This page collects course links, references, tools, hardware access, and fun project material for the practical quantum course. Use [[Source Reading Guide]] for how to pair sources with concept notes. Use [[Review Questions]] for a compact review pass. Use this page when you need a reference, simulator, hardware provider, or optional extension path. ## Primary Texts - Scott Aaronson, [Introduction to Quantum Information Science lecture notes](https://www.scottaaronson.com/qclec.pdf) - Scott Aaronson, [Quantum Computing since Democritus](https://www.scottaaronson.com/democritus/) ## Optional References - N. David Mermin, *Quantum Computer Science: An Introduction* - Thomas Wong, [Introduction to Quantum and Classical Computing](http://www.thomaswong.net/) - Ryan O'Donnell, [15-859BB: Quantum Computation and Information](https://www.cs.cmu.edu/~odonnell/quantum15/) - Scott Aaronson, [MIT 6.845 materials](https://stellar.mit.edu/S/course/6/fa14/6.845/materials.html) - Scott Aaronson, [Barbados 2016 lecture notes](https://www.scottaaronson.com/barbados-2016.pdf) - John Watrous, [Quantum Computation lecture notes](https://cs.uwaterloo.ca/~watrous/QC-notes/) ## Core Concept Seed Notes These were called out as especially important starter topics: - [[concepts/Separable vs. Entangled States]] - [[concepts/Entanglement Entropy]] - [[concepts/Pure vs. Mixed States]] ## Blogs And Commentary - Scott Aaronson, [Shtetl-Optimized](https://scottaaronson.blog/) - [Quantum Advantage Tracker](https://quantum-advantage-tracker.github.io/) - [IBM Quantum Blog](https://www.ibm.com/quantum/blog/) - [Google Quantum AI learning map](https://quantumai.google/learn/map) ## Software Frameworks Use the tools for different teaching jobs rather than treating them as interchangeable. ## Companion Code - [quantum-code repository](https://github.com/montekkundan/quantum-code): planned public home for the runnable notebooks, tested helpers, Q# comparison lane, assignments, and notebook smoke checks. - [COURSE_MAP.md](https://github.com/montekkundan/quantum-code/blob/main/COURSE_MAP.md): lecture-to-code map. - [[Quantum Code Map]]: local Obsidian map from concept notes to notebooks, helpers, and tests. - [[Final Capstone Workflow]]: final-project rubric and evidence checklist. - [animations/](https://github.com/montekkundan/quantum-code/tree/main/animations): Manim source. - [capstone/](https://github.com/montekkundan/quantum-code/tree/main/capstone): project workflow and report template. | Tool | Best course use | | --- | --- | | [IBM Quantum Learning](https://quantum.cloud.ibm.com/learning/en) | primary Qiskit path, classroom modules, IBM hardware workflow | | [PennyLane demos](https://pennylane.ai/qml/demonstrations) | variational algorithms, QML, resource-estimation demos, paper-based examples | | [Google Quantum AI resources](https://quantumai.google/resources) | ecosystem learning maps and hardware-aware context | | [Classiq insights](https://www.classiq.io/insights#Algorithms) | algorithm-design examples and high-level circuit synthesis context | | [Q-CTRL Black Opal](https://q-ctrl.com/black-opal) | visual intuition, controls, and learning modules | | [NVIDIA CUDA-Q](https://developer.nvidia.com/cuda-q) | accelerated simulation, hybrid workflows, Hamiltonian and tensor-network extensions | | [QuTiP](https://qutip.org/) | density matrices, Hamiltonians, open systems, and noise models | ## Simulators And Hardware Access ### Real Hardware Access - [IBM Quantum Platform](https://quantum.cloud.ibm.com/) - [Amazon Braket](https://aws.amazon.com/braket/) for access to multiple hardware providers and managed quantum workflows ### Simulators - Scott Aaronson, [CHP stabilizer simulator](https://www.scottaaronson.com/chp/) - [CUDA-Q documentation](https://nvidia.github.io/cuda-quantum/latest/index.html) - [Les Houches Lecture Notes on Tensor Networks](https://arxiv.org/abs/2512.24390) ### Hardware Pathways - Superconducting qubits: [UC Berkeley EE290 notes](https://qudev.notion.site/ee290), [Qiskit Metal](https://qiskit-community.github.io/qiskit-metal/) - Trapped ions: [IonQ documentation](https://docs.ionq.com/) - Neutral atoms: [Pasqal Pulser](https://github.com/pasqal-io/Pulser), [QuEra Bloqade](https://www.quera.com/bloqade) ## Suggested Articles And Papers - [A simplified version of the quantum OTOC$^{(2)}$ problem](https://arxiv.org/abs/2510.19751) - Ewin Tang, [blog post](https://ewintang.com/blog/2025/04/22/open/) - [Les Houches Lecture Notes on Tensor Networks](https://arxiv.org/abs/2512.24390) ## Video Lectures And Playlists - [MITx 8.370.1x](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8.370.1x+1T2018/about) - [MITx 8.370.2x](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8.370.2x+1T2018/about) - [MITx 8.370.3x](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8.370.3x+1T2018/about) - [MITx 8.371.1x](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8.371.1x+2T2018/about) - [MITx 8.371.2x](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8.371.2x+2T2018/about) - [MITx 8.371.3x](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+8.371.3x+2T2018/about) - [MIT OCW 6.845 Quantum Complexity Theory](https://ocw.mit.edu/courses/6-845-quantum-complexity-theory-fall-2010/) ## Hackathon And Fun Projects - BlueQubit, [Quantum Advantage Challenge](https://www.bluequbit.io/quantum-advantage-challenge) ## Review Material Use [[Review Questions]] first. Then use these checks to test whether a concept note is teachable: **Can I answer the note's study checks without looking?** If not, reread the source section in [[Source Reading Guide]], then write a one-paragraph explanation before trying the lab. **Can I connect the math to a runnable tool?** For each concept, pick one of Qiskit, QuTiP, PennyLane, CUDA-Q, or a stabilizer simulator and state what observable, runtime, entropy, circuit depth, or error rate you would measure.