Zobrazeno 1 - 10
of 172
pro vyhledávání: '"Chellu, A."'
Autor:
Chellu, Abhiroop, Bej, Subhajit, Wahl, Hanna, Kahle, Hermann, Uusitalo, Topi, Hytönen, Roosa, Rekola, Heikki, Lang, Jouko, Schöll, Eva, Hanschke, Lukas, Kallert, Patricia, Kipp, Tobias, Strelow, Christian, Tuominen, Marjukka, Jöns, Klaus D., Karvinen, Petri, Niemi, Tapio, Guina, Mircea, Hakkarainen, Teemu
On-chip emitters that generate single and entangled photons are essential for photonic quantum information processing technologies. Semiconductor quantum dots (QDs) are attractive candidates that emit high-quality quantum states of light, however at
Externí odkaz:
http://arxiv.org/abs/2407.11642
Autor:
Hakkarainen, Teemu, Hilska, Joonas, Hietalahti, Arttu, Ranta, Sanna, Peil, Markus, Kantola, Emmi, Chellu, Abhiroop, Sen, Efsane, Penttinen, Jussi-Pekka, Guina, Mircea
Deterministic light sources capable of generating quantum states on-demand at wavelengths compatible with fiber optics and atmospheric transmission are essential for practical applications in quantum communication, photonic quantum computing, and qua
Externí odkaz:
http://arxiv.org/abs/2404.06083
Autor:
Leguay, Lucie, Chellu, Abhiroop, Hilska, Joonas, Luna, Esperanza, Schliwa, Andrei, Guina, Mircea, Hakkarainen, Teemu
Epitaxially-grown semiconductor quantum dots (QDs) provide an attractive platform for the development of deterministic sources of high-quality quantum states of light. Such non-classical light sources are essential for quantum information processing
Externí odkaz:
http://arxiv.org/abs/2308.15418
Autor:
Michl, Johannes, Peniakov, Giora, Pfenning, Andreas, Hilska, Joonas, Chellu, Abhiroop, Bader, Andreas, Guina, Mircea, Höfling, Sven, Hakkarainen, Teemu, Huber-Loyola, Tobias
Creating single photons in the telecommunication wavelength range from semiconductor quantum dots (QDs) and interfacing them with spins of electrons or holes has been of high interest in recent years, with research mainly focusing on indium based QDs
Externí odkaz:
http://arxiv.org/abs/2305.04384
Distance Metric Learning (DML) seeks to learn a discriminative embedding where similar examples are closer, and dissimilar examples are apart. In this paper, we address the problem of Semi-Supervised DML (SSDML) that tries to learn a metric using a f
Externí odkaz:
http://arxiv.org/abs/2105.05061
Publikováno v:
APL Materials 9, 051116 (2021)
We demonstrate a new quantum-confined semiconductor material based on GaSb quantum dots (QDs) embedded in single-crystalline AlGaSb matrix by filling droplet-etched nanoholes. The droplet-mediated growth mechanism allows formation of low QD densities
Externí odkaz:
http://arxiv.org/abs/2102.11716
Publikováno v:
Crystal Growth & Design 21,1917 (2021)
We demonstrate nanohole formation in AlGaSb by Ga droplet etching within a temperature range from 270{\deg}C to 500{\deg}C, allowing a wide range of tunability of the nanohole density. By leveraging the low vapor pressure of Sb, we can obtain high de
Externí odkaz:
http://arxiv.org/abs/2101.09106
Metric learning is an important problem in machine learning. It aims to group similar examples together. Existing state-of-the-art metric learning approaches require class labels to learn a metric. As obtaining class labels in all applications is not
Externí odkaz:
http://arxiv.org/abs/2008.09880
In this paper, we revamp the forgotten classical Semi-Supervised Distance Metric Learning (SSDML) problem from a Riemannian geometric lens, to leverage stochastic optimization within a end-to-end deep framework. The motivation comes from the fact tha
Externí odkaz:
http://arxiv.org/abs/2002.12394
For challenging machine learning problems such as zero-shot learning and fine-grained categorization, embedding learning is the machinery of choice because of its ability to learn generic notions of similarity, as opposed to class-specific concepts i
Externí odkaz:
http://arxiv.org/abs/1912.08275