MQV Early-Career Afternoon

Abstract
In a quantum computer, the quantum processor, whose core is an array of qubits, is controlled and read-out by a classical controller, i.e. implemented with classical electronic components. To scale up the number of qubits, the classical controller has to be integrated physically close to the quantum processor, meaning that it should operate at cryogenic temperature. The cryogenic controller is commonly implemented in silicon CMOS technology, which ensures low-power consumption and sub-Kelvin functionality. However, the commercial compact models of transistor in such technology, an essential tool for the design and simulation of control electronic circuits, do not cover the mK-4K temperature range of interest and thus cannot predict the behavior of the devices at such cryogenic temperatures. To solve the problem, and to provide to the circuit designers the possibility to simulate and thus to better design the cryogenic controller modules, novel compact models have to be developed. In this talk we will explore the different approaches that can be used to this scope and present results obtained within the MQV project about cryogenic compact models for the CMOS technology selected for the realization of the qubits controller.

Short bio
Chiara Rossi is a post-doctoral researcher at the Fraunhofer Institute for Integrated Systems and Device Technology IISB, located in Erlangen, Germany. Her research interests include semiconductor devices modeling, with focus on compact modelling, and process simulations. She received the PhD degree in Microsystems and Microelectronics from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, in 2021, with a thesis on SPICE compatible modeling of optoelectronic devices and radiation effects in integrated circuits, and the Master’s degree in Micro and Nanotechnologies for Integrated Systems from the Politecnico di Torino, Italy, the Institut Polytechnique de Grenoble - École Nationale Supérieure de Physique, Électronique et Matériaux, France, and the École Polytechnique Fédérale de Lausanne, Switzerland, in 2016. Within the MQV project, she is currently involved in K6 SHARE, working on compact modeling of transistors operated at cryogenic temperatures, used for the control electronics of the qubits.

Abstract
Tensor Network algorithms have been used for three decades to simulate quantum systems on classical computers. They exploit the fact that physical states have a much lower entanglement than generic states in the exponentially large Hilbert space. Quantum computers, on the other hand, use this entanglement as a resource to speed up calculations. Yet, entanglement is still a limited resource on NISQ devices. After a brief introduction to tensor network algorithms on classical computers, I will present some key ideas how to we can leverage some of their power to the current NISQ devices.

Short bio
Johannes Hauschild finished his undergraduate studies at the LMU Munich, after which he started working on tensor network algorithms and wrote the Tensor Network Python (TeNPy) package before he obtained his PhD from the TUM in 2019. He then spent two years as postdoc at the UC Berkeley working on large-scale simulations of twisted bilayer graphene and first applications of tensor networks to quantum computers, before he came back to TUM Munich on a combined postdoc and project coordinator position for the MQV K4.