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Tathagat Tulsi

Publications and source records attributed to Tathagat Tulsi.

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A new algorithm for fixed point quantum search

The standard quantum search lacks a feature, enjoyed by many classical algorithms, of having a fixed point, i.e. monotonic convergence towards the solution. Recently a fixed point quantum search algorithm has been discovered, referred to as the Phase-$π/3$ search algorithm, which gets around this limitation. While searching a database for a target state, this algorithm reduces the error probability from $ε$ to $ε^{2q+1}$ using $q$ oracle queries, which has since been proved to be asymptotically optimal. A different algorithm is presented here, which has the same worst-case behavior as the Phase-$π/3$ search algorithm but much better average-case behavior. Furthermore the new algorithm gives $ε^{2q+1}$ convergence for all integral $q$, whereas the Phase-$π/3$ search algorithm requires $q$ to be $(3^{n}-1)/2$ with $n$ a positive integer. In the new algorithm, the operations are controlled by two ancilla qubits, and fixed point behavior is achieved by irreversible measurement operations applied to these ancillas. It is an example of how measurement can allow us to bypass some restrictions imposed by unitarity on quantum computing.

quant-ph

Quantum Algorithms with Fixed Points: The Case of Database Search

The standard quantum search algorithm lacks a feature, enjoyed by many classical algorithms, of having a fixed-point, i.e. a monotonic convergence towards the solution. Here we present two variations of the quantum search algorithm, which get around this limitation. The first replaces selective inversions in the algorithm by selective phase shifts of $\fracπ{3}$. The second controls the selective inversion operations using two ancilla qubits, and irreversible measurement operations on the ancilla qubits drive the starting state towards the target state. Using $q$ oracle queries, these variations reduce the probability of finding a non-target state from $ε$ to $ε^{2q+1}$, which is asymptotically optimal. Similar ideas can lead to robust quantum algorithms, and provide conceptually new schemes for error correction.

quant-ph