HAL Portal IOGS (nstitut d'Optique Graduate School)
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Tomonaga-Luttinger Liquid Behavior in a Rydberg-encoded Spin Chain
No full textInternational audienceQuantum fluctuations can disrupt long-range order in one-dimensional systems, and replace it with the universal paradigm of the Tomonaga-Luttinger liquid (TLL), a critical phase of matter characterized by power-law decaying correlations and linearly dispersing excitations. Using a Rydberg quantum simulator, we study how TLL physics manifests in the low-energy properties of a spin chain, interacting under either the ferromagnetic or the antiferromagnetic dipolar XY Hamiltonian. Following quasi-adiabatic preparation, we directly observe the power-law decay of spin-spin correlations in real-space, allowing us to extract the Luttinger parameter. In the presence of an impurity, the chain exhibits tunable Friedel oscillations of the local magnetization. Moreover, by utilizing a quantum quench, we directly probe the propagation of correlations, which exhibit a light-cone structure related to the linear sound mode of the underlying TLL. Our measurements demonstrate the influence of the long-range dipolar interactions, renormalizing the parameters of TLL with respect to the case of nearest-neighbor interactions. Finally, comparison to numerical simulations exposes the high sensitivity of TLLs to doping and finite-size effects
Credal ensembling in multi-class classification
No full textInternational audienceIn this paper, we present a formal framework to (1) aggregate probabilistic ensemble members into either a representative classifier or a credal classifier, and (2) perform various decision tasks based on this uncertainty quantification. We first elaborate on the aggregation problem under a class of distances between distributions. We then propose generic methods to robustify uncertainty quantification and decisions, based on the obtained ensemble and representative probability. To facilitate the scalability of the proposed framework, for all the problems and applications covered, we elaborate on their computational complexities from the theoretical aspects and leverage theoretical results to derive efficient algorithmic solutions. Finally, relevant sets of experiments are conducted to assess the usefulness of the proposed framework in uncertainty sampling, classification with a reject option, and set-valued prediction-making
Optimizing NN reduction in an atom interferometer network for GW detection
No full textInternational audienceThe sensitivity of an atom gradiometer aiming to detect gravitational waves (GW) is impacted by fluctuations of Earth's gravity field also called Newtonian Noise (NN). Sensor arrays have proved to be a promising technique for NN reduction. In our study, we further investigate the benefits of Atom Interferometer (AI) networks by improving their geometry and the extraction of the GW signal. We focus on Seismic Newtonian Noise in the frequency band from 0.1 to 10 Hz. On one hand, we show that using a specific detector geometry, a better NN rejection can occur optimizing the number of gradiometers in the network. On the other hand, we show that carrying out optimization in sub frequency bands - which results in using various detector geometries from a common network - allows even higher NN rejection while keeping a similar number of interferometers
Ultrafast laser high-aspect-ratio extreme nanostructuring of glass beyond λ/100
No full textInternational audienceThe ultimate feature size is key in ultrafast laser material processing. A capacity to significantly exceed optical limits and to structure below 100 nm is essential to advance ultrafast processing into the field of metamaterials. Such achievement requires to combine the control of optical near-fields and of material reactions, while preserving the flexibility of long working distances, compatible with a mature laser process. Using sub-ps and ps non-diffractive Bessel beams, we demonstrate unprecedented feature sizes below a hundredth of the incident 1 µm wavelength over an extended focus depth of tens of µm. Record features sizes, down to 7 nm, result from self-generated near-field light components initiated by cavities induced by far-field radiation in a back-surface illumination geometry. This sustains the generation of more confined near-field evanescent components along the laser scan with nm pitch, perpendicular to the incident field direction, driving by local thermal ablation a super-resolved laser structuring process. The near-field pattern is replicated with high robustness, advancing towards a 10 nm nanoscribing tool with a µm-sized laser pen. The process is controllable by the field orientation.The non-diffractive irradiation develops evanescent fields over the focusing length, resulting in a high aspect ratio trenching with nm section and µm depth. Higher energy doses trigger the selforganization of quasi-periodic patterns seeded by spatially modulated scattering, similarly to optical modelocking. A predictive multipulse simulation method validates the far-field-induced near-field electromagnetic scenario of void nanochannel growth and replication, indicating the processing range and resolution on the surface and in the depth.</div
Message-recovery Horizontal Correlation Attack on Classic McEliece
No full textInternational audienceAs the technical feasibility of a quantum computer becomes more and more likely, post-quantum cryptography algorithms are receiving particular attention in recent years. Among them, code-based cryptosystems were first considered unsuited for hardware and embedded software implementations because of their very large key sizes. However, recent work has shown that such implementations are practical, which also makes them susceptible to physical attacks. In this article, we propose a horizontal correlation attack on the Classic McEliece cryptosystem, more precisely on the matrix-vector multiplication over F2 that computes the shared key in the encapsulation process. The attack is applicable in the broader context of Niederreiter-like code-based cryptosystems and is independent of the code structure, i.e. it does not need to exploit any particular structure in the parity check matrix. Instead, we take advantage of the constant time property of the matrix-vector multiplication over F2. We extend the feasibility of the basic attack by leveraging information-set decoding methods and carry it out successfully on the reference embedded software implementation. Interestingly, we highlight that implementation choices, like the word size or the compilation options, play a crucial role in the attack success, and even contradict the theoretical analysis
Decoding the Hierarchy: A Hybrid Approach to Hierarchical Multi-label Text Classification
No full textInternational audienceHierarchical multi-label text classification (HMTC) aims to predict multiple labels from a tree-like hierarchy for a given input text. Recent approaches frame HMTC as a seq2seq problem, where the objective is to predict the sequence of associated labels, regardless of their order or position in the hierarchy. Despite promising results, these approaches rely solely on attention mechanisms from previously generated tokens. This limit prevents them from acquiring information about the global hierarchy and may lead to the accumulation of errors as the model learns hierarchical cues among labels. We propose a novel HMTC model based on a hybrid version of the encoder-decoder architecture where the decoder is pre-populated with the entire label embeddings. By leveraging the decoder’s Cross-Attention and Hierarchical Self-Attention mechanisms, we achieve a label representation that benefits from instance and global label-wise information. Empirical experiments on four HMTC benchmark datasets demonstrated the effectiveness of our approach by settling new state-of-the-art results. Code (https://github.com/FatosTorba/HLPD) and datasets are made available to facilitate the reproducibility and future work
Design, manufacture and characterization of compact optics for micro-CPV
No full textInternational audienceConcentrator photovoltaics (CPV) modules are complex, heavy and bulky which hinders the deployment of this technology. Over the past few years, the miniaturization of this technology, called micro-CPV, promises to make more compact and less expensive modules. This article focuses on the design, fabrication and characterization of a 350× single-stage concentrator optic made of PMMA. A matrix of 16 lenses has been produced, and a prototype module has been fabricated and characterized outdoors, achieving an optical efficiency of over 80%
Optical Superlattice for Engineering Hubbard Couplings in Quantum Simulation
No full textInternational audienceQuantum simulations of Hubbard models with ultracold atoms rely on the exceptional control of coherent motion provided by optical lattices. Here we demonstrate enhanced tunability using an optical superlattice in a fermionic quantum gas microscope, evidenced by long-lived coherent double-well oscillations, next-nearest-neighbor quantum walks in a staggered configuration, and correlated quantum walks of two particles initiated through a resonant pair-breaking mechanism. We furthermore demonstrate tunable spin couplings through local offsets and engineer a spin ladder with ferromagnetic and antiferromagnetic couplings along the rungs and legs, respectively. Our Letter underscores the high potential of optical superlattices for engineering, simulating, and detecting strongly correlated many-body quantum states, with direct applications ranging from the study of mixed-dimensional systems to fermionic quantum computing. Published by the American Physical Society 202
