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Updated: Aug 5, 2026
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Published on: September 8, 2023
Solving the Portfolio Optimization Problem on a Photonic Quantum Computer
Łukasz Grodzki1, Mateusz Slysz1,2, Grzegorz Waligóra1
1Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 61-138 Poznań, Poland.
Entropy (Basel, Switzerland)
|July 28, 2026
Summary
Photonic quantum computing, using the Binary Bosonic Solver, successfully tackles portfolio optimization problems. This hybrid quantum-classical algorithm demonstrates practical potential for complex combinatorial optimization tasks on current hardware.
Area of Science:
- Quantum computing
- Combinatorial optimization
- Photonic quantum computing
Background:
- Combinatorial optimization problems are increasingly complex.
- Photonic quantum computers offer a promising avenue for sampling-based optimization.
- The Binary Bosonic Solver is a hybrid algorithm for photonic processors.
Purpose of the Study:
- Investigate the Binary Bosonic Solver for portfolio optimization.
- Evaluate feasibility on photonic quantum hardware.
- Analyze algorithm behavior under varying parameters.
Main Methods:
- Applied Binary Bosonic Solver to portfolio optimization.
- Generated benchmark instances from historical financial data.
- Conducted experiments on a simulator and the ORCA PT-1 quantum processor.
Main Results:
- Portfolio optimization successfully executed on photonic quantum hardware.
- Binary Bosonic Solver consistently yielded feasible, high-quality solutions.
- Results compared favorably against classical optimization algorithms.
Conclusions:
- Photonic quantum computing is viable for current portfolio optimization.
- The Binary Bosonic Solver shows practical potential for combinatorial optimization.
- This work highlights the capabilities of photonic quantum processors.
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