Notation of the approximation in quantum phase estimation algorithm

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SUMMARY

The discussion focuses on the notation of approximation in the quantum phase estimation algorithm, specifically examining two definitions of the error term, δ. In Case 1, the approximation is defined as φ = a/2m + δ, where 0 < |δ| ≤ 1/2m+1, based on Cleve et al.'s work. In Case 2, δ is defined as δ ≡ φ − b/2t, where 0 ≤ δ ≤ 2−t, following Nielsen and Chuang. The author questions the preference for the first definition in literature, which appears less accurate compared to the second.

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  • Familiarity with binary representation and bit approximation
  • Knowledge of error analysis in quantum computing
  • Basic concepts from quantum information theory, particularly from Cleve et al. and Nielsen & Chuang
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  • Research "Quantum Phase Estimation Algorithm" for foundational knowledge
  • Study "Error Analysis in Quantum Computing" to understand approximation errors
  • Examine "Binary Representation in Quantum Algorithms" for insights on bit approximations
  • Review "Cleve et al. and Nielsen & Chuang on Quantum Algorithms" for deeper context on definitions of δ
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Peter_Newman
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I'am interested in the notation of the approximation in quantum phase estimation algorithm.
In the literature there are different definitions, which I divide into two cases here. Both different in their definition of the ##\delta##. In both cases I start with a quote of the source and show an example of how I understand this in that context.

Let ##\phi_\text{exact} = \varphi_\text{exact} = 0.1011_2## in this scenario we limit our approximation of the phase (##\varphi,\phi##) to 2 Bits.

Case 1:

... let ##\frac{a}{2^m} = 0.a_1...a_m## be the best ##m##-bit estimate of ##\phi##. Then ##\phi = \frac{a}{2^m} + \delta##, where ##0<|\delta|\leq \frac{1}{2^{m+1}}## [Cleve et al. from quant-ph/9708016, p11]

With ##m = 2## Bits e.g. best we can get with ##0 < |\delta| \leq \frac{1}{2^{m+1}}## is:

##\phi_\text{approx} = 0.10_2 + (-0.001_2 \leq \delta \leq 0.001_2) = 0.10_2 + 0.001_2##, since maximum value of ##\delta## is ##\frac{1}{2^3} = 0.001_2##, we leave out ##0.0001## in case of ##\delta## as defined above. I assumed ##0.10_2## is the best estimate we can get with two bits.

Case 2:

Let ##b## be the integer in the range ##0## to ##2^t−1## such that ##b/2^t = 0.b_1 ... b_t## is the best ##t## bit approximation to ##\varphi## which is less than ##\varphi##. That is, the difference ##\delta ≡ \varphi − b/2^t## between
##\varphi## and ##b/2^t## satisfies ##0 ≤ \delta ≤ 2^{−t}##. [Nielsen and Chuang from QC, p223]

With ##t = 2## Bits e.g. best we can get with ##0 < \delta \leq \frac{1}{2^{t}}## is:

##\varphi_\text{approx} = 0.10_2 + (0 < \delta \leq 0.01_2)= 0.10_2 + 0.0011_2##, we see with ##\delta## defined in this way, we get a better approximation. We can at least describe the missing part of delta here exactly. I assumed ##0.10_2## is the best estimate we can get with two bits.My final question is, why do people in the literature also use the first definition of delta (##0<|\delta|\leq \frac{1}{2^{m+1}}##), which would be more inaccurate according to my calculation?I hope that I have written my question understandably and I am very much looking forward to your opinions on this.
 
Last edited:
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Unfortunately, I haven't made any progress myself, otherwise I would have presented a solution here. Therefore, I am still interested in helpful tips and hints. Is the question so far clear, or is there a need to concretize it a bit?
 

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