On-chip hybrid quantum circuits (Conference Presentation)

2017 ◽  
Author(s):  
Klaus D. Jöns ◽  
Ali W. Elshaari ◽  
Iman Esmaeil Zadeh ◽  
Andreas Fognini ◽  
Michael E. Reimer ◽  
...  
Keyword(s):  
2016 ◽  
Vol 741 ◽  
pp. 012104
Author(s):  
A Vasilev ◽  
A Kozubov ◽  
A Gaidash ◽  
S Chivilikhin
Keyword(s):  

2017 ◽  
Vol 7 (4) ◽  
Author(s):  
Benjamin J. Chapman ◽  
Eric I. Rosenthal ◽  
Joseph Kerckhoff ◽  
Bradley A. Moores ◽  
Leila R. Vale ◽  
...  

2020 ◽  
Vol 29 (16) ◽  
pp. 2050263
Author(s):  
Anirban Bhattacharjee ◽  
Chandan Bandyopadhyay ◽  
Bappaditya Mondal ◽  
Hafizur Rahaman

In the last couple of years, quantum computing has come out as emerging trends of computation not only due to its immense popularity but also for its commitment towards physical realization of quantum circuit in on-chip units. At the same time, the process of physical realization has faced several design constraints and one such problem is nearest neighbor (NN) enforcement which demands all the operating qubits to be placed adjacent in the implementable circuit. Though SWAP gate embedment can transform a design into NN architecture, it still creates overhead in the design. So, designing algorithms to restrict the use of SWAPs bears high importance. Considering this fact, in this work, we are proposing a heuristic-based improved qubit placement strategy for efficient implementation of NN circuit. Two different design policies are being developed here. In the first scheme, a global reordering technique based on clustering approach is shown. In the second scheme, a local reordering technique based on look-ahead policy is developed. This look-ahead strategy considers the impact over the gates in the circuit and thereby estimates the effect using a cost metric to decide the suitable option for SWAP implementation. Furthermore, the joint use of both the ordering schemes also has been explored here. To ascertain the correctness of our design algorithms, we have tested them over a wide range of benchmarks and the obtained results are compared with some state-of-the-art design approaches. From this comparison, we have witnessed a considerable reduction on SWAP cost in our design scheme against the reported works’ results.


2020 ◽  
Vol 477 (14) ◽  
pp. 2679-2696
Author(s):  
Riddhi Trivedi ◽  
Kalyani Barve

The intestinal microbial flora has risen to be one of the important etiological factors in the development of diseases like colorectal cancer, obesity, diabetes, inflammatory bowel disease, anxiety and Parkinson's. The emergence of the association between bacterial flora and lungs led to the discovery of the gut–lung axis. Dysbiosis of several species of colonic bacteria such as Firmicutes and Bacteroidetes and transfer of these bacteria from gut to lungs via lymphatic and systemic circulation are associated with several respiratory diseases such as lung cancer, asthma, tuberculosis, cystic fibrosis, etc. Current therapies for dysbiosis include use of probiotics, prebiotics and synbiotics to restore the balance between various species of beneficial bacteria. Various approaches like nanotechnology and microencapsulation have been explored to increase the permeability and viability of probiotics in the body. The need of the day is comprehensive study of mechanisms behind dysbiosis, translocation of microbiota from gut to lung through various channels and new technology for evaluating treatment to correct this dysbiosis which in turn can be used to manage various respiratory diseases. Microfluidics and organ on chip model are emerging technologies that can satisfy these needs. This review gives an overview of colonic commensals in lung pathology and novel systems that help in alleviating symptoms of lung diseases. We have also hypothesized new models to help in understanding bacterial pathways involved in the gut–lung axis as well as act as a futuristic approach in finding treatment of respiratory diseases caused by dysbiosis.


2016 ◽  
Vol 136 (6) ◽  
pp. 244-249
Author(s):  
Takahiro Watanabe ◽  
Fumihiro Sassa ◽  
Yoshitaka Yoshizumi ◽  
Hiroaki Suzuki

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