Cognitive photonic networks are researched to efficiently solve computationally hard problems. Flexible fabrication techniques for the implementation of such networks into compact and scalable chips are desirable for the study of new optical computing schemes and algorithm optimization. Here we demonstrate a femtosecond laser-written optical oracle based on cascaded directional couplers in glass, for the solution of the Hamiltonian path problem. By interrogating the integrated photonic chip with ultrashort laser pulses, we were able to distinguish the different paths traveled by light pulses, and thus infer the existence or the absence of the Hamiltonian path in the network by using an optical correlator. This work proves that graph theory ...
We report photonic quantum circuits created using an ultrafast laser processing technique that is ra...
Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasing...
In emerging artificial intelligence applications, massive matrix operations require high computing s...
Cognitive photonic networks are researched to efficiently solve computationally hard problems. Flexi...
The modern information society is enabled by photonic fiber networks of huge coverage and complexity...
Laws of physics have proved useful for solving combinatorial optimization problems. This chapter int...
Indisputably, software run in conventional Von-Neumann architectures has provided solutions to most ...
We propose graph representations for reconfigurable photonic mesh circuits. Waveguide mesh circuits ...
Analog optical computing uses nonlinear optics and photonics to bring new approaches to attacking se...
Photonic neuromorphic computing has emerged as a promising approach to building a low-latency and en...
International audienceOver the past decade, articial Neural Networks (NNs) have revolutionized co...
International audienceNeural networks are one of the disruptive computing concepts of our time. Howe...
Using simple fiber networks for proof-of-principle demonstrations, we give examples of natural compu...
Frontiers in Optics 2017. Washington, D.C. United States, 18–21 September 2017.We introduce a novel ...
Cost-effective and programmable photonic-driven solutions like electronic counterparts (FPGAs) can b...
We report photonic quantum circuits created using an ultrafast laser processing technique that is ra...
Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasing...
In emerging artificial intelligence applications, massive matrix operations require high computing s...
Cognitive photonic networks are researched to efficiently solve computationally hard problems. Flexi...
The modern information society is enabled by photonic fiber networks of huge coverage and complexity...
Laws of physics have proved useful for solving combinatorial optimization problems. This chapter int...
Indisputably, software run in conventional Von-Neumann architectures has provided solutions to most ...
We propose graph representations for reconfigurable photonic mesh circuits. Waveguide mesh circuits ...
Analog optical computing uses nonlinear optics and photonics to bring new approaches to attacking se...
Photonic neuromorphic computing has emerged as a promising approach to building a low-latency and en...
International audienceOver the past decade, articial Neural Networks (NNs) have revolutionized co...
International audienceNeural networks are one of the disruptive computing concepts of our time. Howe...
Using simple fiber networks for proof-of-principle demonstrations, we give examples of natural compu...
Frontiers in Optics 2017. Washington, D.C. United States, 18–21 September 2017.We introduce a novel ...
Cost-effective and programmable photonic-driven solutions like electronic counterparts (FPGAs) can b...
We report photonic quantum circuits created using an ultrafast laser processing technique that is ra...
Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasing...
In emerging artificial intelligence applications, massive matrix operations require high computing s...