QUANTA: A quantum annealing framework for species tree estimation using weighted quartet amalgamation

QUANTA, a quantum-annealing quartet amalgamation method for multi-locus species tree estimation, achieves state-of-the-art accuracy and delivers a 4100x speedup over wQFM’s FM bipartitioning for 90–200 taxa.

• Why it matters: Gene tree discordance makes species tree reconstruction from genome-scale data difficult, and classical quartet amalgamation methods can be too slow to scale due to expensive bipartitioning heuristics.
• What they did: QUANTA formulates weighted quartet bipartitioning as a QUBO for quantum annealing, proves it uses the minimum qubits for bipartitions, and runs on real D-Wave hardware.
• The result: Across simulated and biological datasets, QUANTA matches ASTRAL and wQFM accuracy under challenging conditions, reconstructs a higher-quartet-score avian tree than wQFM, and maintains comparable accuracy while achieving 4100x speedup on 90–200 taxa.

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