This thesis explores the impact of numerical representation on memory usage within a quantum circuit emulator architecture implemented on FPGA. Quantum circuit simulation is memory intensive due to the exponential growth of quantum state space with the number of qubits. Representing an n-qubit system requires storing many complex values—each representing the probability amplitude of a basis state—organized into a quantum state vector. The application of quantum gates involves transformations using unitary matrices of similarly exponential size, making memory efficiency a critical concern in emulation platforms. To reduce memory usage while preserving accuracy, the study explores various numerical representations, including fixed-point, reduced floating-point, and UNUM III (Posit), focusing on values constrained to the interval [-1,+1] which is relevant in quantum emulation as it corresponds to normalized qubit amplitudes.