202311 Quantum Computers: from Basics to Compilers
Quantum Computers: from Basics to Compilers
The topical days are this time especially meant for the members of the RTG. There will be talks on quantum computing, on quantum algorithms, and on the quantum internet. Moreover, there will be three interactive sessions of tutorials on programming with quantum computers / neural network quantum states.
Beginning:  Wednesday, November 29th, 13:45 
End:  Friday December 1st, 12:00 
Place:  Campus, Universität des Saarlandes, 66123 Saarbrücken 
Preliminary Program
Wednesday November 29th
13:0015:00 
Quantum computers – from basics to compilers: Welcome and 1st session 
Horsaal 1, Geb E2.5 
13:0014:15 
Welcome 
Giovanna Morigi (UdS) 
14:1515:00 
Quantum Computing: A Classical Perspective 
Antonio Macaluso (DFKI, Saarbrücken) 
15:0015:30 
Coffee Break 

15:3018:00 
Laboratoy on neural network quantum states for open systems 
Horsaal 1, Geb E2.5 
15:3016:30 
• Phase I: Neural network quantum states 
Marjan Macek and Michael Hartmann (FAU) 
16:3018:00 
• Phase II: Introduction to the code library for neural network quantum states 
Marjan Macek and Michael Hartmann (FAU) 
19:30 
Dinner 
Thursday November 30th
9:0012:30 
Focus session: Quantum computing 
Graduate Center C9 3 
9:0010:00 
The quantum internet 
Jürgen Eschner (UdS) 
10:0010:45 
Basics of (Quantum) Algorithmic complexity 
Markus Bläser (UdS) 
10:4511:15 
Coffee Break 

11:1512:00 
The variational quantum algorithm: An introduction 
Peter Orth (UdS) 
12:0012:45 
A mathematical framework for quantum information 
Moritz Weber (UdS) 
12:4514:00 
Lunch Break 

14:0017:30 
Intermediate quantum computing laboratory 
Graduate Center C9 3 
14:0015:00 
• Phase I: Review and discuss the selftest problems 
F. WilhelmMauch, T. Stollenwerk, & Team (FZJ) 
15:0016:00 
• Phase II: Discuss the material previously distributed 
F. WilhelmMauch, T. Stollenwerk, & Team (FZJ) 
16:0017:30 
• Phase III: Start working together on a new set of problems 
F. WilhelmMauch, T. Stollenwerk, & Team (FZJ) 
19:00 
Dinner 
Friday December 1st
9:0012:00 
The Ion Trap Quantum Computer 
U.39 Zeichensaal, Geb E25 
9:0010:00 
Part 1: The Ion Trap Quantum Computer at Mainz 
J. Hilder and F. SchmidtKaler (JGU) 
10:0012:00 
Part 2: An introduction to the compiler and user interface. 
J. Hilder and F. SchmidtKaler (JGU) 
12:00 
End of the workshop 
Description of interactive sessions
Wednesday, November 29th: Laboratoy on neural network quantum states for open systems
Simulating quantum manybody systems on classical computers is extremely challenging because the number of degrees of freedom scales exponentially in the system size. Already for moderate system sizes, one needs to resort to approximation methods such as Monte Carlo or Tensor Network techniques. This laboratory introduces NeuralNetwork Quantum States, a parametrization of the quantum states in terms of neural networks, and how can they be used to learning a steadystate of an open system with Variational Monte Carlo technique.
Goals
 Understanding the basics of variational Monte Carlo with Neural Network Quantum States
 Understanding why and when Neural Network Quantum States provide good approximations
 Running a first example code using the NetKet library, see https://www.netket.org/
Prerequisites
 Good knowledge of quantum mechanics
 Coding experience in Python
 A working installation of NetKet
Thursday, November 30th: Intermediate quantum computing laboratory
Quantum computers are an exciting development and their likely ﬁrst application will be in the simulation of manybody quantum systems. Some systems are available online and programming environments as well as application frameworks are become somewhat mature. Standard notions of quantum computing are taught in courses and covered in textbooks and become more or less common knowledge of quantumminded graduate students. This session is meant to take students to the next level.
Goals:
 understanding of the implementation of optimization algorithms on gatebased and adiabatic quantum computers
 understanding of the implementation of linear algebra algorithms on gatebased quantum computers
 understanding of the variational quantum eigensolver and the variational Hamiltonian Ansatz
 practice of these algorithms in IBM QISKIT
Prerequisites:
 Understanding of the quantum gate model
 Understanding of basic quantum algorithms including
 the Grover algorithm
 Quantum phase estimation
 a working instance of IBM QISKIT at your ﬁngertips
Mode of instruction:
Before the laboratory the students will be required to follow online lectures. The laboratory will consist of inpresence discussions. Before the class, you will receive a download link with slides and recorded audio for you to review before as well as a set of test problems on the prerequisites. In the afternoon, we will do three things:
 review and discuss the selftest problems
 discuss the material from the slides
 start working together on a new set of problems
Friday, December 1st: The Ion Trap Quantum Computer
Our trapped ion quantum computers are based on modern segmented ion traps. We will sketch architectures, the required trap technologies and fabrication methods, control electronics for quantum register reconfigurations, and recent improvements of qubit coherence and gate performance. We will present various QC applications, including variational quantum eigensolver approaches for chemistry or high energy relevant models.
The session will provide a detailed inside in the full software stack needed to operate the trappedion quantum computer without specific hardware knowledge and from a remote location. This includes the integration of standardized user interfaces, such as Qiskit and PennyLane, as well as the compilation stack to translate a given arbitrary quantum circuit into an optimized shuttlingbased operation sequence.
Goals
 Understanding the basics of trappedion quantum computers
 Understanding the parts of the software stack to control a trappedion quantum computer, including standard user interfaces, circuit representation on different compiler layers and operation sequences to be executed on the hardware
Prerequisites
 Good knowledge of quantum mechanics
 Understanding of basic quantum algorithms
Registration
Deadline for registration: November 9th, 2023
Registration form