simulated-bifurcation-algorithm
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Python CPU/GPU implementation of the Simulated Bifurcation (SB) algorithm to solve quadratic optimization problems (QUBO, Ising, TSP, optimal asset allocations for a portfolio, etc.).
# 💬 Pull Request Description New documentation website with Furo template and a more relevant architecture. > To build the documentation locally run: > ```bash > sphinx-build -a docs ./docs/_build/...
# 💬 Pull Request Description Based on #41, a reflexion was carried out regarding the difference between the models' dtype and the computation dtype. Because the oscillators in the SB...
# 💬 Pull Request Description When the Stop Window detects that an agent has converged, it is stored in the window's memory and a boolean tensor is sent back to...
# 💬 Pull Request Description > ⚠️ **This PR contains breaking changes. See at the bottom of this description for more information.** Some parameters of the optimization-related functions of backend...
# 💬 Pull Request Description Some tests are parametrized to automate them for all possible computation dtypes and devices. # ✔️ Check list _Before you open the pull request, make...
# 💬 Pull Request Description > ⚠️ **This PR contains breaking changes.** > Requirements: PR #55 must have been merged before merging this pull request With the latest evolutions of...
# 💬 Pull Request Description It is possible to determine the optimal value of some spins before entering the SB algorithm. This ensures that the spins will contribute optimally to...
# 💬 Pull Request Description This PR allows the user to stop manually the run of the Simulated Bifurcation algorithm from the terminal (`ctrl + C`). Instead of an error,...
Currently, the oscillators in the SB optimizer have the same dtype as the IsingCore model which itself inherits its dtype from the polynomial model defined by the user. Although it...
When the stop window is used, it could be interesting to remove the converged agents to reduce the number of computations and thus speed up the convergence of the other...