The practical realization of quantum computer calculators is a challenge. Qubits, or two-level quantum systems, serve as the basis for the vast majority of quantum computing components. These qubits are the fundamental units that allow us to harness the power of quantum information processing by linking and manipulating them coherently to accomplish a wide range of quantum operations. Qubits have been implemented using various technologies, including semiconductors, superconductors, trapped ions, and hybrid technologies. All of these technologies use the same concepts, which are based on the two-level quantum system. Noise, quantum errors, and decoherence are the root causes of scalability issues. Designing multi-level systems is one technique to mitigate or, ideally, prevent these effects. In one of our recent works , we suggested a scalable method for universal quantum computation utilizing four-level cores (such as, connected 4 quantum dots) with discrete rotational symmetry (specifically, the -rotation invariance). We identified several systems that can achieve -rotation invariance. This four-level quantum system built by ’Quansistor’ allows for the achievement of universal quantum gates. We noticed substantial resilience to errors. Each quansistor is connected to four identical semi-infinite leads to facilitate integration, initialization, and reading. We demonstrated that the symmetry protects the logical processes within the quansistors from unbiased noise and provides resilience to decoherence. These cores may also be customized, allowing them to operate as programmable quantum memory units. This work demonstrates that quantum computations based on quansistors with certain symmetry are more resistant to quantum errors and decoherence than qubits technology, giving a blueprint for a 5scalable quantum computer. The quansistor total adjustment enables the creation of customized quantum circuits that may be used in a hybrid quantum machine learning model.