Photonics

Photonics

chaired by Sonia Garcia Blanco & Pepijn Pinkse

Abstracts

Spectroscopic way to detect early stage cancer: Extracellular vesicles, Raman Spectroscopy and Machine Learning, Wooje Lee (OS)

Extracellular vesicles also known as EVs are small spherical particles secreted by almost all mammalian cells. EVs play an important role in inter cellular signaling, transporting biomolecules and garbage disposal. As both diseased and healthy cells release the particles into their micro-environments, EVs can be utilized as disease biomarkers. In this research, 300 spectra from four types of EVs to demonstrate the potential of EVs as prostate cancer biomarker.

To show the potential of EVs, we utilized a machine learning technique for data classification. In particular, we have classified Raman spectral data obtained from extracellular vesicles using a convolutional neural network (CNN).

Obtained EVs’ Raman spectra were divided into a training- (60%), validation- (20%) and testing-dataset (20%). Training was performed with the training set and the model is validated with validation set. After the training process, the predictive ability was evaluated with testing set which was not involved in any way during the learning process. We show CNN trained on raw Raman spectra and CNN trained on baseline-corrected Raman data. Classified testing datasets show an accuracy in excess of 90%.

Unraveling extreme ultraviolet (EUV) light source spectra, Muharrem Bayraktar (XUV)

Laser produced plasmas that are used in EUV lithography light sources are strong emitters around 13.5 nm wavelength with inherent parasitic emission in other wavelengths. The deep ultraviolet (DUV) range of this parasitic emission can be partly absorbed by optics causing heat load. DUV light can also propagate to the imaging plane and cause contrast loss. Additionally, the spectral characteristics in the DUV and visible wavelength bands can provide unique insights in the conditions of the plasma and possible optimization routes. So far, such a comprehensive characterization is proven to be difficult due to challenges in calibration of spectrometers and covering this broad wavelength range with a single spectrometer. Here we present a broadband spectrometer based on free-standing transmission gratings and spectrum measurements in the EUV and DUV ranges. The fabrication, modeling and calibration of the gratings, and treatment of the spectra will be discussed. 

Quantum Photonic Processor based on Silicon Nitride Waveguides, Caterina Taballione (LPNO)

We demonstrate a reconfigurable 8×8 integrated photonic processor circuit suitable for implementing universal gates for quantum information processing protocols. The processor consists of a square mesh of tunable beam splitters based on stoichiometric silicon nitride waveguides, containing 128 tunable elements. We perform a variety of photonic quantum information processing primitives, namely Hong-Ou-Mandel interference, bosonic coalescence/anti-coalescence and high-dimensional single-photon quantum gates exploiting the complete mode structure of the processor. We demonstrate the potential for large-scale photonic quantum information processing using stoichiometric silicon nitride.

Large-alphabet Quantum Key Distribution using spatially encoded light, Tristan Tentrup (COPS)

Secure communication requires a secret key for encryption and decryption. Quantum Key Distribution (QKD) utilizes the quantum nature of light for on-the-fly generation of a secret key between distant parties. The security of this method is based on the no-cloning theorem, which forbids copying quantum states. The standard implementation of the BB84 protocol uses the two-dimensional polarization basis to encode information in photons. Therefore the alphabet contains only two symbols: "0" and "1", limiting the information content per photon to 1 bit. This is a bottleneck especially for encrypted video communication. We encode information in 4096 distinct spatial positions of a photon, which increases the dimensionality and the information content to 8 bit per photon and provides better security. The 2^nd, mutually unbiased basis required for QKD is realized as the Fourier transform of the spatial basis. We experimentally demonstrate an information content of over 8 bit per sifted photon and discuss the security of our method.