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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Submission of Task 2 and Task 3 for the screening of QOSF Mentorship Program\n\n## Task 2\n\nI have used `pennylane` with `qiskit` library plugin to solve the screening task. \n\n#### The steps involved in the solution:\n\n* Creating a parametrized circuit using RX and RY and CNOTs for creating `|01\u003e` and `|10\u003e` with eaual probability and and running it on a noisy simulator.\n  * Applied a parametrized RY gate and RX gate on first and second qubit respectively and measured the probability of the states.\n* Started with chosing random parameters.\n* Created a cost function which returns `((prob_00-0)**2 + (prob_01-0.5)**2 + (prob_10-0.5)**2 + (prob_11-0)**2)` where `prob_x` gives the probability of the given state\n* Used a prebuilt `Gradient Descent Optimizer` in `pennylane` library to find the parameters for different number of measurements.\n* Plotted the state probability for different number of measurements.\n\n#### Steps involved in the bonus question:\n\n* I measured the expectation value of `X@X` for the state, where `@` is the `tensor product`.\n* Then minimized `-1*expectation value` to find the parameter using `Gradient Descent`\n\n## Task 3\n\nI have used `qiskit` library to solve the Task 3. \n\n#### The steps involved in the solution\n\n* Created `H`, `X`, `Y`, `Z`, `CNOT` gate using `RX`, `RZ`, `CZ`.\n* Reduced the overhead by `Basic Swap`.\n\n## Note\n\nIf you want to evaluate with only one task, please go ahead with **Task2**.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frochisha0%2Fqosf-task","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frochisha0%2Fqosf-task","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frochisha0%2Fqosf-task/lists"}