Awesome Quantum Resources#
Curated list of quantum computing tools, libraries, simulators, and learning resources.
Quantum Computing Frameworks#
Framework |
Language |
Provider |
Best For |
|---|---|---|---|
Python |
IBM |
Largest ecosystem, real hardware access |
|
Python |
Low-level control, noise modeling |
||
Python |
Xanadu |
ML integration, autodiff |
|
Python |
Rigetti |
Quilc compiler, Quil language |
|
Q#/Python |
Microsoft |
Topological simulation, resource estimation |
|
Python |
AWS |
Multi-backend access |
|
Python/C++ |
Clifford circuit simulation, QEC |
||
Python/C++ |
NVIDIA |
GPU-accelerated simulation |
Simulators#
Simulator |
Type |
Max Qubits |
Notes |
|---|---|---|---|
Statevector, density matrix, MPS |
~30 (SV), 100+ (MPS) |
GPU support |
|
Statevector, density matrix |
~30 |
Noise model support |
|
Statevector |
~25 |
Autodiff through simulation |
|
Statevector, distributed |
38+ (distributed) |
MPI-parallel |
|
Statevector |
40 (GPU) |
Google’s fast simulator |
|
Decision diagram |
100+ (for specific circuits) |
Memory-efficient |
Quantum Chemistry#
Library |
Focus |
Integration |
|---|---|---|
VQE, molecular simulation |
Qiskit |
|
Quantum chemistry |
PennyLane |
|
Fermion-to-qubit mapping |
Cirq, Qiskit |
|
Classical quantum chemistry |
All (via integrals) |
Quantum Machine Learning#
Library |
Focus |
|---|---|
QML with PyTorch/TensorFlow integration |
|
Quantum kernels, QNNs |
|
Hybrid quantum-classical ML |
|
PyTorch-based QML |
Error Correction#
Tool |
Purpose |
|---|---|
Fast Clifford simulation, decoder benchmarking |
|
Minimum-weight perfect matching decoder |
|
LDPC and quantum LDPC code tools |
Post-Quantum Cryptography#
Library |
Language |
Algorithms |
|---|---|---|
C |
ML-KEM, ML-DSA, SLH-DSA |
|
C |
OpenSSL 3.x PQC provider |
|
Rust |
All NIST PQC algorithms |
|
Java/C# |
ML-KEM, ML-DSA, SLH-DSA |
|
C |
Reference implementations |
|
Rust/Python |
ML-KEM-768 with QRNG |
Physics Simulation#
Library |
Focus |
|---|---|
Open quantum systems, master equations |
|
Quantum transport simulations |
|
Photonic quantum computing |
|
Neural network quantum states |
Learning Resources#
Textbooks#
Nielsen, M.A. and Chuang, I.L. Quantum Computation and Quantum Information (the “bible” of QC)
Schuld, M. and Petruccione, F. Machine Learning with Quantum Computers
Hidary, J.D. Quantum Computing: An Applied Approach
Bernstein, D.J. and Lange, T. Post-Quantum Cryptography (Springer)