The paper introduces a novel method called well-tempered metadynamics, which addresses the limitations of traditional metadynamics by providing a more robust and controllable approach to estimating free energy surfaces (FES). The method uses an adaptive bias potential that converges to the exact FES over time, allowing for the exploration of physically relevant regions of the order parameter space. The authors demonstrate the effectiveness of this method by applying it to the reconstruction of the free energy landscape of alanine dipeptide, showing that it can accurately estimate the free energy difference between metastable states with minimal computational overhead. The key features of well-tempered metadynamics include the ability to tune the bias deposition rate and the temperature difference, which helps in focusing computational efforts on relevant regions and reducing errors. The method is shown to be effective in both low and high-dimensional systems, making it a valuable tool for studying complex molecular systems.The paper introduces a novel method called well-tempered metadynamics, which addresses the limitations of traditional metadynamics by providing a more robust and controllable approach to estimating free energy surfaces (FES). The method uses an adaptive bias potential that converges to the exact FES over time, allowing for the exploration of physically relevant regions of the order parameter space. The authors demonstrate the effectiveness of this method by applying it to the reconstruction of the free energy landscape of alanine dipeptide, showing that it can accurately estimate the free energy difference between metastable states with minimal computational overhead. The key features of well-tempered metadynamics include the ability to tune the bias deposition rate and the temperature difference, which helps in focusing computational efforts on relevant regions and reducing errors. The method is shown to be effective in both low and high-dimensional systems, making it a valuable tool for studying complex molecular systems.