Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Park Taewon"'
Autor:
Pai Sunil, Valdez Carson, Park Taewon, Milanizadeh Maziyar, Morichetti Francesco, Melloni Andrea, Fan Shanhui, Solgaard Olav, Miller David A. B.
Publikováno v:
Nanophotonics, Vol 12, Iss 5, Pp 985-991 (2023)
Programmable feedforward photonic meshes of Mach–Zehnder interferometers are computational optical circuits that have many classical and quantum computing applications including machine learning, sensing, and telecommunications. Such devices can fo
Externí odkaz:
https://doaj.org/article/85a2ed083a004668a26f496e62459f76
Neuro-symbolic neural networks have been extensively studied to integrate symbolic operations with neural networks, thereby improving systematic generalization. Specifically, Tensor Product Representation (TPR) framework enables neural networks to pe
Externí odkaz:
http://arxiv.org/abs/2406.06976
In recent research, Tensor Product Representation (TPR) is applied for the systematic generalization task of deep neural networks by learning the compositional structure of data. However, such prior works show limited performance in discovering and r
Externí odkaz:
http://arxiv.org/abs/2406.01012
Autor:
Park, Taewon, Stokowski, Hubert S., Ansari, Vahid, Gyger, Samuel, Multani, Kevin K. S., Celik, Oguz Tolga, Hwang, Alexander Y., Dean, Devin J., Mayor, Felix M., McKenna, Timothy P., Fejer, Martin M., Safavi-Naeini, Amir H.
Quantum optical technologies promise advances in sensing, computing, and communication. A key resource is squeezed light, where quantum noise is redistributed between optical quadratures. We introduce a monolithic, chip-scale platform that exploits t
Externí odkaz:
http://arxiv.org/abs/2310.12954
Autor:
Stokowski, Hubert S., Dean, Devin J., Hwang, Alexander Y., Park, Taewon, Celik, Oguz Tolga, Jankowski, Marc, Langrock, Carsten, Ansari, Vahid, Fejer, Martin M., Safavi-Naeini, Amir H.
Optical frequency combs have revolutionized precision measurement, time-keeping, and molecular spectroscopy. A substantial effort has developed around "microcombs": integrating comb-generating technologies into compact, reliable photonic platforms. C
Externí odkaz:
http://arxiv.org/abs/2307.04200
Autor:
Hwang, Alexander Y., Stokowski, Hubert S., Park, Taewon, Jankowski, Marc, McKenna, Timothy P., Langrock, Carsten, Mishra, Jatadhari, Ansari, Vahid, Fejer, Martin M., Safavi-Naeini, Amir H.
Mid-infrared spectroscopy, an important and widespread technique for sensing molecules, has encountered barriers stemming from sources either limited in tuning range or excessively bulky for practical field use. We present a compact, efficient, and b
Externí odkaz:
http://arxiv.org/abs/2307.04199
Autor:
Stokowski, Hubert S., McKenna, Timothy P., Park, Taewon, Hwang, Alexander Y., Dean, Devin J., Celik, Oguz Tolga, Ansari, Vahid, Fejer, Martin M., Safavi-Naeini, Amir H.
The quantum noise of light fundamentally limits optical phase sensors. A semiclassical picture attributes this noise to the random arrival time of photons from a coherent light source such as a laser. An engineered source of squeezed states suppresse
Externí odkaz:
http://arxiv.org/abs/2212.09717
Experimental evaluation of digitally-verifiable photonic computing for blockchain and cryptocurrency
Autor:
Pai, Sunil, Park, Taewon, Ball, Marshall, Penkovsky, Bogdan, Milanizadeh, Maziyar, Dubrovsky, Michael, Abebe, Nathnael, Morichetti, Francesco, Melloni, Andrea, Fan, Shanhui, Solgaard, Olav, Miller, David A. B.
As blockchain technology and cryptocurrency become increasingly mainstream, ever-increasing energy costs required to maintain the computational power running these decentralized platforms create a market for more energy-efficient hardware. Photonic c
Externí odkaz:
http://arxiv.org/abs/2205.08512
Autor:
Pai, Sunil, Sun, Zhanghao, Hughes, Tyler W., Park, Taewon, Bartlett, Ben, Williamson, Ian A. D., Minkov, Momchil, Milanizadeh, Maziyar, Abebe, Nathnael, Morichetti, Francesco, Melloni, Andrea, Fan, Shanhui, Solgaard, Olav, Miller, David A. B.
Neural networks are widely deployed models across many scientific disciplines and commercial endeavors ranging from edge computing and sensing to large-scale signal processing in data centers. The most efficient and well-entrenched method to train su
Externí odkaz:
http://arxiv.org/abs/2205.08501
Autor:
Park, Taewon, Stokowski, Hubert S., Ansari, Vahid, McKenna, Timothy P., Hwang, Alexander Y., Fejer, M. M., Safavi-Naeini, Amir H.
We demonstrate second harmonic generation of blue light on an integrated thin-film lithium niobate waveguide and observe a conversion efficiency of $\eta_0= 33000\%/\text{W-cm}^2$, significantly exceeding previous demonstrations.
Comment: 3 page
Comment: 3 page
Externí odkaz:
http://arxiv.org/abs/2108.06398