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Quantum entanglement

As explained in Building Quantum Software with Python

Quantum entanglement is a quantum correlation in which a composite system's state cannot be represented as independent states of its constituent systems.

Quantum entanglement links qubits so their combined state cannot be described as independent states, making individual measurement outcomes dependent. It enables conditional transformations and therefore nontrivial quantum computation. section 1.3 section 4.2.1

Use product and nonproduct states to distinguish independence from entanglement:

  • A product state combines two single-qubit states; its measurement outcomes are independent, like two independent biased coins. section 4.2.1
  • A nonproduct state cannot be factored into independent single-qubit states; its qubits are entangled and their measurement outcomes are linked. section 4.2.1
  • Entanglement is essential for meaningful quantum computing but can increase processing demands and coherence costs. section 4.2.1

Bell states

The state [√0.5, 0, 0, √0.5] permits only matching outcomes, 00 and 11, each with probability 0.5. The other Bell states similarly encode linked two-qubit outcomes through sign or position changes. section 4.2.1

bell_state1 = [sqrt(0.5), 0.0, 0.0, sqrt(0.5)]

bell_state2 = [sqrt(0.5), 0.0, 0.0, -sqrt(0.5)]

Inspect Python state-vector definitions for the first two Bell states. section 4.2.1

How Building Quantum Software with Python covers it

How deep it goes
Defines product and nonproduct states, demonstrates Bell-state probabilities, and stops short of deriving their construction.
Examples
Uses dependent-coin intuition, linked 00 and 11 outcomes, and four Python-defined Bell-state vectors.
What it assumes
Assumes qubits and measurement outcomes while comparing independent and linked states through coin analogies.
What you can do after
Build it from scratch by representing two-qubit product and Bell states as Python amplitude vectors.
How it connects
Links quantum states, qubits, conditional transformations, measurement outcomes, product states, and Bell states.

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This explainer was generated by Manning's knowledge graph from the text of Building Quantum Software with Python. The section links point to the parts of the book it draws on.