5
votes
Can QUBO solve this inverse Ising problem?
Yes it is possible, but it may not be as efficient as the other methods listed in that PDF file. In fact, I'm still not sure there's any problem for which QUBO is the best way to solve it (see this: ...
- 1,268
4
votes
Can QUBO solve this inverse Ising problem?
The log-likelihood function $L$ is continuous while QUBO is discrete. If you really wanted to formulate it as a QUBO, this is how I would do it. In summary, the steps would be as follows:
$L \to \text{...
- 141
4
votes
Accepted
Trouble implementing a line-search algorithm
Your bisection code is returning a tuple of [a,b] but in your main function you are only retrieving a, which should be causing ...
- 11.9k
3
votes
How do I arrive at the form given in this paper, for the QUBO version of the number partitioning problem?
\begin{align}\text{diff}^2&=c^2+4\left(\left(\sum s_jx_j\right)^2-c\sum s_jx_j\right)\\&=c^2+4\left(\sum s_j^2x_j^2+\sum_{\rm cyc}s_ks_\ell x_kx_\ell-c\sum s_jx_j\right)\tag1\\&=c^2+4\left(...
- 5,342
3
votes
Accepted
Why are the bounds 3 and 6 instead of 7, in this binary expansion of a slack variable in this QUBO problem?
According to the equality constraint (the equal to 4 one), at least two of the $x_{?}$ are 1. Therefore, the slack for the 1st constraint is at most 3.
According to the equality constraint, the worst ...
- 523
3
votes
Accepted
How to approximate an uncertain constraint?
Yes, it is always mathematically guaranteed that $$\sum_i \min_\theta a_{i, \theta} ≤ \min_\theta \sum_i a_{i, \theta} \tag{1}$$ and that $$\sum_i \max_\theta a_{i, \theta} ≥ \max_\theta \sum_i a_{i, \...
- 168
2
votes
How to approximate an uncertain constraint?
My simple logic says your constraint states that the lowest of the lhs should always be greater than/equal to the highest values possible in the rhs within the given interval. If you take sum then you ...
- 3,343
2
votes
How to exponentiate binary variables in QUBO-type problems?
Luckily in this case, the exponential can be treated in a way very similar to how we're already familiar. If we use the example that I chose in my answer to your recent question, we would have, where ...
- 1,268
2
votes
Speed of convergence for minimizing Rosenbrock's function
Considering that all your plots will be for the same problem you don't need to normalise by using relative error, so you can use either representation as long as you use it consistently for everything....
- 11.9k
2
votes
Armijo Line Search Parameters
You are correct that the optimal choice of parameters for the Armijo line search can vary depending on the problem and the optimization algorithm being used. In practice, there are several common ...
- 184
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