Tensor network based quantum software framework for the NISQ era

C++ library with Python interface to train quantum circuits, quantum gate synthesis and state preparation.

Code for Kolmogorov-Arnold Network for Quantum Architecture Search i.e., KANQAS

Variational Quantum Algorithms for Unsupervised Image Segmentation

QuACS: Variational Quantum Algorithm for Coalition Structure Generation in Induced Subgraph Games

Quantum algorithms to solve linear systems of equations.

For fermionic quantum simulation

QVoice: Quantum Variational Optimization with In-Constraint Energy

Code for the Lie-Algebraic classical simulation of structured quantum circuits

A variational quantum algorithm for approximate counting based on the Jerrum-Valiant-Vazirani algorithm.

2-QNSCD optimization algorithm for learning from quantum data

Hardware-Aware Variational Quantum Algorithms under Noise (VQE / QAOA Benchmarking Across IBM & IonQ)

Preregistered simulator and IBM hardware pilot for Lambda-IC gradient-scale diagnostics in qMERA trainability.

In this paper we present a VQA for solving the TSP problem that requires only O(n log n) qubits and an Ansatz whose topology evolves via Simulated Annealing.

Benchmarking budget-aware classical optimizers vs COBYLA/SPSA for QAOA parameter tuning on IBM quantum hardware — negative result: shallow QAOA landscapes are too smooth to benefit from constrained optimization techniques.

A training-free, channel-level audit that tests whether a noisy quantum neural network still respects an intended symmetry once the ideal circuit is composed with hardware noise.

A Quantum Method for Constrained Vehicle Dynamics and Green-Wave Optimization

Proof-of-concept hybrid quantum-classical neural network classifier on make_moons using Qiskit EstimatorQNN + PyTorch TorchConnector. Achieves 100% test accuracy

This repository is a personal collection of projects in Quantum Computing, combining theoretical study and practical implementation

A personal repository where I place from time to time some ideas, that I am putting into practice in Quantum Computing to get feedback.