Measurement Postulate
Track: Foundations · Difficulty: Beginner · Est: 14 min
Measurement Postulate
Overview
Up to now, we have talked about what a qubit is (a state vector) and how to picture it (the Bloch sphere). This page introduces the first rule about what we can observe: the measurement postulate.
The key idea is that measurement is a mathematical rule that takes a state and produces:
- a probabilistic outcome, and
- a post-measurement state.
We will focus on measurement in the computational basis and keep the framing rule-based rather than mystical.
Intuition
A qubit state is like a direction in a space. A measurement is like asking a yes/no question tied to reference directions.
When you measure in the computational basis, you are asking:
- “Is the state aligned with ?”
- “Or is it aligned with ?”
The state does not return a deterministic answer in general. Instead, it returns an outcome randomly—but with probabilities predicted by the state.
The second part is equally important: after you receive an outcome, the state you should use for future predictions is updated. The update rule is not an optional interpretation; it is part of the mathematical model.
Formal Description
Fix a measurement basis. For now, use the computational basis .
Let the pre-measurement state be
with normalization .
Outcomes and probabilities
Measurement in the computational basis has two possible outcomes, labeled 0 and 1.
- Outcome 0 occurs with probability .
- Outcome 1 occurs with probability .
This is the probabilistic part.
State update (projection)
If the measurement outcome is 0, the post-measurement state becomes .
If the measurement outcome is 1, the post-measurement state becomes .
This “collapse” is not a claim about what physically happens inside a device; it is the rule for updating the state in the mathematical model after conditioning on the observed outcome.
More generally, measurement can be described using projectors. For computational-basis measurement, the projectors are:
- is the dual (bra) of .
- is an operator that “projects onto the direction.”
The probability of outcome 0 is
and similarly for outcome 1.
The post-measurement state (conditioned on getting 0) is
For a single qubit in the computational basis, this reduces exactly to “the state becomes ” (or ) when the corresponding outcome is observed.
Worked Example
Let
Measurement in the computational basis yields:
- Outcome 0 with probability .
- Outcome 1 with probability .
Suppose you measure and observe outcome 1.
- The post-measurement state is .
- If you immediately measure again in the computational basis, you will get outcome 1 with probability 1.
This is a simple but crucial consequence of the update rule: a basis measurement prepares the system in the corresponding basis state.
Turtle Tip
Separate two questions: “What probabilities will I see?” (computed from the state) and “What state should I use after I see an outcome?” (given by the update rule). Keeping these distinct removes a lot of confusion.
Common Pitfalls
Don’t treat measurement as “revealing a hidden bit value.” For a general state, the outcomes are genuinely probabilistic even if the state is perfectly known.
Also, don’t forget the state update. Many beginner mistakes come from calculating the right outcome probabilities and then continuing to reason using the pre-measurement state.
Quick Check
- If you measure a qubit and observe outcome 0, what is the post-measurement state?
- If a qubit is already in , what is the probability of measuring 0 in the computational basis?
What’s Next
The measurement postulate tells you how outcomes and post-measurement states work. Next we will zoom in on the probability rule itself—Born’s rule—and practice applying it carefully with multiple examples.
