quantum-for-software-engineers

Learn quantum computing the way software engineers think.

A code-first, intuition-driven collection of resources, tools, and platforms for understanding quantum computing without heavy physics or math.

What You Will Learn (Conceptually)

• Qubits as stateful computational objects
• Quantum gates as transformations
• Circuits as execution pipelines
• Measurement as probabilistic output
• Entanglement as shared system state
• How quantum computers differ from classical computers in practice
• Where quantum computing is useful today (and where it is not)

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Visual Overview

Classical vs Quantum

Quantum Gates

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Core Quantum Software Frameworks

Qiskit (IBM)

• https://qiskit.org
• https://github.com/Qiskit/qiskit
• https://learning.quantum.ibm.com

Primary use:

• circuit design
• simulation
• real quantum hardware access

Key components:

• qiskit.circuit
• qiskit.quantum_info
• qiskit_aer
• qiskit_ibm_runtime

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PennyLane (Xanadu)

• https://pennylane.ai
• https://github.com/PennyLaneAI/pennylane

Primary use:

• hybrid quantum–classical computing
• quantum machine learning
• differentiable quantum circuits

Integrates with:

• PyTorch
• TensorFlow
• JAX

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Cirq (Google)

• https://quantumai.google/cirq
• https://github.com/quantumlib/Cirq

Primary use:

• NISQ-era algorithms
• hardware-aware circuit design
• research-focused workflows

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Braket SDK (AWS)

• https://github.com/aws/amazon-braket-sdk-python
• https://aws.amazon.com/braket/

Primary use:

• cloud-native quantum workflows
• access to multiple quantum hardware providers
• scalable experimentation

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Q# (Microsoft)

• https://learn.microsoft.com/azure/quantum/
• https://github.com/microsoft/qsharp

Primary use:

• algorithm design
• quantum program composition
• tight integration with classical control logic

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Quantum Simulation Tools

Used when real quantum hardware is unavailable or impractical.

• Qiskit Aer
  https://qiskit.org/ecosystem/aer/

• Cirq Simulator
  https://quantumai.google/cirq/simulators

• QuTiP
  https://qutip.org

• ProjectQ
  https://projectq.ch

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Cloud Quantum Platforms (Hands-On)

IBM Quantum

• https://quantum.ibm.com
• Free tier available
• Real superconducting quantum processors

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Amazon Braket

• https://aws.amazon.com/braket/
• Access to IonQ, Rigetti, QuEra
• Pay-as-you-go model

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Azure Quantum

• https://azure.microsoft.com/products/quantum
• Multi-vendor quantum access
• Strong tooling and documentation

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Quantum Computer Types

Type	Qubit Technology	Key Characteristics	Used By / Examples	Typical Use Cases
Superconducting	Josephson junctions	Fast gates, cryogenic, scalable	IBM, Google, Rigetti	General-purpose QC, research
Trapped Ion	Electromagnetically trapped ions	High fidelity, long coherence	IonQ, Quantinuum	Algorithms, precision tasks
Photonic	Single photons	Room temperature, optical	Xanadu, PsiQuantum	Quantum networking, ML
Neutral Atom	Atoms in optical tweezers	Highly scalable, flexible	QuEra, Pasqal	Simulation, optimization
Quantum Annealing	Superconducting flux qubits	Optimization-specific, not gate-based	D-Wave	Combinatorial optimization
Spin Qubits	Electron / nuclear spin	CMOS-compatible, compact	Intel, research labs	Future scalable systems
Topological (Research)	Anyons (theoretical)	Error-resistant by design	Microsoft (research)	Fault-tolerant QC

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Quantum Hardware Providers

• IBM Quantum
  https://quantum.ibm.com

• Google Quantum AI
  https://quantumai.google

• IonQ
  https://ionq.com

• Rigetti
  https://www.rigetti.com

• Quantinuum
  https://www.quantinuum.com

• Xanadu
  https://www.xanadu.ai

• D-Wave
  https://www.dwavesys.com

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Learning Resources

Level	Resource	Type	Link	Notes
Beginner	IBM Quantum Learning	Interactive	https://learning.quantum.ibm.com	Best hands-on start
Beginner	Qiskit Textbook	Book / Labs	https://qiskit.org/learn	Code-first explanations
Beginner	Microsoft Quantum Katas	Exercises	https://github.com/microsoft/QuantumKatas	Practice-oriented
Beginner	Quantum Country	Essays	https://quantum.country	Intuition-focused
Intermediate	PennyLane Demos	Tutorials	https://pennylane.ai/qml/demonstrations.html	Quantum ML
Intermediate	Cirq Tutorials	Docs	https://quantumai.google/cirq/tutorials	Hardware-aware
Intermediate	IBM Quantum Lab	Cloud Lab	https://quantum.ibm.com/lab	Real hardware
Intermediate	AWS Braket Notebooks	Notebooks	https://github.com/aws/amazon-braket-examples	Multi-hardware
Advanced	MIT OpenCourseWare (QC)	Course	https://ocw.mit.edu	Academic depth
Advanced	Stanford Quantum Courses	Lectures	https://quantum.stanford.edu/education	Theory + systems
Advanced	Xanadu Quantum Codebook	Book	https://codebook.xanadu.ai	Photonic focus

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Academic References

Title	Authors / Institution	Type	Link	Focus
Quantum Computation and Quantum Information	Nielsen & Chuang	Book	https://doi.org/10.1017/CBO9780511976667	Standard reference
The Quantum Algorithm Zoo	NIST	Survey	https://quantumalgorithmzoo.org	Algorithm catalog
Lecture Notes on Quantum Computation	John Preskill (Caltech)	Notes	http://theory.caltech.edu/~preskill/ph219	Theory
Quantum Computing for Computer Scientists	Yanofsky & Mannucci	Book	https://www.cambridge.org/9780521876582	CS-focused
Fault-Tolerant Quantum Computation	Gottesman	Paper	https://arxiv.org/abs/quant-ph/9705052	Error correction
Shor’s Algorithm	Peter Shor	Paper	https://arxiv.org/abs/quant-ph/9508027	Factoring
Grover’s Algorithm	Lov Grover	Paper	https://arxiv.org/abs/quant-ph/9605043	Search
Quantum Error Correction	Daniel Gottesman	Survey	https://arxiv.org/abs/0904.2557	Reliability
No-Cloning Theorem	Wootters & Zurek	Paper	https://doi.org/10.1038/299802a0	Information theory
Quantum Supremacy Using Superconducting Qubits	Google AI	Paper	https://www.nature.com/articles/s41586-019-1666-5	Hardware milestone
Topological Quantum Computation	Alexei Kitaev	Paper	https://arxiv.org/abs/quant-ph/9707021	Fault tolerance

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Quantum Computing + Software Engineering

Mental Model Mapping

Software Engineering	Quantum Computing
Variable	Qubit
Function	Quantum Gate
Pipeline	Quantum Circuit
Randomized algorithm	Measurement
Shared memory	Entanglement

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Programming Languages Used in Quantum

• Python (dominant)
• Q#
• C++ (hardware control layers)
• Rust (emerging ecosystems)

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Industry & Ecosystem

Quantum computing is relevant to:

• optimization
• communication and networking
• chemistry & materials
• machine learning research
• simulation of physical systems
• information theory

Major contributors:

• IBM
• Google
• Microsoft
• Amazon
• Intel
• Startups and research labs worldwide

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How to Use This Repository

• Pick a framework
• Run examples
• Observe probabilistic behavior
• Compare simulators vs real hardware
• Build intuition through experimentation

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Philosophy

Quantum computing is not magic. It is computation under different rules of information, state, and probability.

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• Curious Developers

Contributing

Pull requests are welcome.

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