 We solve the Poisson equation, one of the most critical and computational-intensive tasks in scientific computing , with different source terms. We test and evaluate PINN performance under different  configurations (depth, activation functions, input data set distribution , and transfer learningimpact).
<clarity>  We solve the Poisson equation, one of the most critical and computational-intensive tasks in scientific computing , with different source terms. We test and evaluate PINN performance under different  configurations (depth, activation functions, input data set distribution , and transfer learningimpact).
 We solve the Poisson equation, one of the most critical and computational-intensive tasks in scientific computing . We characterize PINN linear solvers in terms of accuracy and performance under different configurations (depth, activation functions, input data set distribution , and transfer learningimpact).