CASINO manual - Theory of Condensed Matter
CASINO manual - Theory of Condensed Matter
CASINO manual - Theory of Condensed Matter
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where L is a cut<strong>of</strong>f length, C is the truncation order and Θ denotes the Heaviside function.<br />
Notice that the above can be easily extended to inhomogeneities other than atoms by introducing any<br />
other coordinates appearing in the potential energy into the expressions. This is not implemented in<br />
casino yet.<br />
23.1.1 The η function<br />
Three forms <strong>of</strong> the homogeneous backflow function have been tested with casino. Following extensive<br />
tests, no advantages were found from using the rational and Gaussian forms, and only the polynomial<br />
form remains in the code,<br />
N<br />
∑ η<br />
η ij = f(r ij ; L η ) c k rij k , (175)<br />
where N η is the expansion order and {c l } are the optimizable coefficients. We expect this simple form<br />
to be flexible and efficient. The natural polynomial basis is used to improve the speed <strong>of</strong> evaluation,<br />
and rounding errors are not likely to appear for N η + C < 20 24 .<br />
k=0<br />
23.1.2 The µ function<br />
We use the following polynomial expansion for µ,<br />
N<br />
∑ µ,I<br />
µ iI = f(r iI ; L µ,I )<br />
k=0<br />
d k,I r k iI , (176)<br />
where L µ,I is the cut<strong>of</strong>f length for ion I, N µ,I is the expansion order and {d k,I } are the optimizable<br />
coefficients.<br />
23.1.3 The Φ and Θ functions<br />
Our choice for Φ jI<br />
i<br />
and Θ jI<br />
i<br />
are the following power expansions,<br />
N<br />
∑ eN,I<br />
Φ jI<br />
i = f(r iI ; L Φ,I )f(r jI ; L Φ,I )<br />
k=0<br />
N<br />
∑ eN,I<br />
Θ jI<br />
i = f(r iI ; L Φ,I )f(r jI ; L Φ,I )<br />
k=0<br />
N<br />
∑ eN,I<br />
l=0<br />
N<br />
∑ eN,I<br />
l=0<br />
N<br />
∑ ee,I<br />
m=0<br />
N<br />
∑ ee,I<br />
m=0<br />
ϕ klm,I r k iIr l jIr m ij , (177)<br />
θ klm,I r k iIr l jIr m ij , (178)<br />
where N eN,I and N ee,I are the expansion orders, L Φ,I are the truncation lengths and ϕ klm,I and θ klm,I<br />
are optimizable coefficients.<br />
23.2 Constraints on the backflow parameters<br />
In SJ wave functions it is common practice to impose the electron–electron cusp conditions on the<br />
parameters in the Jastrow factor and the electron–nucleus ones on the orbitals in the Slater determinant.<br />
Backflow can modify the cusp conditions; we have constrained the backflow parameters so that<br />
they do not.<br />
When AE atoms are present, it can be shown that the electron–nucleus cusp conditions cannot be<br />
fulfilled unless there is no homogeneous backflow term present. However, this issue can be bypassed<br />
by smoothly truncating η(r ij ) around such nuclei. This is automatically done by casino.<br />
An additional set <strong>of</strong> constraints can be added in order to satisfy the relation<br />
ξ i ({r j }) = ∇ i Y ({r j }) , (179)<br />
where Y ({r j }) is an object called backflow potential, which appears in the derivation <strong>of</strong> backflow <strong>of</strong><br />
Ref. [47]. This equation is already satisfied by both the electron–electron and the electron–nucleus<br />
24 It is estimated that numerical problems arise in the evaluation <strong>of</strong> polynomials beyond order ∼ 20 when using<br />
double-precision arithmetics. More complicated polynomial forms (e.g., Chebyshev polynomials) should be used to be<br />
able to exceed this limit.<br />
150