Quantum state verification plays a vital role in many quantum cryptographic protocols, as it allows the use of quantum states from untrusted sources. While some progress has been made in this direction, the question of whether the most prevalent type of quantum state verification, namely cut-and-choose verification, can be efficient and secure, is still not answered in full generality. In this work, we show a fundamental limit for quantum state verification for all cut-and-choose approaches used to verify arbitrary quantum states. We provide a no-go result showing that the cut-and-choose techniques cannot lead to quantum state verification protocols that are both efficient in the number of rounds and secure. We show this trade-off for stand-alone and composable security, where the scaling of the lower bound for the security parameters renders cut-and-choose quantum state verification effectively unusable.

Quantum key distribution (QKD) can be used to establish a secret key between trusted parties. Many practical use-cases in communication networks, however, involve parties who do not trust each other. A fundamental cryptographic building block for such distrustful scenarios is quantum coin flipping, which has been investigated only in few experimental studies to date, all of which used probabilistic quantum light sources imposing fundamental limitations. Here, we experimentally implement a quantum strong coin flipping protocol using single-photon states and demonstrate a quantum advantage compared to both classical realizations and implementations using faint laser pulses. We achieve this by employing a state-of-the-art deterministic quantum dot light source in combination with fast, random polarization-state encoding enabling sufficiently low quantum bit error ratio. By demonstrating a single-photon quantum advantage in a cryptographic primitive beyond QKD, our work represents a major advance towards the implementation of complex cryptographic tasks in a future quantum internet.

Delegated quantum computing (DQC) allows clients with low quantum capabilities to outsource computations to a server hosting a quantum computer. This process is often envisioned within the measurement-based quantum computing framework, as it naturally facilitates blindness of inputs and computation. Hence, the overall process of setting up and conducting the computation encompasses a sequence of three stages: preparing the qubits, entangling the qubits to obtain the resource state, and measuring the qubits to run the computation. There are two primary approaches to distributing these stages between the client and the server that impose different constraints on cryptographic techniques and experimental implementations. In the prepare-and-send setting, the client prepares the qubits and sends them to the server, while in the receive-and-measure setting, the client receives the qubits from the server and measures them. Although these settings have been extensively studied independently, their interrelation and whether setting-dependent theoretical constraints are inevitable remain unclear. By implementing the key components of most DQC protocols in the respective missing setting, we provide a method to build prospective protocols in both settings simultaneously and to translate existing protocols from one setting into the other.

Variational quantum algorithms (VQAs) have emerged as promising candidates for solving complex optimization and machine learning tasks on near-term quantum hardware. However, executing quantum operations remains challenging for small-scale users because of several hardware constraints, making it desirable to delegate parts of the computation to more powerful quantum devices. In this work, we introduce a framework for delegated variational quantum algorithms (DVQAs), where a client with limited quantum capabilities delegates the execution of a VQA to a more powerful quantum server. In particular, we introduce a protocol that enables a client to delegate a variational quantum algorithm to a server while ensuring that the input, the output and also the computation itself remain secret. Additionally, if the protocol does not abort, the client can be certain that the computation outcome is indeed correct. This work builds on the general verification protocol introduced by Fitzimons and Kashefi (2017), tailoring it to VQAs. Our approach first proposes a verifiable Protocol for delegating the quantum computation required at each optimization step of a VQA, and then combines the iterative steps into an error-resilient optimization process that offers end-to-end verifiable algorithm execution. We also simulate the performance of our protocol tackling the Transverse Field Ising Model. Our results demonstrate that secure delegation of variational quantum algorithms is a realistic solution for near-term quantum networks, paving the way for practical quantum cloud computing applications.

Delegated quantum computation enables a client with limited quantum capabilities to outsource computations to a more powerful quantum server while preserving correctness and privacy. Verification is crucial in this setting to ensure that the untrusted quantum server performs the computation honestly and returns correct results. A common verification method is the quantum cut-and-choose technique. Inspired by classical verification methods for two-party computation, the client uses the majority of the delegated rounds to test the server's honesty, while keeping the remaining ones for the actual computation. Combining this technique with other methods, such as quantum error correction, could help achieve negligible cheating probabilities for the server; however, such methods can impose significant overheads making implementations unfeasible for the near-term future. In this work, we investigate whether cut-and-choose can yield efficient and secure verifiable quantum computation without additional costly techniques. We find that verifiable delegated quantum computation protocols relying solely on cut-and-choose techniques cannot be secure and efficient at the same time.

This article presents a hybrid methodology for building a multilingual corpus designed tosupport the study of emerging concepts in the humanities and social sciences (HSS), illustrated herethrough the case of “non-technological innovation”. The corpus relies on two complementarysources: (1) textual content automatically extracted from company websites, cleaned for French andEnglish, and (2) annual reports collected and automatically filtered according to documentary criteria(year, format, duplication). The processing pipeline includes automatic language detection, filteringof non-relevant content, extraction of relevant segments, and enrichment with structural metadata.From this initial corpus, a derived dataset in English is created for machine learning purposes. Foreach occurrence of a term from the expert lexicon, a contextual block of five sentences is extracted(two preceding and two following the sentence containing the term). Each occurrence is annotatedwith the thematic category associated with the term, enabling the construction of data suitable forsupervised classification tasks.This approach results in a reproducible and extensible resource, suitable both for analyzing lexicalvariability around emerging concepts and for generating datasets dedicated to natural languageprocessing applications. Cet article présente une méthodologie hybride pour la création d’un corpus multilingue des-tiné à faire émerger des termes associés à des concepts nouveaux en sciences humaines et so-ciales (SHS), en prenant pour cas d’étude « l’innovation non technologique ». Le corpus repose surdeux sources textuelles complémentaires : (1) des contenus extraits automatiquement des sitesweb d’entreprises, nettoyés pour le français et l’anglais, et (2) des rapports annuels collectés etfiltrés automatiquement selon des critères documentaires (année, format, duplication). Le pipelineintègre la détection automatique des langues, le filtrage des contenus non pertinents, l’extraction desegments pertinents et l’enrichissement en métadonnées structurelles.À partir de ce corpus initial, un dataset dérivé en anglais est construit pour des usages en appren-tissage automatique. Il regroupe, pour chaque occurrence d’un terme du lexique expert, un bloccontextuel de cinq phrases (deux précédant et deux suivant la phrase contenant le terme). Chaqueoccurrence est annotée avec la catégorie thématique associée au terme, permettant de structurerles données pour des tâches de l’apprentissage automatique.Cette approche produit une ressource reproductible, extensible et adaptée à l’analyse de la varia-bilité lexicale autour de concepts nouveaux, ainsi qu’à la création de jeux de données destinés auxapplications de traitement automatique des langues.

This article presents a hybrid methodology for building a multilingual corpus designed to support the study of emerging concepts in the humanities and social sciences (HSS), illustrated here through the case of “non-technological innovation”. The corpus relies on two complementary sources: (1) textual content automatically extracted from company websites, cleaned for French and English, and (2) annual reports collected and automatically filtered according to documentary criteria (year, format, duplication). The processing pipeline includes automatic language detection, filtering of non-relevant content, extraction of relevant segments, and enrichment with structural metadata. From this initial corpus, a derived dataset in English is created for machine learning purposes. For each occurrence of a term from the expert lexicon, a contextual block of five sentences is extracted (two preceding and two following the sentence containing the term). Each occurrence is annotated with the thematic category associated with the term, enabling the construction of data suitable for supervised classification tasks. This approach results in a reproducible and extensible resource, suitable both for analyzing lexical variability around emerging concepts and for generating datasets dedicated to natural language processing applications.

Anonymity and privacy are two key properties of modern communication networks. In quantum networks, distributed quantum sensing has emerged as a powerful use case, with applications to clock synchronization, detecting gravitational effects, and more. In this work, we develop a new protocol that, for the first time, combines the different cryptographic properties of anonymity and privacy for the task of distributed parameter estimation. That is, we present a protocol that allows a selected subset of network participants to anonymously collaborate in estimating the average of their private parameters. Crucially, this is achieved without disclosing either the individual parameter values or the identities of the participants, neither to each other nor to the broader network.

In quantum cryptography, fundamental laws of quantum physics are exploited to enhance the security of cryptographic tasks. Quantum key distribution (QKD) is by far the most studied protocol to date, enabling the establishment of a secret key between trusted parties. Many practical use-cases in communication networks, however, involve parties who do not know or trust each other. The most fundamental quantum cryptographic building block in such a distrustful setting is quantum coin flipping, which has been studied only in few experimental studies to date using probabilistic quantum light sources facing fundamental limitations. Here, we experimentally implement a quantum strong coin flipping protocol using single-photon states and demonstrate an advantage compared to both classical realizations and implementations using faint laser pulses. We achieve this by employing a state-of-the-art deterministic single-photon source based on the Purcell-enhanced emission of a semiconductor quantum dot in combination with fast polarization-state encoding with sufficiently low quantum bit error ratio. The reduced multi-photon emission of the single-photon source yields a smaller bias of the coin flipping protocol compared to an attenuated laser implementation, both in simulations and in the experiment. By demonstrating a single-photon quantum advantage in a cryptographic primitive beyond QKD, our work represents a major advance towards the implementation of complex cryptographic tasks in a future quantum internet.

The development of large-scale quantum communication networks necessitates the efficient distribution of quantum states to enable advanced cryptographic applications and distributed tasks. Multipartite entanglement is a key resource in many of these proposals, yet its generation is experimentally challenging, especially in noisy and lossy networks. While a substantial body of work focuses on the distribution of multi-partite entanglement in star-like topologies, practical implementations often rely on linear network structures constrained by existing infrastructure. In this work, we investigate the generation of high-fidelity multipartite entangled states in a realistic quantum network, leveraging the existing infrastructure of the Q-net-Q project - a real-world long-distance link connecting Berlin and Frankfurt via seven trusted relay nodes. Given that only bipartite entanglement sources are available in our setting and that the network is highly lossy, we explore the role of quantum memories in enhancing multi-partite entanglement distribution and identify key performance requirements. Furthermore, we analyze the feasibility and performance of cryptographic primitives - including (Anonymous) Conference Key Agreement and Quantum Secret Sharing - highlighting the scenarios where the use of multipartite entanglement yields clear advantages.

Graph states are a class of multipartite entangled quantum states that are ubiquitous in quantum information. We study equivalence relations between graph states under local unitaries (LU) to obtain distinguishing methods both in local and in networked settings. Based on the marginal structure of graph states, we introduce a family of easy-to-compute LU invariants. We show that these invariants uniquely identify the entanglement classes of every graph state up to eight qubits and discuss their reliability for larger numbers of qubits. To handle larger graphs, we generalize tools to test for local Clifford (LC) equivalence of graph states that work by condensing large graphs into smaller graphs. In turn, we show that statements on the equivalence of these smaller graphs (which are easier to compute) can be used to infer statements on the equivalence of the original, larger graphs. We analyze LU equivalence in two key settings, with and without allowing for the permutation of qubits. We identify entanglement classes, whose marginal structure does not allow us to distinguish them. As a result, we increase the bound on the number of qubits where the LU-LC conjecture holds from 8 to 10 qubits in the setting where qubit permutations are allowed.

This paper presents the development of a lexicon centered on emerging concepts, focusing on non-technological innovation. It introduces a four-step methodology that combines human expertise, statistical analysis, and machine learning techniques to establish a model that can be generalized across multiple domains. This process includes the creation of a thematic corpus, the development of a Gold Standard Lexicon, annotation and preparation of a training corpus, and finally, the implementation of learning models to identify new terms. The results demonstrate the robustness and relevance of our approach, highlighting its adaptability to various contexts and its contribution to lexical research. The developed methodology promises applicability in conceptual fields.

In this work we focus on two classes of games: XOR nonlocal games and XOR* sequential games with monopartite resources. XOR games have been widely studied in the literature of nonlocal games, and we introduce XOR* games as their natural counterpart within the class of games where a resource system is subjected to a sequence of controlled operations and a final measurement. Examples of XOR* games are $2\rightarrow 1$ quantum random access codes (QRAC) and the CHSH* game introduced by Henaut et al. in [PRA 98,060302(2018)]. We prove, using the diagrammatic language of process theories, that under certain assumptions these two classes of games can be related via an explicit theorem that connects their optimal strategies, and so their classical (Bell) and quantum (Tsirelson) bounds. We also show that two of such assumptions -- the reversibility of transformations and the bi-dimensionality of the resource system in the XOR* games -- are strictly necessary for the theorem to hold by providing explicit counterexamples. We conclude with several examples of pairs of XOR/XOR* games and by discussing in detail the possible resources that power the quantum computational advantages in XOR* games.

While the advantages of photonic quantum computing, including direct compatibility with communication, are apparent, several imperfections such as loss and distinguishability presently limit actual implementations. These imperfections are unlikely to be completely eliminated, and it is therefore beneficial to investigate which of these are the most dominant and what is achievable under their presence. In this work, we provide an in-depth investigation of the influence of photon loss, multi-photon terms and photon distinguishability on the generation of photonic 3-partite Greenberger-Horne-Zeilinger states via established fusion protocols. We simulate the generation process for spontaneous parametric down-conversion and solid-state-based single-photon sources using realistic parameters and show that different types of imperfections are dominant with respect to the fidelity and generation success probability. Our results indicate what are the dominant imperfections for the different photon sources and in which parameter regimes we can hope to implement photonic quantum computing in the near future.

Quantum information processing architectures typically only allow for nearest-neighbour entanglement creation. In many cases, this prevents the direct generation of GHZ states, which are commonly used for many communication and computation tasks. Here, we show how to obtain GHZ states between nodes in a network that are connected in a straight line, naturally allowing them to initially share linear cluster states. We prove a strict upper bound of $\lfloor (n+3)/2 \rfloor$ on the size of the set of nodes sharing a GHZ state that can be obtained from a linear cluster state of $n$ qubits, using local Clifford unitaries, local Pauli measurements, and classical communication. Furthermore, we completely characterize all selections of nodes below this threshold that can share a GHZ state obtained within this setting. Finally, we demonstrate these transformations on the IBMQ Montreal quantum device for linear cluster states of up to $n=19$ qubits.

Quantum correlations between entangled particles can be used by parties in a network to verify that they share a specific quantum state. A proposal for network-assisted self-testing generalizes this approach to states of any number of qubits.

Sharing multi-partite quantum entanglement between parties allows for diverse secure communication tasks to be performed. Among them, conference key agreement (CKA) - an extension of key distribution to multiple parties - has received much attention recently. Interestingly, CKA can also be performed in a way that protects the identities of the participating parties, therefore providing $anonymity$. In this work, we propose an anonymous CKA protocol for three parties that is implemented in a highly practical network setting. Specifically, a line of quantum repeater nodes is used to build a linear cluster state among all nodes, which is then used to anonymously establish a secret key between any three of them. The nodes need only share maximally entangled pairs with their neighbours, therefore avoiding the necessity of a central server sharing entangled states. This linear chain setup makes our protocol an excellent candidate for implementation in future quantum networks. We explicitly prove that our protocol protects the identities of the participants from one another and perform an analysis of the key rate in the finite regime, contributing to the quest of identifying feasible quantum communication tasks for network architectures beyond point-to-point.

We present a semi-supervised annotation process for identifying and labelling explicit aspects of an initially unlabelled corpus. Firstly, we employ cross-domain learning to pre-annotate the initial data, deliberately excluding domain-related input features to ensure effective learning transfer. Then, we apply an active learning strategy to enhance the pre-annotation performance and enrich the learning data. We adjust the strategy to sequence labeling and address class imbalance. We evaluate this process using two unlabelled datasets in French, consisting of user opinions on beauty products and electronic devices, respectively. The results show an improved F1-score achieved by increasing and correcting 30% of the training dataset.

Multipartite entanglement enables secure and anonymous key exchange between multiple parties in a network. In particular Greenberger-Horne-Zeilinger (GHZ) states have been introduced as resource states for anonymous key exchange protocols, in which an anonymous subset of parties within a larger network establishes a secret key. However, the use of other types of multipartite entanglement for such protocols remains relatively unexplored. Here we demonstrate that linear cluster states can serve as a versatile and potentially scalable resource in such applications. We implemented an anonymous key exchange protocol with four photons in a linear cluster state and established a shared key between three parties in our network. We show how to optimize the protocol parameters to account for noise and to maximize the finite key rate under realistic conditions. As cluster states have been established as a flexible resource in quantum computation, we expect that our demonstration provides a first step towards their hybrid use for networked computing and communication.