Showing papers by "Technical University of Berlin published in 2022"

Quantum Communication Using Semiconductor Quantum Dots

Abstract: Worldwide, enormous efforts are directed toward the development of the so-called quantum internet. Turning this long-sought-after dream into reality is a great challenge that will require breakthroughs in quantum communication and computing. To establish a global, quantum-secured communication infrastructure, photonic quantum technologies will doubtlessly play a major role, by providing and interfacing essential quantum resources, for example, flying- and stationary qubits or quantum memories. Over the last decade, significant progress has been made in the engineering of on-demand quantum light sources based on semiconductor quantum dots, which enable the generation of close-to-ideal single- and entangled-photon states, useful for applications in quantum information processing. This review focuses on implementations of, and building blocks for, quantum communication using quantum-light sources based on epitaxial semiconductor quantum dots. After reviewing the main notions of quantum communication and introducing the devices used for single-photon and entangled-photon generation, an overview of experimental implementations of quantum key distribution protocols using quantum dot based quantum light sources is provided. Furthermore, recent progress toward quantum-secured communication networks as well as building blocks thereof is summarized. The article closes with an outlook, discussing future perspectives in the field and identifying the main challenges to be solved.

Privacy and Confidentiality in Process Mining: Threats and Research Challenges

Abstract: Privacy and confidentiality are very important prerequisites for applying process mining to comply with regulations and keep company secrets. This article provides a foundation for future research ...

Fair Top-k Ranking with multiple protected groups

Abstract: Ranking items or people is a fundamental operation at the basis of several processes and services, not all of them happening online. Ranking is required for different tasks, including search, personalization, recommendation, and filtering. While traditionally ranking has been aimed solely at maximizing some global utility function, recently the awareness of potential discrimination for some of the elements to rank, has captured the attention of researchers, which have thus started devising ranking systems which are non-discriminatory or fair for the items being ranked. So far, researchers have mostly focused on group fairness, which is usually expressed in the form of constraints on the fraction of elements from some protected groups that should be included in the top- k positions, for any relevant k . These constraints are needed in order to correct implicit societal biases existing in the input data and reflected in the relevance or fitness score computed. In this article, we tackle the problem of selecting a subset of k individuals from a pool of n ≫ k candidates, maximizing global utility (i.e., selecting the “best” candidates) while respecting given group-fairness criteria. In particular, to tackle this Fair Top- k Ranking problem, we adopt a ranked group-fairness definition which extends the standard notion of group fairness based on protected groups, by ensuring that the proportion of protected candidates in every prefix of the top- k ranking remains statistically above, or indistinguishable from, a given minimum threshold. Our notion of utility requires, intuitively, that every individual included in the top- k should be more qualified than every candidate not included; and that for every pair of candidates in the top- k , the more qualified candidate should be ranked above. The main contribution of this paper is an algorithm for producing a fair top- k ranking that can be used when more than one protected group is present, which means that a statistical test based on a multinomial distribution needs to be used instead of one for a binomial distribution, as the original FA*IR algorithms does. This poses important technical challenges and increases both the space and time complexity of the re-ranking algorithm. Our experimental assessment on real-world datasets shows that our approach yields small distortions with respect to rankings that maximize utility without considering our fairness criteria.

A quantum key distribution testbed using a plug&play telecom-wavelength single-photon source

Abstract: Deterministic solid state quantum light sources are considered key building blocks for future communication networks. While several proof-of-principle experiments of quantum communication using such sources have been realized, most of them required large setups—often involving liquid helium infrastructure or bulky closed-cycle cryotechnology. In this work, we report on the first quantum key distribution (QKD) testbed using a compact benchtop quantum dot single-photon source operating at telecom wavelengths. The plug&play device emits single-photon pulses at O-band wavelengths (1321 nm) and is based on a directly fiber-pigtailed deterministically fabricated quantum dot device integrated into a compact Stirling cryocooler. The Stirling is housed in a 19 in. rack module including all accessories required for stand-alone operation. Implemented in a simple QKD testbed emulating the BB84 protocol with polarization coding, we achieve an multiphoton suppression of g(2)(0)=0.10±0.01 and a raw key rate of up to (4.72 ± 0.13) kHz using an external pump laser. In this setting, we further evaluate the performance of our source in terms of the quantum bit error ratios, secure key rates, and tolerable losses expected in full implementations of QKD while accounting for finite key size effects. Furthermore, we investigate the optimal settings for a two-dimensional temporal acceptance window applied on the receiver side, resulting in predicted tolerable losses up to 23.19 dB. Not least, we compare our results with previous proof-of-concept QKD experiments using quantum dot single-photon sources. Our study represents an important step forward in the development of fiber-based quantum-secured communication networks exploiting sub-Poissonian quantum light sources.

Creep and creep damage behavior of stainless steel 316L manufactured by laser powder bed fusion

Abstract: This study presents a thorough characterization of the creep properties of austenitic stainless steel 316L produced by laser powder bed fusion (LPBF 316L) contributing to the sparse available data to date. Experimental results (mechanical tests, microscopy, X-ray computed tomography) concerning the creep deformation and damage mechanisms are presented and discussed. The tested LPBF material exhibits a low defect population, which allows for the isolation and improved understanding of the effect of other typical aspects of an LPBF microstructure on the creep behavior. As a benchmark to assess the material properties of the LPBF 316L, a conventionally manufactured variant of 316L was also tested. To characterize the creep properties, hot tensile tests and constant force creep tests at 600 °C and 650 °C are performed. The creep stress exponents of the LPBF material are smaller than that of the conventional variant. The primary and secondary creep stages and the times to rupture of the LPBF material are shorter than the hot rolled 316L. Overall the creep damage is more extensive in the LPBF material. The creep damage of the LPBF material is overall mainly intergranular. It is presumably caused and accelerated by both the appearance of precipitates at the grain boundaries and the unfavorable orientation of the grain boundaries. Neither the melt pool boundaries nor entrapped gas pores show a significant influence on the creep damage mechanism.

Zapline‐plus: A Zapline extension for automatic and adaptive removal of frequency‐specific noise artifacts in M/ <scp>EEG</scp>

Abstract: Removing power line noise and other frequency-specific artifacts from electrophysiological data without affecting neural signals remains a challenging task. Recently, an approach was introduced that combines spectral and spatial filtering to effectively remove line noise: Zapline. This algorithm, however, requires manual selection of the noise frequency and the number of spatial components to remove during spatial filtering. Moreover, it assumes that noise frequency and spatial topography are stable over time, which is often not warranted. To overcome these issues, we introduce Zapline-plus, which allows adaptive and automatic removal of frequency-specific noise artifacts from M/electroencephalography (EEG) and LFP data. To achieve this, our extension first segments the data into periods (chunks) in which the noise is spatially stable. Then, for each chunk, it searches for peaks in the power spectrum, and finally applies Zapline. The exact noise frequency around the found target frequency is also determined separately for every chunk to allow fluctuations of the peak noise frequency over time. The number of to-be-removed components by Zapline is automatically determined using an outlier detection algorithm. Finally, the frequency spectrum after cleaning is analyzed for suboptimal cleaning, and parameters are adapted accordingly if necessary before re-running the process. The software creates a detailed plot for monitoring the cleaning. We highlight the efficacy of the different features of our algorithm by applying it to four openly available data sets, two EEG sets containing both stationary and mobile task conditions, and two magnetoencephalography sets containing strong line noise.

An Isolable 2,5‐Disila‐3,4‐Diphosphapyrrole and a Conjugated Si=P−Si=P−Si=N Chain Through Degradation of White Phosphorus with a <i>N,N</i> ‐Bis(Silylenyl)Aniline

Abstract: White phosphorus (P4 ) undergoes degradation to P2 moieties if exposed to the new N,N-bis(silylenyl)aniline PhNSi2 1 (Si=Si[N(tBu)]2 CPh), furnishing the first isolable 2,5-disila-3,4-diphosphapyrrole 2 and the two novel functionalized Si=P doubly bonded compounds 3 and 4. The pathways for the transformation of the non-aromatic 2,5-disila-3,4-diphosphapyrrole PhNSi2 P2 2 into 3 and 4 could be uncovered. It became evident that 2 reacts readily with both reactants P4 and 1 to afford either the polycyclic Si=P-containing product [PhNSi2 P2 ]2 P2 3 or the unprecedented conjugated Si=P-Si=P-Si=NPh chain-containing compound 4, depending on the employed molar ratio of 1 and P4 as well as the reaction conditions. Compounds 3 and 4 can be converted into each other by reactions with 1 and P4 , respectively. All new compounds 1-4 were unequivocally characterized including by single-crystal X-ray diffraction analysis. In addition, the electronic structures of 2-4 were established by Density Functional Theory (DFT) calculations.

Architectures for Neural Networks as Surrogates for Dynamic Systems in Chemical Engineering

Abstract: Surrogate models for dynamic systems in chemical engineering are increasingly of interest. Neural networks have already been applied in research, but it remains unclear which types of neural network architectures are actually required for practical systems. The focus here lies on recurrent neural networks of type Jordan, Elman, and LSTM layers. These are investigated for different types of data sets as training basis: batch trajectories, data of a proper excitation of a continuous process, and a typical operation trajectory of a large chemical plant. To ensure a rigorous investigation, hyperparameter tuning by Bayesian and Bandit optimization is included. As a first, a dynamic surrogate model using LSTM layers for a batch distillation system is presented, which is valid from start-up until shutdown. The evaluation shows further need for adjustments in data preparation and objective / loss function compared to the state of the art.

Architectures for neural networks as surrogates for dynamic systems in chemical engineering

Abstract: Surrogate models for dynamic systems in chemical engineering are increasingly of interest. Neural networks have already been applied in research, but it remains unclear which types of neural network architectures are actually required for practical systems. The focus here lies on recurrent neural networks of type Jordan, Elman, and LSTM layers. These are investigated for different types of data sets as training basis: batch trajectories, data of a proper excitation of a continuous process, and a typical operation trajectory of a large chemical plant. To ensure a rigorous investigation, hyperparameter tuning by Bayesian and Bandit optimization is included. As a first, a dynamic surrogate model using LSTM layers for a batch distillation system is presented, which is valid from start-up until shutdown. The evaluation shows further need for adjustments in data preparation and objective/loss function compared to the state of the art.

Improved Peptide Backbone Fragmentation Is the Primary Advantage of MS-Cleavable Crosslinkers

Abstract: Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of mass spectrometry (MS)-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently, such studies have also been published with noncleavable crosslinkers, suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the commonly used MS-cleavable crosslinker, disuccinimidyl sulfoxide (DSSO). Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS cleavability of the crosslinker, but improved peptide backbone fragmentation which reduces the ambiguity of peptide identifications. This also holds true for another commonly used MS-cleavable crosslinker, DSBU. We show furthermore that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped higher-energy collisional dissociation (HCD) method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.

Intraligand Charge Transfer Enables Visible‐Light‐Mediated Nickel‐Catalyzed Cross‐Coupling Reactions**

Abstract: We demonstrate that several visible-light-mediated carbon-heteroatom cross-coupling reactions can be carried out using a photoactive NiII precatalyst that forms in situ from a nickel salt and a bipyridine ligand decorated with two carbazole groups (Ni(Czbpy)Cl2 ). The activation of this precatalyst towards cross-coupling reactions follows a hitherto undisclosed mechanism that is different from previously reported light-responsive nickel complexes that undergo metal-to-ligand charge transfer. Theoretical and spectroscopic investigations revealed that irradiation of Ni(Czbpy)Cl2 with visible light causes an initial intraligand charge transfer event that triggers productive catalysis. Ligand polymerization affords a porous, recyclable organic polymer for heterogeneous nickel catalysis of cross-coupling reactions. The heterogeneous catalyst shows stable performance in a packed-bed flow reactor during a week of continuous operation.