove that 2-Local Hamiltonian (2-LH) with Low Complexity problem is QCMA-complete by combining the results from the QMA-completeness[4] of 2-LH and QCMA-completeness of 3-LH with Low Complexity[6]. The idea is straightforward. It has been known that 2-LH is QMA-complete. By putting a low complexity constraint on the input state, we make the problem QCMA. Finally, we use similar arguments as in [4] to show that all QCMA problems can be reduced to our proposed problem.


page 1

page 2

page 3

page 4


Coding for Optical Communications – Can We Approach the Shannon Limit With Low Complexity?

Approaching capacity with low complexity is a very challenging task. In ...

Combining Networks using Cherry Picking Sequences

Phylogenetic networks are important for the study of evolution. The numb...

Improved Hardness Results for the Guided Local Hamiltonian Problem

Estimating the ground state energy of a local Hamiltonian is a central p...

Decidability and Periodicity of Low Complexity Tilings

We investigate the tiling problem, also known as the domino problem, tha...

Distilling BERT for low complexity network training

This paper studies the efficiency of transferring BERT learnings to low ...

Low complexity, low probability patterns and consequences for algorithmic probability applications

Developing new ways to estimate probabilities can be valuable for scienc...

Low-complexity Architecture for AR(1) Inference

In this Letter, we propose a low-complexity estimator for the correlatio...