Speaker
Description
Traditional heuristics for phylogenetic tree construction are classically intractable due to the NP hard nature of the problem, this is because of the super-exponential growth of the number of possible tree topologies. In other words, the search space is far too large for classical computations This projects looks into the use of Quantum algorithms, specifically Quantum Approximate Optimization Algorithm, to address this classically intractable problem in the quantum environment where a massive search space can be tackled by leveraging concepts like superposition. The importance of phylogenetic trees in not lost to anyone in evolutionary biology, bioinformatics and more broadly genetics, the classical approaches to their construction have computational limitations that this project has the potential to mitigate. From its utility in tracking disease outbreaks/spread on a global scale to drug discovery and conservation efforts, the utility of determining the evolutionary history from DNA or Amino Acid Sequences has only increased. This project aims to use the strengths of quantum computing to address computational bottlenecks in biological research, starting with phylogenetic tree construction.
| Topic | Hybrid quantum-classical approaches for learning and optimization |
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