Explain: Cirq is the main open-source quantum framework from Google Quantum AI. It is widely used for NISQ (Noisy Intermediate-Scale Quantum) research, with strong support for hardware-aware circuits, noise modeling, parameterized circuits, and integration with Google’s quantum hardware. With ~4.9k GitHub stars and active development, it is a standard tool for quantum algorithm research and hardware experiments.
How It Differs
If similar entries exist, what makes this one unique?
Qiskit is IBM-focused and emphasizes broad hardware support and transpilation. PennyLane targets quantum machine learning and differentiable circuits. QuTiP focuses on quantum dynamics and open quantum systems. Cirq is built for NISQ-era hardware: it emphasizes hardware-aware circuit design, noise modeling, and integration with Google’s quantum hardware. It is distinct from the others in its NISQ focus and hardware-oriented abstractions.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.
## 📋 Pull Request Information
**Original PR:** https://github.com/vinta/awesome-python/pull/2920
**Author:** [@dakshp26](https://github.com/dakshp26)
**Created:** 2/18/2026
**Status:** ✅ Merged
**Merged:** 2/19/2026
**Merged by:** [@JinyangWang27](https://github.com/JinyangWang27)
**Base:** `master` ← **Head:** `dakshp26-add-cirq`
---
### 📝 Commits (1)
- [`062545c`](https://github.com/vinta/awesome-python/commit/062545c83bf29437537c014c29dcbb89bb689f9b) add cirq library to quantum computing section
### 📊 Changes
**1 file changed** (+1 additions, -0 deletions)
<details>
<summary>View changed files</summary>
📝 `README.md` (+1 -0)
</details>
### 📄 Description
## Project
[Cirq](https://github.com/quantumlib/Cirq)
## Checklist
- [x] One project per PR
- [x] PR title format: `Add cirq`
- [x] Entry format: `* [Cirq](https://github.com/quantumlib/Cirq) - Google-developed framework for creating, editing, and running NISQ quantum circuits with hardware-aware design.`
- [x] Description is concise and short
## Why This Project Is Awesome
Which criterion does it meet? (pick one)
- [x] **Industry Standard** - The go-to tool for a specific use case
- [ ] **Rising Star** - 5000+ stars in < 2 years, significant adoption
- [ ] **Hidden Gem** - Exceptional quality, solves niche problems elegantly
**Explain:** Cirq is the main open-source quantum framework from Google Quantum AI. It is widely used for NISQ (Noisy Intermediate-Scale Quantum) research, with strong support for hardware-aware circuits, noise modeling, parameterized circuits, and integration with Google’s quantum hardware. With ~4.9k GitHub stars and active development, it is a standard tool for quantum algorithm research and hardware experiments.
## How It Differs
If similar entries exist, what makes this one unique?
**Qiskit** is IBM-focused and emphasizes broad hardware support and transpilation. **PennyLane** targets quantum machine learning and differentiable circuits. **QuTiP** focuses on quantum dynamics and open quantum systems. **Cirq** is built for NISQ-era hardware: it emphasizes hardware-aware circuit design, noise modeling, and integration with Google’s quantum hardware. It is distinct from the others in its NISQ focus and hardware-oriented abstractions.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
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📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/2920
Author: @dakshp26
Created: 2/18/2026
Status: ✅ Merged
Merged: 2/19/2026
Merged by: @JinyangWang27
Base:
master← Head:dakshp26-add-cirq📝 Commits (1)
062545cadd cirq library to quantum computing section📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
Project
Cirq
Checklist
Add cirq* [Cirq](https://github.com/quantumlib/Cirq) - Google-developed framework for creating, editing, and running NISQ quantum circuits with hardware-aware design.Why This Project Is Awesome
Which criterion does it meet? (pick one)
Explain: Cirq is the main open-source quantum framework from Google Quantum AI. It is widely used for NISQ (Noisy Intermediate-Scale Quantum) research, with strong support for hardware-aware circuits, noise modeling, parameterized circuits, and integration with Google’s quantum hardware. With ~4.9k GitHub stars and active development, it is a standard tool for quantum algorithm research and hardware experiments.
How It Differs
If similar entries exist, what makes this one unique?
Qiskit is IBM-focused and emphasizes broad hardware support and transpilation. PennyLane targets quantum machine learning and differentiable circuits. QuTiP focuses on quantum dynamics and open quantum systems. Cirq is built for NISQ-era hardware: it emphasizes hardware-aware circuit design, noise modeling, and integration with Google’s quantum hardware. It is distinct from the others in its NISQ focus and hardware-oriented abstractions.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.