Qrisp Implementation and Resource Analysis of a T-Count-Optimized Non-Restoring Quantum Square-Root Circuit

\noindent Efficient quantum arithmetic operations are essential building blocks for complex quantum algorithms, yet few theoretical designs have been implemented in practical quantum programming frameworks. This paper presents the first complete implementation of the T-count optimized non-restoring quantum square root algorithm using the Qrisp quantum programming framework. The algorithm offers better resource efficiency compared to alternative methods, achieving reduced T-count and qubit requirements while avoiding garbage output. Our implementation validates the theoretical resource estimates, confirming a T-count of $14n-14$ and a T-depth of $5n+3$ for $n$-bit inputs. The modular design approach enabled by Qrisp allows the construction of reusable components, including reversible adders, subtractors, and conditional logic blocks built from fundamental quantum gates. The three-stage algorithm, comprising initial subtraction, iterative conditional addition/subtraction, and remainder restoration, is successfully translated from algorithmic description to executable quantum code. Experimental validation across multiple test cases confirms the correctness, with the circuit producing accurate integer square roots and remainders. This work demonstrates the practical realizability of resource-optimized quantum arithmetic algorithms and establishes a foundation for implementing different arithmetic operations in modern quantum programming frameworks.