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External Awards LIFE2024 Young Presenter AwardWinner: Koji Sakai, NTT Basic Research Laboratories Date: September 14, 2024 Organization: The Society of Life Support Engineering For “Self-folding Microelectrode Array for Electrical Recordings from in vitro Modular 3D Neuronal Network.” Published as: K. Sakai, “Self-folding Microelectrode Array for Electrical Recordings from in vitro Modular 3D Neuronal Network,” LIFE2024, OS-5-8, Tokyo, Japan, Sept. 2024. Best Paper AwardWinners: Takuma Tsurugaya, NTT Device Technology Laboratories; Koji Takeda, NTT Device Technology Laboratories; Takuro Fujii, NTT Device Technology Laboratories; Toru Segawa, NTT Device Technology Laboratories; Shinji Matsuo, NTT Device Technology Laboratories Date: October 2, 2024 Organization: The 29th IEEE International Semiconductor Laser Conference (ISLC) 2024 For “Continuous-wave Operation of 1D Photonic-crystal Nanolasers on SiO2/Si at up to 100°C.” Published as: T. Tsurugaya, K. Takeda, T. Fujii, T. Segawa, and S. Matsuo, “Continuous-wave Operation of 1D Photonic-crystal Nanolasers on SiO2/Si at up to 100°C,” ISLC 2024, Orlando, Florida, USA, Sept./Oct. 2024. CSS2024 Encouragement AwardWinners: Osamu Saisho, NTT Social Informatics Laboratories; Takayuki Miura, NTT Social Informatics Laboratories; Kazuki Iwahana, NTT Social Informatics Laboratories; Masanobu Kii, NTT Social Informatics Laboratories; Rina Okada, NTT Social Informatics Laboratories Date: October 25, 2024 Organization: Information Processing Society of Japan (IPSJ)/Computer Security Symposium 2024 (CSS2024) For “Active Synthetic Data Generation with Joint Consideration of Differential Privacy and Labeling Efficiency.” Published as: O. Saisho, T. Miura, K. Iwahana, M. Kii, and R. Okada, “Active Synthetic Data Generation with Joint Consideration of Differential Privacy and Labeling Efficiency,” Proc. of CSS2024, pp. 1839–1845, Kobe, Hyogo, Japan, Oct. 2024. CSS2024 Paper AwardWinners: Tomoya Yamashita, NTT Social Informatics Laboratories; Takayuki Miura, NTT Social Informatics Laboratories; Yuuki Yamanaka, NTT Social Informatics Laboratories; Toshiki Shibahara, NTT Social Informatics Laboratories; Masanori Yamada, NTT Social Informatics Laboratories Date: October 25, 2024 Organization: IPSJ/CSS2024 For “Concept Unlearning for Large Language Models.” Published as: T. Yamashita, T. Miura, Y. Yamanaka, T. Shibahara, and M. Yamada, “Concept Unlearning for Large Language Models,” Proc. of CSS2024, pp. 295–302, Kobe, Hyogo, Japan, Oct. 2024. Best Paper AwardWinners: Hiroshi Hamada, NTT Device Technology Laboratories; Abdo Ibrahim, NTT Device Technology Laboratories; Takuya Tsutsumi, NTT Device Technology Laboratories; Hiroyuki Takahashi, NTT Device Technology Laboratories Date: October 30, 2024 Organization: The 2024 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS 2024) For “300-GHz 160-Gb/s InP-HEMT Wireless Front-end with Fully Differential Architecture.” Published as: H. Hamada, A. Ibrahim, T. Tsutsumi, and H. Takahashi, “300-GHz 160-Gb/s InP-HEMT Wireless Front-end with Fully Differential Architecture,” BCICTS 2024, Florida, USA, Oct. 2024. Best Paper Award 1st Runner-upWinners: Yu Mitsuzumi, NTT Communication Science Laboratories; Akisato Kimura, NTT Communication Science Laboratories; Go Irie, Tokyo University of Science/NTT Communication Science Laboratories; Atsushi Nakazawa, Okayama University/Kyoto University Date: October 30, 2024 Organization: The 2024 IEEE International Conference on Image Processing (ICIP 2024) For “Cross-action Cross-subject Skeleton Action Recognition via Simultaneous Action-subject Learning with Two-step Feature Removal.” Published as: Y. Mitsuzumi, A. Kimura, G. Irie, and A. Nakazawa, “Cross-action Cross-subject Skeleton Action Recognition via Simultaneous Action-subject Learning with Two-step Feature Removal,” Proc. of ICIP 2024, pp. 2182–2186, Abu Dhabi, United Arab Emirates, Oct. 2024. BMVC 2024 Outstanding ReviewerWinner: Akisato Kimura, NTT Communication Science Laboratories Date: November 4, 2024 Organization: The 35th British Machine Vision Conference (BMVC 2024) ACP/IPOC 2024 Best Paper AwardWinners: Akio Yamasaki, Graduate School of Engineering, Osaka University; Daisuke Hisano, Graduate School of Engineering, Osaka University; Takahiro Suzuki, NTT Access Network Service Systems Laboratories; Sang-Yuep Kim, NTT Access Network Service Systems Laboratories; Jun-ichi Kani, NTT Access Network Service Systems Laboratories; Tomoaki Yoshida, NTT Access Network Service Systems Laboratories Date: November 4, 2024 Organization: Asia Communications and Photonics Conference (ACP)/Information Photonics and Optical Communications (IPOC) 2024 For “CMA-based Multi-thread Adaptive Frequency Domain Equalization for Fully Virtualized Coherent Access Networks.” Published as: A. Yamasaki, D. Hisano, T. Suzuki, S.-Y. Kim, J. Kani, and T. Yoshida, “CMA-based Multi-thread Adaptive Frequency Domain Equalization for Fully Virtualized Coherent Access Networks,” ACP/IPOC 2024, Beijing, China, Nov. 2024. Papers Published in Technical Journals and Conference ProceedingsOn Computational Complexity of Unitary and State Design PropertiesY. Nakata, Y. Takeuchi, M. Kliesch, and A. Darmawan arXiv:2410.23353, October 2024. We study unitary and state t-designs from a computational complexity theory perspective. First, we address the problems of computing frame potentials that characterize (approximate) t-designs. We provide a quantum algorithm for computing the frame potential and show that 1. exact computation can be achieved by a single query to a #P-oracle and is #P-hard, 2. for state vectors, it is BQP-complete to decide whether the frame potential is larger than or smaller than certain values, if the promise gap between the two values is inverse-polynomial in the number of qubits, and 3. both for state vectors and unitaries, it is PP-complete if the promise gap is exponentially small. As the frame potential is closely related to the out-of-time-ordered correlators (OTOCs), our result implies that computing the OTOCs with exponential accuracy is also hard. Second, we address promise problems to decide whether a given set is a good or bad approximation to a t-design and show that this problem is in PP for any constant t and is PP-hard for t=1,2 and 3. Remarkably, this is the case even if a given set is promised to be either exponentially close to or worse than constant away from a 1-design. Our results illustrate the computationally hard nature of unitary and state designs. |