State what scales in a quantum limit
Derive independent-probe and entangled-probe phase scaling from a normalized collective generator and compare equal resource budgets honestly.
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The question for today
What you’ll understand
- Derive shot-noise and Heisenberg scaling for a fixed linear phase generator.
- Keep probe number, interrogation time, and repetitions separate.
- Identify why noise, multipass exposure, and phase aliases change a resource comparison.
Calling a measurement Heisenberg limited is incomplete until the resource and encoding are specified. The familiar inverse-square-root and inverse-number phase scalings refer to a particular linear generator, a fixed interrogation, and ideal preparation and readout. They describe how information can grow as more probes participate coherently. Repetitions still matter, and the phrase does not guarantee the same scaling under loss, drift, nonlinear interactions, or a different accounting of time.
Fix the generator before counting probes
Take spin-one-half probes with dimensionless generator , and encode one common phase through . For independent equatorial inputs, each single-probe generator variance is . Independent variances add, giving collective variance and quantum Fisher information . Convexity extends the information ceiling to separable mixtures for this local linear encoding. With independent complete preparations, the regular locally unbiased phase standard-deviation bound is .
This is often called shot-noise scaling even when the probes are atoms rather than detected photons. The name refers to independent contributions, not to a universal source of all laboratory noise. Technical noise can make precision worse, and correlations can change the scaling. A comparison must keep the generator's single-probe spectral range fixed. Increasing the coupling strength with probe number changes the physical encoding and cannot be credited solely to preparing a better state under the original resource model.
Use the full collective spectral range
The collective generator has extreme eigenvalues and . An equal superposition of their eigenstates, the GHZ state, has variance , so its phase quantum information is . A suitable collective coherence readout can access a fringe whose argument is . Repeating the entire preparation times gives the local standard-deviation benchmark . The gain arises from a larger spread of generator eigenvalues, not from eliminating quantum fluctuations.
The faster fringe also repeats more often. A single enhanced fringe cannot choose the correct phase interval across a full turn, and a local precision number does not account for that ambiguity. Practical estimation can combine different group sizes or start with a coarse measurement. Those preparations consume resources. Moreover, creating and reading the GHZ coherence must be feasible at the required size. Treat the scaling derivation as an idealized information ceiling under explicit operations, then compare a complete protocol that actually obtains unambiguous estimates.
Compare complete resource budgets
If the total number of particle interrogations is , the ideal GHZ total phase information is rather than merely . Increasing group size at fixed Q therefore improves the local bound within the ideal model, while reducing the number of independent preparations. That change can undermine asymptotic inference or branch identification. At fixed N, repeating the experiment improves standard deviation only as the inverse square root of m for both strategies. Never substitute a total particle count for N in one formula while leaving m implicit in another.
A single probe making several coherent passes can accumulate the same phase amplification as several entangled probes. Counting only detected particles would hide those extra interactions and longer exposure. Frequency estimation additionally depends on interrogation duration, and the number of repetitions available in a fixed elapsed time falls as cycles get longer. Loss and dephasing may grow with either group size or duration. Nonlinear generators can produce other exponents, but those exponents refer to different interactions and need their own energy, time, and coupling budgets.
Work it through
Equal particle interrogations, different grouping
Use a fixed interrogation time and one hundred particle interrogations. Compare preparations of independent equatorial probes with twenty-five ideal four-probe GHZ preparations. Assume usable readout and known local phase branch.
Both designs consume particle interrogations. The independent preparation contributes phase information per batch, so its total is .
The four-probe GHZ preparation contributes per batch. Its total information is , four times the independent total at the same declared particle-interrogation budget.
Taking inverse square roots gives local standard-deviation benchmarks and . The improvement is a factor of two in standard deviation and four in variance; it is not a factor of four in both.
The ideal GHZ grouping halves the phase standard-deviation bound in this comparison. The result assumes noiseless encoding, an already identified phase branch, and successful preparation and readout without extra budget penalties.
The living notebook
Explore the model
Interactive lab · sampling
Check the independent repetition exponent
Reset and set p = 0.5 and n = 25, then predict sample-mean variance 0.01. Reset and set p = 0.5 and n = 100, predicting variance 0.0025. The exact distributions show the square-root reduction of standard deviation under independent sampling. Playback highlights exact count outcomes and does not resample data. This lab has no entanglement or collective generator, so it illustrates only the independent baseline, not Heisenberg scaling.
- Mean sample proportion
- 0.5
- Sample-mean variance
- 0.0125
- Uniform CDF error bound
- ≤ 0.1062
Exact binomial masses for the mean of n independent Bernoulli trials, compared with normal mass between adjacent half-count boundaries; normal tails outside the finite support remain outside the bars. Playback highlights outcomes, not random samples. The Berry–Esseen bound applies to standardized CDFs, not individual bars or continuity-corrected errors. At p = 0 or 1, normal comparison and that bound are disabled. Normal-CDF evaluation uses a numerical approximation with absolute error below 7.5×10⁻⁸ (at most 1.5×10⁻⁷ per interval, before rounding). Parameter changes pause playback and recompute the model at the current elapsed time. Reset restores both parameters and returns time to zero. Playback starts paused. Adjust either parameter, then choose Play or Step.
Look forFour times as many independent outcomes halves standard deviation; coherent grouping is a separate physical resource.
Pause & reason
Check your understanding
Your turn
Try it yourself
An ideal experiment uses sixteen independent preparations of eight probes. Compute total phase information and the local phase bound for GHZ inputs and independent equatorial inputs. State the total particle-interrogation count.
Take a moment to make a prediction or work it out on paper. Open a hint when you need one.
Give me a hint
Apply the per-batch information appropriate to each preparation, then multiply by sixteen.
Compare with the solution
The budget is particle interrogations. GHZ inputs give information and bound . Independent inputs give information and bound . The ratio of standard-deviation bounds is . Both calculations presume the same interrogation duration, valid local inference, and ideal readout; the arithmetic does not demonstrate that an eight-probe GHZ state survives realistic noise.
Keep the idea
Take it with you
- Shot-noise and Heisenberg exponents require a declared fixed generator and resource.
- GHZ information scales quadratically with probe number in the noiseless linear model.
- Independent repetitions retain square-root improvement, and multipass interactions must be counted.
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