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Systems with pronounced spin anisotropy play a pivotal role in advancing magnetization switching and spin-wave generation mechanisms, which are fundamental for spintronic technologies. Quasi-van der Waals ferromagnets, particularly Cr$_{1+\delta}$Te$_2$ compounds, represent seminal materials in this field, renowned for their delicate balance between frustrated layered geometries and magnetism. Despite extensive investigation, the precise nature of their magnetic ground state, typically described as a canted ferromagnet, remains contested, as does the mechanism governing spin reorientation under external magnetic fields and varying temperatures. In this work, we leverage a multimodal approach, integrating complementary techniques, to reveal that Cr$_{1+\delta}$Te$_2$ ($\delta = 0.25 - 0.50$) hosts a previously overlooked magnetic phase, which we term orthogonal-ferromagnetism. This single phase consists of alternating atomically sharp single layers of in-plane and out-of-plane ferromagnetic blocks, coupled via exchange interactions and as such, it differs significantly from crossed magnetism, which can be achieved exclusively by stacking multiple heterostructural elements together. Contrary to earlier reports suggesting a gradual spin reorientation in CrTe$_2$-based systems, we present definitive evidence of abrupt spin-flop-like transitions. This discovery, likely due to the improved crystallinity and lower defect density in our samples, repositions Cr$_{1+\delta}$Te$_2$ compounds as promising candidates for spintronic and orbitronic applications, opening new pathways for device engineering.

The $^{18}$Ne(d,t)$^{17}$Ne and $^{18}$Ne(d,$^3$He)$^{17}$F single-nucleon pickup reactions were measured at 16.5 MeV/nucleon in inverse kinematics together with elastic and inelastic scattering channels. The full set of measured exclusive differential cross sections was compared with the mirror reaction channels on stable $^{18}$O after consistent reanalysis using coupled reaction channels calculations. Within this interpretation scheme, most of the spectroscopic factors extracted for the population of unbound states in $^{17}$F match within uncertainties with their mirror partners in $^{17}$O. However, for the deeply-bound neutron removal channel to $^{17}$Ne, a significant symmetry breaking with the mirror proton-removal channel leading to $^{17}$N is evidenced by an overall single-particle strength reduction.

We present the first measurement of the $^{47}$K($d,p\gamma$)$^{48}$K transfer reaction, performed in inverse kinematics using a reaccelerated beam of $^{47}$K. The level scheme of $^{48}$K has been greatly extended with nine new bound excited states identified and spectroscopic factors deduced. Detailed comparisons with SDPF-U and SDPF-MU shell-model calculations reveal a number of discrepancies with these results, and a preference for SDPF-MU is found. Intriguingly, an apparent systematic overestimation of spectroscopic factors and a poor reproduction of the energies for 1$^-$ states suggests that the mixing between the $\pi s^{\,\,\,1}_{1/2} d^{\,\,\,4}_{3/2}$ and $\pi s^{\,\,\,2}_{1/2} d^{\,\,\,3}_{3/2}$ proton configurations in $^{48}$K is not correctly described using current interactions, challenging our descriptions of light $N=28$ nuclei., Comment: 7 pages, 3 figures, 1 table

This paper explores the application of the Condorcet Jury theorem to the domain of sentiment analysis, specifically examining the performance of various large language models (LLMs) compared to simpler natural language processing (NLP) models. The theorem posits that a majority vote classifier should enhance predictive accuracy, provided that individual classifiers' decisions are independent. Our empirical study tests this theoretical framework by implementing a majority vote mechanism across different models, including advanced LLMs such as ChatGPT 4. Contrary to expectations, the results reveal only marginal improvements in performance when incorporating larger models, suggesting a lack of independence among them. This finding aligns with the hypothesis that despite their complexity, LLMs do not significantly outperform simpler models in reasoning tasks within sentiment analysis, showing the practical limits of model independence in the context of advanced NLP tasks.

Two-dimensional and van der Waals ferromagnets are ideal platform to study low dimensional magnetism and proximity effects in van der Waals heterostructures. Their ultimate two dimensional character offers also the opportunity to easily adjust their magnetic properties using strain or electric fields. Among 2D ferromagnets, the Cr$_{1+x}$Te$_2$ compounds with $x$=0-1 are very promising because their magnetic properties depend on the amount of self-intercalated Cr atoms between pure CrTe$_2$ layers and the Curie temperature (T$_C$) can reach room temperature for certain compositions. Here, we investigate the evolution of the composition, structural and magnetic properties of thin Cr$_{1.33}$Te$_2$ (Cr$_2$Te$_3$) films epitaxially grown on graphene upon annealing. We observe a transition above 450{\deg}C from the Cr$_{1.33}$Te$_2$ phase with perpendicular magnetic anisotropy and a T$_C$ of 180 K to a composition close to Cr$_{1.39}$Te$_2$ with in-plane magnetic anisotropy and a T$_C$ of 240-250 K. This phase remains stable up to 650{\deg}C above which a pure Cr film starts to form. This work demonstrates the complex interplay between intercalated Cr, lattice parameters and magnetic properties in Cr$_{1+x}$Te$_2$ compounds., Comment: 5 pages, 5 figures

Recently uncovered archives at the University of Franche-Comt\'e in Besan\c{c}on (France) reveal a rich history of research and teaching in physics since the Faculty of Science was first established in 1845. Here, we describe a selection of notable activities conducted by the named Chairs of Physics during the period 1845-1970. We uncover a long tradition of major contributions to physics education and research, including the production of highly regarded physics textbooks that were widely used in Europe, as well as pioneering contributions to electron diffraction and microscopy, Fourier optics, and holography. These discoveries yield valuable insights into the historical development of physics research in France, and show how even a small provincial university was able to stay up-to-date with international developments across several areas of physics.

This paper introduces a new risk-on risk-off strategy for the stock market, which combines a financial stress indicator with a sentiment analysis done by ChatGPT reading and interpreting Bloomberg daily market summaries. Forecasts of market stress derived from volatility and credit spreads are enhanced when combined with the financial news sentiment derived from GPT-4. As a result, the strategy shows improved performance, evidenced by higher Sharpe ratio and reduced maximum drawdowns. The improved performance is consistent across the NASDAQ, the S&P 500 and the six major equity markets, indicating that the method generalises across equities markets.

Neutron dark decays have been suggested as a solution to the discrepancy between bottle and beam experiments, providing a dark matter candidate that can be searched for in halo nuclei. The free neutron in the final state following the decay of $^6$He into $^4$He $+$ $n$ + $\chi$ provides an exceptionally clean detection signature when combined with a high efficiency neutron detector. Using a high-intensity $^6$He$^+$ beam at GANIL, a search for a coincident neutron signal resulted in an upper limit on a dark decay branching ratio of Br$_\chi \leq 4.0\times10^{-10}$ (95\% C.L.). Using the dark neutron decay model proposed originally by Fornal and Grinstein, we translate this into an upper bound on a dark neutron branching ratio of $\mathcal{O}(10^{-5})$, improving over global constraints by one to several orders of magnitude depending on $m_\chi$.

In machine learning and particularly in topological data analysis, $\epsilon$-graphs are important tools but are generally hard to compute as the distance calculation between n points takes time O(n^2) classically. Recently, quantum approaches for calculating distances between n quantum states have been proposed, taking advantage of quantum superposition and entanglement. We investigate the potential for quantum advantage in the case of quantum distance calculation for computing $\epsilon$-graphs. We show that, relying on existing quantum multi-state SWAP test based algorithms, the query complexity for correctly identifying (with a given probability) that two points are not $\epsilon$-neighbours is at least O(n^3 / ln n), showing that this approach, if used directly for $\epsilon$-graph construction, does not bring a computational advantage when compared to a classical approach.

Achieving large-scale growth of two-dimensional (2D) ferromagnetic materials with high Curie temperature (TC) and perpendicular magnetic anisotropy (PMA) is highly desirable for the development of ultra-compact magnetic sensors and magnetic memories. In this context, van der Waals (vdW) Cr2Te3 appears as a promising candidate. Bulk Cr2Te3 exhibits strong PMA and a TC of 180 K. Moreover, both PMA and TC might be adjusted in ultrathin films by engineering composition, strain, or applying an electric field. In this work, we demonstrate the molecular beam epitaxy (MBE) growth of vdW heterostructures of five-monolayer quasi-freestanding Cr2Te3 on three classes of 2D materials: graphene (semimetal), WSe2 (semiconductor) and Bi2Te3 (topological insulator). By combining structural and chemical analysis down to the atomic level with ab initio calculations, we confirm the single crystalline character of Cr2Te3 films on the 2D materials with sharp vdW interfaces. They all exhibit PMA and TC close to the bulk Cr2Te3 value of 180 K. Ab initio calculations confirm this PMA and show how its strength depends on strain. Finally, Hall measurements reveal a strong anomalous Hall effect, which changes sign at a given temperature. We theoretically explain this effect by a sign change of the Berry phase close to the Fermi level. This transition temperature depends on the 2D material in proximity, notably as a consequence of charge transfer. MBE-grown Cr2Te3/2D material bilayers constitute model systems for the further development of spintronic devices combining PMA, large spin-orbit coupling and sharp vdW interface., Comment: 18 pages, 13 figures and Supplemental Material

Nuclear fission is still one of the most complex physical processes we can observe in nature due to the interplay of macroscopic and microscopic nuclear properties that decide the result. An example of this coupling is the presence of nuclear dissipation as an important ingredient that contributes to drive the dynamics and has a clear impact on the time of the process. However, different theoretical interpretations, and scarce experimental data make it poorly understood. In this letter, we present the first experimental determination of the dissipation energy in fission as a function of the fragment split, for three different fissioning systems. The amount of dissipation was obtained through the measurement of the relative production of fragments with even and odd atomic numbers with respect to different initial fission energies. The results reveal a clear effect of particular nuclear shells on the dissipation and fission dynamics. In addition, the relative production of fragments with even and odd atomic numbers appears as a potential contributor to the long-standing problem of the time scale in fission.

We develop a novel randomised block coordinate primal-dual algorithm for a class of non-smooth ill-posed convex programs. Lying in the midway between the celebrated Chambolle-Pock primal-dual algorithm and Tseng's accelerated proximal gradient method, we establish global convergence of the last iterate as well optimal $O(1/k)$ and $O(1/k^{2})$ complexity rates in the convex and strongly convex case, respectively, $k$ being the iteration count. Motivated by the increased complexity in the control of distribution level electric power systems, we test the performance of our method on a second-order cone relaxation of an AC-OPF problem. Distributed control is achieved via the distributed locational marginal prices (DLMPs), which are obtained \revise{as} dual variables in our optimisation framework., Comment: Changed title and revised manuscript

Fission at low excitation energy is an ideal playground to probe the impact of nuclear structure on nuclear dynamics. While the importance of structural effects in the nascent fragments is well-established in the (trans-)actinide region, the observation of asymmetric fission in several neutron-deficient pre-actinides can be explained by various mechanisms. To deepen our insight into that puzzle, an innovative approach based on inverse kinematics and an enhanced version of the VAMOS++ heavy-ion spectrometer was implemented at the GANIL facility, Caen. Fission of $^{178}$Hg was induced by fusion of $^{124}$Xe and $^{54}$Fe. The two fragments were detected in coincidence using VAMOS++ supplemented with a new SEcond Detection arm. For the first time in the pre-actinide region, access to the pre-neutron mass and total kinetic energy distributions, and the simultaneous isotopic identification of one the fission fragment, was achieved. The present work describes the experimental approach, and discusses the pre-neutron observables in the context of an extended asymmetric-fission island located south-west of $^{208}Pb. A comparison with different models is performed, demonstrating the importance of this "new" asymmetric-fission island for elaborating on driving effects in fission.

The structure of $^{83}$As, $^{85}$As and $^{87}$As have been studied in fusion-fission reaction $^{238}$U+$^9$Be. Fission fragments were identified in mass and atomic number using the VAMOS++ spectrometer and the coincident $\gamma$-rays were detected in the $\gamma$-ray tracking array AGATA. New transitions in $^{83}$As and $^{85}$As are reported and placed in the level schemes. A level scheme of the excited states in $^{87}$As is proposed for the first time. The data are interpreted in frame of Large-Scale Shell-Model calculations, SU3 symmetries and Beyond Mean-Field frameworks. A spherical regime at magic number $N$=50 is predicted and the location of the proton $g_{9/2}$ orbital is proposed for the first time. Development of collectivity in a prolate deformed, $\gamma$-soft regime in the open shell cases $^{85}$As and $^{87}$As, most neutron-rich isotopes beyond $N$=50, is concluded. Data and theoretical calculations give confidence to a relatively high extrapolated excitation energy about 4 MeV of the $9/2^+$ state in $^{79}$Cu, one proton above $^{78}$Ni.

The numerical wavefront backpropagation principle of digital holography confers unique extended focus capabilities, without mechanical displacements along z-axis. However, the determination of the correct focusing distance is a non-trivial and time consuming issue. A deep learning (DL) solution is proposed to cast the autofocusing as a regression problem and tested over both experimental and simulated holograms. Single wavelength digital holograms were recorded by a Digital Holographic Microscope (DHM) with a 10$\mathrm{x}$ microscope objective from a patterned target moving in 3D over an axial range of 92 $\mu$m. Tiny DL models are proposed and compared such as a tiny Vision Transformer (TViT), tiny VGG16 (TVGG) and a tiny Swin-Transfomer (TSwinT). The proposed tiny networks are compared with their original versions (ViT/B16, VGG16 and Swin-Transformer Tiny) and the main neural networks used in digital holography such as LeNet and AlexNet. The experiments show that the predicted focusing distance $Z_R^{\mathrm{Pred}}$ is accurately inferred with an accuracy of 1.2 $\mu$m in average in comparison with the DHM depth of field of 15 $\mu$m. Numerical simulations show that all tiny models give the $Z_R^{\mathrm{Pred}}$ with an error below 0.3 $\mu$m. Such a prospect would significantly improve the current capabilities of computer vision position sensing in applications such as 3D microscopy for life sciences or micro-robotics. Moreover, all models reach an inference time on CPU, inferior to 25 ms per inference. In terms of occlusions, TViT based on its Transformer architecture is the most robust.

Sampling random variables following a Boltzmann distribution is an NP-hard problem involved in various applications such as training of \textit{Boltzmann machines}, a specific kind of neural network. Several attempts have been made to use a D-Wave quantum computer to sample such a distribution, as this could lead to significant speedup in these applications. Yet, at present, several challenges remain to efficiently perform such sampling. We detail the various obstacles and explain the remaining difficulties in solving the sampling problem on a D-wave machine.

In blackbox optimization, evaluation of the objective and constraint functions is time consuming. In some situations, constraint values may be evaluated independently or sequentially. The present work proposes and compares two strategies to define a hierarchical ordering of the constraints and to interrupt the evaluation process at a trial point when it is detected that it will not improve the current best solution. Numerical experiments are performed on a closed-form test problem.

The properties of nuclei with extreme neutron-to-proton ratios, far from those naturally occurring on Earth, are key to understand nuclear forces and how nucleons hold together to form nuclei. $^7$H, with six neutrons and a single proton, is the nuclear system with the most unbalanced neutron-to-proton ratio known so far. However, its sheer existence and properties are still a challenge for experimental efforts and theoretical models. Here we report experimental evidences on the formation of $^7$H as a resonance, detected with independent observables, and the first measurement of the structure of its ground state. The resonance is found at $\sim$0.7 MeV above the $^3$H+4n mass, with a narrow width of $\sim$0.2 MeV and a $1/2^+$ spin and parity. These data are consistent with a $^7$H as a $^3$H core surrounded by an extended four-neutron halo, with a unique four-neutron decay and a relatively long half-life thanks to neutron pairing; a prime example of new phenomena occurring in what would be the most pure-neutron nuclear matter we can access in the laboratory.

The neutrons for science facility (NFS), the first operational experimental area of the new GANIL/SPIRAL-2 facility, received its first beams in December 2019. Proton-induced reaction cross-sections as well as neutron beam characteristics were measured during the first commissioning phases. The first results, showing the features of the facility, are presented here and compared with previously published data. The physics cases and the first accepted experiments are presented as well.

In recent years, two-dimensional van der Waals materials have emerged as an important platform for the observation of long-range ferromagnetic order in atomically thin layers. Although heterostructures of such materials can be conceived to harness and couple a wide range of magneto-optical and magneto-electrical properties, technologically relevant applications require Curie temperatures at or above room-temperature and the ability to grow films over large areas. Here we demonstrate the large-area growth of single-crystal ultrathin films of stoichiometric Fe5GeTe2 on an insulating substrate using molecular beam epitaxy. Magnetic measurements show the persistence of soft ferromagnetism up to room temperature, with a Curie temperature of 293 K, and a weak out-of-plane magnetocrystalline anisotropy. Surface, chemical, and structural characterizations confirm the layer-by-layer growth, 5:1:2 Fe:Ge:Te stoichiometric elementary composition, and single crystalline character of the films.

We report on a novel material, namely two-dimensional (2D) V$_{1-x}$Pt$_x$Se$_2$ alloy, exhibiting simultaneously ferromagnetic order and Rashba spin-orbit coupling. While ferromagnetism is absent in 1T-VSe$_2$ due to the competition with the charge density wave phase, we demonstrate theoretically and experimentally that the substitution of vanadium by platinum in VSe$_2$ (10-50 %) to form an homogeneous 2D alloy restores ferromagnetic order with Curie temperatures of 6 K for 5 monolayers and 25 K for one monolayer of V$_{0.65}$Pt$_{0.35}$Se$_2$. Moreover, the presence of platinum atoms gives rise to Rashba spin-orbit coupling in (V,Pt)Se$_2$ providing an original platform to study the interplay between ferromagnetism and spin-orbit coupling in the 2D limit., Comment: 5 pages, 5 figures

An important issue in today's electricity markets is the management of flexibilities offered by new practices, such as smart home appliances or electric vehicles. By inducing changes in the behavior of residential electric utilities, demand response (DR) seeks to adjust the demand of power to the supply for increased grid stability and better integration of renewable energies. A key role in DR is played by emergent independent entities called load aggregators (LAs). We develop a new decentralized algorithm to solve a convex relaxation of the classical Alternative Current Optimal Power Flow (ACOPF) problem, which relies on local information only. Each computational step can be performed in an entirely privacy-preserving manner, and system-wide coordination is achieved via node-specific distribution locational marginal prices (DLMPs). We demonstrate the efficiency of our approach on a 15-bus radial distribution network., Comment: 8 pages, 3 figures; submitted for publication

High-resolution gamma-ray spectroscopy of 18N is performed with the Advanced GAmma Tracking Array AGATA, following deep-inelastic processes induced by an 18O beam on a 181Ta target. Six states are newly identified, which together with the three known excitations exhaust all negative-parity excited states expected in 18N below the neutron threshold. Spin and parities are proposed for all located states on the basis of decay branchings and comparison with large-scale shell-model calculations performed in the p-sd space, with the YSOX interaction. Of particular interest is the location of the 0^-_1 and 1^-_2 excitations, which provide strong constrains for cross-shell p-sd matrix elements based on realistic interactions, and help to simultaneously reproduce the ground and first-excited states in 16N and 18N, for the first time. Understanding the 18N structure may also have significant impact on neutron-capture cross-section calculations in r-process modeling including light neutron-rich nuclei.

New transitions in neutron rich $^{100}$Y have been identified in a $^9$Be+$^{238}$U experiment with mass- and Z- gates to provide full fragment identification. These transitions and high spin levels of $^{100}$Y have been investigated by analyzing the high statistics $\gamma$-$\gamma$-$\gamma$ and $\gamma$-$\gamma$-$\gamma$-$\gamma$ coincidence data from the spontaneous fission of $^{252}$Cf at the Gammasphere detector array. Two new bands, 14 new levels and 23 new transitions have been identified. The $K^{\pi}=4^+$ new band decaying to an 1s isomeric state is assigned to be the high-$K$ Gallagher-Moszkowski (GM) partner of the known $K^{\pi}=1^+$ band, with the $\pi 5/2[522] \otimes \nu 3/2[411]$ configuration. This 4$^+$ band is also proposed to be the pseudo spin partner of the new $K^{\pi}=5^+$ band with a 5$^{+}$ $\pi 5/2[422] \otimes \nu 5/2[413]$ configuration, to form a $\pi 5/2[422] \otimes \nu [312$ $5/2,3/2]$ neutron pseudospin doublet. Constrained triaxial covariant density functional theory and quantal particle rotor model calculations have been applied to interpret the band structure and available electromagnetic transition probabilities and are found in good agreement with experimental values.

A novel Monte Carlo technique has been developed to determine lifetimes of excited states in the tens-to-hundreds femtoseconds range. The method is applied to low-energy heavy-ion binary reactions populating nuclei with complex velocity distributions. Its relevance is demonstrated in connection with the $^{18}$O(7.0 MeV/u) + $^{181}$Ta experiment, performed at GANIL with the AGATA+VAMOS+PARIS setup, to study neutron-rich O, C, N, ... nuclei. Excited states in $^{17}$O and $^{19}$O, with known lifetimes, are used to validate the method over the $\sim$20-400 fs lifetime-sensitivity range. Emphasis is given to the unprecedented position resolution provided by $\gamma$-tracking arrays, which turns out to be essential for reaching the required accuracy in Doppler-shift correction, at the basis of the detailed analysis of $\gamma$-ray lineshape and resulting state lifetime determination. The technique is anticipated to be an important tool for lifetime investigations in exotic neutron-rich nuclei, produced with intense ISOL-type beams.

The fusion and transfer induced fission reaction $^{9}$Be($^{238}$U,~f) with 6.2 MeV/u beam energy, using a unique setup consisting of AGATA, VAMOS++ and EXOGAM detectors, was used to populate through the fission process and study the neutron-rich $^{119,121}$In isotopes. This setup enabled the prompt-delayed $\gamma$-ray spectroscopy of isotopes in the time range of $100~\rm{ns} - 200~\mu\rm{s}$. In the odd-$A$ $^{119,121}$In isotopes, indications of a short half-life $19/2^{-}$ isomeric state, in addition to the previously known $25/2^{+}$ isomeric state, were observed from the present data. Further, new prompt transitions above the $25/2^{+}$ isomer in $^{121}$In were identified along with reevaluation of its half-life. The experimental data were compared with the theoretical results obtained in the framework of large-scale shell-model calculations in a restricted model space. The $\langle \pi g_{9/2} \nu h_{11/2};I \arrowvert \hat{\mathcal{H}}\arrowvert \pi g_{9/2} \nu h_{11/2};I\rangle$ two-body matrix elements of residual interaction were modified to explain the excitation energies and the $B(E2)$ transition probabilities in the neutron-rich In isotopes. The (i) decreasing trend of $E(29/2^{+}) - E(25/2^{+})$ in odd-In (with dominant configuration $\pi g_{9/2}^{-1}\nu h_{11/2}^{-2}$ and maximum aligned spin of $29/2^{+}$) and (ii) increasing trend of $E(27/2^{+}) - E(23/2^{+})$ in odd-Sb (with dominant configuration $\pi g_{7/2}^{+1}\nu h_{11/2}^{-2}$ and maximum aligned spin of $27/2^{+}$) with increasing neutron number could be understood as a consequence of hole-hole and particle-hole interactions, respectively., Comment: Accepted for publication in Phys. Rev. C

Large spin Hall angles have been observed in 3d ferromagnets, but their origin, and especially their link with the ferromagnetic order, remain unclear. Here, we investigate the inverse spin Hall effect of Ni60Cu40 and Ni50Cu50 across their Curie temperature using spin pumping experiments. We evidence that the inverse spin Hall effect in these samples is comparable to that of platinum, and that it is insensitive to the magnetic order. These results points towards a Heisenberg localized model of the transition, and suggest that the large spin Hall effects in 3d ferromagnets can be independent of the magnetic phase., Comment: 3 figures

The simultaneous measurement of the isotopic fission-fragment yields and fission-fragment velocities of $^{239}$U has been performed for the first time. The $^{239}$U fissioning system was produced in one-neutron transfer reactions between a $^{238}$U beam at 5.88 MeV/nucleon and a $^{9}$Be target. The combination of inverse kinematics at low energy and the use of the VAMOS++ spectrometer at the GANIL facility allows the isotopic identification of the full fission-fragment distribution and their velocity in the reference frame of the fissioning system. The proton and neutron content of the fragments at scission, their total kinetic and total excitation energy, as well as the neutron multiplicity were determined. Information from the scission point configuration is obtained from these observables and the correlation between them. The role of the octupole-deformed proton and neutron shells in the fission-fragment production is discussed., Comment: 8 pages, 7 figures

Load aggregators are independent private entities whose goal is to optimize energy consumption flexibilities offered by multiple residential consumers. Although aggregators optimize their decisions in a decentralized way, they are indirectly linked together if their respective consumers belong to the same distribution grid. This is an important issue for a distribution system operator (DSO), in charge of the reliability of the distribution network, it has to ensure that decentralized decisions taken do not violate the grid constraints and do not increase the global system costs. From the information point of view,the network state and characteristics are confidential to the DSO, which makes a decentralized solution even more relevant. To address this issue, we propose a decentralized coordination mechanism between the DSO and multiple aggregators that computes the optimal demand response profiles while solving the optimal power flow problem. The procedure, based on distribution locational marginal prices (DLMP), preserves the decentralized structure of information and decisions, and lead to a feasible and optimal solution for both the aggregators and the DSO. The procedure is analyzed from a mechanism design perspective, and different decentralized methods that could be used to implement this procedure are presented., Comment: 25pages. Update theoretical proof of convergence of primal-dual Gauss-Seidel iterative algo, add a Mechanism design discussion over the proposed DLMP-based mechanism; add numerical results for ADMM and primal-dual GS convergence

Deep Learning has driven recent and exciting progress in computer vision, instilling the belief that these algorithms could solve any visual task. Yet, datasets commonly used to train and test computer vision algorithms have pervasive confounding factors. Such biases make it difficult to truly estimate the performance of those algorithms and how well computer vision models can extrapolate outside the distribution in which they were trained. In this work, we propose a new action classification challenge that is performed well by humans, but poorly by state-of-the-art Deep Learning models. As a proof-of-principle, we consider three exemplary tasks: drinking, reading, and sitting. The best accuracies reached using state-of-the-art computer vision models were 61.7%, 62.8%, and 76.8%, respectively, while human participants scored above 90% accuracy on the three tasks. We propose a rigorous method to reduce confounds when creating datasets, and when comparing human versus computer vision performance. Source code and datasets are publicly available., Comment: poster at CVPR 2020, includes supplementary figures

A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems have recently implemented some or all of these operations, yet the focus was placed on addressing technological challenges. Fundamental questions regarding learning in hardware neural networks remain largely unexplored. Noise in particular is unavoidable in such architectures, and here we investigate its interaction with a learning algorithm using an opto-electronic recurrent neural network. We find that noise strongly modifies the system's path during convergence, and surprisingly fully decorrelates the final readout weight matrices. This highlights the importance of understanding architecture, noise and learning algorithm as interacting players, and therefore identifies the need for mathematical tools for noisy, analogue system optimization., Comment: 8 pages, 5 figures

To test the predictive power of ab initio nuclear structure theory, the lifetime of the second 2+ state in neutron-rich 20O, tau(2+_2 ) = 150(+80-30) fs, and an estimate for the lifetime of the second 2+ state in 16C have been obtained, for the first time. The results were achieved via a novel Monte Carlo technique that allowed us to measure nuclear state lifetimes in the tens-to-hundreds femtoseconds range, by analyzing the Doppler-shifted gamma-transition line shapes of products of low-energy transfer and deep-inelastic processes in the reaction 18O (7.0 MeV/u) + 181Ta. The requested sensitivity could only be reached owing to the excellent performances of the AGATA gamma-tracking array, coupled to the PARIS scintillator array and to the VAMOS++ magnetic spectrometer. The experimental lifetimes agree with predictions of ab initio calculations using two- and three-nucleon interactions, obtained with the valence-space in-medium similarity renormalization group for 20O, and with the no-core shell model for 16C. The present measurement shows the power of electromagnetic observables, determined with high-precision gamma spectroscopy, to assess the quality of first-principles nuclear structure calculations, complementing common benchmarks based on nuclear energies. The proposed experimental approach will be essential for short lifetimes measurements in unexplored regions of the nuclear chart, including r-process nuclei, when intense ISOL-type beams become available.

Photonic waveguides are prime candidates for integrated and parallel photonic interconnects. Such interconnects correspond to large-scale vector matrix products, which are at the heart of neural network computation. However, parallel interconnect circuits realized in two dimensions, for example by lithography, are strongly limited in size due to disadvantageous scaling. We use three dimensional (3D) printed photonic waveguides to overcome this limitation. 3D optical-couplers with fractal topology efficiently connect large numbers of input and output channels, and we show that the substrate's footprint area scales linearly. Going beyond simple couplers, we introduce functional circuits for discrete spatial filters identical to those used in deep convolutional neural networks., Comment: 7 pages, 6 figures

High electronic excitations in radiation of metallic targets with swift heavy ion beams at the coulomb barrier play a dominant role in the damaging processes of some metals. The inelastic thermal spike model was developed to describe tracks in materials and is applied in this paper to some systems beams/targets employed recently in some nuclear physics experiments. Taking into account the experimental conditions and the approved electron-phonon coupling factors, the results of the calculation enable to interpret the observation of the fast deformation of some targets.

Aggregative games have many industrial applications, and computing an equilibrium in those games is challenging when the number of players is large. In the framework of atomic aggregative games with coupling constraints, we show that variational Nash equilibria of a large aggregative game can be approximated by a Wardrop equilibrium of an auxiliary population game of smaller dimension. Each population of this auxiliary game corresponds to a group of atomic players of the initial large game. This approach enables an efficient computation of an approximated equilibrium, as the variational inequality characterizing the Wardrop equilibrium is of smaller dimension than the initial one. This is illustrated on an example in the smart grid context., Comment: arXiv admin note: substantial text overlap with arXiv:1810.01436

The concepts of Fourier optics were established in France in the 1940s by Pierre-Michel Duffieux, and laid the foundations of an extensive series of activities in the French research community that have touched on nearly every aspect of contemporary optics and photonics. In this paper, we review a selection of results where applications of the Fourier transform and transfer functions in optics have been applied to yield significant advances in unexpected areas of optics, including the spatial shaping of complex laser beams in amplitude and in phase, real-time ultrafast measurements, novel ghost imaging techniques, and the development of parallel processing methodologies for photonic artificial intelligence.

A direct and complete measurement of isotopic fission-fragment yields of $^{239}$U has been performed for the first time. The $^{239}$U fissioning system was produced with an average excitation energy of 8.3 MeV in one-neutron transfer reactions between a $^{238}$U beam and a $^{9}$Be target at Coulomb barrier energies. The fission fragments were detected and isotopically identified using the VAMOS++ spectrometer at the GANIL facility. This measurement allows to directly evaluate the fission models at excitation energies of fast neutrons, relevant for next-generation nuclear reactors. The present data, in agreement with model calculations, do not support the recently reported anomaly in the fission-fragment yields of $^{239}$U and confirm the persistence of spherical shell effects in the Sn region at excitation energies exceeding the fission barrier by few MeV.

When spin relaxation is governed by spontaneous emission of a photon into the resonator used for signal detection (the Purcell effect), the relaxation time $T_1$ depends on the spin-resonator frequency detuning $\delta$ and coupling constant $g$. We analyze the consequences of this unusual dependence for the amplitude and temporal shape of a spin-echo in a number of different experimental situations. When the coupling $g$ is distributed inhomogeneously, we find that the effective spin-echo relaxation time measured in a saturation recovery sequence strongly depends on the parameters of the detection echo. When the spin linewidth is larger than the resonator bandwidth, the Fourier components of the echo relax with different characteristic times, which implies that the temporal shape of the echo becomes dependent on the repetition time of the experiment. We provide experimental evidence of these effects with an ensemble of donor spins in silicon at millikelvin temperatures measured by a superconducting micro-resonator., Comment: 10 pages, 8 figures

We consider a resource allocation problem involving a large number of agents with individual constraints subject to privacy, and a central operator whose objective is to optimize a global, possibly nonconvex, cost while satisfying the agents' constraints, for instance an energy operator in charge of the management of energy consumption flexibilities of many individual consumers. We provide a privacy-preserving algorithm that does compute the optimal allocation of resources, avoiding each agent to reveal her private information (constraints and individual solution profile) neither to the central operator nor to a third party. Our method relies on an aggregation procedure: we compute iteratively a global allocation of resources, and gradually ensure existence of a disaggregation, that is individual profiles satisfying agents' private constraints, by a protocol involving the generation of polyhedral cuts and secure multiparty computations (SMC). To obtain these cuts, we use an alternate projection method, which is implemented locally by each agent, preserving her privacy needs. We adress especially the case in which the local and global constraints define a transportation polytope. Then, we provide theoretical convergence estimates together with numerical results, showing that the algorithm can be effectively used to solve the allocation problem in high dimension, while addressing privacy issues., Comment: 35 pages, revised version accepted for publication in SIAM journal on Optimization (SIOPT)

The implementation of artificial neural networks in hardware substrates is a major interdisciplinary enterprise. Well suited candidates for physical implementations must combine nonlinear neurons with dedicated and efficient hardware solutions for both connectivity and training. Reservoir computing addresses the problems related with the network connectivity and training in an elegant and efficient way. However, important questions regarding impact of reservoir size and learning routines on the convergence-speed during learning remain unaddressed. Here, we study in detail the learning process of a recently demonstrated photonic neural network based on a reservoir. We use a greedy algorithm to train our neural network for the task of chaotic signals prediction and analyze the learning-error landscape. Our results unveil fundamental properties of the system's optimization hyperspace. Particularly, we determine the convergence speed of learning as a function of reservoir size and find exceptional, close to linear scaling. This linear dependence, together with our parallel diffractive coupling, represent optimal scaling conditions for our photonic neural network scheme.

We study and analyze the fundamental aspects of noise propagation in recurrent as well as deep, multi-layer networks. The main focus of our study are neural networks in analogue hardware, yet the methodology provides insight for networks in general. The system under study consists of noisy linear nodes, and we investigate the signal-to-noise ratio at the network's outputs which is the upper limit to such a system's computing accuracy. We consider additive and multiplicative noise which can be purely local as well as correlated across populations of neurons. This covers the chief internal-perturbations of hardware networks and noise amplitudes were obtained from a physically implemented recurrent neural network and therefore correspond to a real-world system. Analytic solutions agree exceptionally well with numerical data, enabling clear identification of the most critical components and aspects for noise management. Focusing on linear nodes isolates the impact of network connections and allows us to derive strategies for mitigating noise. Our work is the starting point in addressing this aspect of analogue neural networks, and our results identify notoriously sensitive points while simultaneously highlighting the robustness of such computational systems.

Photonic networks are considered a promising substrate for high-performance future computing systems. Compared to electronics, photonics has significant advantages for a fully parallel implementation of networks. A promising approach for parallel large-scale photonic networks is realizing the connections using diffraction. Here, we characterize the scalability of such diffractive coupling in great detail. Based on experiments, analytically obtained bounds and numerical simulations considering real-world optical imaging setups, we find that the concept in principle enables networks hosting over a million optical emitters. This would be a breakthrough in multiple areas, illustrating a clear path toward future, large scale photonic networks.

The magnetic order associated with the degree of freedom of spin in two-dimensional (2D) materials is subjected to intense investigation because of its potential application in 2D spintronics and valley-related magnetic phenomena. We report here a bottom-up strategy using molecular beam epitaxy to grow and dope large-area (cm$^2$) few-layer MoSe$_2$ with Mn as a magnetic dopant. High-quality Mn-doped MoSe$_2$ layers are obtained for Mn content of less than 5 % (atomic). When increasing the Mn content above 5 % we observe a clear transition from layer-by-layer to cluster growth. Magnetic measurements involving a transfer process of the cm$^2$-large doped layers on 100-micron-thick silicon substrate, show plausible proof of high-temperature ferromagnetism of 1 % and 10 % Mn-doped MoSe$_2$. Although we could not point to a correlation between magnetic and electrical properties, we demonstrate that the transfer process described in this report permits to achieve conventional electrical and magnetic measurements on the doped layers transferred on any substrate. Therefore, this study provides a promising route to characterize stable ferromagnetic 2D layers, which is broadening the current start-of-the-art of 2D materials-based applications., Comment: 18 pages and 5 figures