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I am trying to formulate a problem as QUBO problem and am not able to transform the inequality constraint.

$$ \sum_i^N x_i \geq 1 $$ into a suitable penalty function. For N = 2, the penalty term can be written as $$ P(1-x_1-x_2+x_1x_2)$$ as mentioned in A Tutorial on Formulating and Using QUBO Models. Can someone help me in generalising the above constraint to equivalent penalty.

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It would help if you used slack variables and squared penalties. One way of doing it is by defining the following penalty $$P\left(\sum_{i=1}^{N}x_i - 1 - Z \right)^2,$$ where $Z$ is an integer variable such that $0 \leq Z \leq N-1$.

If you use the D-Wave API, I believe you can easily define an integer (discrete) variable $Z$. If you use something else, you may need to express $Z$ as an expansion of auxiliary binary variables: $$ Z = \sum_{k=0}^{M-1} 2^ky_k + ry_M, $$ where $M = \lfloor \log_2 Z \rfloor$ and $r$ is the remainder so that $Z \leq N-1$. The remainder can be written as $r = N + 1 - 2^M$. For more details on this, see Section 2.4.

Intuitively, whenever $\sum_i x_i \geq 1$, the values of $Z$ make the entire penalty term disappear. However, when $\sum_i x_i =0$, no matter what $Z$ is, we get the penalty $P(1 + Z)^2$.

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