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Quantum Computing - Notes

Overview

Quantum Computing : It's the use of quantum mechanics to run calculations on specialized hardware.

Applications

  • Artificial Intelligence
  • optimization and simulation, and data management and searching.
  • Cloud Computing
  • Healthcare
  • cybersecurity
  • data analytics
  • ...

Tools and Frameworks

  1. ProjectQ
  2. Cirq
  3. Q-CTRL Python Open Controls
  4. Quantify
  5. Intel Quantum Simulator
  6. Perceval
  7. Mitaq Tool
  8. Berkeley Quantum Synthesis Toolkit
  9. QCircuits
  10. Yao
  11. Silq
  12. Paddle Quantum
  13. Tequila
  14. Qulacs
  15. staq
  16. Bayesforge
  17. Bluqat
  18. Quantum Programming Studio
  19. Quirk
  20. QuEST
  21. XACC
  22. Quantum++
  23. Quantum Inspire 24.QuCAT
  24. QuTiP
  25. OpenFermion
  26. TensorFlow Quantum
  27. Quipper
  28. QX Quantum Computing Simulator
  29. Quantum Algorithm Zoo
  30. ScaffCC
  31. TriQ
  32. Qbsolv from D-Wave
  33. Quantum Computing Playground
  34. Microsoft LIQUi|> Other Quantum Computing Developer Tools

Src: The Quantum insider

Quantum Computing Algorithms

@TODO

Hello World!

import cirq

# Pick a qubit.
qubit = cirq.GridQubit(0, 0)

# Create a circuit
circuit = cirq.Circuit(
    cirq.X(qubit)**0.5,  # Square root of NOT.
    cirq.measure(qubit, key='m')  # Measurement.
)
print("Circuit:")
print(circuit)

# Simulate the circuit several times.
simulator = cirq.Simulator()
result = simulator.run(circuit, repetitions=20)
print("Results:")
print(result)

Expected Output:

Circuit:
(0, 0): ───X^0.5───M('m')───
Results:
m=11000111111011001000
More examples on Cirq Github repo

References

Wikipedia:

Google:

Microsoft:

Amazon AWS: - Quantum Technologies - What Is Quantum Computing - Quantum Technologies - Amazon Braket

"If you think you understand quantum mechanics, you don't understand quantum mechanics"

~ Richard Feynman