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Non-linear Multi-objective Optimization with Probabilistic Branch and Bound
Hao Huang, Zelda B. Zabinsky
https://arxiv.org/abs/2506.04554 https://

Non-linear Multi-objective Optimization with Probabilistic Branch and Bound
A multiple objective simulation optimization algorithm named Multiple Objective Probabilistic Branch and Bound with Single Observation (MOPBnB(so)) is presented for approximating the Pareto optimal set and the associated efficient frontier for stochastic multi-objective optimization problems. MOPBnB(so) evaluates a noisy function exactly once at any solution and uses neighboring solutions to estimate the objective functions, in contrast to a variant that uses multiple replications at a solution…

This https://arxiv.org/abs/2504.05549 has been replaced.
initial toot: https://mastoxiv.page/@…

Fast and direct preparation of a genuine lattice BEC via the quantum Mpemba effect
We present an efficient method for dissipatively preparing a Bose-Einstein condensate (BEC) directly on a lattice, avoiding the need for a two-staged preparation procedure currently used in ultracold-atom platforms. Our protocol is based on driving the lattice-subsystem into a non-equilibrium steady state, which we show to exhibit a lattice analog of a true BEC, where the depletion can be controlled via the dissipation strength. Furthermore, exploiting a symmetry-based Mpemba effect, we analyti…

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