Publications

2024

• Design optimization of on-chip III-V/SiN quantum well/dot lasers
  
  • Alkhazraji Emad
  • Chow Weng W
  • Grillot Frederic
  • Bowers John E
  • Madaras Scott E
  • Gehl Michael
  • Skogen Erik
  • Wan Yating
  , 2024.
• Be my guesses: The interplay between side-channel leakage metrics
  
  • Béguinot Julien
  • Cheng Wei
  • Guilley Sylvain
  • Rioul Olivier
  Microprocessors and Microsystems: Embedded Hardware Design, Elsevier, 2024, 107, pp.105045. (10.1016/j.micpro.2024.105045)
  DOI : 10.1016/j.micpro.2024.105045
• Parallelization of frequency domain quantum gates: manipulation and distribution of frequency-entangled photon pairs generated by a 21 GHz silicon microresonator
  
  • Henry Antoine
  • Fioretto Dario
  • Procopio Lorenzo
  • Monfray Stéphane
  • Boeuf Frédéric
  • Vivien Laurent
  • Cassan Eric
  • Alonzo-Ramos Carlos
  • Bencheikh Kamel
  • Zaquine Isabelle
  • Belabas Nadia
  Advanced photonics, SPIE, 2024, 6 (03), pp.036003-1/036003-10. Harnessing the frequency dimension in integrated photonics offers key advantages in terms of scalability, noise resilience, parallelization, and compatibility with telecom multiplexing techniques. Integrated ring resonators have been used to generate frequency-entangled states through spontaneous four-wave mixing. However, state-of-the-art integrated resonators are limited by trade-offs among size, spectral separation, and efficient photon pair generation. We have developed silicon ring resonators with a footprint below 0.05mm2 providing more than 70 frequency channels separated by 21 GHz. We exploit the narrow frequency separation to parallelize and independently control 34 single qubit-gates with a single set of three off-the-shelf electro-optic devices. We fully characterize 17 frequency-bin maximally entangled qubit pairs by performing quantum state tomography. We demonstrate for the first time, we believe, a fully connected five-user quantum network in the frequency domain. These results are a step towards a generation of quantum circuits implemented with scalable silicon photonics technology, for applications in quantum computing and secure communications. (10.1117/1.AP.6.3.036003)
  DOI : 10.1117/1.AP.6.3.036003
• Communication cachée via le champ magnétique émis par un ordinateur
  
  • Apvrille Ludovic
  MISC : multi-system & internet security cookbook, Diamond ed., 2024. Tout courant électrique émet un champ magnétique … dont celui qui alimente les processeurs. Cet article montre comment on peut, assez facilement, exploiter le champ magnétique émis par l’alimentation d’un processeur pour émettre des données. Ce canal caché a notamment été utilisé lors du CTF ph0wn pour un des challenges...
• Complexity of the uniqueness problem of a minimum vertex cover in a graph
  
  • Hudry Olivier
  , 2024.
• Data encryption with chaotic light in the long wavelength infrared atmospheric window
  
  • Didier Pierre
  • Zaminga Sara
  • Spitz Olivier
  • Wu Jiagui
  • Awwad Élie
  • Maisons Gregory
  • Grillot Frederic
  Optica, Optical Society of America - OSA Publishing, 2024, 11 (5), pp.626-633. In environments where traditional fiber optic cables are impractical, free-space optical communications offer a promising solution for transmitting large amounts of data, especially in the mid-infrared wavelength range. Despite the advantages of minimal atmospheric interference and stable signals, the vulnerability of wireless optical communications to eavesdropping poses a significant challenge. This study addresses this challenge by demonstrating a method for privately transmitting optical data using photonic chaos from distributed feedback quantum cascade lasers operating at 9.3 µm. Signal processing techniques are applied to enhance the quality of the transmission over distances exceeding 30 m, accompanied by a comprehensive analysis of the photonic chaos complexity to ensure data confidentiality. These findings mark a significant advancement in developing private communications systems within the thermal atmospheric window, with a substantially reduced risk of interception by adversaries. The research not only contributes to secure communications but also has potential implications for enhancing security of data transmission in challenging environments, impacting various industries and applications. (10.1364/OPTICA.511171)
  DOI : 10.1364/OPTICA.511171
• Embodied exploration of deep latent spaces in interactive dance-music performance
  
  • Nabi Sarah
  • Esling Philippe
  • Peeters Geoffroy
  • Bevilacqua Frédéric
  , 2024. (10.1145/3658852.3659072)
  DOI : 10.1145/3658852.3659072
• A historical perspective on Schützenberger-Pinsker inequalities (extended version)
  
  • Rioul Olivier
  information geometry, Springer, 2024, 7 (S2), pp.737-779. This paper presents a tutorial overview of so-called Pinsker inequalities which establish a precise relationship between information and statistics, and whose use have become ubiquitous in many applications. According to Stigler’s law of eponymy, no scientific discovery is named after its original discoverer. Pinsker’s inequality is no exception: Years before the publication of Pinsker’s book in 1960, the French medical doctor, geneticist, epidemiologist, and mathematician Marcel-Paul (Marco) Schützenberger, in his 1953 doctoral thesis, not only proved what is now called Pinsker’s inequality (with the optimal constant that Pinsker himself did not establish) but also the optimal second-order improvement, more than a decade before Kullback’s derivation of the same inequality. We review Schützenberger and Pinsker contributions as well as those of Volkonskii and Rozanov, Sakaguchi, McKean, Csiszár, Kullback, Kemperman, Vajda, Bretagnolle and Huber, Krafft and Schmitz, Toussaint, Reid and Williamson, Gilardoni, as well as the optimal derivation of Fedotov, Harremoës, and Topsøe. We also present some historical elements on the life and work of Schützenberger, and discuss an interesting problem of an erroneous constant in the Schützenberger-Pinsker inequality. (10.1007/s41884-024-00138-z)
  DOI : 10.1007/s41884-024-00138-z
• MARLIM: Multi-Agent Reinforcement Learning for Inventory Management
  
  • Leluc Rémi
  • Kadoche Elie
  • Bertoncello Antoine
  • Gourvénec Sébastien
  , 2022. Maintaining a balance between the supply and demand of products by optimizing replenishment decisions is one of the most important challenges in the supply chain industry. This paper presents a novel reinforcement learning framework called MARLIM, to address the inventory management problem for a single-echelon multi-products supply chain with stochastic demands and lead-times. Within this context, controllers are developed through single or multiple agents in a cooperative setting. Numerical experiments on real data demonstrate the benefits of reinforcement learning methods over traditional baselines. (10.48550/arXiv.2308.01649)
  DOI : 10.48550/arXiv.2308.01649
• DNS flooding attack detection scheme through Machine Learning
  
  • Chbib Fadlallah
  • Attar Ali El
  • Khatoun Rida
  • Fadlallah Ahmad
  • Serhrouchni Ahmed
  , 2024.
• SPARSITY CONSTRAINED LINEAR TANGENT SPACE ALIGNMENT MODEL (LTSA) FOR 3D CARDIAC EXTRACELLULAR VOLUME MAPPING
  
  • Mounime Ismaël
  • Lee Wonil
  • Marin Thibault
  • Han Paul K.
  • Djebra Yanis
  • Eslahi Samira V.
  • Gori Pietro
  • Angelini Elsa
  • Fakhri Georges El
  • Ma Chao
  , 2024. Cardiac longitudinal relaxation time (T1) and extracellular volume (ECV) are valuable bio-markers used for the quantitative characterization of cardiac tissue properties, showing great potential in many clinical applications such as diffuse fibrosis. However, cardiac T1 and ECV mapping is difficult because of respiratory and cardiac motions. A unique challenge for post-contrast T1 mapping is that the concentration of contrast agent also changes over time. Recently, a linear tangent space alignment (LTSA) model-based fast MRI method has been proposed to enable high-resolution, highframe-rate dynamic MR with sparsely sampled (k, t)-space data by leveraging the intrinsic low-dimensional manifold structure of dynamic MR images, showing superior performance over the low-rank model-based methods. This work extends the LTSA method by imposing an additional sparsity constraint on the subspace alignment matrix of the LTSA model for improved image reconstruction. The performance of the proposed method is validated in 3D freebreathing, pre-and post-contrast cardiac T1 mapping as well as ECV mapping using in vivo data acquired on healthy volunteers at 3T.
• Deep-learning uncertainty estimation for data-consistent breast tomosynthesis reconstruction
  
  • Quillent Arnaud
  • Bismuth Vincent
  • Bloch Isabelle
  • Kervazo Christophe
  • Ladjal Saïd
  , 2024. Digital Breast Tomosynthesis (DBT) is an X-ray modality enabling to reconstruct 3D volumes in the context of breast cancer screening. However, because of the limited angle and sparse view constraints, artefacts emerge in the reconstructions and greatly reduce their quality. In a previous work, we proposed a post-processing deep learning reconstruction pipeline for DBT that is trained using synthetic data. Owing to the geometrical limitations of the acquisition device, the amount of information to extrapolate is important and the neural network could inevitably commit errors. As such, the reconstructed volumes are not completely reliable, and exact consistency with the measurements is not guaranteed. In this study, we first propose two methods to estimate the uncertainty of the model reconstructions, and show that the result can be used as a proxy of the true error. Secondly, we explore the minimisation of a data consistency term constrained by the predicted uncertainty, in order to mitigate the network errors. We demonstrate experimentally that this approach enhances the quality of reconstruction as compared to reintroducing projections information without constraint.
• Supervised diagnosis prediction from cortical sulci: toward the discovery of neurodevelopmental biomarkers in mental disorders
  
  • Auriau Pierre
  • Grigis Antoine
  • Dufumier Benoit
  • Louiset Robin
  • Chavas Joel
  • Gori Pietro
  • Mangin Jean-François
  • Duchesnay Edouard
  , 2024. Recent advances in machine learning applied to structural magnetic resonance imaging (sMRI) may highlight abnormalities in brain anatomy associated with mental disorders. These disorders are multifactorial, resulting from a complex combination of neurodevelopmental and environmental factors. In particular, such factors are present in cortical sulci, whose shapes are determined very early in brain development and are a valuable proxy for capturing specifically the neurodevelopmental contribution of brain anatomy. This paper explores whether the shapes of cortical sulci can be used for diagnosis prediction using deep learning models. These models are applied to three mental disorders (autism spectrum disorder, bipolar disorder, and schizophrenia) in large multicentric datasets. We demonstrate that the neurodevelopmental underpinnings of these disorders can be captured withsMRI. Finally, we show the potential of visual explanations of models’ decisions in discovering biomarkers for mental disorders.
• PARTICLE TRACKING IN BIOLOGICAL IMAGES WITH OPTICAL-FLOW ENHANCED KALMAN FILTERING
  
  • Reme Raphael
  • Newson Alasdair
  • Angelini Elsa
  • Olivo-Marin Jean-Christophe
  • Lagache Thibault
  , 2024. Single-particle-tracking is a fundamental prerequisite for studying biological processes in time-lapse microscopy. However, it remains a challenging task in many applications where numerous particles are driven by fast and complex motion patterns. To anticipate the motion of particles most tracking algorithms usually assume near constant position, velocity or acceleration over consecutive frames. However, such assumptions are not robust to large and sudden velocity changes that typically occur in in vivo imaging. In this paper, we exploit optical flow to directly measure the velocity of particles in a Kalman filtering context. The resulting method shows improved robustness to correctly predict particles positions, even with sudden motions. We validate our method on simulated images with high particle density and fast elastic motion patterns. Quantitative results show a decrease of tracking errors by a factor of two, when compared to other tracking algorithms, while preserving fast computational time.
• Aloha, police d'états: Un contrôle d'admission implicite ?
  
  • Bonald Thomas
  • Combes Richard
  • Mathieu Fabien
  , 2024. Les protocoles Aloha adaptatifs permettent à plusieurs stations émettrices de se partager un même canal de communication, chaque émetteur gérant ses envois à l'aide d'un état interne. Ils sont à la base de nombreux réseaux, dont ceux de type 802.11. Dans cet article, nous considérons un scénario à temps discret où N stations « saturées » ont toujours à émettre. À l'aide d'un modèle à décroissance géométrique, nous apportons les contributions suivantes : nous donnons une nouvelle condition de stabilité basée sur la notion de bruit ambiant et proposons des formules d'approximation du comportement ; nous confrontons ces résultats à des simulations. Nous montrons en particulier que pour N grand la distinction stable/instable perd son sens car seul un régime transitoire est visible à des échelles de temps raisonnables. Dans ce régime transitoire, on observe une forme de contrôle d'admission implicite : Si N est trop grand, une partie des stations est « gelée » dans des états n'émettant presque plus, permettant aux autres un accès au canal dans des conditions raisonnables.
• Digitalisation as threat to resilience: what if there are no more semiconductors?
  
  • Courtillat-Piazza Ludmila
  • Quinton Sophie
  • Marquet Clement
  , 2024.
• Multi-Criteria Optimization of Distributed Real-Time Network Topologies
  
  • Champenois Florient
  • Brandner Florian
  • Grandpierre Thierry
  • Borde Etienne
  • Suissa Abraham
  • Georges Laurent
  , 2024, pp.1-11. Communication needs in avionics and transportation have radically changed over the recent years. Traditionally, the underlying hard real-time networks were designed in a centralized way, focusing on redundancy and isolation. Today, real-time communication is ubiquitous, from large airplanes to small vehicles. The associated networks must support a wide range of applications, and large amounts of data. Centralized approaches from the avionics domain, e.g., AFDX, are too costly, too heavyweight, and not flexible enough for these applications.In this paper we explore a new distributed network architecture designed to support jumbo airliners, but also small aircraft and drones. Communication redundancy is achieved using redundant paths, which have to be adapted and optimized to the application. The main challenge then is to build an optimized network configuration ensuring safety, fault tolerance, timing, and performance of both critical, and non-critical communication. Minimizing volume and weight of the equipment is also mandatory. Since the solution space is too large to be explored in reasonable time, we propose a genetic algorithm. Our experiments show that our algorithm converges quickly and offers solutions of excellent quality. The computed solutions are in the top 2% among the best solutions obtained using an exhaustive exploration. Our approach thus enables system engineers to quickly explore and choose very good solution for their systems. (10.1109/ISORC61049.2024.10551327)
  DOI : 10.1109/ISORC61049.2024.10551327
• Device-independent quantum key distribution with arbitrarily small nonlocality
  
  • Wooltorton Lewis
  • Brown Peter
  • Colbeck Roger
  Physical Review Letters, American Physical Society, 2024, 132 (21), pp.210802. Device-independent quantum key distribution (DIQKD) allows two users to set up shared cryptographic key without the need to trust the quantum devices used. Doing so requires nonlocal correlations between the users. However, in [Phys. Rev. Lett. 127, 050503 (2021)] it was shown that for known protocols nonlocality is not always sufficient, leading to the question of whether there is a fundamental lower bound on the minimum amount of nonlocality needed for any DIQKD implementation. Here we show that no such bound exists, giving schemes that achieve key with correlations arbitrarily close to the local set. Furthermore, some of our constructions achieve the maximum of 1 bit of key per pair of entangled qubits. We achieve this by studying a family of Bell-inequalities that constitute all self-tests of the maximally entangled state with a single linear Bell expression. Within this family there exist non-local correlations with the property that one pair of inputs yield outputs arbitrarily close to perfect key. Such correlations exist for a range of Clauser-Horne-Shimony-Holt (CHSH) values, including those arbitrarily close to the classical bound. Finally, we show the existence of quantum correlations that can generate both perfect key and perfect randomness simultaneously, whilst also displaying arbitrarily small CHSH violation; this opens up the possibility of a new class of cryptographic protocol. (10.1103/PhysRevLett.132.210802)
  DOI : 10.1103/PhysRevLett.132.210802
• Joint Metrics for EMF Exposure and Coverage in Real-World Homogeneous and Inhomogeneous Cellular Networks
  
  • Gontier Quentin
  • Wiame Charles
  • Wang Shanshan
  • Di Renzo Marco
  • Wiart Joe
  • Horlin François
  • Tsigros Christo
  • Oestges Claude
  • de Doncker Philippe
  IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers, 2024, 23 (10), pp.13267 - 13284. This paper evaluates the downlink performance of cellular networks in terms of coverage and electromagnetic field exposure (EMFE), in the framework of stochastic geometry. The model is constructed based on datasets for sub-6 GHz macro cellular networks but it is general enough to be applicable to millimeter-wave networks as well. On the one hand, performance metrics are calculated for β-Ginibre point processes which are shown to faithfully model a large number of motion-invariant networks. On the other hand, performance metrics are derived for inhomogeneous Poisson point processes with a radial intensity measure, which are shown to be a good approximation for motion-variant networks. For both cases, joint and marginal distributions of the EMFE and the coverage, and the first moments of the EMFE are provided and validated by Monte Carlo simulations using realistic sets of parameters from two sub-6 GHz macro urban cellular networks, i.e., 5G NR 2100 (Paris, France) and LTE 1800 (Brussels, Belgium) datasets. In addition, this paper includes the analysis of the impact of the network parameters and discusses the achievable trade-off between coverage and EMFE. (10.1109/TWC.2024.3400612)
  DOI : 10.1109/TWC.2024.3400612
• Misplaced trust in AI : the explanation paradox and the human-centric path. A characterisation of the cognitive challenges to appropriately trust algorithmic decisions and applications in the financial sector
  
  • Bertrand Astrid
  , 2024. As AI is becoming more widespread in our everyday lives, concerns have been raised about comprehending how these opaque structures operate. In response, the research field of explainability (XAI) has developed considerably in recent years. However, little work has studied regulators' need for explainability or considered effects of explanations on users in light of legal requirements for explanations. This thesis focuses on understanding the role of AI explanations to enable regulatory compliance of AI-enhanced systems in financial applications. The first part reviews the challenge of taking into account human cognitive biases in the explanations of AI systems. The analysis provides several directions to better align explainability solutions with people's cognitive processes, including designing more interactive explanations. It then presents a taxonomy of the different ways to interact with explainability solutions. The second part focuses on specific financial contexts. One study takes place in the domain of online recommender systems for life insurance contracts. The study highlights that feature based explanations do not significantly improve non expert users' understanding of the recommendation, nor lead to more appropriate reliance compared to having no explanation at all. Another study analyzes the needs of regulators for explainability in anti-money laundering and financing of terrorism. It finds that supervisors need explanations to establish the reprehensibility of sampled failure cases, or to verify and challenge banks' correct understanding of the AI.
• Non-invasive performance prediction of high-speed softwarized network services with limited knowledge
  
  • Liu Qiong
  • Zhang Tianzhu
  • Linguaglossa Leonardo
  , 2024. Modern telco networks have experienced a significant paradigm shift in the past decade, thanks to the proliferation of network softwarization. Despite the benefits of softwarized networks, the constituent software data planes cannot always guarantee predictable performance due to resource contentions in the underlying shared infrastructure. Performance predictions are thus paramount for network operators to fulfill ServiceLevel Agreements (SLAs), especially in high-speed regimes (e.g., Gigabit or Terabit Ethernet). Existing solutions heavily rely on in-band feature collection, which imposes non-trivial engineering and data-path overhead. This paper proposes a non-invasive performance prediction approach, which complements state-ofthe-art solutions by measuring and analyzing low-level features ubiquitously available in the network infrastructure. Accessing these features does not hamper the packet data path. Our approach does not rely on prior knowledge of the input traffic, VNFs’ internals, and system details. We show that (i) low-level hardware features exposed by the NFV infrastructure can be collected and interpreted for performance issues, (ii) predictive models can be derived with classical ML algorithms, (iii) and can be used to predict performance impairments in real NFV systems accurately. Our code and datasets are publicly available.
• Investigating on mobile phone transmitting power under a non-standalone NR network
  
  • Liu Jiang
  • Zhang Yarui
  • Ben Chikha Wassim
  • Wang Shanshan
  • Samaras Theodoros
  • Jawad Ourouk
  • Ourak Lamine
  • Conil Emmanuelle
  • Wiart Joe
  , 2024, pp.1-3. Since the invention of mobile communication technology, successive generations have consistently superseded their predecessors for the past four decades. Nowadays, with the global deployment of the fifth generation (5G) wireless communication network, there has been a notable surge in awareness regarding the potential risks associated with exposure to radio-frequency electromagnetic fields (RFEMF). To address the public concern, it is crucial to investigate and monitor the RF-EMF exposure. In this paper, we aim to measure and analyze the uplink exposure from the daily usage of mobile phone, especially with data-demanding application running in a 5G network. To achieve this objective, extensive measurements of file transfer protocol (FTP) are conducted in the Greater Paris region, where non standalone (NSA) New Radio (NR) is prevalent across most areas. The statistical distribution of measurement data is given and the comparison between Long Term Evolution (LTE) and NSA-NR is analyzed. (10.46620/URSIATRASC24/SFIF9621)
  DOI : 10.46620/URSIATRASC24/SFIF9621
• Spectral Structure Analysis of FFT-based Digital Predistortion for Wideband 5G Applications
  
  • Bouazza Tayeb
  • Pham Dang-Kièn Germain
  • Mohellebi Reda
  • Desgreys Patricia
  , 2024, pp.1-5. In this paper, a spectral structure analysis for the FFT-based subband digital predistortion is performed. This analysis consists in investigating whether the spectrum of the signal at the output of the power amplifier (PA) shows any particular structuring of the information. Various scenarios are investigated by simulation and validated by experiments, on a real PA. It is found that some spectral zones are more critical than others to maintain good linearization, which makes possible to reduce the requirements of the feedback path. (10.1109/ISCAS58744.2024.10558459)
  DOI : 10.1109/ISCAS58744.2024.10558459
• The Semantic Web : 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings, Part I
  
  • Meroño Peñuela Albert
  • Dimou Anastasia
  • Troncy Raphaël
  • Hartig Olaf
  • Acosta Maribel
  • Alam Mehwish
  • Paulheim Heiko
  • Lisena Pasquale
  , 2024, 14664, pp.XXVI, 344. The two-volume set LNCS 14664 and 14665 constitutes the refereed proceedings of the 21st International Conference on The Semantic Web, ESWC 2024, held in Hersonissos, Crete, Greece, during May 26-30, 2024. The 32 full papers presented were carefully reviewed and selected from 138 submissions. They focus on all aspects of theoretical, analytical, and empirical aspects of the semantic web, semantic technologies, knowledge graphs and semantics on the web in general. (10.1007/978-3-031-60626-7)
  DOI : 10.1007/978-3-031-60626-7
• The Semantic Web : 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings, Part II
  
  • Meroño Peñuela Albert
  • Dimou Anastasia
  • Troncy Raphaël
  • Hartig Olaf
  • Acosta Maribel
  • Alam Mehwish
  • Paulheim Heiko
  • Lisena Pasquale
  , 2024, 14665, pp.XXVI, 252. The two-volume set LNCS 14664 and 14665 constitutes the refereed proceedings of the 21st International Conference on The Semantic Web, ESWC 2024, held in Hersonissos, Crete, Greece, during May 26-30, 2024. The 32 full papers presented were carefully reviewed and selected from 138 submissions. They focus on all aspects of theoretical, analytical, and empirical aspects of the semantic web, semantic technologies, knowledge graphs and semantics on the web in general. (10.1007/978-3-031-60635-9)
  DOI : 10.1007/978-3-031-60635-9