Variational Quantum Eigensolver (VQE) Example - Qiskit Typing CST Test
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Variational Quantum Eigensolver (VQE) Example — Qiskit Code
Minimal VQE circuit for demonstration.
from qiskit import QuantumCircuit, Aer, execute
qc = QuantumCircuit(2,2)
qc.h(0)
qc.cx(0,1)
qc.rx(0.5,0)
qc.ry(1.2,1)
qc.measure([0,1],[0,1])
simulator = Aer.get_backend('qasm_simulator')
result = execute(qc, simulator).result()
counts = result.get_counts()
print('VQE result:', counts)Qiskit Language Guide
Qiskit is an open-source Python framework for quantum computing, allowing users to design, simulate, and execute quantum circuits on both simulators and real quantum hardware.
Primary Use Cases
- ▸Designing and simulating quantum circuits
- ▸Running quantum algorithms on IBM Quantum hardware
- ▸Quantum chemistry simulations
- ▸Quantum machine learning experiments
- ▸Optimization and combinatorial problem solving
Notable Features
- ▸Python-based quantum circuit construction
- ▸Simulation of quantum circuits on classical computers
- ▸Access to IBM Quantum cloud devices
- ▸Built-in visualization tools for circuits and results
- ▸Integration with machine learning and optimization modules
Origin & Creator
Qiskit was created by IBM Research in 2017 to provide an open-source framework for quantum computing accessible to both researchers and developers.
Industrial Note
Qiskit is widely used in research, quantum algorithm development, optimization problems, chemistry simulations, and quantum machine learning.