In second quantization, the Hamiltonian describing the hopping process between two neighboring sites is given (N - number of particles and M - number of sites) by:
ˆH=J∑⟨i,j⟩ˆa†iˆaj
It can be diagonalized using Fourier series
ˆai=1√M∑kˆbke−ik⋅Ri
The ground state is given by
|GS⟩=1√N!(ˆb†k=0)N|0⟩≈C e√Nˆb†k=0|0⟩
How is the approximation justified (C ensures normalization)?
I calculated a few quantities using both states. First of all both states can be represented using site creation operators ˆai in the following way: |GS1⟩=1√N![1√MM∑i=1ˆa†i]N|0⟩
Energy - expectation value of the Hamiltonian: ⟨ˆH⟩1=2JN
⟨ˆH⟩2=2JNParticle density and fluctuations: ⟨ˆni⟩1=NM, ⟨Δˆn2i⟩1=NM(1−1M)
⟨ˆni⟩2=NM, ⟨Δˆn2i⟩2=NMTotal number of particles and fluctuations: ⟨ˆN⟩1=N, ⟨ΔˆN2⟩1=0
⟨ˆN⟩2=N, ⟨ΔˆN2⟩2=N
As @NorberSchuch mentioned in his answer below particle density fluctuations are practically the same and coincide in the thermodynamic limit.
Answer
The basic idea is that the term with the highest weight in the exponential series is exactly the desired term. Further, all of the weight is in terms with closeby particle number, and small fluctuations in this number do not matter in many cases.
(Note: I will omit the k=0 subscript and just write b† in the following for convenience.)
First, we have that
e√Nb†|0⟩=∑√Nkk!(b†)k|0⟩ .
Note that this does in fact not mean that the two states are close in any distance measure (in fact, they aren't). However, it tells us that most of the weight in the sum is in states with |k−N|≤c√N, as the variance of the Poisson distribution is N. Since in many applications, we in fact care about the number of particles per site (which is an intensive quantity and well-defined as the system size goes to infinity), and any such fluctuation in k will vanish as N→∞, both states will have the same particle density in the thermodynamic limit, and thus describe the same physics.
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