Provable bounds for noise-free expectation values computed from noisy samples
- 2024
- Nat. Comput. Sci.
Bio
Dr. Daniel J. Egger is a researcher in the Quantum Applications Research & Software group in IBM Research – Zurich. His current research focuses on quantum information processing with superconducting circuits, pulse-level control of quantum systems, and quantum algorithms.
He was awarded a PhD with distinction from the Saarland University (Germany) in 2014 for his thesis entitled “Optimal control and quantum simulations in superconducting quantum devices”. For his PhD thesis, he received the Dr. Eduard-Martin prize.
Daniel J. Egger holds an MSc degree from EPFL Lausanne Switzerland.
Publications
Challenges and opportunities in quantum optimization
- Amira Abbas
- Andris Ambainis
- et al.
- 2024
- Nature Reviews Physics
A Vision of Quantum-Centric Supercomputing
- 2024
- PASC 2024
Benchmarking digital quantum simulations and optimization above hundreds of qubits using quantum critical dynamics
- 2024
- arXiv
Large-scale quantum approximate optimization on non-planar graphs with machine learning noise mitigation
- Stefan Sack
- Daniel Egger
- 2024
- PRResearch
Squeezing and quantum approximate optimization
- Gopal Chandra Santra
- Fred Jendrzejewski
- et al.
- 2024
- Physical Review A
Qiskit Experiments: A Python package to characterize and calibrate quantum computers
- 2023
- J. Open Source Softw.
Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware
- Johannes Weidenfeller
- Lucia Valor
- et al.
- 2022
- Quantum
Squeezing and quantum approximate optimization
- Gopal Chandra Santra
- Fred Jendrzejewski
- et al.
- 2022
- arXiv
Ancilla-free implementation of POVM measurements for near-term quantum algorithms
- 2022
- APS March Meeting 2022
Patents
- AU
- 2021379051
- US
- 11941490
- US
- 11928004
- CN
- ZL201980020536.0
- FR
- 3769271
- GB
- 3769271
- DE
- 602019043546.0
- US
- 11809964
- US
- 11651264
- US
- 11562281
Projects
Quantum Optimization
Applying quantum algorithms to various optimization problems
Top collaborators
SW
Stefan Woerner
Manager, Quantum Computational Science
JG
Julien Gacon
Research Scientist, Quantum Computational Science
IT
Ivano Tavernelli
Global leader for advanced algorithms for quantum simulations
MW
Mira Luca Wolf-Bauwens
Responsible Quantum Computing Lead