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Qadence
Overview
Qadence
Getting started
Installation
Contributing
Code of conduct
License
Development & Info
Contributing
Code of conduct
License
Contents
Block system
Parametric programs
Quantum models
Quantum registers
State initialization
Noisy Simulation
Arbitrary Hamiltonians
Time-dependent generators
QML Constructors
Wavefunction overlaps
Backends
State conventions
Serialization
Useful info
State conventions
Serialization
Tutorials
Overview
Digital-analog quantum computing
Basic operations on neutral-atoms
Fitting a function with analog blocks
Restricted local addressability
Pulse-level programming with Pulser
Fitting a function with a Hamiltonian ansatz
Solve a QUBO problem
CNOT with interacting qubits
Variational quantum algorithms
Configuring a QNN
Quantum circuit learning
Classification with QNN
Solving MaxCut with QAOA
Solving a 1D ODE
QCNN model
ML Tools
Training
Data and Configurations
Training Callbacks
Accelerator
CPU Training
GPU Training
Advanced Tutorials
Quantum circuits differentiation
Custom quantum models
Projector blocks
Profiling and debugging on CUDA devices
Submission to Pasqal Cloud
Realistic simulations
Measurement protocols
Simulated errors
Error mitigation
Architecture and sharp bits
Drawing
API
Block system
Operations
Register
QuantumCircuit
Parameters
State preparation
Noise
Constructors
Transpilation
Execution
Quantum models
QML tools
Serialization
Types
Drawing
Pasqal Cloud Connection
Abstract backend
PyQTorch
Pulser
DifferentiableBackend
Pasqal organization on GitHub
Pasqal page on LinkedIn
Pasqal channel on YouTube
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Advanced Tutorials
In this section, advanced programming concepts and implementations in Qadence are examplified.
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GPU Training
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Quantum circuits differentiation