Quantum Programming with Q#
Microsoft Quantum Team
6 courses · 19 tutorials
Microsoft Quantum Team
MIT xPRO / Isaac Chuang, William Oliver, Peter Shor, Aram Harrow
Hasso Plattner Institute / IBM Quantum
Purdue University
Quantinuum
IonQ Researchers
A comprehensive guide to the Variational Quantum Eigensolver: ansatz design, optimizer selection, barren plateaus, and a complete H2 ground state calculation using Qiskit's Estimator primitive.
Reduce molecular simulation cost by selecting active orbitals in PennyLane. Combine active space selection with VQE for accurate molecular ground state energies.
Set up molecular Hamiltonians in OpenFermion, apply Jordan-Wigner mapping to convert fermionic operators to Pauli strings, and build a VQE circuit in Cirq.
Implement a simplified ADAPT-VQE algorithm in PennyLane. Build an operator pool, greedily select operators by gradient magnitude, grow the ansatz iteratively, and compare convergence against fixed UCCSD for the H2 molecule.
A practical overview of what quantum computers can actually do today and in the near future: chemistry simulation, optimisation, cryptography, and machine learning.
Build a complete quantum chemistry pipeline: encode the H2 Hamiltonian with OpenFermion, transform it to qubits via Jordan-Wigner, then find the ground state energy using VQE on Qiskit's statevector simulator.
How quantum computers simulate molecular systems: from second quantization and fermion-to-qubit mappings to VQE and the active space approximation.
A complete walkthrough of VQE for the hydrogen molecule in Qiskit Nature, from PySCF driver and Jordan-Wigner mapping through UCCSD ansatz and classical optimization.
Build a complete VQE implementation for H2 using Cirq's parametric gates, OpenFermion for the qubit Hamiltonian, scipy for classical optimization, and the parameter shift rule for exact gradients.
Implement the Variational Quantum Eigensolver to find the ground state energy of a hydrogen molecule using PennyLane and gradient-based optimization.
Use Q# and the Microsoft.Quantum.Chemistry library to simulate molecular ground state energies, covering Jordan-Wigner encoding, Broombridge data, and phase estimation.
Simulate quantum systems by decomposing time evolution into circuits using first and second-order Trotterization. Practical implementation with Qiskit's PauliEvolutionGate and LieTrotter.
Full VQE for LiH using PennyLane's qchem module: molecular Hamiltonian, Hartree-Fock initial state, UCCSD ansatz, optimization, and potential energy surface scan.
Walk through a real VQE simulation in PennyLane: build the H2 Hamiltonian, construct a UCCSD ansatz, and converge to the ground state energy in under 50 iterations.
A complete end-to-end VQE simulation of the water molecule using Qiskit Nature: PySCFDriver setup, active space reduction from 10 electrons in 7 orbitals to 4 electrons in 4 orbitals, Jordan-Wigner mapping, UCCSD ansatz, and comparison with Hartree-Fock and CCSD references.
How VQE works: the variational principle, ansatz design, classical optimizer loop, and a complete Qiskit implementation for finding the ground state of a simple Hamiltonian.
Set up and run a molecular ground state energy calculation in Qiskit Nature: driver setup, active space selection, Jordan-Wigner mapping, and VQE optimization.
How to implement the Variational Quantum Eigensolver (VQE) using tket's parameterized circuits and scipy optimization.
Build and manipulate Hamiltonians efficiently using Qiskit's SparsePauliOp class for variational algorithms and quantum chemistry simulations.