A classical simulation framework called MAST, built by adding magic state injection to stabilizer tensor networks, simulates random T-doped Clifford circuits with up to N T-gates in polynomial time and hidden shift circuits with 4000 qubits and 320 T-gates.
Optimising Matrix Product State Simulations of Shor's Algorithm
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abstract
We detail techniques to optimise high-level classical simulations of Shor's quantum factoring algorithm. Chief among these is to examine the entangling properties of the circuit and to effectively map it across the one-dimensional structure of a matrix product state. Compared to previous approaches whose space requirements depend on $r$, the solution to the underlying order-finding problem of Shor's algorithm, our approach depends on its factors. We performed a matrix product state simulation of a 60-qubit instance of Shor's algorithm that would otherwise be infeasible to complete without an optimised entanglement mapping.
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Stabilizer Tensor Networks with Magic State Injection
A classical simulation framework called MAST, built by adding magic state injection to stabilizer tensor networks, simulates random T-doped Clifford circuits with up to N T-gates in polynomial time and hidden shift circuits with 4000 qubits and 320 T-gates.