Andrew E. Dane

2.1k total citations
27 papers, 1.1k citations indexed

About

Andrew E. Dane is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Artificial Intelligence. According to data from OpenAlex, Andrew E. Dane has authored 27 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Electrical and Electronic Engineering, 15 papers in Atomic and Molecular Physics, and Optics and 9 papers in Artificial Intelligence. Recurrent topics in Andrew E. Dane's work include Photonic and Optical Devices (13 papers), Quantum Information and Cryptography (9 papers) and Advanced Optical Sensing Technologies (8 papers). Andrew E. Dane is often cited by papers focused on Photonic and Optical Devices (13 papers), Quantum Information and Cryptography (9 papers) and Advanced Optical Sensing Technologies (8 papers). Andrew E. Dane collaborates with scholars based in United States, Italy and United Kingdom. Andrew E. Dane's co-authors include Karl K. Berggren, Qingyuan Zhao, Francesco Bellei, Faraz Najafi, Di Zhu, Adam N. McCaughan, Francesco Marsili, Niccolò Calandri, Dirk Englund and Eric A. Dauler and has published in prestigious journals such as Nature Communications, Nano Letters and Applied Physics Letters.

In The Last Decade

Andrew E. Dane

26 papers receiving 978 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andrew E. Dane United States 16 564 548 362 292 163 27 1.1k
Andrew D. Beyer United States 17 526 0.9× 625 1.1× 367 1.0× 260 0.9× 88 0.5× 72 1.2k
Marco Colangelo United States 16 449 0.8× 476 0.9× 270 0.7× 192 0.7× 129 0.8× 49 1.0k
A. Divochiy Russia 13 360 0.6× 501 0.9× 430 1.2× 229 0.8× 109 0.7× 41 871
Roman Sobolewski United States 3 535 0.9× 603 1.1× 419 1.2× 267 0.9× 234 1.4× 4 1.1k
Sean D. Harrington United States 8 431 0.8× 664 1.2× 461 1.3× 238 0.8× 96 0.6× 22 1.0k
Adam N. McCaughan United States 17 478 0.8× 319 0.6× 306 0.8× 165 0.6× 189 1.2× 40 845
A. Gaggero Italy 19 734 1.3× 870 1.6× 852 2.4× 335 1.1× 144 0.9× 66 1.5k
Jason P. Allmaras United States 17 409 0.7× 312 0.6× 231 0.6× 268 0.9× 100 0.6× 46 820
A. Dzardanov Russia 5 575 1.0× 619 1.1× 437 1.2× 276 0.9× 267 1.6× 9 1.2k
Francesco Bellei United States 8 431 0.8× 402 0.7× 266 0.7× 227 0.8× 73 0.4× 12 750

Countries citing papers authored by Andrew E. Dane

Since Specialization
Citations

This map shows the geographic impact of Andrew E. Dane's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew E. Dane with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew E. Dane more than expected).

Fields of papers citing papers by Andrew E. Dane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew E. Dane. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew E. Dane. The network helps show where Andrew E. Dane may publish in the future.

Co-authorship network of co-authors of Andrew E. Dane

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew E. Dane. A scholar is included among the top collaborators of Andrew E. Dane based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew E. Dane. Andrew E. Dane is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kim, Young‐Seok, Luke C. G. Govia, Andrew E. Dane, et al.. (2025). Error mitigation with stabilized noise in superconducting quantum processors. Nature Communications. 16(1). 8439–8439. 1 indexed citations
2.
Dane, Andrew E., Jason P. Allmaras, Di Zhu, et al.. (2022). Self-heating hotspots in superconducting nanowires cooled by phonon black-body radiation. Nature Communications. 13(1). 5429–5429. 20 indexed citations
3.
Baghdadi, Reza, Jason P. Allmaras, Andrew E. Dane, et al.. (2020). Multilayered Heater Nanocryotron: A Superconducting-Nanowire-Based Thermal Switch. Physical Review Applied. 14(5). 18 indexed citations
4.
Charaev, Ilya, et al.. (2020). Large-area microwire MoSi single-photon detectors at 1550 nm wavelength. Applied Physics Letters. 116(24). 59 indexed citations
5.
Wang, Xiaoxi, Boris Korzh, Peter O. Weigel, et al.. (2019). Oscilloscopic capture of 100 GHz modulated optical waveforms at femtowatt power levels. Th4C.1–Th4C.1. 4 indexed citations
6.
Zhu, Di, Marco Colangelo, Boris Korzh, et al.. (2019). Superconducting nanowire single-photon detector with integrated impedance-matching taper. Applied Physics Letters. 114(4). 28 indexed citations
7.
Zhu, Di, Qingyuan Zhao, Hyeongrak Choi, et al.. (2018). A scalable multi-photon coincidence detector based on superconducting nanowires. Nature Nanotechnology. 13(7). 596–601. 54 indexed citations
8.
Korzh, Boris, Qingyuan Zhao, Simone Frasca, et al.. (2018). WSi superconducting nanowire single photon detector with a temporal resolution below 5 ps. Conference on Lasers and Electro-Optics. FW3F.3–FW3F.3. 12 indexed citations
9.
Zhao, Qingyuan, Adam N. McCaughan, Andrew E. Dane, Karl K. Berggren, & Thomas Ortlepp. (2017). A nanocryotron comparator can connect single-flux-quantum circuits to conventional electronics. Superconductor Science and Technology. 30(4). 44002–44002. 43 indexed citations
10.
Dane, Andrew E., Adam N. McCaughan, Di Zhu, et al.. (2017). Bias sputtered NbN and superconducting nanowire devices. Applied Physics Letters. 111(12). 44 indexed citations
11.
Zhao, Qingyuan, Di Zhu, Niccolò Calandri, et al.. (2017). Single-photon imager based on a superconducting nanowire delay line. Nature Photonics. 11(4). 247–251. 120 indexed citations
12.
Zhao, Qingyuan, Di Zhu, Niccolò Calandri, et al.. (2016). A scalable single-photon imager using a single superconducting nanowire. arXiv (Cornell University). 1 indexed citations
13.
Bellei, Francesco, Adam N. McCaughan, Andrew E. Dane, et al.. (2016). Free-space-coupled superconducting nanowire single-photon detectors for infrared optical communications. Optics Express. 24(4). 3248–3248. 38 indexed citations
14.
Calandri, Niccolò, Qingyuan Zhao, Di Zhu, Andrew E. Dane, & Karl K. Berggren. (2016). Superconducting nanowire detector jitter limited by detector geometry. Applied Physics Letters. 109(15). 72 indexed citations
15.
Najafi, Faraz, Jacob Mower, Nicholas C. Harris, et al.. (2015). On-chip detection of non-classical light by scalable integration of single-photon detectors. Nature Communications. 6(1). 5873–5873. 209 indexed citations
16.
Ivry, Yachin, Chung-Soo Kim, Andrew E. Dane, et al.. (2014). Universal scaling of the critical temperature for thin films near the superconducting-to-insulating transition. Physical Review B. 90(21). 65 indexed citations
17.
Najafi, Faraz, Xiaolong Hu, Francesco Bellei, et al.. (2013). Membrane-integrated superconducting nanowire single-photon detectors. 79. QF1A.6–QF1A.6. 1 indexed citations
18.
Hu, Xiaolong, Faraz Najafi, Jacob Mower, et al.. (2013). On-fiber assembly of membrane-integrated superconducting-nanowire single-photon detectors. FW1C.5–FW1C.5.
19.
Marsili, Francesco, Francesco Bellei, Faraz Najafi, et al.. (2012). Efficient Single Photon Detection from 500 nm to 5 μm Wavelength. Nano Letters. 12(9). 4799–4804. 148 indexed citations
20.
Marsili, Francesco, Francesco Bellei, Faraz Najafi, et al.. (2012). Efficient Single Photon Detection From 0.5 To 5 Micron Wavelength. QTu1E.2–QTu1E.2. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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