Add to ORKGWe construct a quantum random walk algorithm, based on the Dirac operator instead of the Laplacian. The algorithm explores multiple evolutionary branches by superposition of states, and does not require the coin toss instruction of classical randomised algorithms. We use this algorithm to search for a marked vertex on a hypercubic lattice in arbitrary dimensions. Our numerical and analytical results match the scaling behaviour of earlier algorithms that use a coin toss instruction
Using numerical simulation, we measured the performance of several poten-tial quantum algorithms, ba...
In this thesis, we discover a new way to analyze quantum random walks over general graphs. We first ...
We give a quantum algorithm for finding a marked element on the grid when there are multiple marked ...
Classical randomized algorithms use a coin toss instruction to explore different evolutionary branch...
Random walks describe diffusion processes, where movement at every time step is restricted to only t...
Random walks describe diffusion processes, where movement at every time step is restricted only to n...
Random walks have been applied in a many different fields for a long time. More recently, classical ...
The development of quantum algorithms based on quantum versions of random walks is placed in the con...
We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evo...
We analyze nearest neighbor one-dimensional quantum random walks with arbitrary unitary coin-flip ma...
This book addresses an interesting area of quantum computation called quantum walks, which play an i...
AbstractQuantum versions of random walks on the line and the cycle show a quadratic improvement over...
We solve an open problem by constructing quantum walks that not only detect but also find marked ver...
Quantum versions of random walks on the line and the cycle show a quadratic improvement over classic...
We analyze several families of one and two-dimensional nearest neighbor Quantum Random Walks. Using ...
Using numerical simulation, we measured the performance of several poten-tial quantum algorithms, ba...
In this thesis, we discover a new way to analyze quantum random walks over general graphs. We first ...
We give a quantum algorithm for finding a marked element on the grid when there are multiple marked ...
Classical randomized algorithms use a coin toss instruction to explore different evolutionary branch...
Random walks describe diffusion processes, where movement at every time step is restricted to only t...
Random walks describe diffusion processes, where movement at every time step is restricted only to n...
Random walks have been applied in a many different fields for a long time. More recently, classical ...
The development of quantum algorithms based on quantum versions of random walks is placed in the con...
We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evo...
We analyze nearest neighbor one-dimensional quantum random walks with arbitrary unitary coin-flip ma...
This book addresses an interesting area of quantum computation called quantum walks, which play an i...
AbstractQuantum versions of random walks on the line and the cycle show a quadratic improvement over...
We solve an open problem by constructing quantum walks that not only detect but also find marked ver...
Quantum versions of random walks on the line and the cycle show a quadratic improvement over classic...
We analyze several families of one and two-dimensional nearest neighbor Quantum Random Walks. Using ...
Using numerical simulation, we measured the performance of several poten-tial quantum algorithms, ba...
In this thesis, we discover a new way to analyze quantum random walks over general graphs. We first ...
We give a quantum algorithm for finding a marked element on the grid when there are multiple marked ...