Publication

Preprints

• [41] Adam Wills, Min-Hsiu Hsieh, Hayata Yamasaki, “Constant-Overhead Magic State Distillation,” arXiv:2408.07764, August 2024.

• [40] Masahito Hayashi, Hayata Yamasaki, “Generalized Quantum Stein's Lemma and Second Law of Quantum Resource Theories,” arXiv:2408.02722, August 2024.

• [39] Shinichi Sunami, Shiro Tamiya, Ryotaro Inoue, Hayata Yamasaki, Akihisa Goban, “Scalable Networking of Neutral-Atom Qubits: Nanofiber-Based Approach for Multiprocessor Fault-Tolerant Quantum Computer,” arXiv:2407.11111, July 2024. 

• [38] Yu Tanaka, Hayata Yamasaki, Mio Murao, “Quantum State Preparation via Free Binary Decision Diagram,” arXiv:2407.01671, July 2024. 

• [37] Yonghae Lee, Joonwoo Bae, Hayata Yamasaki, Soojoon Lee, “Improved bounds on quantum uncommon information,” arXiv:2406.14879, June 2024. 

• [36] Oliver Hahn, Ryuji Takagi, Giulia Ferrini, Hayata Yamasaki, “Classical simulation and quantum resource theory of non-Gaussian optics,” arXiv:2404.07115, April 2024. 

• [35] Satoshi Yoshida, Shiro Tamiya, Hayata Yamasaki, “Concatenate codes, save qubits,” arXiv:2402.09606, February 2024. 

• [34] Hayata Yamasaki, Kohdai Kuroiwa, Patrick Hayden, Ludovico Lami, “Entanglement cost for infinite-dimensional physical systems,” arXiv:2401.09554, January 2024.

• [33] Hayata Yamasaki, Kohdai Kuroiwa, “Generalized Quantum Stein's Lemma: Redeeming Second Law of Resource Theories,” arXiv:2401.01926, January 2024.

• [32] Hayata Yamasaki, Natsuto Isogai, Mio Murao, “Advantage of Quantum Machine Learning from General Computational Advantages,” arXiv:2312.03057, December 2023.

• [31] Koki Shiraishi, Hayata Yamasaki, Mio Murao, “Efficient decoding of stabilizer code by single-qubit local operations and classical communication,” arXiv:2308.14054, August 2023.

• [30] Florian Meier, Hayata Yamasaki, “Energy-Consumption Advantage of Quantum Computation,” arXiv:2305.11212, May 2023.

• [29] Hayata Yamasaki, Sathyawageeswar Subramanian, “Constant-time one-shot testing of large-scale graph states,” arXiv:2201.11127, January 2022.

• [28] Hayata Yamasaki, Sho Sonoda, “Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning,” arXiv:2106.09028, June 2021.

• [27] Hayata Yamasaki, Kosuke Fukui, Yuki Takeuchi, Seiichiro Tani, Masato Koashi, “Polylog-overhead highly fault-tolerant measurement-based quantum computation: all-Gaussian implementation with Gottesman-Kitaev-Preskill code,” arXiv:2006.05416, June 2020.

• [26] Hayata Yamasaki, “Entanglement theory in distributed quantum information processing,” arXiv:1903.09655, March 2019.

• [25] Hayata Yamasaki, Mio Murao, “Spread quantum information in one-shot quantum state merging,” arXiv:1903.03619, March 2019.

Peer-Reviewed Articles

• [24] Andrew S. Darmawan, Yoshifumi Nakata, Shiro Tamiya, Hayata Yamasaki, “Low-depth random Clifford circuits for quantum coding against Pauli noise using a tensor-network decoder,” Physical Review Research 6, 023055, April 2024. arXiv:2212.05071

• [23] Kohdai Kuroiwa, Ryuji Takagi, Gerardo Adesso, Hayata Yamasaki, “Robustness and weight resource measures without convexity restriction: Multicopy witness and operational advantage in static and dynamical quantum resource theories,” Physical Review A, 109, 042403, April 2024. arXiv:2310.09321

• [22] Kohdai Kuroiwa, Ryuji Takagi, Gerardo Adesso, Hayata Yamasaki, “Every quantum helps: Operational advantage of quantum resources beyond convexity,” Physical Review Letters, 132, 150201, April 2024. arXiv:2310.09154

• [21] Hayata Yamasaki, Masato Koashi, “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” Nature Physics 20, 247, January 2024. arXiv:2207.08826

• [20] Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda,  “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” Proceedings of The Fortieth International Conference on Machine Learning (ICML2023), Proceedings of Machine Learning Research 202, 39008, July 2023. arXiv:2301.11936

• [19] Shiro Tamiya, Hayata Yamasaki, “Stochastic gradient line Bayesian optimization for efficient noise-robust optimization of parameterized quantum circuits,” npj Quantum Information 8, 90, May 2022. arXiv:2111.07952

• [18] Simon Morelli*, Hayata Yamasaki* (*: equal contribution), Marcus Huber, Armin Tavakoli, “Entanglement detection with imprecise measurements,” Physical Review Letters 128, 250501, June 2022. arXiv:2202.13131

• [17] Hayata Yamasaki, Simon Morelli, Markus Miethlinger, Jessica Bavaresco, Nicolai Friis, Marcus Huber, “Activation of genuine multipartite entanglement: Beyond the single-copy paradigm of entanglement characterisation,” Quantum 6, 695, April 2022. arXiv:2106.01372

• [16] Kohdai Kuroiwa, Hayata Yamasaki, “Asymptotically consistent measures of general quantum resources: Discord, non-Markovianity, and non-Gaussianity,” Physical Review A Letter 104, L020401, July 2021. arXiv:2103.05665

• [15] Yoshifumi Nakata*, Eyuri Wakakuwa*, Hayata Yamasaki* (*: equal contribution in alphabetical order), “One-shot quantum error correction of classical and quantum information,” Physical Review A 104, 012408, June 2021. arXiv:2011.00668

• [14] Hayata Yamasaki, Madhav Krishnan Vijayan, Min-Hsiu Hsieh, “Hierarchy of quantum operations in manipulating coherence and entanglement,” Quantum 5, 480, June 2021. arXiv:1912.11049

• [13] Yonghae Lee, Hayata Yamasaki, Soojoon Lee, “Quantum state rotation: Circularly transferring quantum states of multiple users,” Physical Review A 103, 062613, June 2021. arXiv:2009.11539

• [12] Kohdai Kuroiwa, Hayata Yamasaki, “General Quantum Resource Theories: Distillation, Formation and Consistent Resource Measures,” Quantum 4 355, November 2020. arXiv:2002.02458  

• [11] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions,” Advances in Neural Information Processing Systems 33, 13674 (NeurIPS 2020), September 2020. arXiv:2004.10756

• [10] Takaya Matsuura, Hayata Yamasaki, Masato Koashi, “Equivalence of approximate Gottesman-Kitaev-Preskill codes,” Physical Review A 102, 032408, September 2020. arXiv:1910.08301 

• [9] Xiao-Hui Sun, He Wang, Hideaki Otsu, Hiroyoshi Sakurai, Hayata Yamasaki (28th author), and other 26 authors, “Spallation and fragmentation cross sections for 168 MeV/nucleon 136Xe ions on proton, deuteron, and carbon targets,” Physical Review C 101, 064623, June 2020.

• [8] Hayata Yamasaki, Takaya Matsuura, Masato Koashi, “Cost-reduced all-Gaussian universality with the Gottesman-Kitaev-Preskill code: Resource-theoretic approach to cost analysis,” Physical Review Research 2, 023270, June 2020. arXiv:1911.11141 

• [7] Yonghae Lee, Hayata Yamasaki, Gerardo Adesso, Soojoon Lee, “One-shot quantum state exchange,” Physical Review A 100, 042306, October 2019. arXiv:1905.12332

• [6] Yonghae Lee, Ryuji Takagi, Hayata Yamasaki, Gerardo Adesso, and Soojoon Lee, “State exchange with quantum side information,” Physical Review Letters 122, 010502, December 2018. arXiv:1809.07030

• [5] Hayata Yamasaki and Mio Murao, “Quantum State Merging for Arbitrarily Small-Dimensional Systems,” IEEE Transactions on Information Theory 65, 3950, December 2018. arXiv:1806.07875

• [4] Hayata Yamasaki and Mio Murao, “Distributed Encoding and Decoding of Quantum Information over Networks,” Advanced Quantum Technologies 2, 1800066, December 2018. arXiv:1807.11483

• [3] Hayata Yamasaki, Alexander Pirker, Mio Murao, Wolfgang Dür, and Barbara Kraus, “Multipartite entanglement outperforming bipartite entanglement under limited quantum system sizes,” Physical Review A 98, 052313, selected to be Editors' Suggestion, November 2018. arXiv:1808.00005

• [2] Hayata Yamasaki, Akihito Soeda, and Mio Murao, “Graph-associated entanglement cost of a multipartite state in exact and finite-block-length approximate constructions,” Physical Review A 96, 032330, September 2017. arXiv:1705.00006

• [1] He Wang, Hideaki Otsu, Hiroyoshi Sakurai, Hayata Yamasaki (27th author), and other 24 authors, “Spallation reaction study for fission products in nuclear waste: Cross section measurements for 137Cs and 90Sr on proton and deuteron,” Physics Letters B 754, 104, January 2016.

• [18] Hayata Yamasaki, “Advantage of Quantum Machine Learning from General Computational Advantages,” Workshop on quantum machine learning ---mathematical foundations and applications, 13th August 2024.

• [17] Hayata Yamasaki, “Concatenate codes, save qubits,” 2024 YITP Quantum Error Correction Workshop, Kyoto, Japan, 21st March 2024.

• [16] Hayata Yamasaki, “量子機械学習 (Quantum Machine Learning),” Computational Physics Spring School 2024, Okinawa, Japan, 15th March 2024.

• [15] Hayata Yamasaki, “高速な量子機械学習の基盤構築 (Foundation of High-Speed Quantum Machine Learning),” さきがけ量子情報処理領域領域公開シンポジウム（２期生成果報告会）, Tokyo, Japan, 7th March 2024.

• [14] Hayata Yamasaki, “Energy-Consumption Advantage of Quantum Computation,” Japanese-French Quantum Information workshop, Tokyo, Japan, 14th December 2023.

• [13] Hayata Yamasaki, “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” QI2023 satellite workshop, Osaka, Japan, 20th November 2023.

• [12]  “高速な量子機械学習の基盤構築 (Foundation of High-Speed Quantum Machine Learning),” 「量子情報処理」×「革新的コンピューティング」合同セミナー, Fukuoka, Japan, 13th September 2023.

• [11]  “高速な量子機械学習の理論基盤の構築 (Construction of Theoretical Foundation of High-Speed Quantum Machine Learning),” 3rd Quantum Software Workshop, Tokyo, Japan, 3rd August 2023.

• [10] Hayata Yamasaki, “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” Quantum error correction workshop, Kyoto, Japan, 20th March 2023.

• [9] Hayata Yamasaki, “Outlook for Photonic Quantum Computing and Quantum Machine Learning,” Session CI-3 機械学習と光・ICT技術, IEICE (The Institute of Electronics, Information and Communication Engineers) General Conference 2023, Saitama, Japan, 7th March 2023.

• [8] Hayata Yamasaki, “Quantum Machine Learning with Optimized Random Features: Applications of Exponential Speedup without Sparse and Low-Rank Matrices,” the JSPS Japan-NUS (Singapore) Joint seminar, Tokyo, Japan, 20th February 2023.

• [7] Hayata Yamasaki, “Quantum Machine Learning with Optimized Random Features: Applications of Exponential Speedup without Sparsity and Low-Rankness Assumptions,” satellite session “Quantum information and low dimensional systems” of the 20th International Symposium on the Physics of Semiconductors and Applications (ISPSA 2022), Jeju, Korea, 19th July 2022.

• [6] Hayata Yamasaki, Shiro Tamiya, “Stochastic Gradient Line Bayesian Optimization: Reducing Measurement Shots in Optimizing Parameterized Quantum Circuits,” The 4th International Workshop on Quantum Resource Estimation (QRE2022), New York, United States, 18th June 2022.

• [5] Hayata Yamasaki, “Polylog-Overhead Highly Fault-Tolerant Measurement-Based Quantum Computation: Application of Entanglement without Geometrical Constraints,” Recent progress in theoretical physics based on quantum information theory (Yukawa Institute for Theoretical Physics (YITP) workshop), Online, 2nd March 2021.

• [4] Hayata Yamasaki, “Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions,” 量子多体系の熱力学––数理の発展と展望 (Thermodynamics on quantum many-body systems –– mathematical progress and outlook), Online, September 2020.

• [3] Hayata Yamasaki, “Resources required for encoding/decoding quantum information over networks,” Workshop on Quantum Networks and Quantum Information, Tokyo, Japan, February 2020.

• [2] Hayata Yamasaki, “Entanglement theory in distributed quantum information processing,” 26th Workshop of Quantum Information Kanto Student Chapter, Tokyo, Japan, March 2019.

• [1] Hayata Yamasaki, Mio Murao, “Partial quantum information and two-way classical communication,” post-AQIS18 workshop, Nagoya, Japan, September 2018.

• [28] Satoshi Yoshida, Shiro Tamiya, Hayata Yamasaki, “Concatenate codes, save qubits,” 19th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC2024), Okinawa, Japan, 13th September 2024.

• [27] Shiro Tamiya, Masato Koashi, Hayata Yamasaki, “Polylog-time- and constant-space-overhead fault-tolerant quantum computation with quantum low-

• density parity-check codes,” 24th Asian Quantum Information Science Conference (AQIS2024), 30th August 2024.

• [26] Hayata Yamasaki, Natsuto Isogai, Mio Murao, “Advantage of Quantum Machine Learning from General Computational Advantages,” 24th Asian Quantum Information Science Conference (AQIS2024), 29th August 2024.

• [25] Kohdai Kuroiwa, Ryuji Takagi, Gerardo Adesso, Hayata Yamasaki, “Every quantum helps: Operational advantage of quantum resources beyond convexity,” Beyond IID in Information Theory 12, Illinois, United States, 29th July 2024.

• [24] Hayata Yamasaki, “Open problem: A perspective on generalized quantum Stein's lemma,” Towards Infinite Dimension and Beyond in Quantum Information (24w5274) workshop, Granada, Spain, 8th May 2024.

• [23] Hayata Yamasaki, “Open Problem: Efficient Maximum-Likelihood Decoder for High-Rate Concatenated Codes,” Advances in Quantum Coding Theory, Berkeley, United States, 16th February 2024.

• [22] Hayata Yamasaki, Kohdai Kuroiwa, Patrick Hayden, Ludovico Lami,  “Entanglement cost for infinite-dimensional physical systems,” Quantum Information Processing 2024 (QIP2024), Taipei, Taiwan, 19th January 2024.

• [21] Florian Meier, Hayata Yamasaki, “Energy-Consumption Advantage of Quantum Computation,” Quantum Resources 2023, Singapore, 15th December 2023.

• [20] Kohdai Kuroiwa, Ryuji Takagi, Gerardo Adesso, Hayata Yamasaki,  “Every quantum helps: Operational advantage of quantum resources beyond convexity,” Quantum Resources 2023, Singapore, 12th December 2023.

• [19] Hayata Yamasaki, Masato Koashi,  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” 6th International Conference on Quantum Error Correction (QEC23), Syndey, Australia, 30th October 2023. 

• [18] Hayata Yamasaki, Simon Morelli, Markus Miethlinger, Jessica Bavaresco, Nicolai Friis, Marcus Huber, “Activation of genuine multipartite entanglement: Beyond the single-copy paradigm of entanglement characterisation,” 23rd Asian Quantum Information Science Conference (AQIS2023), Seoul, Korea, 30th August 2023.

• [17] Hayata Yamasaki, Masato Koashi,  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” 26th Conference on Quantum Information Processing (QIP2023), Ghent, Belgium, 7th February 2023. Selected to be a short plenary talk. 

• [16] Hayata Yamasaki, Kohdai Kuroiwa, “General Quantum Resource Theories: Maximal Resources, Catalytic Replication, and Asymptotically Consistent Measures,” Quantum resources workshop, Singapore, 5th December 2022.

• [15] Hayata Yamasaki, Masato Koashi,  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” Quantum Confession, Älvkarleby, Sweden, 4th August 2022. 

• [14] Hayata Yamasaki, Kohdai Kuroiwa, “General Quantum Resource Theories: Maximal Resources, Catalytic Replication, and Asymptotically Consistent Measures,” Quantum Information Entropy in Physics, Online, 24th March 2022.

• [13] Sho Sonoda, Hayata Yamasaki, Sathyawageeswar Subramanian, and Masato Koashi, "Quantum algorithm for sampling optimal random features", RQC-AIP Joint Seminar, online, November 2021. 

• [12] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Regression and Classication with Optimized Random Features: Applications of Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rankness Assumptions,” Quantum Techniques in Machine Learning 2021 (QTML2021), Online, November 2021.

• [11] Hayata Yamasaki, Simon Morelli, Markus Miethlinger, Jessica Bavaresco, Nicolai Friis, Marcus Huber, “Activation of genuine multipartite entanglement: Beyond the single-copy paradigm of entanglement characterisation,” Beyond IID in Information Theory 9, Online, October 2021.

• [10] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Regression and Classification with Optimized Random Features: Applications of Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rankness Assumptions,” 21th Asian Quantum Information Science Conference (AQIS2021), Online, September 2021.

• [9] Shiro Tamiya, Hayata Yamasaki, “Stochastic Gradient Line Bayesian Optimization: Reducing Measurement-Shot Number in Variational Quantum Algorithms,” 21st Asian Quantum Information Science Conference (AQIS2021), Online, September 2021.

• [8] Kohdai Kuroiwa, Hayata Yamasaki, “General Quantum Resource Theories: Maximal Resources, Catalytic Replication, and Consistent Measures,” SFB BeyondC Autumn Workshop 2021, Innsbruck, Austria, September 2021.

• [7] Hayata Yamasaki, “MBQC and device-independent verification of quantum computation,” Kraus-Huber mini-workshop, Online, March 2021.

• [6] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions,”, 20th Asian Quantum Information Science Conference (AQIS2020), Online, December 2020.

• [5] Hayata Yamasaki, Madhav Krishnan Vijayan, Min-Hsiu Hsieh, “Hierarchy of quantum operations in manipulating coherence and entanglement,” lightening talk, Beyond i.i.d. in information theory VIII, Online, November 2020.

• [4] Hayata Yamasaki, Takaya Matsuura, Masato Koashi, “Cost-Reduced All-Gaussian Universality with the Gottesman-Kitaev-Preskill code,” International Workshop for Young Researchers on the Future of Quantum Science and Technology (FQST2020), Tokyo, Japan, February 2020.

• [3] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Fast quantum algorithm for data approximation by optimized random features,” The 41st Quantum Information Technology Symposium (QIT41), Tokyo, Japan, November 2019.

• [2] Hayata Yamasaki, Mio Murao, “One-way and two-way LOCC separation in entanglement cost of one-shot quantum state merging,” Beyond i.i.d. in information theory VII, Sydney, Australia, July 2019.

• [1] Hayata Yamasaki, Mio Murao, “Quantification of nonlocal properties of quantum encoding and decoding,” New movements in quantum information and condensed matter physics, Chiba, Japan, September 2018.

• [31] Florian Meyer, Hayata Yamasaki, “Energy-Consumption Advantage of Quantum Computation,” Quantum Innovation 2023, Tokyo, Japan, 16th November 2023, Quantum Innovation 2023 Poster Presentation Awards for Young Researchers given to our student coauthor, Florian Meyer.

• [30] Hayata Yamasaki, Sathyawageeswar Subramanian, Satochi Hayakawa, Sho Sonoda, “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” Quantum Innovation 2023, Tokyo, Japan, 16th November 2023.

• [29] Hayata Yamasaki, “Fast and Versatile Quantum Machine Learning,” 4th Japanese-American-German Frontiers of Science (JAGFOS) Symposium, Dresden, Germany, 6th October 2023.

• [28] Hayata Yamasaki, Sathyawageeswar Subramanian, Satochi Hayakawa, Sho Sonoda, “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” 23rd Asian Quantum Information Science Conference (AQIS2023), Seoul, Korea, 28th August 2023.

• [27] Hayata Yamasaki, Sathyawageeswar Subramanian, Satochi Hayakawa, Sho Sonoda, “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” The Fortieth International Conference on Machine Learning (ICML2023), Hawaii, United States, 26th July 2023.

• [26] Hayata Yamasaki, Sathyawageeswar Subramanian, Satochi Hayakawa, Sho Sonoda, “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” The 25th Information-Based Induction Sciences Workshop (IBIS2022), Tsukuba, Japan, 22nd November 2022.

• [25] Kohdai Kuroiwa, Hayata Yamasaki, “General Quantum Resource Theories: Maximal Resources, Catalytic Replication, and Consistent Measures,” 21st Asian Quantum Information Science Conference (AQIS2021), Online, September 2021, Best Student Poster Award given to our student coauthor, Kohdai Kuroiwa.

• [24] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Learning with Optimized Random Features: End-to-End Application of Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions,” 16th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC2021), Online, July 2021.

• [23] Hayata Yamasaki, Kousuke Fukui, Yuki Takeuchi, Seiichiro Tani, and Masato Koashi, “Polylog-Overhead Highly Fault-Tolerant Measurement-Based Quantum Computation: All-Gaussian Implementation with Gottesman-Kitaev-Preskill Code,” SFB BeyondC Winter Workshop 2021, Online, February 2021.

• [22] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions,” 24th Annual Conference on Quantum Information Processing (QIP2021), Online, February 2021.

• [21] Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi, “Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions,” Advances in Neural Information Processing Systems 33 (NeurIPS 2020), Online, December 2020.

• [20] Hayata Yamasaki, Yuki Takeuchi, Seiichiro Tani, Masato Koashi, and Kousuke Fukui, “Polylog-overhead fault-tolerant measurement-based quantum computation by homodyne detection,” 15th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC2020), Online, June 2020.

• [19] Hayata Yamasaki, Madhav Krishnan Vijayan, Min-Hsiu Hsieh, “Hierarchy of quantum operations in manipulating coherence and entanglement,” 23rd Annual Conference on Quantum Information Processing (QIP2020), Shenzhen, China, January 2020.

• [18] Hayata Yamasaki, Yuki Takeuchi, Seiichiro Tani, Masato Koashi, and Kousuke Fukui, “Polylog-overhead fault-tolerant MBQC by homodyne detection,” 27th Workshop of Quantum Information Kanto Student Chapter, Tokyo, Japan, December 2019. 

• [17] Hayata Yamasaki, Sathyawageeswar Subramanian, and Sho Sonoda, “Fast quantum algorithm for data approximation by optimized random features,” The 22nd Information-Based Induction Science Workshop (IBIS2019), Nagoya, Japan, November 2019.

• [16] Hayata Yamasaki and Mio Murao, “Spread quantum information in one-shot quantum state merging,” 19th Asian Quantum Information Science Conference (AQIS2019), Seoul, Korea, August 2019. 

• [15] Hayata Yamasaki and Mio Murao, “Distributed Encoding and Decoding of Quantum Information over Networks,” 19th Asian Quantum Information Science Conference (AQIS2019), Seoul, Korea, August 2019.

• [14] Hayata Yamasaki and Mio Murao, “One-way and two-way LOCC separation in entanglement cost of one-shot quantum state merging,” The 14th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC2019), Maryland, United States, June 2019. 

• [13] Hayata Yamasaki and Mio Murao, “One-shot quantum state merging for arbitrarily-small-dimensional systems under one-way and two-way communication,” 22nd Annual Conference on Quantum Information Processing (QIP2019), Boulder, United States, January 2019.

• [12] Hayata Yamasaki and Mio Murao, “Quantum state merging for arbitrarily-small-dimensional systems,” 18th Asian Quantum Information Science Conference (AQIS2018), Nagoya, Japan, September 2018.

• [11] Hayata Yamasaki and Mio Murao, “One-shot exact quantum state merging and splitting,” 1st International Workshop on Quantum Software and Quantum Machine Learning (QSML2018), Sydney, Australia, July 2018.

• [10] Hayata Yamasaki and Mio Murao, “One-shot exact quantum state merging and splitting,” The 13th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC2018), Sydney, Australia, July 2018.

• [9] Hayata Yamasaki and Mio Murao, “Entanglement cost of distributed quantum encoding/decoding,” 4th Seefeld workshop on Quantum Information, Seefeld, Austria, July 2018.

• [8] Hayata Yamasaki and Mio Murao, “Entanglement cost of distributing and retrieving quantum information over networks,” International Conference on challenges in Quantum Information Science (CQIS2018), Tokyo, Japan, April 2018.

• [7] Hayata Yamasaki and Mio Murao, “Entanglement cost of distributed quantum encoding/decoding,” 25th Workshop of Quantum Information Kanto Student Chapter, Tokyo, Japan, March 2018.

• [6] Hayata Yamasaki and Mio Murao, “Entanglement cost of distributed quantum encoding/decoding,” 6th Regional Conference on Science of Hybrid Quantum Systems, Atsugi, Japan, February 2018.

• [5] Hayata Yamasaki, Akihito Soeda, and Mio Murao, “Graph-Associated Entanglement Cost of Multipartite State in Exact and Finite-Block-Length Approximate Construction,” The JSAP Workshop on Quantum Information and Related Fields, Tokyo, Japan, March 2017.

• [4] Hayata Yamasaki, Akihito Soeda, and Mio Murao, “Graph-Associated Entanglement Cost of Multipartite State in Exact and Finite-Block-Length Approximate Construction,” 20th Annual Conference on Quantum Information Processing (QIP2017), Seattle, United States, January 2017.

• [3] Hayata Yamasaki, Akihito Soeda, and Mio Murao, “Graph-Associated Entanglement Cost of Multipartite State in Exact and Finite-Block-Length Approximate Construction,” 24th Workshop of Quantum Information Kanto Student Chapter, Tokyo, Japan, October 2016.

• [2] Hayata Yamasaki, Akihito Soeda, and Mio Murao, “Graph-Associated Entanglement Cost of Multipartite State in Exact and Finite-Block-Length Approximate Construction,” 16th Asian Quantum Information Science Conference (AQIS2016), Taipei, Taiwan, August 2017.

• [1] Hayata Yamasaki, Akihito Soeda, and Mio Murao, “Distributed Construction of Multipartite Entangled States over Quantum Networks,” The 33rd Quantum Information Technology Symposium (QIT33), Atsugi, Japan, November 2015.