š Optimization is everywhere (like The Matrix), Using SAT solving for Quantum Computing, and how to identify optimization problems
Local Optimum: short, imperfect-yet-useful ideas - Edition #6
Welcome to a new edition of Local Optimum: a short, imperfect-yet-useful collection of ideas related to optimization, decision-making, and applied Operations Research.
Letās dive in! šŖ
1) š¶ļø Optimization is everywhere, like The Matrix
I see optimization everywhere.
Literally.
If we could take that famous quote from The Matrix and just replace those words with optimization, you'd pretty much know what's going on inside my head:
Optimization is everywhere.
It is all around us.
Even now, in this very room.
You can see it when you look out your window or when you turn on your television.
You can feel it when you go to work... when you go to church... when you pay your taxes.
It is the world that has been pulled over your eyes to blind you from the truth.
Despite Iām a big fan of The Matrix, probably (and provably) the best science fiction movie of all time, I must say those previous lines do have a point, donāt they?
I mean, I just realized I can see SAT problemsā¦
In my bathroom š
(picture taken just a few days ago)
2) āØ Using SAT solving for Quantum Computing
Efficient quantum circuit mapping gives you:
Fewer errors
Shorter runtimes
Better use of quantum resources
Why? Becauseā¦
1. š§ Quantum computers have physical constraints
Quantum processors (like those from IBM, Rigetti, or Amazon Braket) have qubits arranged in a specific topology.
But not all qubits can interact directly.
So, if your algorithm requires interactions between qubits that arenāt directly connected, you need to insert extra swap gates to bring them together.
(These swaps are costly (in time and in error rate), so minimizing them is crucial.)
2. āļø Every extra gate increases error
Quantum gates are not perfect, they introduce noise.
More gates = higher chance the entire computation will fail before it finishes.
Especially on NISQ (Noisy Intermediate-Scale Quantum) devices, the fewer the gates, the better.
NISQ devices are the current generation of quantum computers.
3. ā±ļø Execution time matters
Quantum states decohere over time.
(Decoherence is what happens when a quantum state starts to lose its "quantumness" over time.)
Shorter circuits are more likely to complete before decoherence ruins the computation.
Faster compilation ā quicker experimentation and iteration.
4. š Scalability
As quantum algorithms get more complex, mapping them efficiently is the only way to scale.
Better mapping = more powerful algorithms on limited hardware.
šÆ Soā¦
Enhancing the efficiency of mapping quantum computations onto physical quantum circuits is crucial.
And Amazon is using SAT solving to optimize quantum circuit mapping.
3) š How to identify optimization problems
Identifying optimization problems early can be the difference between smooth scalingā¦ Or costly chaos later.
So where should you look?
Identify bottlenecks, inefficiencies, or excessive costs (like long leading times in logistics).
Look for complex decision-making environments (like assigning a big staff to shifts under several constraints).
Consider scalability and impact (if throwing more people at the problem isnāt helping, thatās a sign).
In order to accomplish that, youāll need toā¦
Start with processes, asking questions about decisions.
Collect data and define problems.
Get external perspectives, like consultants, peers, or even your customers.
Want the full breakdown? I covered it in a past post š
What if one of the top three conferences in AI and MLā¦
Had a lot to say in Operations Research?
š Next Monday, Iāll share some of the most interesting papers being presented this year at ICLR, the International Conference on Learning Representations.
Itās one of the most influential AI conferences in the world; a clear window into whatās coming next in the field.
And this year, several papers are diving into OR-related topics.
š If you want to stay ahead of the curve, this roundup will be worth your time. See you Monday!
And thatās it for today!
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Have a nice day ahead āļø
Borja.
