Many bounded versions of undecidable problems are NP-hard

11/24/2022
by   Andreas Klingler, et al.
0

Several physically inspired problems have been proven undecidable; examples are the spectral gap problem and the membership problem for quantum correlations. Most of these results rely on reductions from a handful of undecidable problems, such as the halting problem, the tiling problem, the Post correspondence problem or the matrix mortality problem. All these problems have a common property: they have an NP-hard bounded version. This work establishes a relation between undecidable unbounded problems and their bounded NP-hard versions. Specifically, we show that NP-hardness of a bounded version follows easily from the reduction of the unbounded problems. This leads to new and simpler proofs of the NP-hardness of bounded version of the Post correspondence problem, the matrix mortality problem, the positivity of matrix product operators, the reachability problem, the tiling problem, and the ground state energy problem. This work sheds light on the intractability of problems in theoretical physics and on the computational consequences of bounding a parameter.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/23/2018

Graph Similarity and Approximate Isomorphism

The graph similarity problem, also known as approximate graph isomorphis...
research
06/24/2021

Kemeny ranking is NP-hard for 2-dimensional Euclidean preferences

The assumption that voters' preferences share some common structure is a...
research
11/19/2021

Non-NP-Hardness of Translationally-Invariant Spin-Model Problems

Finding the ground state energy of the Heisenberg Hamiltonian is an impo...
research
07/20/2021

Combinatorial Gap Theorem and Reductions between Promise CSPs

A value of a CSP instance is typically defined as a fraction of constrai...
research
07/01/2019

Improved hardness for H-colourings of G-colourable graphs

We present new results on approximate colourings of graphs and, more gen...
research
10/26/2019

On the Hardness of Energy Minimisation for Crystal Structure Prediction

Crystal Structure Prediction (csp) is one of the central and most challe...
research
12/03/2010

Agnostic Learning of Monomials by Halfspaces is Hard

We prove the following strong hardness result for learning: Given a dist...

Please sign up or login with your details

Forgot password? Click here to reset