# Seminar Report

## iTHEMS Theoretical Physics Seminar on October 23, 2020

2020-10-30

The iTHEMS Theoretical Physics Seminar is held on October 23, 2020. The speaker is Dr. Masanori Hanada in Department of Mathematics, the University of Surrey. The title is ”Toward simulating Superstring/M-theory on a Quantum Computer”.

He present a framework for simulating superstring/M-theory on a quantum computer, based on holographic duality. Because holographicduality maps superstring/M-theory to quantum field theories (QFTs), we can study superstring/M-theory if we can put such QFTs on a quantum computer --- but it still looks like a complicated problem, if we use a usual lattice regularization. Here he propose an alternative approach, which turns out to be rather simple: we map the QFT problems to matrix models, especially the supersymmetric matrix models such as the Berenstein-Maldacena-Nastase (BMN) matrix model. Supersymmetric matrix models have natural applications to superstring/M-theory and gravitational physics, in an appropriate limit of parameters. Furthermore, for certain states in the Berenstein-Maldacena-Nastase (BMN) matrix model, several supersymmetric quantum field theories dual to superstring/M-theory can be realized on a quantum device. It is straightforward to put the matrix models on a quantum computer, because they are just quantum mechanics of matrices, and the construction of QFTs is mapped to the preparation of certain states. He show the procedures are conceptually rather simple and efficient quantum algorithms can be applied. In addition, as a (kind of) byproduct, he provide a new formulation of pure Yang-Mills on quantum computer.

The seminar was held via the Zoom online conference systems, and more than 15 people including outside of iTHEMS attended the seminar.

Toward simulating Superstring/M-theory on a Quantum Computer

October 23 at 17:00 - 18:00, 2020

# Upcoming Events

## Seminar

### Mathematics of thermalization in isolated quantum systems

November 10 at 16:00 - 18:10, 2020

Dr. Naoto Shiraishi (assistant professor, Faculty of Science Department of Physics, Gakushuin University)

If an isolated macroscopic quantum system is left at a nonequilibrium state, then this system will relax to the unique equilibrium state, which is called thermalization. Most of quantum many-body systems thermalize, while some many-body systems including integrable systems do not thermalize. What determines the presence/absence of thermalization and how to understand thermalization from microscopic quantum mechanics are profound long-standing problems.

In the first part of my talk, I briefly review some established results of quantum thermalization. I first clarify the problem of thermalization in a mathematical manner, and then introduce several important results and insights: typicality of equilibrium states [1], relaxation caused by large effective dimension [2], and eigenstate thermalization hypothesis (ETH) [3,4] and weak-ETH [5].

In the second part of my talk, I explain some of my results. First, I introduce a model which is non-integrable and thermalizes but does not satisfy the ETH [6,7]. This finding disproves the conjectures that all nonintegrable systems satisfy the ETH and that the ETH is a necessary condition for thermalization. I also discuss the hardness of the problem of thermalization from the viewpoint of computational science [8]. Then, I move to an analytical approach to a concrete model, and prove that S=1/2 XYZ chain with a magnetic field is nonintegrable [9]. This is the first example of proof of nonintegrability in a concrete quantum many-body system, which will help a mathematical approach to thermalization.

Venue: via Zoom

Event Official Language: English

## Colloquium

### The 13th MACS Colloquium

November 13 at 15:00 - 18:00, 2020

Prof. Shin-ya Kawaguchi (Professor, Division of Biological Sciences, Graduate School of Science, Kyoto University)

Dr. Yuji Sugita (Senior Research Scientist, iTHEMS / Chief Scientist, Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research (CPR))

15:00- Talk by Prof. Shin-ya Kawaguchi

16:15- Talk by Dr. Yuji Sugita

17:15- Discussion

Venue: via Zoom

Event Official Language: Japanese

## Seminar

### Efficient probabilistic assessment of building performance: sequential Monte Carlo and decomposition methods

November 13 at 16:00 - 18:10, 2020

Dr. Tianfeng Hou (Postdoctoral Researcher, iTHEMS / Postdoctoral Researcher, Prediction Science Laboratory, RIKEN Cluster for Pioneering Research (CPR) / Postdoctoral Researcher, Data Assimilation Research Team, RIKEN Center for Computational Science (R-CCS))

The use of numerical simulations for complex systems is common. However, significant uncertainties may exist for many of the involved variables, and in order to ensure the reliability of our simulation results and the safety of such complex systems, a stochastic approach providing statistics of the probability distribution of the results is of crucial importance. However, when a highly accurate result is required, the conventional Monte Carlo based probabilistic methodology inherently requires many repetitions of the deterministic analysis and in cases where that deterministic simulation is (relatively) time consuming, such probabilistic assessment can easily become computationally intractable. Hence, to reduce the computational expense of such probabilistic assessments as much as possible, the targets of this seminar are twofold: (1), to exploit an efficient sampling strategy to minimize the number of needed simulations of Monte Carlo based probabilistic analysis; (2), to investigate a surrogate model to reduce the computational expense of single deterministic simulation.

This seminar contains two parts and will be accompanied by a set of illustrative building physical case studies (analysis of the heat and moisture transfer through building components). The first part of this seminar focusses on the use of quasi-Monte Carlo based probabilistic assessment for building performance, since it has the potential to outperform the standard Monte Carlo method. More specifically, the quasi-Monte Carlo sampling strategies and related error estimation techniques will be introduced in detail. In addition, questions on under which conditions the quasi-Monte Carlo can outperform the standard Monte Carlo method will be answered by a set of analyses. The second part of this seminar targets the investigation of using model order reduction methods for optimizing the deterministic simulation, given that it generally allows a (large) reduction of the simulation time without losing the dynamic behavior of the conventional models (such as the transient finite element analysis). Particularly, the fundamental concepts of one common model order reduction method – proper orthogonal decomposition (POD) will be provided, and its potential use for simulating (building physical) problems with different levels of non-linearity and complexity will be illustrated.

Venue: via Zoom

Event Official Language: English

## Colloquium

### The Unreasonable Effectiveness of Quantum Theory in Mathematics

November 26 at 10:00 - 11:30, 2020

Prof. Robbert Dijkgraaf (Director, Institute for Advanced Study in Princeton, USA)

November 26 at 10:00-11:30, 2020 (JST)

November 25 at 20:00-21:30, 2020 (EST)

The physical concepts of quantum theory, in particular of quantum gravity and string theory, have proven to be extremely powerful in addressing deep problems in pure mathematics, from knot invariants to algebraic geometry. Is there such a thing as “quantum mathematics”? Should we add Feynman diagrams, strings, branes and black holes to the language of mathematics?

Venue: via Zoom

Event Official Language: English

# Person of the Week

## Self-introduction: Tianfeng Hou

2020-11-05

My name is Tianfeng Hou and I joined iTHEMS in November 2020. I am originally from a city in the east of China. After I finished my undergraduate study, I moved to the Netherlands (Leiden University) to study applied mathematics. And after that I moved to Belgium (KU Leuven) to continue with my PhD career. Recently, I finished my PhD with a title ’Efficient Probabilistic Assessment of Hygrothermal Performance: sequential Monte Carlo and decomposition methods’. Particularly, two tasks are included in this research. First, a faster surrogate model is developed in order to replace the current time-consuming building simulation models. Second, an efficient sampling strategy that can minimize the needed simulations in the framework of Monte Carlo based probabilistic analysis is set up. All in all, I think mathematics is fun, and I am very enthusiastic about the use of mathematics to solve different engineering problems. During my stay in iTHEMS I hope I can have the opportunity to cooperate with researchers from different disciplines and explore more about the beauty of mathematics.

If you would like to cancel your subscription or change your email address,

please let us know via our contact form.