There is an immediate need for computers to be able to handle such vast amounts of data and be able to find the relevant piece of information. The current linear search algorithms require about O(N) steps in order to find the relevant pieces of information containing N data sets. But, with the use of quantum computers and a little modification to grover’s search algorithm we can reduce the time to O(sqrt(N)) the only other time which is required is in the original state preparation, even after that there is a huge difference in time consumed.
What it does
A quantum algorithm for closest pattern matching which allows us to search for as many distinct patterns as we wish in a given string (database), requiring a query function per symbol of the pattern alphabet.
How we built it
We Modified grover's search algorithm to solve the problem for increasing amount of information.
Challenges we ran into
Our original idea was to create a website which we were not able to merge with our code from QISKIT
Accomplishments that we're proud of
Being able to make a prototype which has the capacity to grow into something large and save a lot of time .
What we learned
That we can modify the existing algorithms to solve upcoming problems
What's next for Qsearch
Becoming an all out quantum search engine and helping MNCs by saving time and resources