Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

Hardware Technologies and Applications

In course

QUANT-400: Introduction to quantum science and technology

A broad view of the diverse aspects of the field is provided: quantum physics, communication, quantum computation, simulation of physical systems, physics of qubit platforms, hardware technologies. Students will grasp the field as a whole and better orient ...

Description

This lecture covers hardware technologies and applications, focusing on the quantum stack, fidelity to electronic circuit specifications, cryogenic electronics, quantum sensing, interfacing qubits with classical processors, quantum computing stack, cryo-CMOS modeling, cryo-CMOS parameters, mobility over temperature, and modern processes. It delves into choosing technologies like single-electron transistors and superconducting devices, discussing cryo-CMOS characterization, transistor mismatch, low-noise amplifiers, quantum-classical interface, amplifier classification, performance, impedance matching, coaxial cables, and ADC examples. The lecture also explores sampling, quantization, signal-to-noise ratio, effective number of bits, quantization noise, ADC limitations, INL, DNL, ADC architectures, and more.

Instructors (7)

Nicolas Macris

Nicolas Macris received the PhD degree in theoretical physics from EPFL and then pursued his scientific activity at the mathematics department of Rutgers University (NJ, USA). He then joined the Faculty of Basic Science of EPFL, working in the field of quantum statistical mechanics and mathematical aspects of the quantum Hall effect. Since 2005 he is with the Communication Theories Laboratory and Information Processing group of the School of Communication and Computer Science and currently works at the interface of statistical mechanics, information theory and error correcting codes, inference and learning theory. He held long-term visiting appointments and collaborations with the University College and the Institute of Advanced studies in Dublin, the Ecole Normale Supérieure de Lyon, the Centre de Physique Theorique Luminy Marseille, Paris XI Orsay, the ETH Zürich and more recently Los Alamos National Lab. CV and publication list.

Pasquale Scarlino

I obtained my master's degree in Physics at the University of Salento, Lecce (Italy) in February 2011. During 2006-2011, I have also been a student of Scuola Superiore ISUFI (SSI). SSI is one of six schools of excellence established in Italy to develop the intellectual capital in technological and social sciences. I conducted an external Master thesis project during an 8 months internship in the Quantum Transport Group at TU Delft, under the supervision of Prof. L.M.K. Vandersypen. There, I implemented the Quantum Point Contact Radio-Frequency Reflectometry technique, which allows increasing the single-shot electron spin readout bandwidth and is currently routinely used in the group.I obtained my Ph.D. degree in February 2016, in the Spin Qubits group of Prof. L.M.K. Vandersypen at the Kavli Institute of Nanoscience-Qutech (TU Delft). During my Ph.D. I have been leading the Si/SiGe spin qubits project, collaborating with the M. Eriksson Group at Wisconsin University. In parallel, I have been working on other different projects, in particular with GaAs depletion quantum dots, high impedance superconducting resonators, and surface acoustic wave resonators. I have been working as a Postdoc fellow in the group of Prof. A. Wallraff (Quantum Device Lab) at ETH Zurich. My main project, in collaboration with the group of Prof. K. Ensslin and Prof. T. Ihn, consisted in integrating semiconductor and superconductor technologies. Realizing a well-controlled interface between the semiconductor and superconductor-based quantum information technologies may allow harnessing the best of both device architectures, for example by providing an interface between strongly coupled charge state and high coherence spin states. Furthermore, it enables the possibility to explore light/matter hybridization in a class of solid-state systems and regimes that are new in the context of quantum optics.From June 2019 till September 2020, I have been a Senior Researcher at Microsoft Station Q Copenhagen and at the Center for Quantum Devices in Copenhagen, focusing on developing semiconductor-superconducting hybrid hardware for topologically protected quantum computation.Since October 2020, I am a tenure track Assistant Professor of Physics in the School of Basic Sciences at the EPFL where I founded the Hybrid Quantum Circuit (HQC) laboratory.

Official source

Ontological neighbourhood

Information engineering

Signal processing: Digital image processing

Physics

Electromagnetism: Electrical networks

Related concepts (32)

Noise (electronics)

In electronics, noise is an unwanted disturbance in an electrical signal. Noise generated by electronic devices varies greatly as it is produced by several different effects. In particular, noise is inherent in physics and central to thermodynamics. Any conductor with electrical resistance will generate thermal noise inherently. The final elimination of thermal noise in electronics can only be achieved cryogenically, and even then quantum noise would remain inherent. Electronic noise is a common component of noise in signal processing.

Input impedance

The input impedance of an electrical network is the measure of the opposition to current (impedance), both static (resistance) and dynamic (reactance), into a load network that is external to the electrical source network. The input admittance (the reciprocal of impedance) is a measure of the load network's propensity to draw current. The source network is the portion of the network that transmits power, and the load network is the portion of the network that consumes power.

Signal-to-noise ratio

Signal-to-noise ratio (SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to noise power, often expressed in decibels. A ratio higher than 1:1 (greater than 0 dB) indicates more signal than noise. SNR is an important parameter that affects the performance and quality of systems that process or transmit signals, such as communication systems, audio systems, radar systems, imaging systems, and data acquisition systems.

Noise figure

Noise figure (NF) and noise factor (F) are figures of merit that indicate degradation of the signal-to-noise ratio (SNR) that is caused by components in a signal chain. These figures of merit are used to evaluate the performance of an amplifier or a radio receiver, with lower values indicating better performance. The noise factor is defined as the ratio of the output noise power of a device to the portion thereof attributable to thermal noise in the input termination at standard noise temperature T0 (usually 290 K).

Quantum computing

A quantum computer is a computer that exploits quantum mechanical phenomena. At small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior, specifically quantum superposition and entanglement, using specialized hardware that supports the preparation and manipulation of quantum states. Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern "classical" computer.

Related lectures (57)

Noise Reduction Techniques

Explores noise reduction techniques in electrical systems, covering concepts like Fourier transform, impedance matching, and dithering.

Understanding Noise in Electrical Systems

Explores noise sources, Fluctuation-Dissipation Theorem, amplifier noise, interference effects, and quantization error in electrical systems.

Noise in Data Acquisition

Explores noise sources in data acquisition, including thermal, shot, and amplifier noise, as well as the effects of ADC noise.

RIN, Shot Noise, Circuit Noise - Examples

Explores laser operation basics, shot noise, and photodetectors' noise characteristics, emphasizing the importance of signal-to-noise ratio in signal detection.

Amplified Spontaneous Emission Noise in Fiber Amplifiers