Visiting Scientist, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS)
Main: Senior Research Scientist, Quantum Machine Learning and Algorithms, Quantinuum K.K.
Enrico Rinaldi
Ph.D
- Research Fields
- Particle and Nuclear Physics, Machine Learning
- Term and History
- 2019/10/01 - 2019/10/23 Research Part-time Worker Ⅰ
- 2019/11/16 - 2021/02/28 Visiting Scientist (Main: AI Researcher/Engineer, Arithmer Inc.)
- 2021/05/01 - 2022/10/31 Visiting Scientist (Main: Research Fellow, Physics Department, University of Michigan, USA)
- 2023/02/16 - Visiting Scientist (Main: Senior Research Scientist, Quantum Machine Learning and Algorithms, Quantinuum K.K.)
Self-introduction
I am Enrico Rinaldi, a part-time researcher in iTHEMS, who was previously a SPDR fellow in RIKEN BNL and Quantum Hadron Physics Laboratory.
My expertise is Monte Carlo numerical simulations of quantum field theories, also known as Lattice Field Theory simulations, which use massively parallel supercomputers (CPU and GPU-based) around the world to solve the complex equations hiding the mysteries of particle physics.
My research is focused on understanding high energy strongly-coupled gauged theories, in particular in the context of extensions of the Standard Model (SM) of particle physics, like Dark Matter physics or theories of Composite Higgs. New discoveries are hinging on the theoreticians’ ability to make predictions that can be tested by experimentalists, and that is precisely the my goal.
I am also engaged in projects related to low-energy nuclear physics, for example calculating nucleon-nucleon interactions or nuclear form-factors directly from the theory of Quantum Chromo-Dynamics (QCD). Moreover, I have been working on matrix models to study the gauge/gravity duality conjecture with the aim of understanding the possible intriguing relation between gauge theories and quantum gravity.
I am currently researching new Machine Learning (ML) approaches to physics, mainly based on the promising rise of generative models. The aim is to improve our ability to get access to multi-dimensional parametric distributions describing physical systems with specific models.
Related Events
Using a trapped ion quantum computer for hamiltonian simulations
February 28 (Wed) at 10:30 - 12:00, 2024 Seminar Quantum Computation SG Seminar
Simulation-based inference for multi-type cortical circuits
November 29 (Mon) at 13:30 - 15:00, 2021 Seminar Information Theory SG Seminar
iTHEMS-phys Intro Meeting on June 1, 2021
June 1 (Tue) at 13:00 - 15:00, 2021 Seminar iTHEMS Theoretical Physics Seminar
Composite Dark matter and gravitational waves
October 20 (Tue) at 10:00 - 11:00, 2020 Seminar DMWG Seminar
A new lamppost in dark matter searches: Composite Dark Matter
October 1 (Tue) at 10:00 - 18:00, 2019 Seminar DMWG Seminar
Related News
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Dr. Yuki Yokokura and Dr. Enrico Rinaldi will appear in the NHK TV program Cosmic Front
2022-09-20 Announcement
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RIKEN Research: Quantum computing and deep learning could help solve the mysteries of quantum gravity
2022-04-25 Research News
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What’s inside a black hole? U-M physicist uses quantum computing, machine learning to find out
2022-02-22 Hot Topic
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The work of a research group, including Dr. Maria Dainotti and Enrico Rinaldi, has been featured in several institutional press releases and websites
2021-06-01 Hot Topic
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Enrico Rinaldi interviewed by RIKEN Research
2019-10-09 Hot Topic
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Self-introduction: Enrico Rinaldi
2019-09-30 Person of the Week