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This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dataset has unique properties that are uncommon to current benchmarks for 2D and 3D puzzle solving. The fragments and fractures are realistic, caused by a collapse of a fresco during a World War II bombing at the Pompeii archaeological park. The fragments are also eroded and have missing pieces with irregular shapes and different dimensions, challenging further the reassembly algorithms. The dataset is multi-modal providing high resolution images with characteristic pictorial elements, detailed 3D scans of the fragments and meta-data annotated by the archaeologists. Ground truth has been generated through several years of unceasing fieldwork, including the excavation and cleaning of each fragment, followed by manual puzzle solving by archaeologists of a subset of approx. 1000 pieces among the 16000 available. After digitizing all the fragments in 3D, a benchmark was prepared to challenge current reassembly and puzzle-solving methods that often solve more simplistic synthetic scenarios. The tested baselines show that there clearly exists a gap to fill in solving this computationally complex problem., Comment: NeurIPS 2024, Track Datasets and Benchmarks, 10 pages

Photo-realistic image restoration algorithms are typically evaluated by distortion measures (e.g., PSNR, SSIM) and by perceptual quality measures (e.g., FID, NIQE), where the desire is to attain the lowest possible distortion without compromising on perceptual quality. To achieve this goal, current methods typically attempt to sample from the posterior distribution, or to optimize a weighted sum of a distortion loss (e.g., MSE) and a perceptual quality loss (e.g., GAN). Unlike previous works, this paper is concerned specifically with the optimal estimator that minimizes the MSE under a constraint of perfect perceptual index, namely where the distribution of the reconstructed images is equal to that of the ground-truth ones. A recent theoretical result shows that such an estimator can be constructed by optimally transporting the posterior mean prediction (MMSE estimate) to the distribution of the ground-truth images. Inspired by this result, we introduce Posterior-Mean Rectified Flow (PMRF), a simple yet highly effective algorithm that approximates this optimal estimator. In particular, PMRF first predicts the posterior mean, and then transports the result to a high-quality image using a rectified flow model that approximates the desired optimal transport map. We investigate the theoretical utility of PMRF and demonstrate that it consistently outperforms previous methods on a variety of image restoration tasks.

The potential of circulating antideuterons ($\mathrm{\overline{d}}$) in the AD/ELENA facility at CERN is currently under investigation. Approximately 100 $\mathrm{\overline{d}}$ per bunch could be delivered as a $100\,\mathrm{keV}$ beam based on measured cross-sections. These $\mathrm{\overline{d}}$ could be further decelerated to $12\,\mathrm{keV}$ using the GBAR scheme, enabling the synthesis of antideuterium ($\mathrm{\overline{D}}$) via charge exchange with positronium, a technique demonstrated with $6\,\mathrm{keV}$ antiprotons for antihydrogen production. While this would demonstrate the production of low-energy $\mathrm{\overline{D}}$, higher fluxes are required to facilitate spectroscopic studies. We propose enhancing the anti-atom production by using laser-excited positronium in the $2P$ state within a cavity, which is expected to increase the $\mathrm{\overline{D}}(2S)$ production cross-section by almost an order of magnitude for $\mathrm{\overline{d}}$ with $2\,\mathrm{keV}$ energy. The ELENA team is currently studying the possibility of increasing the $\mathrm{\overline{d}}$ rate using an optimized new target geometry. We present the projected precision for measuring the antideuterium Lamb shift and extracting the antideuteron charge radius, as a function of the beam flux.

In muonic bound systems, the dominant radiative correction is due to vacuum polarization. Yet, for the interpretation of precision experiments, self-energy effects are also important. In turn, additional vacuum-polarization loops perturb the self-energy. Here, we show that combined self-energy vacuum-polarization effects can perturb the bound-state self-energy at the percent level in one-muon bound systems with nuclear charges Z = 1-6. We also update previous treatments of the corrections for muonic hydrogen, muonic deuterium, and muonic helium bound systems., Comment: 11 pages; RevTeX

We present a review of absolute root-mean-square charge radii of stable nuclei up to $Z=32$, which includes a previously overlooked uncertainty in the combined analysis of muonic x-ray and electron scattering experiments. From these \textit{reference radii} and isotope shift measurements, we obtain those of 12 mirror pairs with a traceable and realistic uncertainty budget. The difference in radii between mirror nuclei is found to be proportional to the isospin asymmetry, confirming recent calculations by Novario \emph{et al.} [PRL~130, 032501]. From the fitted proportionality constant and its uncertainty, the radii of 73 previously unknown mirror partners are predicted. These are useful e.g. for benchmarking atomic and nuclear theory, calibrating entire chains, and as an input to nuclear beta-decay calculations. The radii of $(T=1,T_z=0)$ nuclei are interpolated assuming negligible isospin symmetry breaking. This completes a model-independent, high-precision extraction of the charge and weak radii of all nuclei involved in the testing of the unitarity of the CKM matrix.

The development of atomic many-body methods, capable of incorporating electron correlation effects accurately, is required for isotope shift (IS) studies. In combination with precise measurements, such calculations help to extract nuclear charge radii differences, and to probe for signatures of physics beyond the Standard Model of particle physics. We review here a few recently-developed methods in the relativistic many-body perturbation theory (RMBPT) and relativistic coupled-cluster (RCC) theory frameworks for calculations of IS factors in the highly charged ions (HCIs), and neutral or singly-charged ions, respectively. The results are presented for a wide range of atomic systems in order to demonstrate the interplay between quantum electrodynamics (QED) and electron correlation effects. In view of this, we start our discussions with the RMBPT calculations for a few HCIs by rigorously treating QED effects; then we outline methods to calculate IS factors in the one-valence atomic systems using two formulations of the RCC approach. Then we present calculations for two valence atomic systems, by employing the Fock-space RCC methods. For completeness, we briefly discuss theoretical input required for the upcoming experiments, their possibilities to probe nuclear properties and implications to fundamental physics studies., Comment: Topical Review Preprint for J. Phys. B, Comments and Suggestions are welcome!

Large Language Models (LLMs) have significantly advanced natural language processing (NLP), providing versatile capabilities across various applications. However, their application to complex, domain-specific tasks, such as cyber-security, often faces substantial challenges. In this study, we introduce SecKnowledge and CyberPal.AI to address these challenges and train security-expert LLMs. SecKnowledge is a domain-knowledge-driven cyber-security instruction dataset, meticulously designed using years of accumulated expert knowledge in the domain through a multi-phase generation process. CyberPal.AI refers to a family of LLMs fine-tuned using SecKnowledge, aimed at building security-specialized LLMs capable of answering and following complex security-related instructions. Additionally, we introduce SecKnowledge-Eval, a comprehensive and diverse cyber-security evaluation benchmark, composed of an extensive set of cyber-security tasks we specifically developed to assess LLMs in the field of cyber-security, along with other publicly available security benchmarks. Our results show a significant average improvement of up to 24% over the baseline models, underscoring the benefits of our expert-driven instruction dataset generation process. These findings contribute to the advancement of AI-based cyber-security applications, paving the way for security-expert LLMs that can enhance threat-hunting and investigation processes.

Fairness in image restoration tasks is the desire to treat different sub-groups of images equally well. Existing definitions of fairness in image restoration are highly restrictive. They consider a reconstruction to be a correct outcome for a group (e.g., women) only if it falls within the group's set of ground truth images (e.g., natural images of women); otherwise, it is considered entirely incorrect. Consequently, such definitions are prone to controversy, as errors in image restoration can manifest in various ways. In this work we offer an alternative approach towards fairness in image restoration, by considering the Group Perceptual Index (GPI), which we define as the statistical distance between the distribution of the group's ground truth images and the distribution of their reconstructions. We assess the fairness of an algorithm by comparing the GPI of different groups, and say that it achieves perfect Perceptual Fairness (PF) if the GPIs of all groups are identical. We motivate and theoretically study our new notion of fairness, draw its connection to previous ones, and demonstrate its utility on state-of-the-art face image restoration algorithms.

We introduce a novel methodology for identifying adversarial attacks on deepfake detectors using eXplainable Artificial Intelligence (XAI). In an era characterized by digital advancement, deepfakes have emerged as a potent tool, creating a demand for efficient detection systems. However, these systems are frequently targeted by adversarial attacks that inhibit their performance. We address this gap, developing a defensible deepfake detector by leveraging the power of XAI. The proposed methodology uses XAI to generate interpretability maps for a given method, providing explicit visualizations of decision-making factors within the AI models. We subsequently employ a pretrained feature extractor that processes both the input image and its corresponding XAI image. The feature embeddings extracted from this process are then used for training a simple yet effective classifier. Our approach contributes not only to the detection of deepfakes but also enhances the understanding of possible adversarial attacks, pinpointing potential vulnerabilities. Furthermore, this approach does not change the performance of the deepfake detector. The paper demonstrates promising results suggesting a potential pathway for future deepfake detection mechanisms. We believe this study will serve as a valuable contribution to the community, sparking much-needed discourse on safeguarding deepfake detectors., Comment: Accepted at TMLR 2024

Nuclear charge radius differences in the silver isotopic chain have been reported through different combinations of experiment and theory, exhibiting a tension of two combined standard errors. This study investigates this issue by combining high-accuracy calculations for six low-lying states of atomic silver with an improved measurement of the $5s ^2S_{1/2} - 5p ^2P_{3/2}$ transition optical isotope shift. Our calculations predict measured electronic transition energies in Ag I at the 0.3\% level, the highest accuracy achieved in this system so far. We calculate electronic isotope shift factors by employing analytical response relativistic coupled-cluster theory, and find that a consistent charge radius difference between $^{107,109}$Ag is returned when combining our calculations with the available optical isotope shift measurements. We therefore recommend an improved value for the mean-squared charge radius difference between $^{107}$Ag and $^{109}$Ag as $0.207(3)[4]$ fm$^2$, within one combined error from the value derived from muonic Ag experiments, and an updated set of charge radii differences across the isotopic chain.

The QUARTET collaboration aims to significantly improve the precision of the absolute nuclear charge radii of light nuclei from Li to Ne by using an array of metallic magnetic calorimeters to perform high-precision X-ray spectroscopy of low-lying states in muonic atoms. A proof-of-principle measurement with lithium, beryllium and boron is planned for fall 2023 at the Paul Scherrer Institute. We discuss the performance achieved with the maXs-30 detector module to be used. To place the detector close to the target chamber where the muon beam will impact the material under study, we have developed a new dilution refrigerator sidearm. We further discuss the expected efficiency given the transparency of the X-ray windows and the quantum efficiency of the detector. The expected muonic X-ray rate combined with the high resolving power and detection efficiency of the detector suggest that QUARTET will be able to study the de-excitation of light muonic atoms at an unprecedented level, increasing the relative energy resolution by up to a factor of 20 compared to conventional detector techniques.

We study the behavior of deterministic methods for solving inverse problems in imaging. These methods are commonly designed to achieve two goals: (1) attaining high perceptual quality, and (2) generating reconstructions that are consistent with the measurements. We provide a rigorous proof that the better a predictor satisfies these two requirements, the larger its Lipschitz constant must be, regardless of the nature of the degradation involved. In particular, to approach perfect perceptual quality and perfect consistency, the Lipschitz constant of the model must grow to infinity. This implies that such methods are necessarily more susceptible to adversarial attacks. We demonstrate our theory on single image super-resolution algorithms, addressing both noisy and noiseless settings. We also show how this undesired behavior can be leveraged to explore the posterior distribution, thereby allowing the deterministic model to imitate stochastic methods.

We propose an experiment to measure the nuclear charge radii of light elements with up to 20~times higher accuracy. These are essential both for understanding nuclear physics at low energies, and for experimental and theoretical applications in simple atomic systems. Such comparisons advance the understanding of bound-state quantum electrodynamics and are useful for searching for new physics beyond the Standard Model. The energy levels of muonic atoms are highly susceptible to nuclear structure, especially to the mean square charge radius. The radii of the lightest nuclei (with the atomic number, $Z=1,2$) have been determined with high accuracy using laser spectroscopy in muonic atoms, while those of medium mass and above were determined using X-ray spectroscopy with semiconductor detectors. In this communication, we present a new experiment, aiming to obtain precision measurements of the radii of light nuclei $3 \leq Z \leq 10$ using single-photon energy measurements with cryogenic microcalorimeters; a quantum-sensing technology capable of high efficiency with outstanding resolution for low-energy X-rays.

We report absolute frequency, isotope shift, radiative lifetime and hyperfine structure measurements of the $^1P_1 \leftarrow{} ^{1}S_0$ (213.8 nm) transition in Zn I using a cryogenic buffer gas beam. Laser-induced fluorescence is collected with two orthogonally oriented detectors to take advantage of differences in the emission pattern of the isotopes. This enables clear distinction between isotopes whose resonances are otherwise unresolved, and a measurement of the fermion hyperfine structure parameters, $A(^{67}$Zn)$=20(2)$ MHz and $B(^{67}$Zn)$=10(5)$ MHz. We reference our frequency measurements to an ultralow expansion cavity and achieve an uncertainty at the level of 1 MHz, about 1 percent of the natural linewidth of the transition., Comment: 5 figures, 9 pages

We conduct high-accuracy calculations of isotope shift (IS) factors of the states involving the $D_1$ and $D_2$ lines in Zn II. Together with a global fit to the available optical IS data, we extract nuclear-model-independent, precise differential radii for a long chain of Zn isotopes. These radii are compared with the ones inferred from muonic X-ray measurements. Some deviations are found, which we ascribe to the deformed nature of Zn nuclei that introduces nuclear-model dependency into radii extractions from muonic atoms. We arrive at the conclusion that in cases where the many-body atomic calculations of IS factors are well-established, optical determinations of differential radii are more reliable than those extracted from the muonic X-ray measurements, opening the door to improved determination of nuclear radii across the nuclear chart.

We report on the first production of an antihydrogen beam by charge exchange of 6.1 keV antiprotons with a cloud of positronium in the GBAR experiment at CERN. The antiproton beam was delivered by the AD/ELENA facility. The positronium target was produced from a positron beam itself obtained from an electron linear accelerator. We observe an excess over background indicating antihydrogen production with a significance of 3-4 standard deviations.

We propose an image restoration algorithm that can control the perceptual quality and/or the mean square error (MSE) of any pre-trained model, trading one over the other at test time. Our algorithm is few-shot: Given about a dozen images restored by the model, it can significantly improve the perceptual quality and/or the MSE of the model for newly restored images without further training. Our approach is motivated by a recent theoretical result that links between the minimum MSE (MMSE) predictor and the predictor that minimizes the MSE under a perfect perceptual quality constraint. Specifically, it has been shown that the latter can be obtained by optimally transporting the output of the former, such that its distribution matches the source data. Thus, to improve the perceptual quality of a predictor that was originally trained to minimize MSE, we approximate the optimal transport by a linear transformation in the latent space of a variational auto-encoder, which we compute in closed-form using empirical means and covariances. Going beyond the theory, we find that applying the same procedure on models that were initially trained to achieve high perceptual quality, typically improves their perceptual quality even further. And by interpolating the results with the original output of the model, we can improve their MSE on the expense of perceptual quality. We illustrate our method on a variety of degradations applied to general content images of arbitrary dimensions.

Conjugated polymer films that can conduct ionic and electronic charges are central to building soft electronic sensors and actuators. Despite the possible interplay between light absorption and mixed conductivity of these materials in aqueous biological media, no polymer film has ever been used to realize a solar-switchable organic bioelectronic circuit relying on a fully reversible, redox reaction-free mechanism. Here we show that light absorbed by an electron and cation-transporting polymer film reversibly modulates its electrochemical potential and conductivity in an aqueous electrolyte, leveraged to design an n-type photo-electrochemical transistor (n-OPECT). We generate transistor output characteristics by solely varying the intensity of light that hits the n-type polymeric gate electrode, emulating the gate voltage-controlled modulation of the polymeric channel current. The micron-scale n-OPECT shows a high signal-to-noise ratio and an excellent sensitivity to low light intensities. We demonstrate three direct applications of the n-OPECT, i.e., a photoplethysmogram recorder, a light-controller inverter circuit, and a light-gated artificial synapse, underscoring the suitability of this platform for a myriad of biomedical applications that involve light intensity changes.

We present a novel technique for in-vacuum cavity-enhanced UV spectroscopy that allows nearly continuous measurements over several days, minimizing mirror degradation caused by high-power UV radiation. Our method relies on pulsing of the cavity's internal power, which increases the UV intensity to maximum only for short periods when the studied atom is within the cavity mode volume while keeping the average power low to prevent mirror degradation. Additionally, this method significantly decreases laser-induced background on charged particle detectors. The described 244 nm laser system is designed for 1S-2S two-photon CW spectroscopy of muonium in the Mu-MASS project. It was tested to provide intracavity powers above 20 W, requiring maintenance only a few times a day. The pulsing technique demonstrates minimal impact on the radiation frequency, with no observed shifts exceeding 15 kHz. Our approach represents a promising new technique for high-precision spectroscopy of atoms in harsh UV environments and demonstrates the feasibility of CW spectroscopy of muonium., Comment: 10 pages, 5 figures

We present an updated value of the Muonium 1S-2S transition frequency, highlighting contributions from different QED corrections as well as the large uncertainty in the Dirac contribution, stemming from the uncertainty of the electron-to-muon mass ratio. Improving the measurement of this spectral line would allow to extract a more accurate determination of fundamental constants, such as the electron-to-muon mass ratio or, combined with the Muonium hyperfine splitting, an independent value of the Rydberg constant. Furthermore we report on the current status of the Mu-MASS experiment, which aims at measuring the Muonium 1S-2S transition frequency at a 10 kHz uncertainty level., Comment: 6 pages, 1 figure, prepared for PSAS22 proceedings

JPEG is arguably the most popular image coding format, achieving high compression ratios via lossy quantization that may create visual artifacts degradation. Numerous attempts to remove these artifacts were conceived over the years, and common to most of these is the use of deterministic post-processing algorithms that optimize some distortion measure (e.g., PSNR, SSIM). In this paper we propose a different paradigm for JPEG artifact correction: Our method is stochastic, and the objective we target is high perceptual quality -- striving to obtain sharp, detailed and visually pleasing reconstructed images, while being consistent with the compressed input. These goals are achieved by training a stochastic conditional generator (conditioned on the compressed input), accompanied by a theoretically well-founded loss term, resulting in a sampler from the posterior distribution. Our solution offers a diverse set of plausible and fast reconstructions for a given input with perfect consistency. We demonstrate our scheme's unique properties and its superiority to a variety of alternative methods on the FFHQ and ImageNet datasets., Comment: Presented in NTIRE workshop as part of CVPR 2023

Stochastic restoration algorithms allow to explore the space of solutions that correspond to the degraded input. In this paper we reveal additional fundamental advantages of stochastic methods over deterministic ones, which further motivate their use. First, we prove that any restoration algorithm that attains perfect perceptual quality and whose outputs are consistent with the input must be a posterior sampler, and is thus required to be stochastic. Second, we illustrate that while deterministic restoration algorithms may attain high perceptual quality, this can be achieved only by filling up the space of all possible source images using an extremely sensitive mapping, which makes them highly vulnerable to adversarial attacks. Indeed, we show that enforcing deterministic models to be robust to such attacks profoundly hinders their perceptual quality, while robustifying stochastic models hardly influences their perceptual quality, and improves their output variability. These findings provide a motivation to foster progress in stochastic restoration methods, paving the way to better recovery algorithms.

Recent progress in laser and x-ray spectroscopy of muonic atoms offers promising long-term possibilities at the intersection of atomic, nuclear and particle physics. In muonic hydrogen, laser spectroscopy measurements will determine the ground-state hyperfine splitting (HFS) and additionally improve the Lamb shift by a factor of 5. Precision spectroscopy with cryogenic microcalorimeters has the potential to significantly improve the charge radii of the light nuclei in the $Z=3-8$ range. Complementary progress in precision should be achieved on the theory of nucleon- and nuclear-structure effects. The impact of this muonic-atom spectroscopy program will be amplified by the upcoming results from H and He$^+$ spectroscopy, simple molecules such as HD$^+$ and Penning trap measurements. In this broader context, one can test ab-initio nuclear theories, bound-state QED for two- or three-body systems, and determine fundamental constants, such as the Rydberg ($R_\infty$) and the fine-structure ($\alpha$) constants., Comment: 8 pages, 2 figures, submitted as community input for the NuPECC Long Range Plan 2024 (https://indico.ph.tum.de/event/7050/)

We present absolute frequency measurements of the ${}^{1}\text{P}_1 \leftarrow {}^{1}\text{S}_0$ ($229$nm) and ${}^{3}\text{P}_1 \leftarrow {}^{1}\text{S}_0$ ($326$nm) transitions for all naturally occurring isotopes of cadmium. The isotope shifts and hyperfine intervals of the fermionic isotopes are determined with an accuracy of 3.3MHz. We find that quantum interference in the laser-induced fluorescence spectra of the ${}^{1}\text{P}_1 \leftarrow {}^{1}\text{S}_0$ transition causes an error of up to 29(5)MHz in determining the hyperfine splitting, when not accounted for with an appropriate model. Using a King-plot analysis, we extract the field- and mass-shift parameters and determine nuclear charge radius differences for the fermions. The lifetime of the $^1\text{P}_1$ state is determined to be 1.60(5)ns by measuring the natural linewidth of the ${}^{1}\text{P}_1 \leftarrow {}^{1}\text{S}_0$ transition. These results resolve significant discrepancies among previous measurements.

Isotope shifts (ISs) in atomic energy levels are sensitive probes of nuclear structure and new physics beyond the Standard Model. We present an analysis of the ISs of the cadmium atom (Cd I) and singly charged cadmium ion (Cd II). ISs of the 229 nm, 326 nm, 361 nm and 480 nm lines of Cd I are measured with a variety of techniques; buffer-gas-cooled beam spectroscopy, capturing atoms in a magneto-optic-trap, and optical pumping. IS constants for the D1 and D2 lines of Cd II are calculated with high accuracy by employing analytical response relativistic coupled-cluster theory in the singles, doubles and triples approximations. Combining the calculations for Cd II with experiments, we infer IS constants for all low-lying transitions in Cd I. We benchmark these constants as calculated via different many-body methods. Our calculations for Cd II enable nuclear charge radii of Cd isotopes to be extracted with unprecedented accuracy. The combination of our precise calculations and measurements shows that King Plots for Cd I can improve the state-of-theart sensitivity to a new heavy boson by up to two orders of magnitude.