Jun Kang and Lin-Wang Wang
Phys. Rev. Applied 18, 064001 (2022) - Published 1 December, 2022
Shallow impurities play critical roles in the applications of semiconductor materials, but their simulations through first-principles calculations are challenging due to the delocalized nature of the impurity wave function. The authors propose a first-principles approach to study shallow impurities, which allows simulations of extremely large supercells to obtain converged impurity levels and wave functions. The method is applied to acceptor-carbon complexes in silicon and yields good agreement with experiments. This work thus presents a feasible approach for accurate simulations of shallow impurities and can provide helpful insights to assist experimental dopant engineering.
Bas van der Zee, Yungui Li, Gert-Jan A.H. Wetzelaer, and Paul W.M. Blom
Phys. Rev. Applied 18, 064002 (2022) - Published 1 December, 2022
Organic light-emitting diodes (OLEDs) based on thermally activated delayed fluorescence (TADF) are alternatives to today’s commercial phosphorescent OLEDs with heavy-metal dopants, but their limited stability remains a key issue. This work provides a quantitative insight into the degradation mechanisms. The authors reproduce the voltage and light output using a recently developed device model, and find that triplet-polaron annihilation is the driving force behind the formation of degradation traps. This understanding leads to the experimental demonstration of enhanced device lifetime, and will provide guidance towards improved stability of TADF OLEDs.
Jake Horder, Simon J.U. White, Angus Gale, Chi Li, Kenji Watanabe, Takashi Taniguchi, Mehran Kianinia, Igor Aharonovich, and Milos Toth
Phys. Rev. Applied 18, 064021 (2022) - Published 8 December, 2022
Lattice defects in two-dimensional materials are compelling sources of single photons for applications in quantum information processing. However, the range of emission wavelengths is broad, the defect types vary and the atomic structures of most are unknown, and the inability to fabricate defects systematically on demand has limited progress. This work leverages a robust, site-specific fabrication technique to produce arrays of blue quantum emitters for study via cryogenic spectroscopy. The authors characterize processes that limit emitter coherence and observe Rabi oscillations, demonstrating the potential of these defects for scalable quantum technologies.
Anasua Chatterjee, Fabio Ansaloni, Torbjørn Rasmussen, Bertram Brovang, Federico Fedele, Heorhii Bohuslavskyi, Oswin Krause, and Ferdinand Kuemmeth
Phys. Rev. Applied 18, 064040 (2022) - Published 14 December, 2022
In spin-based quantum processors, each quantum dot of a qubit is populated by exactly one electron, which requires careful tuning of each gate voltage such that it lies inside the charge-stability region (the “Coulomb diamond”) associated with the dot array. However, mapping the boundary of a multidimensional Coulomb diamond by traditional dense raster scanning would take years, so the authors develop a sparse acquisition technique that autonomously learns Coulomb-diamond boundaries from a small number of measurements. Here we have hardware-triggered line searches in the gate-voltage space of a silicon quadruple dot, with smart search directions proposed by an active-learning algorithm.
Emilien Lavie and Charles C.-W. Lim
Phys. Rev. Applied 18, 064053 (2022) - Published 19 December, 2022
Coherent one-way quantum key distribution (COW-QKD) is a popular cryptography protocol, due to its fairly simple implementation and passive measurement device. Its security analysis is challenging, though, and extra assumptions or modifications are typically employed. Here the authors propose minor modifications to COW-QKD’s prepared states while retaining the original, fully passive measurement device, and generalize the “universal squashing” framework to analyze their system’s security. The results suggest that performance should be comparable to upper bounds from the literature, making this protocol a viable alternative to one based on phase-modulated coherent states.
A.E.E. Dubois, D.A. Broadway, A. Stark, M.A. Tschudin, A.J. Healey, S.D. Huber, J.-P. Tetienne, E. Greplova, and P. Maletinsky
Phys. Rev. Applied 18, 064076 (2022) - Published 26 December, 2022
Magnetic materials are a vital resource in designing energy-efficient information technologies. To try to learn how magnetism develops in ultrathin systems, we measure, but deducing the physics afterward is an ill-posed problem. This study uses neural networks to facilitate the reconstruction of the underlying magnetic textures of thin magnets through measurements of their stray fields. The technique is surprisingly robust to experimental noise, and can reliably reconstruct magnetism in arbitrary directions. Importantly, prior training of the network is not required, and the technique is broadly applicable for solving ill-posed inverse problems when the forward problem is well defined.
Peter Breitman, Michael Pukshansky, Anna Zigelman, Ezra Ben Abu, Ofek Peretz, Sefi Givli, and Amir D. Gat
Phys. Rev. Applied 18, 064077 (2022) - Published 26 December, 2022
The authors study the interaction between a viscous flow and a one-dimensional mechanical metamaterial composed of bistable unit cells, much like a drinking straw. Their twofold model shows excellent agreement with experimental results. While prior studies have focused on tailoring unit-cell structure to obtain a desired multistable behavior, here the viscous fluid allows tuning of rate-dependent properties and nonlocal interaction between unit cells. The ability to manipulate both structural and nonlocal rate-related properties points to the development of smart materials with tunable kinetic relations, large reversible deformations, and tailored dynamic properties.
Yue Meng, Wei Li, and Ruben Juanes
Phys. Rev. Applied 18, 064081 (2022) - Published 27 December, 2022
Unraveling the complex behavior of wet granular media has been challenging, because the effective stresses transmitted through the particles have remained unobservable. The authors use their recently developed extension of photoelasticity for coupled fluid-granular systems to image particle stresses during fracture by air injection in an oil-saturated granular pack. They discover two states of the granular medium evolving with the fractures, plus an “effective-stress shadow” behind the propagating fracture tips. This study points out the power of photoporomechanics for studying coupled fluid-solid processes in granular media, including energy recovery, gas venting, and geohazards.
M.B. Clavel, F. Murphy-Armando, Y. Xie, K.T. Henry, M. Kuhn, R.J. Bodnar, G.A. Khodaparast, D. Smirnov, J.J. Heremans, and M.K. Hudait
Phys. Rev. Applied 18, 064083 (2022) - Published 27 December, 2022
For applications such as low-power tunneling transistors and memory, lasers, qubits, and spintronics, there is interest in using strain to enhance carrier mobility in semiconductors. This experimental and theoretical study investigates transport in highly strained germanium, in which multivalley electron conduction emerges. Surprisingly, all conduction occurs via the L valley in Ge for biaxial tensile strain below 1.6%, while above the contribution from the Γ valley increases, with negligible contributions from the underlying strain template.
Chaitali Joshi, Wenyuan Chen, Henry G. LeDuc, Peter K. Day, and Mohammad Mirhosseini
Phys. Rev. Applied 18, 064088 (2022) - Published 28 December, 2022
The kinetic inductance of charge carriers in disordered superconductors provides a broadband low-loss source of nonlinear electromagnetic response. This work investigates TiN nanowires as an alternative to Josephson junctions for applications involving elevated temperatures, higher frequencies, and strong magnetic fields. An extreme nanowire geometry for TiN microwave resonators leads to current-density concentration and enhanced self-Kerr coefficient, yielding a nonlinearity-to-loss ratio as high as 21% and quality factor exceeding 10,000. Such devices may find application in quantum frequency conversion of microwave photons, and with improvement might attain strong quantum nonlinearity.
P. Kumar, F. Fabre, A. Durand, T. Clua-Provost, J. Li, J.H. Edgar, N. Rougemaille, J. Coraux, X. Marie, P. Renucci, C. Robert, I. Robert-Philip, B. Gil, G. Cassabois, A. Finco, and V. Jacques
Phys. Rev. Applied 18, L061002 (2022) - Published 21 December, 2022
This work bridges research on two-dimensional (2D) materials and quantum sensing technology by demonstrating that optically active spin defects in hexagonal boron nitride can be used for quantitative magnetic field imaging. As proof of concept, the authors image the magnetic field produced by CrTe, a room-temperature van der Waals ferromagnet. This h-BN-based magnetic sensor offers high flexibility and the ability to be placed in atomic-scale proximity to a target sample, and thus is expected to find numerous applications in 2D materials research by offering a simple means to probe in situ the physics of van der Waals heterostructures.
Ziwen Huang, Xinyuan You, Ugur Alyanak, Alexander Romanenko, Anna Grassellino, and Shaojiang Zhu
Phys. Rev. Applied 18, L061001 (2022) - Published 2 December, 2022
The understanding and characterization of realistic noise are critical for assessing and reducing errors in qubits, but theoretical studies often overlook the different roles of Gaussian and non-Gaussian noise in reducing qubit coherence. The authors employ two theoretical approaches to inspect such differences in solid-state qubits, and find a symmetry-breaking effect that is unique to non-Gaussian noise and can be detected experimentally. They also propose a protocol that can significantly increase the coherence time. These findings provide simple yet powerful tools for detecting non-Gaussian noise as well as mitigating its detrimental effect on the qubits.
P. Kumar, F. Fabre, A. Durand, T. Clua-Provost, J. Li, J.H. Edgar, N. Rougemaille, J. Coraux, X. Marie, P. Renucci, C. Robert, I. Robert-Philip, B. Gil, G. Cassabois, A. Finco, and V. Jacques
Phys. Rev. Applied 18, L061002 (2022) - Published 21 December, 2022
This work bridges research on two-dimensional (2D) materials and quantum sensing technology by demonstrating that optically active spin defects in hexagonal boron nitride can be used for quantitative magnetic field imaging. As proof of concept, the authors image the magnetic field produced by CrTe, a room-temperature van der Waals ferromagnet. This h-BN-based magnetic sensor offers high flexibility and the ability to be placed in atomic-scale proximity to a target sample, and thus is expected to find numerous applications in 2D materials research by offering a simple means to probe in situ the physics of van der Waals heterostructures.
Arian Vezvaee, Paul Hilaire, Matthew F. Doty, and Sophia E. Economou
Phys. Rev. Applied 18, L061003 (2022) - Published 21 December, 2022
While multiphoton entangled states are the essential building blocks of quantum photonic technologies, large-scale production of such states has proven to be difficult. This study utilizes the unique structure of hole spins in quantum dot molecules to propose an approach that overcomes many of the existing obstacles in the deterministic generation of such states. With high fidelity and production rates that are unmatched among currently available protocols, this proposal seems quite promising as a basis for tomorrow’s optical quantum communication hardware.
Mikhail Silaev
Phys. Rev. Applied 18, L061004 (2022) - Published 27 December, 2022
The dynamic interplay of superconductivity and magnetism is promising for developing quantum magnonics and spintronics. Recent experiments have reported significant, enigmatic shifts of ferromagnetic resonance frequency in layered SFS structures. The author explains that the origin of this effect is spontaneous generation of magnon mass due to the celebrated Anderson-Higgs mechanism, a cornerstone of the Standard Model of particle physics. Upon cooling below the superconducting critical temperature, the magnons acquire a frequency gap and change their propagation direction. This effect enables the creation of magnon resonators, crystals, parametric amplifiers, and other useful devices.
Jun Kang and Lin-Wang Wang
Phys. Rev. Applied 18, 064001 (2022) - Published 1 December, 2022
Shallow impurities play critical roles in the applications of semiconductor materials, but their simulations through first-principles calculations are challenging due to the delocalized nature of the impurity wave function. The authors propose a first-principles approach to study shallow impurities, which allows simulations of extremely large supercells to obtain converged impurity levels and wave functions. The method is applied to acceptor-carbon complexes in silicon and yields good agreement with experiments. This work thus presents a feasible approach for accurate simulations of shallow impurities and can provide helpful insights to assist experimental dopant engineering.
Bas van der Zee, Yungui Li, Gert-Jan A.H. Wetzelaer, and Paul W.M. Blom
Phys. Rev. Applied 18, 064002 (2022) - Published 1 December, 2022
Organic light-emitting diodes (OLEDs) based on thermally activated delayed fluorescence (TADF) are alternatives to today’s commercial phosphorescent OLEDs with heavy-metal dopants, but their limited stability remains a key issue. This work provides a quantitative insight into the degradation mechanisms. The authors reproduce the voltage and light output using a recently developed device model, and find that triplet-polaron annihilation is the driving force behind the formation of degradation traps. This understanding leads to the experimental demonstration of enhanced device lifetime, and will provide guidance towards improved stability of TADF OLEDs.
B.T. Buijtendorp, S. Vollebregt, K. Karatsu, D.J. Thoen, V. Murugesan, K. Kouwenhoven, S. Hähnle, J.J.A. Baselmans, and A. Endo
Phys. Rev. Applied 18, 064003 (2022) - Published 1 December, 2022
Jeffrey Rable, Benjamin Piazza, Jyotirmay Dwivedi, and Nitin Samarth
Phys. Rev. Applied 18, 064004 (2022) - Published 1 December, 2022
Lintao Li, William Huie, Neville Chen, Brian DeMarco, and Jacob P. Covey
Phys. Rev. Applied 18, 064005 (2022) - Published 2 December, 2022
Rui Asaoka, Julio Gea-Banacloche, Yuuki Tokunaga, and Kazuki Koshino
Phys. Rev. Applied 18, 064006 (2022) - Published 2 December, 2022
Samantha I. Davis, Andrew Mueller, Raju Valivarthi, Nikolai Lauk, Lautaro Narvaez, Boris Korzh, Andrew D. Beyer, Olmo Cerri, Marco Colangelo, Karl K. Berggren, Matthew D. Shaw, Si Xie, Neil Sinclair, and Maria Spiropulu
Phys. Rev. Applied 18, 064007 (2022) - Published 2 December, 2022
Ya-Feng Jiao, Jing-Xue Liu, Ying Li, Ronghua Yang, Le-Man Kuang, and Hui Jing
Phys. Rev. Applied 18, 064008 (2022) - Published 2 December, 2022
Yan-Hui Zhou, Xing-Yuan Zhang, Tong Liu, Qi-Cheng Wu, Zhi-Cheng Shi, Hong-Zhi Shen, and Chui-Ping Yang
Phys. Rev. Applied 18, 064009 (2022) - Published 5 December, 2022
Matias Risaro, Paolo Savio, Marco Pizzocaro, Filippo Levi, Davide Calonico, and Cecilia Clivati
Phys. Rev. Applied 18, 064010 (2022) - Published 5 December, 2022
B.A. McCullian, H.F.H. Cheung, H.Y. Chen, and G.D. Fuchs
Phys. Rev. Applied 18, 064011 (2022) - Published 5 December, 2022
Hao Wu, Deniz Turan, Quanjun Pan, Chao-Yao Yang, Guanjie Wu, Seyed Armin Razavi, Bingqian Dai, Nezih Tolga Yardimci, Zhi Huang, Jing Zhang, Yi-Ying Chin, Hong-Ji Lin, Chih-Huang Lai, Zongzhi Zhang, Mona Jarrahi, and Kang L. Wang
Phys. Rev. Applied 18, 064012 (2022) - Published 5 December, 2022
Matthew D. Biviano, Magnus V. Paludan, Anneline H. Christensen, Emil V. Østergaard, and Kaare H. Jensen
Phys. Rev. Applied 18, 064013 (2022) - Published 6 December, 2022
Cen Wang, Kuan Wang, Xinyu Wen, Wei Luo, Shiheng Liang, Yue Zhang, and Yuhui He
Phys. Rev. Applied 18, 064014 (2022) - Published 6 December, 2022
Carsten Richter, Vladimir M. Kaganer, Armelle Even, Amélie Dussaigne, Pierre Ferret, Frédéric Barbier, Yves-Matthieu Le Vaillant, and Tobias U. Schülli
Phys. Rev. Applied 18, 064015 (2022) - Published 6 December, 2022
Bingzhi Zhang, Jing Wu, Linran Fan, and Quntao Zhuang
Phys. Rev. Applied 18, 064016 (2022) - Published 6 December, 2022
Zhiguo Wang, Chunchun Li, Hongyuan Xie, Zhen Zhang, Wenbin Huang, Shanming Ke, and Longlong Shu
Phys. Rev. Applied 18, 064017 (2022) - Published 7 December, 2022
Hiroaki Shinkawa, Nicolas Chauvet, André Röhm, Takatomo Mihana, Ryoichi Horisaki, Guillaume Bachelier, and Makoto Naruse
Phys. Rev. Applied 18, 064018 (2022) - Published 7 December, 2022
Rafał Korlacki, Matthew Hilfiker, Jenna Knudtson, Megan Stokey, Ufuk Kilic, Akhil Mauze, Yuewei Zhang, James Speck, Vanya Darakchieva, and Mathias Schubert
Phys. Rev. Applied 18, 064019 (2022) - Published 7 December, 2022
Ke Yin, Yuangen Huang, Wenjing Yin, Xianglin Hao, Xikui Ma, and Tianyu Dong
Phys. Rev. Applied 18, 064020 (2022) - Published 7 December, 2022
Jake Horder, Simon J.U. White, Angus Gale, Chi Li, Kenji Watanabe, Takashi Taniguchi, Mehran Kianinia, Igor Aharonovich, and Milos Toth
Phys. Rev. Applied 18, 064021 (2022) - Published 8 December, 2022
Lattice defects in two-dimensional materials are compelling sources of single photons for applications in quantum information processing. However, the range of emission wavelengths is broad, the defect types vary and the atomic structures of most are unknown, and the inability to fabricate defects systematically on demand has limited progress. This work leverages a robust, site-specific fabrication technique to produce arrays of blue quantum emitters for study via cryogenic spectroscopy. The authors characterize processes that limit emitter coherence and observe Rabi oscillations, demonstrating the potential of these defects for scalable quantum technologies.
Aditya Dash, Dorothea Scheunemann, and Martijn Kemerink
Phys. Rev. Applied 18, 064022 (2022) - Published 8 December, 2022
Shunsuke Nishimura, Kohei M. Itoh, Junko Ishi-Hayase, Kento Sasaki, and Kensuke Kobayashi
Phys. Rev. Applied 18, 064023 (2022) - Published 8 December, 2022
Yan Wang, Matteo Piccolini, Ze-Yan Hao, Zheng-Hao Liu, Kai Sun, Jin-Shi Xu, Chuan-Feng Li, Guang-Can Guo, Roberto Morandotti, Giuseppe Compagno, and Rosario Lo Franco
Phys. Rev. Applied 18, 064024 (2022) - Published 8 December, 2022
Yun Shen, Jie Ji, Hui-Chang Li, Le Zhang, Xin Yu, Shu-Bin Yan, Mattias Rasmussen, Qian Shen, Daena Madhi, Bin-Bin Zhou, Peter Uhd Jepsen, and Xiao-Hua Deng
Phys. Rev. Applied 18, 064025 (2022) - Published 9 December, 2022
J.S. Harms, H.Y. Yuan, and Rembert A. Duine
Phys. Rev. Applied 18, 064026 (2022) - Published 9 December, 2022
Shiyuan Zhao and Frédéric Grillot
Phys. Rev. Applied 18, 064027 (2022) - Published 9 December, 2022
A.R. Mills, C.R. Guinn, M.M. Feldman, A.J. Sigillito, M.J. Gullans, M.T. Rakher, J. Kerckhoff, C.A.C. Jackson, and J.R. Petta
Phys. Rev. Applied 18, 064028 (2022) - Published 12 December, 2022
Zihao Su, Hao Luo, Siyuan Gao, Zhitao Luo, Yifan Zhu, and Hui Zhang
Phys. Rev. Applied 18, 064029 (2022) - Published 12 December, 2022
Jacob J. Cordell, Moira K. Miller, M. Brooks Tellekamp, Adele Tamboli, Garritt J. Tucker, and Stephan Lany
Phys. Rev. Applied 18, 064030 (2022) - Published 12 December, 2022
Gerald Q. Yan, Senlei Li, Tatsuya Yamamoto, Mengqi Huang, Nathan J. Mclaughlin, Takayuki Nozaki, Hailong Wang, Shinji Yuasa, and Chunhui Rita Du
Phys. Rev. Applied 18, 064031 (2022) - Published 12 December, 2022
Xiong Deng, Ximin Tian, Lirong Ren, Jiangtao Liu, and Zhi-Yuan Li
Phys. Rev. Applied 18, 064032 (2022) - Published 12 December, 2022
S. Kanhirathingal, B. Thyagarajan, B.L. Brock, Juliang Li, E. Jeffrey, M.P. Blencowe, J.Y. Mutus, and A.J. Rimberg
Phys. Rev. Applied 18, 064033 (2022) - Published 13 December, 2022
Ming-Hung Wu, I-Ting Wang, Ming-Chun Hong, Kuan-Ming Chen, Yuan-Chieh Tseng, Jeng-Hua Wei, and Tuo-Hung Hou
Phys. Rev. Applied 18, 064034 (2022) - Published 13 December, 2022
Richard Bing-Shiun Tsai, Henrique Silvério, and Loc Henriet
Phys. Rev. Applied 18, 064035 (2022) - Published 13 December, 2022
Wei Feng, Guo-Qiang Zhang, Qi-Ping Su, Jun-Xiang Zhang, and Chui-Ping Yang
Phys. Rev. Applied 18, 064036 (2022) - Published 13 December, 2022
Stephen P. Fluckey, Sabyasachi Tiwari, Christopher L. Hinkle, and William G. Vandenberghe
Phys. Rev. Applied 18, 064037 (2022) - Published 13 December, 2022
Zheheng Xu and David Burghoff
Phys. Rev. Applied 18, 064038 (2022) - Published 14 December, 2022
Hodaka Kurokawa, Moyuki Yamamoto, Yuhei Sekiguchi, and Hideo Kosaka
Phys. Rev. Applied 18, 064039 (2022) - Published 14 December, 2022
Anasua Chatterjee, Fabio Ansaloni, Torbjørn Rasmussen, Bertram Brovang, Federico Fedele, Heorhii Bohuslavskyi, Oswin Krause, and Ferdinand Kuemmeth
Phys. Rev. Applied 18, 064040 (2022) - Published 14 December, 2022
In spin-based quantum processors, each quantum dot of a qubit is populated by exactly one electron, which requires careful tuning of each gate voltage such that it lies inside the charge-stability region (the “Coulomb diamond”) associated with the dot array. However, mapping the boundary of a multidimensional Coulomb diamond by traditional dense raster scanning would take years, so the authors develop a sparse acquisition technique that autonomously learns Coulomb-diamond boundaries from a small number of measurements. Here we have hardware-triggered line searches in the gate-voltage space of a silicon quadruple dot, with smart search directions proposed by an active-learning algorithm.
Arkady Kurnosov, Lucas J. Fernández-Alcázar, Raúl Bustos-Marún, and Tsampikos Kottos
Phys. Rev. Applied 18, 064041 (2022) - Published 14 December, 2022
Kin On Ho, Man Yin Leung, P. Reddy, Jianyu Xie, King Cho Wong, Yaxin Jiang, Wei Zhang, King Yau Yip, Wai Kuen Leung, Yiu Yung Pang, King Yiu Yu, Swee K. Goh, M.W. Doherty, and Sen Yang
Phys. Rev. Applied 18, 064042 (2022) - Published 14 December, 2022
Pauline Rovillain, Jean-Yves Duquesne, Louis Christienne, Mahmoud Eddrief, Maria Gloria Pini, Angelo Rettori, Silvia Tacchi, and Massimiliano Marangolo
Phys. Rev. Applied 18, 064043 (2022) - Published 15 December, 2022
Michiel Burgelman, Pierre Rouchon, Alain Sarlette, and Mazyar Mirrahimi
Phys. Rev. Applied 18, 064044 (2022) - Published 15 December, 2022
Yuntao Xu, Wei Fu, Yiyu Zhou, Mingrui Xu, Mohan Shen, Ayed Al Sayem, and Hong X. Tang
Phys. Rev. Applied 18, 064045 (2022) - Published 15 December, 2022
Rutian Huang, Xiao Geng, Xinyu Wu, Genting Dai, Liangliang Yang, Jianshe Liu, and Wei Chen
Phys. Rev. Applied 18, 064046 (2022) - Published 15 December, 2022
Jin Chen, Guangyuan Su, Shaohang Xu, Mingji Chen, Yongquan Liu, Daining Fang, and Ji Zhou
Phys. Rev. Applied 18, 064047 (2022) - Published 15 December, 2022
Antonio Martí, Elisa Antolín, and Iñigo Ramiro
Phys. Rev. Applied 18, 064048 (2022) - Published 16 December, 2022
Navdeep Rana, M. S. Mrudul, and Gopal Dixit
Phys. Rev. Applied 18, 064049 (2022) - Published 16 December, 2022
Yahui Ji, Chenye Zhang, and Tianxiang Nan
Phys. Rev. Applied 18, 064050 (2022) - Published 16 December, 2022
Luca Erhart, Kosuke Mitarai, Wataru Mizukami, and Keisuke Fujii
Phys. Rev. Applied 18, 064051 (2022) - Published 16 December, 2022
Lijun Zhu, Jingwei Li, Lujun Zhu, and Xinyue Xie
Phys. Rev. Applied 18, 064052 (2022) - Published 16 December, 2022
Emilien Lavie and Charles C.-W. Lim
Phys. Rev. Applied 18, 064053 (2022) - Published 19 December, 2022
Coherent one-way quantum key distribution (COW-QKD) is a popular cryptography protocol, due to its fairly simple implementation and passive measurement device. Its security analysis is challenging, though, and extra assumptions or modifications are typically employed. Here the authors propose minor modifications to COW-QKD’s prepared states while retaining the original, fully passive measurement device, and generalize the “universal squashing” framework to analyze their system’s security. The results suggest that performance should be comparable to upper bounds from the literature, making this protocol a viable alternative to one based on phase-modulated coherent states.
Feihu Wang, Xiaoqiong Qi, Valentino Pistore, Lianhe Li, Gary Agnew, Edmund Linfield, Giles Davies, Jérôme Tignon, Juliette Mangeney, Aleksandar D. Rakić, and Sukhdeep S. Dhillon
Phys. Rev. Applied 18, 064054 (2022) - Published 19 December, 2022
Jinbo Yuan, Linlin Geng, Jiahui Huang, Qiuquan Guo, Jun Yang, Gengkai Hu, and Xiaoming Zhou
Phys. Rev. Applied 18, 064055 (2022) - Published 19 December, 2022
Gabriel O. Samach, Ami Greene, Johannes Borregaard, Matthias Christandl, Joseph Barreto, David K. Kim, Christopher M. McNally, Alexander Melville, Bethany M. Niedzielski, Youngkyu Sung, Danna Rosenberg, Mollie E. Schwartz, Jonilyn L. Yoder, Terry P. Orlando, Joel I-Jan Wang, Simon Gustavsson, Morten Kjaergaard, and William D. Oliver
Phys. Rev. Applied 18, 064056 (2022) - Published 19 December, 2022
Ao Chen, Xiaoguang Zhao, Zhiwei Yang, Stephan Anderson, and Xin Zhang
Phys. Rev. Applied 18, 064057 (2022) - Published 19 December, 2022
Lezheng Fang and Michael J. Leamy
Phys. Rev. Applied 18, 064058 (2022) - Published 20 December, 2022
Ye-Hong Chen, Adam Miranowicz, Xi Chen, Yan Xia, and Franco Nori
Phys. Rev. Applied 18, 064059 (2022) - Published 20 December, 2022
Zhiyuan Ye, Wanting Hou, Jilun Zhao, Hai-Bo Wang, and Jun Xiong
Phys. Rev. Applied 18, 064060 (2022) - Published 20 December, 2022
Anna Rupp, Jonas Göser, Zhijie Li, Philipp Altpeter, Ismail Bilgin, and Alexander Högele
Phys. Rev. Applied 18, 064061 (2022) - Published 20 December, 2022
T. Chang, I. Holzman, T. Cohen, B. C. Johnson, D. N. Jamieson, and M. Stern
Phys. Rev. Applied 18, 064062 (2022) - Published 20 December, 2022
Dmitrii Khokhriakov, Shehrin Sayed, Anamul Md. Hoque, Bogdan Karpiak, Bing Zhao, Supriyo Datta, and Saroj P. Dash
Phys. Rev. Applied 18, 064063 (2022) - Published 21 December, 2022
Jinjie Shi, Chenkai Liu, Chang Guo, Hongchen Chu, Xiaozhou Liu, Johan Christensen, and Yun Lai
Phys. Rev. Applied 18, 064064 (2022) - Published 21 December, 2022
Tian Yang, Zibin Lin, Xuefeng Zhu, and Tianzhi Yang
Phys. Rev. Applied 18, 064065 (2022) - Published 21 December, 2022
Feng Li, Robert J. Davis, Sara M. Kandil, and Daniel F. Sievenpiper
Phys. Rev. Applied 18, 064066 (2022) - Published 22 December, 2022
Tingwei Li, Peng-Hu Du, Ling Bai, Qiang Sun, and Puru Jena
Phys. Rev. Applied 18, 064067 (2022) - Published 22 December, 2022
Valeria Rodríguez-Fajardo and Andrew Forbes
Phys. Rev. Applied 18, 064068 (2022) - Published 22 December, 2022
Francesco Tani, Jacob Lampen, Martin Butryn, Michael H. Frosz, Jie Jiang, Martin E. Fermann, and Philip St.J. Russell
Phys. Rev. Applied 18, 064069 (2022) - Published 22 December, 2022
Stefan Meinecke and Kathy Lüdge
Phys. Rev. Applied 18, 064070 (2022) - Published 22 December, 2022
Shoichi Sato, Masaaki Tanaka, and Ryosho Nakane
Phys. Rev. Applied 18, 064071 (2022) - Published 23 December, 2022
Sougata Mallick, Sujit Panigrahy, Gajanan Pradhan, and Stanislas Rohart
Phys. Rev. Applied 18, 064072 (2022) - Published 23 December, 2022
Yan Meng, Yiran Hao, Liyou Luo, and Jensen Li
Phys. Rev. Applied 18, 064073 (2022) - Published 23 December, 2022
Claudio Bonizzoni, Mirco Tincani, Fabio Santanni, and Marco Affronte
Phys. Rev. Applied 18, 064074 (2022) - Published 23 December, 2022
Jianqing Li, Pengyu Zhao, and Yongmao Pei
Phys. Rev. Applied 18, 064075 (2022) - Published 23 December, 2022
A.E.E. Dubois, D.A. Broadway, A. Stark, M.A. Tschudin, A.J. Healey, S.D. Huber, J.-P. Tetienne, E. Greplova, and P. Maletinsky
Phys. Rev. Applied 18, 064076 (2022) - Published 26 December, 2022
Magnetic materials are a vital resource in designing energy-efficient information technologies. To try to learn how magnetism develops in ultrathin systems, we measure, but deducing the physics afterward is an ill-posed problem. This study uses neural networks to facilitate the reconstruction of the underlying magnetic textures of thin magnets through measurements of their stray fields. The technique is surprisingly robust to experimental noise, and can reliably reconstruct magnetism in arbitrary directions. Importantly, prior training of the network is not required, and the technique is broadly applicable for solving ill-posed inverse problems when the forward problem is well defined.
Peter Breitman, Michael Pukshansky, Anna Zigelman, Ezra Ben Abu, Ofek Peretz, Sefi Givli, and Amir D. Gat
Phys. Rev. Applied 18, 064077 (2022) - Published 26 December, 2022
The authors study the interaction between a viscous flow and a one-dimensional mechanical metamaterial composed of bistable unit cells, much like a drinking straw. Their twofold model shows excellent agreement with experimental results. While prior studies have focused on tailoring unit-cell structure to obtain a desired multistable behavior, here the viscous fluid allows tuning of rate-dependent properties and nonlocal interaction between unit cells. The ability to manipulate both structural and nonlocal rate-related properties points to the development of smart materials with tunable kinetic relations, large reversible deformations, and tailored dynamic properties.
William N. Bodé, Fabian Lickert, Per Augustsson, and Henrik Bruus
Phys. Rev. Applied 18, 064078 (2022) - Published 26 December, 2022
Qingyang Mo, Yeyang Sun, Junkai Li, Zhichao Ruan, and Zhaoju Yang
Phys. Rev. Applied 18, 064079 (2022) - Published 26 December, 2022
Wyatt Adams, Anindya Ghoshroy, and Durdu Ö. Güney
Phys. Rev. Applied 18, 064080 (2022) - Published 26 December, 2022
Yue Meng, Wei Li, and Ruben Juanes
Phys. Rev. Applied 18, 064081 (2022) - Published 27 December, 2022
Unraveling the complex behavior of wet granular media has been challenging, because the effective stresses transmitted through the particles have remained unobservable. The authors use their recently developed extension of photoelasticity for coupled fluid-granular systems to image particle stresses during fracture by air injection in an oil-saturated granular pack. They discover two states of the granular medium evolving with the fractures, plus an “effective-stress shadow” behind the propagating fracture tips. This study points out the power of photoporomechanics for studying coupled fluid-solid processes in granular media, including energy recovery, gas venting, and geohazards.
Steve M. Young, N. Tobias Jacobson, and Jason R. Petta
Phys. Rev. Applied 18, 064082 (2022) - Published 27 December, 2022
M.B. Clavel, F. Murphy-Armando, Y. Xie, K.T. Henry, M. Kuhn, R.J. Bodnar, G.A. Khodaparast, D. Smirnov, J.J. Heremans, and M.K. Hudait
Phys. Rev. Applied 18, 064083 (2022) - Published 27 December, 2022
For applications such as low-power tunneling transistors and memory, lasers, qubits, and spintronics, there is interest in using strain to enhance carrier mobility in semiconductors. This experimental and theoretical study investigates transport in highly strained germanium, in which multivalley electron conduction emerges. Surprisingly, all conduction occurs via the L valley in Ge for biaxial tensile strain below 1.6%, while above the contribution from the Γ valley increases, with negligible contributions from the underlying strain template.
Vitalii Mikheev, Ekaterina Kondratyuk, and Anastasia Chouprik
Phys. Rev. Applied 18, 064084 (2022) - Published 27 December, 2022
Song Zhang, Hao Xue, Shihao Zhao, Jiaqi Han, Long Li, and Tie Jun Cui
Phys. Rev. Applied 18, 064085 (2022) - Published 28 December, 2022
Wen Dang, Mengyu Zhu, Ziye Zhu, Xiaofang Chen, Zhigang Song, and Jingshan Qi
Phys. Rev. Applied 18, 064086 (2022) - Published 28 December, 2022
Nicolae Filipoiu, Amanda Teodora Preda, Dragos-Victor Anghel, Roxana Patru, Rachel Elizabeth Brophy, Movaffaq Kateb, Cristina Besleaga, Andrei Gabriel Tomulescu, Ioana Pintilie, Andrei Manolescu, and George Alexandru Nemnes
Phys. Rev. Applied 18, 064087 (2022) - Published 28 December, 2022
Chaitali Joshi, Wenyuan Chen, Henry G. LeDuc, Peter K. Day, and Mohammad Mirhosseini
Phys. Rev. Applied 18, 064088 (2022) - Published 28 December, 2022
The kinetic inductance of charge carriers in disordered superconductors provides a broadband low-loss source of nonlinear electromagnetic response. This work investigates TiN nanowires as an alternative to Josephson junctions for applications involving elevated temperatures, higher frequencies, and strong magnetic fields. An extreme nanowire geometry for TiN microwave resonators leads to current-density concentration and enhanced self-Kerr coefficient, yielding a nonlinearity-to-loss ratio as high as 21% and quality factor exceeding 10,000. Such devices may find application in quantum frequency conversion of microwave photons, and with improvement might attain strong quantum nonlinearity.
Langlang Xiong, Yu Zhang, Yufu Liu, Yaoxian Zheng, and Xunya Jiang
Phys. Rev. Applied 18, 064089 (2022) - Published 29 December, 2022
Yi Hua Chang and Sandra M. Troian
Phys. Rev. Applied 18, 064090 (2022) - Published 29 December, 2022
X. F. Shen, A. Pukhov, O. N. Rosmej, and N. E. Andreev
Phys. Rev. Applied 18, 064091 (2022) - Published 29 December, 2022
G. Liu, X. Cao, T.-C. Chien, C. Zhou, P. Lu, and M. Hatridge
Phys. Rev. Applied 18, 064092 (2022) - Published 29 December, 2022
A.A. Martyshkin, C.S. Davies, and A.V. Sadovnikov
Phys. Rev. Applied 18, 064093 (2022) - Published 30 December, 2022
Peng Zhang, Han Jia, Jiuyang Lu, Xinghang Yang, Suhao Wang, Xiangyuan Xu, Yuzhen Yang, Zhengyou Liu, and Jun Yang
Phys. Rev. Applied 18, 064094 (2022) - Published 30 December, 2022
Zhen Guo Ban, Yan Shi, Ning Qian Huang, Long Li, Xue Guang Lu, Hong Fu Zhu, Qi Wu Shi, Wan Xia Huang, and Tie Jun Cui
Phys. Rev. Applied 18, 064095 (2022) - Published 30 December, 2022
Zhiqiang Wang, Qi Jiang, Nithyanandan Kanagaraj, Benli Yu, and Zuxing Zhang
Phys. Rev. Applied 18, 064096 (2022) - Published 30 December, 2022
S. van den Wildenberg, X. Jia, J.L. Gennisson, and A. Tourin
Phys. Rev. Applied 18, 064097 (2022) - Published 30 December, 2022
Wenqiang Wang, Qingwei Fu, Kaiyuan Zhou, Lina Chen, Liupeng Yang, Zishuang Li, Zui Tao, Chunjie Yan, Like Liang, Xiang Zhan, Youwei Du, and Ronghua Liu
Phys. Rev. Applied 18, 069901 (2022) - Published 9 December, 2022
