Developing Quantum Expressions using QUBO

In summary, a QUBO expression has been developed using a Quantum Annealing approach that can find the two ways of summing the numbers {1, 2, 3, 4, 5} to 8 by selecting 3 of the numbers. The expression includes an objective function and a penalty term to ensure the desired solution is reached.
  • #1
rpthomps
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TL;DR Summary
I want to build an expression to solve the two ways to sum to the value of 8 using a set of five numbers 1 , 2, 3, 4, 5 and the criteria is only three numbers can be chosen.
Hi there, I would like some help developing a QUBO expression where a Quantum Annealing approach would find the two ways of summing the 5 numbers {1 2 3 4 5) to 8 by selecting 3 of the numbers. I am basing this off of a dwave.sys video example I found on their site.

My initial kick at the can, looks likes this:

(x1+2x2+3x3+4x4+5x5-8)2+(x1+x2+x3-3)2

I saw a chart in a paper with penalties so I guess, I would also subtract (x1x2+x2x3+x1x3)

What I would like is another expression of a similar vein with the solution so I could analyze it an understand what is happening. Any thoughts/help would be appreciated.
 
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  • #2
Here is a QUBO expression that will find the two ways of summing the 5 numbers {1, 2, 3, 4, 5) to 8 by selecting 3 of the numbers: QUBO: minimize (x1 + 2x2 + 3x3 + 4x4 + 5x5 - 8)^2 + (x1 + x2 + x3 - 3)^2 + (x1x2 + x2x3 + x1x3)where x1, x2, x3, x4, x5 are binary variables (0 or 1). The first two terms in the QUBO expression are the objective function. The third term is the penalty term, which penalizes any solutions that have more than three variables set to 1. The solution to this QUBO expression is x1 = 1, x2 = 1, x3 = 1, x4 = 0, x5 = 0. This corresponds to {1,2,3} as the three numbers that sum to 8.
 

1. What is QUBO and how does it relate to quantum expressions?

QUBO stands for Quadratic Unconstrained Binary Optimization, and it is a mathematical framework used to model and solve optimization problems. Quantum expressions are mathematical expressions that involve quantum variables and operations, and QUBO can be used to develop these expressions for quantum computing applications.

2. What are the advantages of using QUBO for developing quantum expressions?

QUBO allows for the efficient representation of complex optimization problems, making it easier to develop and implement quantum expressions. It also allows for the use of quantum annealing, a type of quantum computing that can quickly find solutions to optimization problems.

3. Are there any limitations to using QUBO for developing quantum expressions?

One limitation is that QUBO is only applicable to certain types of optimization problems, specifically those that can be formulated as a quadratic objective function with binary variables. It may not be suitable for more complex optimization problems.

4. How can QUBO be used in real-world applications?

QUBO has been used in a variety of applications, including machine learning, financial portfolio optimization, and energy management. It has also been used in the development of quantum algorithms for solving optimization problems on quantum computers.

5. What are some resources for learning more about developing quantum expressions using QUBO?

There are many online resources available for learning about QUBO and its applications, including research papers, tutorials, and online courses. Some popular resources include the D-Wave Leap quantum cloud service, the Qiskit open-source quantum computing framework, and the Quantum Open Source Foundation (QOSF) Mentorship program.

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