Hybrid CVaR and IQP quantum workflows find CPLEX-verified optimal solutions for mRNA-folding QUBO instances up to 156 qubits, but simulated scaling shows steeply declining success rates.
Permutational Quantum Computing
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abstract
In topological quantum computation the geometric details of a particle trajectory are irrelevant; only the topology matters. Taking this one step further, we consider a model of computation that disregards even the topology of the particle trajectory, and computes by permuting particles. Whereas topological quantum computation requires anyons, permutational quantum computation can be performed with ordinary spin-1/2 particles, using a variant of the spin-network scheme of Marzuoli and Rasetti. We do not know whether permutational computation is universal. It may represent a new complexity class within BQP. Nevertheless, permutational quantum computers can in polynomial time approximate matrix elements of certain irreducible representations of the symmetric group and simulate certain processes in the Ponzano-Regge spin foam model of quantum gravity. No polynomial time classical algorithms for these problems are known.
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Towards secondary structure prediction of longer mRNA sequences using a quantum-centric optimization scheme
Hybrid CVaR and IQP quantum workflows find CPLEX-verified optimal solutions for mRNA-folding QUBO instances up to 156 qubits, but simulated scaling shows steeply declining success rates.