新メンバー：Almiranteさん New member: Almirante
2026年4月16日 | 新着情報
A new postdoctoral researcher, Almirante, has joined our group.
研究員のAlmiranteさんが研究室のメンバーに加わりました。
新メンバー：三河さん、赤池さん、秋吉さん、倉持さん、山本さん New members: Mikawa, Akaike, Akiyoshi, Kuramochi, and Yamamoto
2026年4月10日 | 新着情報
A new graduate student in the Doctor course, Mikawa, and a new graduate student in the Master course, Akaike, have joined our group. In addition, three undergraduate fourth-year students, Akiyoshi, Kuramochi, and Yamamoto, will perform the graduation research in our group.
大学院生（D1）の三河さん、M1の赤池さん、４年生・卒研生の秋吉さん、倉持さん、山本さんが研究室のメンバーに加わりました。
Tokinaga-san received Meikeikai Award 時長さん茗渓会賞受賞
2026年3月25日 | 新着情報
Mr. Tokinaga has received the Meikeikai Award in March 2026. Congratulations!
時長隆乃介さん（物理学類4年生）が茗渓会賞（2026年3月）を受賞しました。おめでとうございます。
Yoshinaga-san, got a PhD degree; 吉永さん博士（理学）取得
| 新着情報
Dr. Yoshinaga has been awarded a PhD degree (Doctor’s degree) of Science. His PhD thesis is “Density-Dependent Effective Hamiltonian for Shell-Model Calculation”. Congratulations!
吉永孝太さんが博士号を取得しました。学位を取得した博士論文は、「殻模型計算における密度依存有効相互作用」です。おめでとうございます。
Shoji-san received Meikeikai Award 庄司さん茗渓会賞受賞
| 新着情報
Mr. Shoji has received the Meikeikai Award in March 2026. Congratulations!
庄司拓未さん（物理学学位プログラム M2）が茗渓会賞（2026年3月）を受賞しました。おめでとうございます。
Hagihara-san received Dean Award of Degree Programs in Pure and Applied Sciences 萩原さん数理物質科学研究群長賞受賞
| 新着情報
Mr. Hagihara has received the Dean’s Award of Degree Programs in Pure and Applied Sciences. Congratulations!
萩原健太さん(物理学学位プログラム M2)が数理物質科学研究群長賞を受賞しました。おめでとうございます。
Shoji-san, Hagihara-san got Msc degrees; Ishii-san, Uchino-san, Tokinaga-san got Bsc degrees; 庄司さん、萩原さん修士（理学）取得、石井さん、内野さん、時長さん学士（理学）取得
| 新着情報
Mr. Shoji and Mr. Hagihara have been awarded the Master’s degree of Science on March 25th, 2026. Ms. Ishii, Mr Unicho, and Mr. Tokinaga have been awarded the Bachelor’s degree of Science on March 25th, 2026. Congratulations!
庄司さん、萩原さんが修士（理学）を取得しました。また、石井さん、内野さん、時長さんが学士（理学）を取得しました。おめでとうございます。
Seminar (セミナー)2026.3.31 Matthias Heinz (Oak Ridge Nat. Lab.)
2026年3月24日 | 新着情報
The following seminar will be held on March 31st, 2026, in Meeting Room A, CCS, University of Tsukuba.
Lecturer: Matthias Heinz (Oak Ridge National Laboratory, USA)
Place: Meeting Room A (1F), Center for Computational Sciences, University of Tsukuba
Date/Time: March 31st, 2026, 13:30-
Title:
Towards precise ab initio predictions of neutron densities and skins
Abstract:
While proton densities of atomic nuclei are experimentally relatively accessible, measuring neutron densities is a formidable challenge. Knowledge of neutron densities, however, is crucial. Neutron densities contribute to fundamental interactions in nuclei, making them relevant for searches for physics beyond the standard model. The development of neutron skins in heavy nuclei with more neutrons than protons impacts our understanding nuclear forces in neutron-rich environments. This then has implications for the properties of matter in neutron stars. As neutron densities are very difficult to measure, we rely on nuclear theory for predictions. In this seminar, I discuss work on ab initio computations of neutron densities of nuclei. Ab initio, or first-principles, nuclear theory employs nuclear forces from effective field theory and systematically improvable many-body methods, allowing for complete uncertainty quantification. This enables precise predictions of nuclear properties with robust uncertainty estimates. I present work on neutron densities for muon to electron conversion, a proposed beyond-standard-model process, and analyses of high-precision electron scattering and parity violating electron scattering, which aim to determine the neutron skins of key nuclei. Because of the complete control over the uncertainties that enter our calculations, our ab initio computations give new insights into the nuclear structure physics in each of these domains.
Seminar (セミナー)2026.2.20 Hjorth-Jensen, Morten (Univ. Oslo)
2026年2月10日 | 新着情報
The following seminar will be held on February 20th, 2026, in Meeting Room A, CCS, University of Tsukuba.
Lecturer: Morten Hjorth-Jensen (University of Oslo)
Place: Meeting Room A (1F), Center for Computational Sciences, University of Tsukuba
Date/Time: February 20th, 2026, 13:45-
Title: Machine Learning for Nuclear Physics and Many-body Physics
Abstract: In this talk, I will present a focused overview of recent developments in machine learning methods (both discriminative and generative) and their application to quantum many-body problems in nuclear physics. The emphasis will be on first-principles approaches to strongly interacting fermionic systems, where the exponential growth of Hilbert space presents a fundamental computational challenge.
I will discuss in particular the framework of neural-network quantum states (NQS), in which variational wave functions are represented using deep neural architectures and optimized via stochastic variational Monte Carlo, as well as physics-informed neural networks (PINNs) applied to many-body Schrödinger-type equations and related differential formulations. These approaches enable flexible representations of correlated wave functions, improved variational ansätze beyond traditional Slater–Jastrow forms, and scalable treatments of high-dimensional configuration spaces.
Applications will be presented for systems of direct relevance to nuclear physics, including infinite neutron matter and strongly correlated nuclear Hamiltonians, with comparisons to traditional many-body techniques such as coupled-cluster theory, quantum Monte Carlo, and configuration interaction methods. Selected examples from condensed matter physics will also be discussed to highlight common methodological structures and differences in correlation regimes.The overarching goal is to assess how modern machine learning architectures can systematically improve variational accuracy, capture nontrivial correlation effects, and potentially reshape computational strategies for strongly interacting quantum systems.
