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logpsi is complex in general, that quantity is not positive if your ansatz is in the complex domain |
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In a variational Monte Carlo algorithm, expectation is
where, O is operator, x belongs to "vstate.samples", {x'} is the complete set of Hilbert space, and \Psi is variational state.
The sign of <\Psi|x> and <\Psi|x'> do matter.
However, in "netket.vqs.mc.kernels.py", it calculates O(x) in such a following way:
jnp.exp(logpsi(pars, σp) - logpsi(pars, σ)) is always positive and, then gives the wrong result when <\Psi|x'>/<\Psi|x> is negative, leading to false expectation.
I'm pondering how to fix this problem?
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