Quantum Noise
https://github.com/qiskit-community/qgss-2025/blob/main/lab-2/Lab2.ipynb Accessing device properties Qiskit https://quantum.cloud.ibm.com/docs/en/guides/get-qpu-information
Quantum Teleportation
Resources: https://github.com/Qiskit/textbook/blob/main/notebooks/ch-algorithms/teleportation.ipynb https://quantum.cloud.ibm.com/learning/en/courses/basics-of-quantum-information/entanglement-in-action/quantum-teleportation https://quantum.cloud.ibm.com/learning/images/courses/basics-of-quantum-information/entanglement-in-action/teleportation.svg https://quantum.cloud.ibm.com/learning/images/courses/basics-of-quantum-information/entanglement-in-action/teleportation-time-steps.svg https://quantum.cloud.ibm.com/docs/en/guides/classical-feedforward-and-control-flow https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.5.030339 https://github.com/qiskit-community/ibm-quantum-challenge-spring-2023/blob/main/content/lab_2/lab2.ipynb https://quantum.cloud.ibm.com/learning/en/modules/computer-science/quantum-teleportation
WSL terminal access
To go to the wsl terminal, In windows terminal PS,
IBM Quantum Platorm – Upgraded
https://www.ibm.com/quantum/blog/iqp-upgrade https://quantum.cloud.ibm.com/docs/en/migration-guides/classic-iqp-to-cloud-iqp New version of IBM Quantum Platformhttps://quantum.cloud.ibm.com/ https://quantum.cloud.ibm.com/docs/en/guides/cloud-setup Major Differences:https://quantum.cloud.ibm.com/docs/en/migration-guides/classic-iqp-to-cloud-iqp#major-differences
Bounding Boxes – Autonomous Driving
References:
Calculus – The Derivative
Suppose function $latex y = f(x)$, then the derivative of the function can be denoted as: $latex f'(x), \frac{dy}{dx}, y’ or \frac{d}{dx}(f(x))$ BUT what does that mean actually? Derivative of a function? https://math.libretexts.org/Bookshelves/Calculus/Calculus_(OpenStax)/03%3A_Derivatives/3.02%3A_The_Derivative_as_a_Function
Optimization
Rosenbrock Function $latex f(x,y) = (1-x)^2 + 100(y-x^2)^2$ https://docs.scipy.org/doc/scipy/tutorial/optimize.html
Mongo DB – Quick notes from website
https://learn.mongodb.com/
Autonomous Vehicle/ Datasets
https://github.com/waymo-research/waymo-open-dataset/blob/master/tutorial/tutorial_v2.ipynb https://github.com/nutonomy/nuscenes-devkit/tree/master/python-sdk/tutorials https://neptune.ai/blog/self-driving-cars-with-convolutional-neural-networks-cnn
What is Gradient? Loss Function? Model Parameters? Gradient Descent?
Gradient Descent: Optimization algorithm; minimizes errors between predicted and actual results; updates parameters by moving against the gradient Loss Function: aim is to minimize this function, closer to zero; measures how bad the prediction is in comparison to the actual true value; various methods are used; one is Mean Squared Error (MSE) Gradient: Slope; direction ... Read More