Validity of Mathematical Proof of Uncertainty Principle

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SUMMARY

The forum discussion centers on the validity of a proof of the Heisenberg Uncertainty Principle found in Walter Strauss's textbook "Partial Differential Equations." The proof utilizes the Cauchy-Schwartz inequality and Parseval's Equality to establish that the product of the expectation values of position and momentum, \(\overline{x} \cdot \overline{p}\), is greater than or equal to 1/2. A key point of contention is the assertion that \(\int |ip F(p)|^2 \frac{dp}{2\pi} = \overline{p}^2\), which raises questions about the Fourier transform of \(xf(x)\). The discussion highlights the need for clarity on this mathematical relationship.

PREREQUISITES
  • Understanding of Fourier transforms and their properties
  • Familiarity with Cauchy-Schwartz inequality
  • Knowledge of Parseval's Equality
  • Basic concepts of quantum mechanics and expectation values
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  • Study the properties of Fourier transforms in quantum mechanics
  • Review the Cauchy-Schwartz inequality and its applications
  • Explore Parseval's Equality in the context of signal processing
  • Read "Quantum Mechanics: Concepts and Applications" by Nouredine Zettili for a deeper understanding of quantum mechanics
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Students and professionals in physics, particularly those studying quantum mechanics, mathematicians interested in applications of PDEs, and anyone seeking to understand the Heisenberg Uncertainty Principle in depth.

phreak
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I saw a rather easy proof of the Heisenberg Uncertainty Principle in a PDE textbook the other day, but I'm not sure if it's correct. The proof goes as following:

Note that \left| \int xf(x) f'(x) \right| \le \left[ \int |xf(x)|^2 dx \right]^{1/2} \left[ \int |f'(x)|^2 dx \right]^{1/2}, by the Cauchy-Schwartz inequality. Now, the Fourier transform of df/dx is ipF(p), so along with Parseval's Equality, the right side of the above equation equals:

\overline{x} \cdot \left[ \int |ipF(p)|^2 \frac{dp}{2\pi} \right]^{1/2} = \overline{x} \cdot \overline{p}.

Integrating the left side by parts, we then get that it is 1/2, so that \overline{x} \cdot \overline{p} \ge 1/2.

Now, here is my problem with this proof. I don't understand why \int |ip F(p)|^2 \frac{dp}{2\pi} = \overline{p}^2. Using Parseval's equality, this would be fine if the Fourier transform of xf(x) is kF(k), but as far as I know this isn't true. Can anyone point me in the right direction?
 
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phreak said:
I don't understand why \int |ip F(p)|^2 \frac{dp}{2\pi} = \overline{p}^2.

Whatever the observable O, if \psi(o) is the wave function in the representation defined by O (that means, \psi(o) is the amplitude of O having the value o), and whatever the function f(o), the expectation value of f(o) is


\int f(o)|\psi(o)|^2 do = \overline{f(o)}


Apply this to o=p and f(o)=o2.
 
can anybody here please suggest me a book for quantum mechanics.(i'm good at math)
 
@phreak
can please give the name of the book you reffered.
 
Thank you for your comments.

Josyulasharma: The book this is from is 'Partial Differential Equations' by Walter Strauss.
 
Josyulasharma said:
can anybody here please suggest me a book for quantum mechanics.(i'm good at math)

i) don't ask unrelated questions to the thread, i.e don't get off topic.

ii) We have science book sub forum here, look around an you'll find it.

iii) when you do find it, please search for old threads, this question has been asked 100000 times before,
 

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