## 1 Introduction  
Physics-based simulation methods are increasingly studied to realistically represent virtual objects, thus enabling their physical properties to resemble those of real-world entities. Since realistic motion representation plays a crucial role in enhancing visual realism, the simulation of deformable objects has become a central focus of computer graphics research. Recently, such simulations have gained prominence in applications like medical simulations and education, facilitated by the use of diverse physics engines such as Unity, Unreal, and CryEngine [1]. In this study, simulations were implemented using the Unity engine, a versatile platform that supports various operating system environments, including Windows, Linux, and iOS, and finds application across multiple domains [2, 3, 4]. Among physics-based simulations, cloth simulation represents a vital research area to achieve realistic visual depictions of objects like clothing, curtains, and flags [5]. Cloth simulations demand accurate physical modeling along with high computational performance to support real-time interaction. However, increased complexity, particularly with numerous nodes, leads to elevated computational costs and potential performance degradation [6, 7, 8, 9]. Since the 1980s, numerous researchers, including [PERSON] et al. and [PERSON] et al.,have explored the Mass-Spring System approach for deformable object simulation, particularly in the context of cloth simulation algorithms. The Mass-Spring System represents deformable materials using a network of mass nodes connected by springs, providing a relatively straightforward structural model; however, it presents inherent limitations in physical accuracy [10; 11; 12; 13]. Conversely, the Finite Element Method (FEM), which simulates the elastic deformability of objects, excels in accurately modeling complex physical properties, especially for 3D deformable objects. Nevertheless, FEM is predominantly used in high-quality rendering scenarios due to its intensive computational demands, making it less suitable for real-time applications [14; 15; 16]. More recently, a range of algorithms has emerged to enhance the accuracy and efficiency of real-time simulations. Among these, Vertex Block Descent (VBD) and Position-Based Dynamics (PBD), which this study examines, are notable for their respective strengths and weaknesses. PBD is widely recognized for its robust and intuitive handling of object positions, yielding stable and visually coherent results across various simulations, while supporting real-time performance. It is particularly effective in handling inter-object and self-collisions [17; 18]. However, PBD's frame-by-frame computational approach can lead to inaccuracies in object representation during larger time-step simulations [19]. On the other hand, VBD leverages block-based parallel processing to enable stable and efficient performance, even with high-resolution meshes and increased node counts. However, the block-wise processing nature of VBD may introduce accuracy challenges in more complex simulation scenarios [20]. Real-time simulation plays a crucial role in interactive content, such as games, VR, and AR. Maintaining a stable frame rate (fps) is essential to achieve real-time responsiveness, with minimum fps requirements differing by application: 30 fps for animations, 60 fps for games, and 90 fps for VR and AR environments [21; 22; 23]. In this study, we implemented real-time cloth simulation using two algorithms (VBD and PBD) and compared their performance. The simulations were evaluated under identical conditions in terms of node count and time steps, and the scenarios included hanging, object-to-object collision, and self-collision to assess fps consistency for each algorithm. Table 1 below compares the advantages and disadvantages of each algorithm. In this paper, we implement and compare cloth simulations using both the VBD and PBD algorithms.