Consider the problem of estimating the median of N items to a precision ε, i.e. the estimate µ should be such that, with a large probability, the number of items with values smaller than µ is less than and those with values greater than µ is also less than. Any classical algorithm to do this will need at least samples. Quantum mechanical systems can simultaneously carry out multiple computations due to their wave like properties. This paper gives an step algorithm for the above problem.
Abstract We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with st...
We will give a precise estimate for Grover's extended quantum search algorithm. It is shown by Grove...
In Weighted Model Counting (WMC) we assign weights to Boolean literals and we want to compute the su...
Ten pages, no figures, three algorithmsWe describe two quantum algorithms to approximate the mean va...
A framework is presented for the design and analysis of quantum mechanical algorithms, the O(sqrt(N)...
The ever increasing demand for high image quality requires fast and efficient methods for noise redu...
Quantum algorithms have gained a lot of consideration especially for the need to find out the extrem...
The theories of optimization and machine learning answer foundational questions in computer science ...
We give a quantum algorithm for solving semidefinite programs (SDPs). It has worst-case running time...
Consider a database most of whose entries are marked but the precise fraction of marked entries is n...
The Quantum Approximate Optimization Algorithm (QAOA) is one of the promising near-term algorithms d...
Quantum expectation-maximization algorithm, Physical Review A (2020), 10.1103/PhysRevA.101.01232
The Quantum Approximation Optimization Algorithm (QAOA) is one of the most promising applications fo...
this paper, we show how the use of quantum computing can speed up some computations related to inter...
The quantum approximate optimization algorithm (QAOA) requires that circuit parameters are determine...
Abstract We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with st...
We will give a precise estimate for Grover's extended quantum search algorithm. It is shown by Grove...
In Weighted Model Counting (WMC) we assign weights to Boolean literals and we want to compute the su...
Ten pages, no figures, three algorithmsWe describe two quantum algorithms to approximate the mean va...
A framework is presented for the design and analysis of quantum mechanical algorithms, the O(sqrt(N)...
The ever increasing demand for high image quality requires fast and efficient methods for noise redu...
Quantum algorithms have gained a lot of consideration especially for the need to find out the extrem...
The theories of optimization and machine learning answer foundational questions in computer science ...
We give a quantum algorithm for solving semidefinite programs (SDPs). It has worst-case running time...
Consider a database most of whose entries are marked but the precise fraction of marked entries is n...
The Quantum Approximate Optimization Algorithm (QAOA) is one of the promising near-term algorithms d...
Quantum expectation-maximization algorithm, Physical Review A (2020), 10.1103/PhysRevA.101.01232
The Quantum Approximation Optimization Algorithm (QAOA) is one of the most promising applications fo...
this paper, we show how the use of quantum computing can speed up some computations related to inter...
The quantum approximate optimization algorithm (QAOA) requires that circuit parameters are determine...
Abstract We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with st...
We will give a precise estimate for Grover's extended quantum search algorithm. It is shown by Grove...
In Weighted Model Counting (WMC) we assign weights to Boolean literals and we want to compute the su...