Quantum and Nano Systems Laboratory (QNANOLab)

The QNANO laboratory conducts interdisciplinary research in quantum computing, nanoscale electronics, and emerging computing paradigms. Its activities range from the development of advanced quantum and classical architectures — including quantum circuit design, hardware-aware compilation, and FPGA/GPU-based emulation — to the study of nanoscale and molecular devices, such as quantum dots, molecular sensors, and single-molecule devices. The lab combines theoretical, simulation, and experimental approaches, collaborating with international partners on the design, fabrication, and characterization of novel technologies. Its ultimate goal is to explore efficient and scalable solutions for information processing, with applications in AI, cryptography, and low-power systems.

Keywords: Quantum Computing and Control & Readout, Quantum Optimizations, Molecular Electronics and field-coupled nanocomputing, Quantum and Nanoelectronic Architectures, Quantum dots for Nano and Quantum Computing.

Contact e-mail: det.QNANOLab@polito.it 

Position: Polito Maps

Research topics:

  • Quantum Computing and Nanoscale Architectures: The group develops end-to-end solutions, from control electronics for qubits, going through compact modeling of physical qubits to high-level applications. Research covers quantum circuit design, hardware-aware compilation, FPGA/GPU emulators, and QUBO-based optimization, with a focus on technologies such as superconducting, spin, and molecular qubits.
  • Novel Computing Paradigms Beyond von Neumann: The lab designs reconfigurable memory-computing arrays (CLiMA, Hybrid-SIMD) and CAD tools (DExIMA, Octantis) for performance and exploration. It also develops near-memory CGRA-based architectures for AI, cryptography, and approximate computing, targeting scalable, energy-efficient solutions.
  • Ab initio study and compact modeling of nanoscale sensors based on nanowires or single molecules for the detection of gases, air pollutants, or toxins (e.g. aflatoxin). Research activities also focus on their integration with CMOS for the realization of smart sensors and experimental fabrication.
  • Ab initio study and modeling of single-molecule devices (single-molecule junctions, field-coupled nanocomputing) for computing and memory. The studies focus on technological feasibility - bridging theoretical models and experimental results - and CAD-based (MagCAD/SCERPA) design of high-speed low-power circuits.
  • Quantum Dots Research: Activities focus on semiconductor and molecular quantum dots, combining process-level device studies with physical simulations and experiments. The work integrates fabrication and characterization with simulation, and includes analog/digital microelectronic systems for low-temperature, low-noise control and readout.

Available services:

  • Quantum-enhanced bank fraud detection: Use of Quantum Machine Learning models (VQC, QNN, QSVM) to identify fraudulent transactions in large, imbalanced financial datasets.
  • Financial portfolio optimization and risk management: QUBO-based models for optimal asset allocation and risk control in banking and fintech applications.
  • Intelligent urban mobility and traffic management: Optimized traffic light regulation and flow control using QAOA and QUBO formulations, with applications in Smart Cities.
  • Optimization of logistics and distribution networks: Improvement of delivery routes and supply chain flows through quantum routing and scheduling techniques.
  • Telecommunication network optimization: Efficient placement of network resources (e.g., virtualized functions or 5G/6G infrastructures) through quantum simulation and compilation approaches.
  • Quantum key distribution (QKD) and secure communications: Design and simulation of photon-based secure communication systems providing theoretical guarantees of inviolability.
  • Quantum image processing and computer vision: Quantum circuit–based compression and advanced image analysis for applications in robotics, industrial inspection, and computer vision.
  • Qubit Control and Readout: Design and implementation of scalable control and readout architectures for the precise characterization and efficient execution of algorithms on quantum processors
  • Quantum analysis of biomedical images: Application of Quantum Image Processing techniques to medical imaging (e.g., MRI, histological images) for early diagnosis and automated classification.
  • Quantum-assisted drug discovery and molecular simulation: Quantum emulation for studying molecules and complex chemical processes, accelerating pharmaceutical and computational chemistry research.
  • Intelligent molecular sensing systems: Study of miniaturized electronic sensors based on nanowires and single-molecule devices for selective detection of chemical, biological, and environmental agents, with applications in healthcare, environmental monitoring, and agri-food sectors.
  • Sensor design optimization through simulation: Use of ab initio, device, and process simulations to analyze molecule–sensor interactions and develop compact models integrable into electronic design tools.
  • Sensors for food traceability and safety: Design of advanced sensors for detecting contaminants (e.g., aflatoxins) in food, using molecular detection and electronic signal analysis techniques.
  • Molecular-scale electronic computation: Design and simulation of logic circuits and memory cells based on single molecules, for ultra-dense, low-power, beyond-CMOS electronics.
  • Simulation and modeling of molecular devices: Development of predictive models for molecular electronic devices through ab initio simulations and dedicated tools for circuit design and performance estimation, including Beyond-CMOS technologies such as Molecular Field-Coupled Nanocomputing.
  • CAD tools and simulators for emerging devices: Development and integration of software environments for graphical circuit design and physical simulation of emerging technologies, enabling design flows compatible with CMOS platforms.