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Content LAMARR Efficient Light Source Placement using Quantum Computing tU teetmische universtat Fraunhofer Distance between floor tiles is detined as the fewest rom noise voxespace illustration of the game- specific distance functon Light level decreases linearly with distance; multiple ated with the max function withTss VSES The main optimization problem is to light up all floor ties to a given minimum light level using as few torches as possible estrines Binary Opinication (QUBO) is a of Model iti To bring above pro oblem into QUBO form, we assign fixed indices 1 . n to all floor tiles. al raisin ary variable x to c each tile, which res if a i torch is placed on it This way, a torch placement is re presented by a binary of size n. To use as few torches as possible, we need to if nice more To formulate our constraints, we first define a matrix D u whose entries are Ay -1(45.5) S Lank 6 - Lain), Vi,J (n) Now, to ensure that tiles are property lit, we need to ensure the following vi 27d, (Da), 21 subject to Da 1 optimization problem with n inequality constraints. As QUBO, by definition , we use ADMM to Integrate the constraints into a ing Lagrange multipliers, which we earn a single unconstrained Algorithms 1 Alternating Direction Method of Multipliers (ADM? tagange mutticlars A and u, which we then Solvable or Quantum computer nerated from Perlin noise. Those Instances with few le results with no constraint violations, using b. - QA

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Junior developers pushing code straight to production is the tech equivalent of giving car keys to someone who just got their learner's permit. The terrifying confidence of asking "How much review do I need?" only to immediately decide "None? I merge now. Good luck, everybody else!" perfectly captures that moment when inexperience meets fatal optimism. Senior devs watching this unfold are already updating their resumes while the production server starts smoking. That merge button might as well be labeled "Career Russian Roulette."

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