Department of Physics "Giuseppe Occhialini"
Design and characterization of superconducting quantum devices. Superconducting qubits for astroparticle research. Quantum noise limited superconducting amplifiers. Single photon detectors for quantum communication and metrology. Cryogenic microwave electronics for quantum computing.Quantum algorithms.
M. Borghesi, M. Faverzani, E. Ferri, A.Giachero, A. Nucciotti
The goal of DartWars is to develop superconducting traveling wave parametric amplifiers, also known as TWPAs. Superconducting parametric amplifiers allow the quantum limit of added noise to be reached and are suitable both as amplifiers for ultra-low temperature detectors for astro-particle physics and as amplifiers for high-fidelity readout of superconducting qubits. Two types of parametric amplifiers are developed within DartWars: KI-TWPAs exploit the non-linearity of the kinetic inductance (KI) of certain superconductors, and TWJPAs are based on the non-linearity of metamaterials obtained by series of Josephson junctions. With these TWPAs, the aim is to realize a wide-band (4-8GHz) and high-gain (20dB) parametric amplifier.
DartWars is an international collaboration led by Milano-Bicocca and funded by INFN National Commission 5 and EU (MSCA-IF-2020).
Within DartWars the Milano-Bicocca group is responsible for the design of the devices and their characterisation at low temperature using the facilities of the Cryogenic Laboratory.
M. Borghesi, M. Faverzani, E. Ferri, A.Giachero, A. Nucciotti
The recently-acquired ability to manipulate and measure single quanta such as microwave photons, phonons and magnons is opening up new perspectives in the detection of Dark Matter and the Fifth Force, in testing Quantum Gravitation and Quantum Mechanics of macroscopic objects. Superconducting qubits have become an important part of these recent advances. This has been made possible by the ability to engineer and fabricate nanostructured superconductive devices that exhibit macroscopic quantum behavior analogous to that of artificial 2-level atoms (qubits) and by the possibility of manipulating the qubit state with classical electromagnetic fields.
In the last 15 years, quantum sensing with superconducting qubits has started to be successfully applied in fundamental physics experiments.
Qub-IT is a project funded by INFN's National Commission 5 that aims to develop superconducting qubits for the search of axionic dark matter.
The idea of Qub-IT is to exploit quantum superposition and entanglement in arrays of superconducting transmon qubits to perform highly sensitive Quantum-Non-Demolition (QND) measurements of single itinerant microwave photons produced by the interaction of axions or Dark-Sector photons with electromagnetic fields.
Within the framework of Qub-IT, the Milano-Bicocca group is responsible for the design of the qubits and their characterisation at low temperature in the Cryogenic Laboratory, as well as for the dispersive readout and coherent control system. In collaboration with the Department of Materials Science, new materials and deposition techniques are also being studied to improve the quality of the devices.
Radioactivity is known to have detrimental effects on superconducting quantum processors, being responsible for inducing correlated errors among qubits and a reduction of their coherence time [1,2].
These effects were demonstrated recently, however a full understanding of this phenomenon, and a corresponding optimization of quantum devices is still missing.
The goal of the research project is to perform a radioactivity characterization of the materials used for the realization of superconducting qubits and their surrounding environment.
This will make it possible to define the criteria for the selection, cleaning and treatment of the materials used for the realization of superconducting quantum processors.
We will also upgrade the design of qubit with the use of thin films that can act as phonon traps, protecting the qubits and then enhancing their coherence.
While quantum computers are not yet usable on a large scale due to their limited number and still critically technology-dependent computing capabilities, the development of quantum machine learning (QML) algorithms is already underway. In the Department of Physics "G. Occhialini" we study the performance of these algorithms in example cases of data analysis.
In each case, a comparison is made with the performance of classical classification algorithms in terms of, for example, precision, accuracy and recall, in order to understand in which cases QML algorithms perform better than classical ones.
Particular attention is put in the preparation of input data, in order to understand what are the properties of datasets that most affect the performance of QML algorithms.
Existing use cases where the algorithms may be applied are the event reconstruction from imaging information produced by large volume particle detectors, and signal/background events classification in particle physics experiments. However, the application spectrum is wide and other examples could be the identification of phases and phase transitions in a variety of condensed matter Hamiltonians or the classification of medical images such as in breast cancer detection in screening mammography.
M. Borghesi, M. Faverzani, E. Ferri, A.Giachero, A. Nucciotti
High-efficiency detection of single photons in the IR/optical range is of paramount importance for quantum communication and metrology applications. In particular, quantum applications also require a low dark count rate and the ability to resolve the number of photons hitting the single detector. The detection of single photons, given the low energies involved, requires state-of-the-art techniques that make it possible to distinguish the faint signal produced by the detector from the characteristic noise of the reading system while ensuring the other required characteristics. The Milano-Bicocca group is developing photon detectors using superconductive materials, in which the variation of quasi-particle density resulting from an interaction is detected. This detection mechanism is exploited with two types of superconducting sensors operating at very low temperature: Transition Edge Sensors (TES) or Microwave Kinetic Inductance Detectors (MKID). These two detection techniques not only make it possible to detect single interactions of very low-energy photons with energy resolutions of the order of a few tenths of an eV, but also make it possible to build arrays of dozens of detectors with a microwave multiplexed readout (as in the HOLMES experiment).
The Milano-Bicocca group, in collaboration with FBK and INRIM, designs, produces and characterizes these sensors at low temperatures and develops, also in collaboration with NIST, the electronics for multiplexed readout. The activity takes place in the Cryogenics Laboratory.
A. Baschirotto, M. De Matteis, V. Vadalà, E. A. Vallicelli
Practical quantum computers should integrate millions of qubits together with the electronic circuits used to control and readout their values. Solid-state qubits fabricated in ultra-scaled CMOS enable large-scale integration of millions of qubits onto a single chip. The research activity of the group is related to the development of reliable cryogenic microwave electronics in 16-nm FinFET technology. Thanks to its scalability and integration property FinFET is the most promising option to embed, in a near future, both the qubit and its control/readout circuits onto a single cryogenic chip operating at few K. The main research topics are related to the characterization and modeling of 16-nm FinFETs at microwave frequencies (up to tens of GHz) and at cryogenic temperatures (few kelvin), including the physical phenomena appearing at such temperatures, as freeze-out effect, increased threshold voltage, bandgap widening, mobility increase, that typically are not included in standard compact models. Research activity is also aimed to the design, using the developed models, of advanced 16-nm FinFET integrated circuits for the qubit readout circuit. In particular, the focus of design activity is the low noise amplifier (LNA) that is the most important and critical block of the qubit readout chain.
Numerical strategies are constantly developed by our group to benefit from the progress in HPC systems, with an emphasis on efficient exploitation of multi/many-cores architectures. Our group is currently involved in the development of a new multi-level computational strategy based on the multi-boson domain-decomposed Hybrid Monte Carlo. Our future plans include the further development of this numerical strategy to integrate it with the master-field paradigm and to perform a precise study of the string breaking in QCD.
The team of Computational Physics of the Bicocca Theory Group has a wide experience in the study of computing architectures for calculation-intensive problems such as the numerical simulations of strong interactions. In the early 1980s some members of the team have been among the pioneers in the development of numerical simulations of Quantum Chromodynamics (QCD) in the non perturbative regime and have also been involved in the design and manufacturing of four generations of computers with an architecture specifically suited for the calculation structures typical of the numerical simulation of QCD on a lattice (LQCD). Starting from the first machine, APE (1985) with a maximum power of 1 GFlops, a power of 800 GFlops has been reached with apeNEXT (2002) with two other projects of intermediate power.
These computers have given the Italian LQCD community a tool to obtain physics results that, as far as statistical and systematic reliability is concerned, were among the best available at the time and impossible to attain with ordinary computing facilities.
The APE project has been constantly funded by INFN and has soon become an international collaboration with installations in many European research centers.
A description of the project and useful references for a further insight can be found in:
Our group is directly involved in the development of highly-parallel codes, optimized for the latest generation architectures and with excellent scalability. Moreover we have actively contributed to several other publicly available packages, such as openQCD, DDHMC, Grid and gpt. Finally we authored and currently maintain the open-source analysis package pyobs.
Research and development: cluster KNUTH
Teaching: cluster WILSON