Quick Navigation

Topics

Quantum Simulation

Quantum Algorithms for the Minimum Steiner Tree problem with application to Binary Near-Perfect Phylogenies

arXiv
Authors: Lingfa Meng, David Salvador Novo, Albert H. Werner, Samir Bhatt

Year

2025

Paper ID

51372

Status

Preprint

Abstract Read

~2 min

Abstract Words

81

Citations

N/A

Abstract

We present a quantum algorithm in bioinformatics for solving the Binary Near-Perfect Phylogeny Problem (BNPP) with a complexity bound of O\(8.926q + 8q nm2\), where n is the number of input taxa and m is the sequence length for each taxon with each character in the sequence being a binary bit using the QRAM model. We give another polynomial space exact algorithm for the Minimum Steiner Tree (MST) problem with complexity O^*\(e(1+g(k,l\))k) in the circuit model.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • We present a quantum algorithm in bioinformatics for solving the Binary Near-Perfect Phylogeny Problem (BNPP) with a complexity bound of O(8.926^q + 8^q nm2), where n is the...

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

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #51372 #69599 Tensor network compression usin... #69594 A Collective-Spin Derivation of... #69593 Local correlations in long-rang... #69592 Direct/adaptive-mixture phase-g...

External citation index: OpenAlex citation signal

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.