Teoria e Metodi dell’informazione e del Calcolo Quantistico
The quantum world is a resource. The goal of quantum science is to harness, and exploit, quantum phenomena like superposition, where particles can exist in multiple states simultaneously, and entanglement, where particles become interconnected. Quantum technologies leverage these principles to develop advanced tools and applications, from computing to communication, from sensing to simulation, and complete these tasks with performance and accuracy unavailable to classical machines.
Staff
Full Professors:Simone Montangero
Associate Professors: Marco Di Liberto, Carmelo Mordini, Ilaria Siloi, Pietro Silvi
Post-doc
Flavio Baccari, Francesco Campaioli, Lorenzo Maffi, Simone Notarnicola, Luka Pavesic, Davide Rattacaso, Marco Rigobello, Darvin Wanisch
PhD students
Marco Ballarin, Rocco Barac, Giovanni Cataldi, Asmita Datta, Maria Lanaro, Peter Roland Majcen, Mattia Morgavi, Alice Pagano, Nora Reinić, Simone Scarlatella, Marco Tesoro
External collaborators
Giuseppe Calajò, Daniel Jaschke, Lisa Zangrando
Research activities
Tensor Network Methods
Tensor network methods are an advanced numerical technique inspired to the information distribution in correlated quantum systems. Tensor Networks aim, alongside other applications, to express a many-body state as a tailored wavefunction ansatz which efficiently encodes quantum entanglement with the appropriate amount of classical information. From this key concept, it is possible to develop a plethora of efficient and accurate methods for the simulation of strongly correlated quantum many-body systems. Our research activity in this field is twofold: on one hand side we develop the already existing methods even further, to improve their efficiency and accuracy. On the other hand side, we apply these mthods to the study of complex quantum systems, from lattice gauge theories, to spin models, to molecules, and other condensed matter problems, especially those suffering from MonteCarlo sign problem. Recent investigation regards their application in the field of machine learning.
Contacts: Simone Montangero, Pietro Silvi
Programmable Atomic Devices
Among the possible hardware platforms for the quantum technologies of the near future are those based on suspended atoms (and molecules), either neutral or ionized. The center-of mass motion of these particles is carefully controlled through tailored electromagnetic fields, either optical lattices, traps, or tweezers. Similarly, it is possible to couple the orbital motion of the electrons with precise laser beams, thus manipulating the electron into coherently shifting from one quantum atomic orbital to another, effectively turning each atom into a unit of quantum information, the quantum bit (or qubit). Currently, atom-based hardware is the most prominent competitor to superconductor-based hardware in the development of quantum technologies. Our research activity in this field involves (1) improve the state-of-the-art for quantum information processing on atom-based quantum hardware, which will allow us to obtain faster, more precise operations, resilient to noise and errors, and (2) develop quantum algorithms, sensors, and simulation strategies specifically tailored to the features and advantages of these platforms.
Contacts: Carmelo Mordini, Pietro Silvi, Marco Fedele Di Liberto, Simone Montangero,
Quantum Algorithms and Applications
Quantum algorithms represent a significant advancement in computational techniques, leveraging principles like superposition and entanglement to address complex tasks. Our research focuses on three primary areas: 1) the implementation, improvement, and benchmarking of quantum algorithms using advanced classical techniques. 2) the exploration of quantum-enhanced applications in fields such as simulation of quantum many-body physics, graph problems, industrial optimizations, and cybersecurity. 3) the development of hardware-aware algorithms for error correction and for the optimal execution of quantum algorithms on actual devices. Our work aims to extend the boundaries of computational feasibility, enabling advancements in secure communication, efficient resource management, and robust optimization strategies across diverse industrial applications. Additionally, our work ensures these advancements are accessible and adaptable to various quantum computing hardware, fostering a versatile and forward-looking approach to quantum computing applications.
Contacts: Ilaria Siloi, Simone Montangero
Quantum Simulation and Engineering
Quantum simulators provide a unique opportunity to explore quantum many-body physics, either to target the physics of models of interest, long-sought and never observed phenomena, or to exploit the large programmability to explore novel possibilities. Our research in this area focuses on two main aspects: 1) Quantum Simulation and 2) Quantum Engineering. Within the Quantum Simulation aspect, we study many-body properties of models that can be realized in quantum simulator platforms with the goal of identifying and understanding key properties (phase transitions, ground state features, entanglement or excitation properties) and also to develop protocols and methodologies to probe them in and out of equilibrium. Some of these models and phenomena include Hubbard models, spin models, topological or chiral phases, lattice gauge theories. The Quantum Engineering aspect instead focuses on employing a variety of methods and strategies (e.g. based on Floquet methods, atomic physics and quantum optics methods) to control available quantum degrees of freedom of existing platforms in order to encode and engineer tunable Hamiltonians of interest, pushing the boundaries of what a quantum simulator can be employed for.
Contacts: Marco Fedele Di Liberto, Pietro Silvi, Simone Montangero,
