Publications

2025

• Device Independent Quantum Key Activation
  
  • Ulu Bora
  • Brunner Nicolas
  • Weilenmann Mirjam
  Physical Review Letters, American Physical Society, 2025, 135 (19), pp.190801. Device-independent quantum key distribution (DIQKD) allows two distant parties to establish a secret key, based only on the observed Bell nonlocal distribution. It remains however, unclear what the minimal resources for enabling DIQKD are and how to maximize the key rate from a given distribution. In the present work, we consider a scenario where several copies of a given quantum distribution are jointly processed via a local and classical wiring operation. We find that, under few assumptions, it is possible to activate device-independent key. That is, starting from a distribution that is useless in a DIQKD protocol, we obtain a positive key rate by wiring several copies together. We coin this effect device-independent key activation. Our analysis focuses on the standard DIQKD protocol with one-way post-processing, and we resort to semi-definite programming techniques for computing lower bounds on the key rate. (10.1103/f8jc-q1kg)
  DOI : 10.1103/f8jc-q1kg
• Resilience for Regular Path Queries: Towards a Complexity Classification
  
  • Amarilli Antoine
  • Gatterbauer Wolfgang
  • Makhija Neha
  • Monet Mikaël
  Proceedings of the ACM on Management of Data, ACM, 2025, 3 (2), pp.1-18. The resilience problem for a query and an input set or bag database is to compute the minimum number of facts to remove from the database to make the query false. In this paper, we study how to compute the resilience of Regular Path Queries (RPQs) over graph databases. Our goal is to characterize the regular languages $L$ for which it is tractable to compute the resilience of the existentially-quantified RPQ built from $L$. We show that computing the resilience in this sense is tractable (even in combined complexity) for all RPQs defined from so-called local languages. By contrast, we show hardness in data complexity for RPQs defined from the following language classes (after reducing the languages to eliminate redundant words): all finite languages featuring a word containing a repeated letter, and all languages featuring a specific kind of counterexample to being local (which we call four-legged languages). The latter include in particular all languages that are not star-free. Our results also imply hardness for all non-local languages with a so-called neutral letter. We also highlight some remaining obstacles towards a full dichotomy. In particular, for the RPQ $abc|be$, resilience is tractable but the only PTIME algorithm that we know uses submodular function optimization. (10.1145/3725245)
  DOI : 10.1145/3725245
• On regression in extreme regions
  
  • Clémençon Stéphan
  • Huet Nathan
  • Sabourin Anne
  Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2025, 19 (2), pp.4784–4828. We establish a statistical learning theoretical framework aimed at extrapolation, or out-of-domain generalization, on the unobserved tails of covariates in continuous regression problems. Our strategy involves performing statistical regression on a subsample of observations with continuous labels that are the furthest away from the origin, focusing specifically on their angular components. The underlying assumptions of our approach are grounded in the theory of multivariate regular variation, a cornerstone of extreme value theory. We address the stylized problem of nonparametric least squares regression with predictors chosen from a Vapnik-Chervonenkis class.This work contributes to a broader initiative to develop statistical learning theoretical foundations for supervised learning strategies that enhance performance on the supposedly heavy tails of covariates. Previous efforts in this area have focused exclusively on binary classification on extreme covariates. Although the continuous target setting necessitates different techniques and regularity assumptions, our main results echo findings from earlier studies. We quantify the predictive performance on tail regions in terms of excess risk, presenting it as a finite sample risk bound with a clear bias-variance decomposition. Numerical experiments with simulated and real data illustrate our theoretical findings. (10.1214/25-EJS2441)
  DOI : 10.1214/25-EJS2441
• Complexity of mixed Schatten norms of quantum maps
  
  • Kochanowski Jan
  • Fawzi Omar
  • Rouzé Cambyse
  , 2025. We study the complexity of computing the mixed Schatten $\|Φ\|_{q\to p}$ norms of linear maps $Φ$ between matrix spaces. When $Φ$ is completely positive, we show that $\| Φ\|_{q \to p}$ can be computed efficiently when $q \geq p$. The regime $q \geq p$ is known as the non-hypercontractive regime and is also known to be easy for the mixed vector norms $\ell_{q} \to \ell_{p}$ [Boyd, 1974]. However, even for entanglement-breaking completely-positive trace-preserving maps $Φ$, we show that computing $\| Φ\|_{1 \to p}$ is $\mathsf{NP}$-complete when $p>1$. Moving beyond the completely-positive case and considering $Φ$ to be difference of entanglement breaking completely-positive trace-preserving maps, we prove that computing $\| Φ\|^+_{1 \to 1}$ is $\mathsf{NP}$-complete. In contrast, for the completely-bounded (cb) case, we describe a polynomial-time algorithm to compute $\|Φ\|_{cb,1\to p}$ and $\|Φ\|^+_{cb,1\to p}$ for any linear map $Φ$ and $p\geq1$.
• Routing Quantum Control of Causal Order
  
  • Grothus Maarten
  • Abbott Alastair A.
  • Vanrietvelde Augustin
  • Branciard Cyril
  , 2025. In recent years, various frameworks have been proposed for the study of quantum processes with indefinite causal order. In particular, quantum circuits with quantum control of causal order (QC-QCs) form a broad class of physical supermaps obtained from a bottom-up construction and are believed to represent all quantum processes physically realisable in a fixed spacetime. Complementarily, the formalism of routed quantum circuits introduces quantum operations constrained by "routes" to represent processes in terms of a more fine-grained routed circuit decomposition. This decomposition, formalised using a so-called routed graph, represents the information flow within the respective process. However, the existence of routed circuit decompositions has only been established for a small set of processes so far, including both certain specific QC-QCs and more exotic processes as examples. In this work, we remedy this fact by connecting these two frameworks. We prove that for any given $N$, one can use a single routed graph to systematically obtain a routed circuit decomposition for any QC-QC with $N$ parties. We detail this construction explicitly and contrast it with other routed circuit decompositions of QC-QCs, which we obtain from alternative routed graphs. We conclude by pointing out how this connection can be useful to tackle various open problems in the field of indefinite causal order, particularly establishing circuit representations of subclasses of QC-QCs.
• Exact distinguishability between real-valued and complex-valued Haar random quantum states
  
  • Nemoz Tristan
  • Alléaume Romain
  • Brown Peter
  Quantum, Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften, 2025, 10, pp.2120. Haar random states are fundamental objects in quantum information theory and quantum computing. We study the density matrix resulting from sampling $t$ copies of a $d$-dimensional quantum state according to the Haar measure on the orthogonal group. In particular, we analytically compute its spectral decomposition. This allows us to compute exactly the trace distance between $t$-copies of a real Haar random state and $t$-copies of a complex Haar random state. Using this we show a lower-bound on the approximation parameter of real-valued state $t$-designs and improve the lower-bound on the number of copies required for imaginarity testing. (10.22331/q-2026-05-29-2120)
  DOI : 10.22331/q-2026-05-29-2120
• Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology: A Benchmark Study
  
  • Mammadov Ali
  • Le Folgoc Loic
  • Adam Julien
  • Buronfosse Anne
  • Hayem Gilles
  • Hocquet Guillaume
  • Gori Pietro
  Journal of Medical Imaging, SPIE Digital Library, 2025. Multiple Instance Learning (MIL) has emerged as the best solution for Whole Slide Image (WSI) classification. It consists of dividing each slide into patches, which are treated as a bag of instances labeled with a global label. MIL includes two main approaches: instance-based and embedding-based. In the former, each patch is classified independently, and then the patch scores are aggregated to predict the bag label. In the latter, bag classification is performed after aggregating patch embeddings. Even if instance-based methods are naturally more interpretable, embedding-based MILs have usually been preferred in the past due to their robustness to poor feature extractors. However, recently, the quality of feature embeddings has drastically increased using self-supervised learning (SSL). Nevertheless, many authors continue to endorse the superiority of embedding-based MIL. To investigate this further, we conduct 710 experiments across 4 datasets, comparing 10 MIL strategies, 6 self-supervised methods with 4 backbones, 4 foundation models, and various pathology-adapted techniques. Furthermore, we introduce 4 instance-based MIL methods never used before in the pathology domain. Through these extensive experiments, we show that with a good SSL feature extractor, simple instance-based MILs, with very few parameters, obtain similar or better performance than complex, state-of-the-art (SOTA) embedding-based MIL methods, setting new SOTA results on the BRACS and Camelyon16 datasets. Since simple instance-based MIL methods are naturally more interpretable and explainable to clinicians, our results suggest that more effort should be put into well-adapted SSL methods for WSI rather than into complex embedding-based MIL methods.
• White matter hyperintensities and their role in major depressive episodes: a cross-sectional study in adults under 65
  
  • Baudouin Édouard
  • Corruble Emmanuelle
  • Gori Pietro
  • Bloch Isabelle
  • Becquemont Laurent
  • Duron Emmanuelle
  • Colle Romain
  Brazilian Journal of Psychiatry, Brazilian Psychiatric Association, 2025, 47, pp.e20243921. Objective: White matter hyperintensities (WMH) are associated with major depressive episodes (MDE) in individuals aged 65 and older. WMH are prevalent in adults under 65, yet the association between their volume and MDE in this population remains uncertain. This study aimed to assess the association of WMH volume with MDE and its severity in patients aged < 65. Methods: Cross-sectional study (ancillary to clinical trial NCT02051413) of subjects under the age of 65. Overall, 69 patients with MDE and 32 healthy controls (HCs) were included. Severity was assessed with the Hamilton Rating Scale (HRS) and WMH were quantified by two experts. Post-hoc mediation analyses were conducted if associations were found between independent variables and WMH. Results: Mean age was 34.5 (12.4) years. There was no difference in WMH between patients and HCs. Higher WMH volumes were observed in extremely severe MDE (2,170.2 [3,767.9] mm3 vs. 416.6 [594.9] mm3 [r = 0.21; p < 0.05]), which completely mediated the effect of age on severity. Conclusions: In a sample of adults under 65, this study failed to identify higher WMH volume in patients with MDE compared to HCs. However, WMH may act as a mediator of the association between age and MDE severity. This finding suggests that WMH could contribute to more severe depression in late life. (10.47626/1516-4446-2024-3921)
  DOI : 10.47626/1516-4446-2024-3921
• When Statistical Physics Meets Image Processing
  
  • Descombes Xavier
  • Sigelle Marc
  • Tupin Florence
  Markov Processes And Related Fields, Polymat Publishing Company, 2025, 31 (3-4), pp.177-204. In this paper we review the contribution of Evgueny (Eugène for the French community) Pechersky to image processing. Eugène discovered image processing as he was visiting Telecom Paris in 1994. During his stay at Telecom Paris and later on, during some visits and collaboration at INRIA Sophia Antipolis, his work was focused on designing multi-body interaction models to overcome the limits of the well known Ising and Potts model for image processing applications. Notably, the derived models were applied to different applications both in remote sensing and biomedical images. In this paper we summarize Eugène's contribution to the so-called Bayesian approach in image processing. (10.61102/1024-2953-mprf.2025.31.3-4.001)
  DOI : 10.61102/1024-2953-mprf.2025.31.3-4.001