Search

The half-life of $^{39}$Ar is measured using the DEAP-3600 detector located 2 km underground at SNOLAB. In 2016-2020, DEAP-3600 used a target mass of (3269 $\pm$ 24) kg of liquid argon distilled from the atmosphere in a direct-detection dark matter search. Such an argon mass also enables direct measurements of argon isotope properties. The decay of $^{39}$Ar in DEAP-3600 is the dominant source of triggers by two orders of magnitude, ensuring high statistics and making DEAP-3600 well-suited for measuring this isotope's half-life. Use of the pulse-shape discrimination technique in DEAP-3600 allows for powerful discrimination between nuclear recoils and electron recoils, resulting in the selection of a clean sample of $^{39}$Ar decays. Observing over a period of 3.4 years, the $^{39}$Ar half-life is measured to be $(302 \pm 8_{\rm stat} \pm 6_{\rm sys})$ years. This new direct measurement suggests that the half-life of $^{39}$Ar may be significantly longer than the accepted value, with potential implications for measurements using this isotope's half-life as input., Comment: 11 pages, 8 figures

We present results for the dominant light-quark connected contribution to the long-distance window (LD) of the hadronic vacuum polarization contribution (HVP) to the muon $g-2$ from lattice quantum chromodynamics (QCD). Specifically, with a new determination of the lattice scale on MILC's physical-mass HISQ ensembles, using the $\Omega^-$ baryon mass, we obtain a result of $a^{ll,\,{\mathrm{LD}}}_{\mu}(\mathrm{conn.}) = 401.2(2.3)_{\mathrm{stat}}(3.6)_{\mathrm{syst}}[4.3]_{\mathrm{total}} \times 10^{-10}$. In addition, following up on our recent work on the short- (SD) and intermediate-distance (W) windows, we report updated values for these quantities with this new scale-setting determination. Summing these individual window contributions enables a sub-percent precision determination of the light-quark-connected contribution to HVP of $a^{ll}_{\mu}(\mathrm{conn.}) = 656.2(1.9)_{\mathrm{stat}}(4.0)_{\mathrm{syst}}[4.4]_{\mathrm{total}} \times 10^{-10}$. Finally, as a consistency check, we verify that an independent analysis of the full contribution is in agreement with the sum of individual windows. We discuss our future plans for improvements of our HVP calculations to meet the target precision of the Fermilab $g-2$ experiment., Comment: arXiv admin note: text overlap with arXiv:2411.09656

Ring resonators are crucial in silicon photonics for various applications, but conventional designs face performance trade-offs. Here a third-order polynomial interconnected circular (TOPIC) bend is proposed to revolutionize the ring designs fundamentally. The TOPIC bend has a unique feature of continuous curvature and curvature derivative, which is theoretically derived to be essential for waveguide loss optimization. With the TOPIC bend, the silicon ring resonators demonstrated here have achieved three records to the best of our knowledge: the smallest radius (0.7 $\mathrm{\mu m}$) for silicon rings resonating with single guided mode, the lowest thermal tuning power (5.85 mW/$\pi$) for silicon rings with FSR $\geq$3.2 THz, and the first silicon ring-based WDM 32$\times$100 GHz filter. The filter has doubled the channel amount compared to the state of the art, and meanwhile achieved low insertion loss (1.91 $\pm$ 0.28 dB) and low tuning power (283 GHz/mW). Moreover, the TOPIC bend is not limited to ring applications, it can also be used to create bends with an arbitrary angle, with the advantages of ultra-compact radius and heater integration, which are expected to replace all circular bends in integrated photonics, greatly reducing system size and power consumption.

We present complete results for the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment $a_\mu$ in the short- and intermediate-distance window regions, which account for roughly 10% and 35% of the total HVP contribution to $a_\mu$, respectively. In particular, we perform lattice-QCD calculations for the isospin-symmetric connected and disconnected contributions, as well as corrections due to strong isospin-breaking. For the short-distance window observables, we investigate the so-called log-enhancement effects as well as the significant oscillations associated with staggered quarks in this region. For the dominant, isospin-symmetric light-quark connected contribution, we obtain $a^{ll,\,{\mathrm{SD}}}_{\mu}(\mathrm{conn.}) = 48.116(16)(94)[96] \times 10^{-10}$ and $a^{ll,\,{\mathrm{W}}}_{\mu}(\mathrm{conn.}) = 207.06(17)(63)[66] \times 10^{-10}$. We use Bayesian model averaging combined with a global bootstrap to fully estimate the covariance matrix between the individual contributions. Our determinations of the complete window contributions are $a^{{\mathrm{SD}}}_{\mu} = 69.01(2)(21)[21] \times 10^{-10}$ and $a^{{\mathrm{W}}}_{\mu} = 236.57(20)(94)[96] \times 10^{-10}$. This work is part of our ongoing effort to compute all contributions to HVP with an overall uncertainty at the few permille level.

We calculate the decay rate for $\eta_b \to \gamma \gamma$ in lattice QCD for the first time, providing a precise prediction for the Belle II experiment. Our calculation includes $u$, $d$, $s$ and $c$ quarks in the sea, using gluon field configurations generated by the MILC collaboration, at three values of the lattice spacing from $0.06\;\mathrm{fm}$ to $0.03\;\mathrm{fm}$. All quarks are treated in the Highly Improved Staggered Quark formalism, which enables us to reach the $b$ quark mass for our valence quarks on these fine lattices. By working at additional heavy quark masses between those of $c$ and $b$ we also map out the behaviour of the ratio $f_{\eta_h}/(M_{\eta_h}^2F_{\eta_h}(0,0))$, where $f$ is the decay constant, $M$, the mass and $F(0,0)$, the form factor for decay to two on-shell photons for the pseudoscalar heavyonium meson, $\eta_h$. This ratio takes the approximate value 0.5 in leading-order non-relativistic QCD but we are able to give a much more accurate analysis than this. Focussing on the $b$ quark mass, we find a ratio of $0.468(11)$, giving $\Gamma (\eta_b \to \gamma \gamma) = 0.557(32)_{\text{fit}}(1)_{\text{syst}} \: \mathrm{keV}$. Combined with a value for the branching fraction from potential nonrelativistic QCD, our result can be used to determine the total width of the $\eta_b$ with a $7\%$ uncertainty., Comment: 4 pages, 3 figures, 2 tables, plus supplementary materials: 5 pages, 8 figures, 5 tables

An accurate calculation of the leading-order hadronic vacuum polarisation (LOHVP) contribution to the anomalous magnetic moment of the muon ($a_\mu$) is key to determining whether a discrepancy, suggesting new physics, exists between the Standard Model and experimental results. This calculation can be expressed as an integral over Euclidean time of a current-current correlator $G(t)$, where $G(t)$ can be calculated using lattice QCD or, with dispersion relations, from experimental data for $e^+e^-\to\mbox{hadrons}$. The BMW/DMZ collaboration recently presented a hybrid approach in which $G(t)$ is calculated using lattice QCD for most of the contributing $t$ range, but using experimental data for the largest $t$ (lowest energy) region. Here we study the advantages of varying the position $t=t_1$ separating lattice QCD from data-driven contributions. The total LOHVP contribution should be independent of $t_1$, providing both a test of the experimental input and the robustness of the hybrid approach. We use this criterion and a correlated fit to show that Fermilab/HPQCD/MILC lattice QCD results from 2019 strongly favour the CMD-3 cross-section data for $e^+e^-\to\pi^+\pi^-$ over a combination of earlier experimental results for this channel. Further, the resulting total LOHVP contribution obtained is consistent with the result obtained by BMW/DMZ, and supports the scenario in which there is no significant discrepancy between the experimental value for $a_\mu$ and that expected in the Standard Model. We then discuss how improved lattice results in this hybrid approach could provide a more accurate total LOHVP across a wider range of $t_1$ values with an uncertainty that is smaller than that from either lattice QCD or data-driven approaches on their own., Comment: 8 pages, 5 figures

We present a quantum algorithm for portfolio optimisation. Specifically, We present an end-to-end quantum approximate optimisation algorithm (QAOA) to solve the discrete global minimum variance portfolio (DGMVP) model. This model finds a portfolio of risky assets with the lowest possible risk contingent on the number of traded assets being discrete. We provide a complete pipeline for this model and analyses its viability for noisy intermediate-scale quantum computers. We design initial states, a cost operator, and ans\"atze with hard mixing operators within a binary encoding. Further, we perform numerical simulations to analyse several optimisation routines, including layerwise optimisation, utilising COYBLA and dual annealing. Finally, we consider the impacts of thermal relaxation and stochastic measurement noise. We find dual annealing with a layerwise optimisation routine provides the most robust performance. We observe that realistic thermal relaxation noise levels preclude quantum advantage. However, stochastic measurement noise will dominate when hardware sufficiently improves. Within this regime, we numerically demonstrate a favourable scaling in the number of shots required to obtain the global minimum -- an indication of quantum advantage in portfolio optimisation., Comment: 35 pages, 23 figures

This paper describes our submitted systems to the ASVspoof 5 Challenge Track 1: Speech Deepfake Detection - Open Condition, which consists of a stand-alone speech deepfake (bonafide vs spoof) detection task. Recently, large-scale self-supervised models become a standard in Automatic Speech Recognition (ASR) and other speech processing tasks. Thus, we leverage a pre-trained WavLM as a front-end model and pool its representations with different back-end techniques. The complete framework is fine-tuned using only the trained dataset of the challenge, similar to the close condition. Besides, we adopt data-augmentation by adding noise and reverberation using MUSAN noise and RIR datasets. We also experiment with codec augmentations to increase the performance of our method. Ultimately, we use the Bosaris toolkit for score calibration and system fusion to get better Cllr scores. Our fused system achieves 0.0937 minDCF, 3.42% EER, 0.1927 Cllr, and 0.1375 actDCF.

Two adaptive relaxation strategies are proposed for Anderson acceleration. They are specifically designed for applications in which mappings converge to a fixed point. Their superiority over alternative Anderson acceleration is demonstrated for linear contraction mappings. Both strategies perform well in three nonlinear fixed-point applications that include partial differential equations and the EM algorithm. One strategy surpasses all other Anderson acceleration implementations tested in terms of computation time across various specifications, including composite Anderson acceleration., Comment: 23 pages, 9 figures

Back translation, as a technique for extending a dataset, is widely used by researchers in low-resource language translation tasks. It typically translates from the target to the source language to ensure high-quality translation results. This paper proposes a novel way of utilizing a monolingual corpus on the source side to assist Neural Machine Translation (NMT) in low-resource settings. We realize this concept by employing a Generative Adversarial Network (GAN), which augments the training data for the discriminator while mitigating the interference of low-quality synthetic monolingual translations with the generator. Additionally, this paper integrates Translation Memory (TM) with NMT, increasing the amount of data available to the generator. Moreover, we propose a novel procedure to filter the synthetic sentence pairs during the augmentation process, ensuring the high quality of the data.

This work presents a formalization of analogy on numbers that relies on generalized means. It is motivated by recent advances in artificial intelligence and applications of machine learning, where the notion of analogy is used to infer results, create data and even as an assessment tool of object representations, or embeddings, that are basically collections of numbers (vectors, matrices, tensors). This extended analogy use asks for mathematical foundations and clear understanding of the notion of analogy between numbers. We propose a unifying view of analogies that relies on generalized means defined in terms of a power parameter. In particular, we show that any four increasing positive real numbers is an analogy in a unique suitable power. In addition, we show that any such analogy can be reduced to an equivalent arithmetic analogy and that any analogical equation has a solution for increasing numbers, which generalizes without restriction to complex numbers. These foundational results provide a better understanding of analogies in areas where representations are numerical.

Background: The high dimensionality of radiomic feature sets, the variability in radiomic feature types and potentially high computational requirements all underscore the need for an effective method to identify the smallest set of predictive features for a given clinical problem. Purpose: Develop a methodology and tools to identify and explain the smallest set of predictive radiomic features. Materials and Methods: 89,714 radiomic features were extracted from five cancer datasets: low-grade glioma, meningioma, non-small cell lung cancer (NSCLC), and two renal cell carcinoma cohorts (n=2104). Features were categorized by computational complexity into morphological, intensity, texture, linear filters, and nonlinear filters. Models were trained and evaluated on each complexity level using the area under the curve (AUC). The most informative features were identified, and their importance was explained. The optimal complexity level and associated most informative features were identified using systematic statistical significance analyses and a false discovery avoidance procedure, respectively. Their predictive importance was explained using a novel tree-based method. Results: MEDimage, a new open-source tool, was developed to facilitate radiomic studies. Morphological features were optimal for MRI-based meningioma (AUC: 0.65) and low-grade glioma (AUC: 0.68). Intensity features were optimal for CECT-based renal cell carcinoma (AUC: 0.82) and CT-based NSCLC (AUC: 0.76). Texture features were optimal for MRI-based renal cell carcinoma (AUC: 0.72). Tuning the Hounsfield unit range improved results for CECT-based renal cell carcinoma (AUC: 0.86). Conclusion: Our proposed methodology and software can estimate the optimal radiomics complexity level for specific medical outcomes, potentially simplifying the use of radiomics in predictive modeling across various contexts.

Recent advancements in Self-Supervised Learning (SSL) have shown promising results in Speaker Verification (SV). However, narrowing the performance gap with supervised systems remains an ongoing challenge. Several studies have observed that speech representations from large-scale ASR models contain valuable speaker information. This work explores the limitations of fine-tuning these models for SV using an SSL contrastive objective in an end-to-end approach. Then, we propose a framework to learn speaker representations in an SSL context by fine-tuning a pre-trained WavLM with a supervised loss using pseudo-labels. Initial pseudo-labels are derived from an SSL DINO-based model and are iteratively refined by clustering the model embeddings. Our method achieves 0.99% EER on VoxCeleb1-O, establishing the new state-of-the-art on self-supervised SV. As this performance is close to our supervised baseline of 0.94% EER, this contribution is a step towards supervised performance on SV with SSL., Comment: accepted at INTERSPEECH 2024

Self-Supervised Learning (SSL) frameworks became the standard for learning robust class representations by benefiting from large unlabeled datasets. For Speaker Verification (SV), most SSL systems rely on contrastive-based loss functions. We explore different ways to improve the performance of these techniques by revisiting the NT-Xent contrastive loss. Our main contribution is the definition of the NT-Xent-AM loss and the study of the importance of Additive Margin (AM) in SimCLR and MoCo SSL methods to further separate positive from negative pairs. Despite class collisions, we show that AM enhances the compactness of same-speaker embeddings and reduces the number of false negatives and false positives on SV. Additionally, we demonstrate the effectiveness of the symmetric contrastive loss, which provides more supervision for the SSL task. Implementing these two modifications to SimCLR improves performance and results in 7.85% EER on VoxCeleb1-O, outperforming other equivalent methods., Comment: accepted at Odyssey 2024: The Speaker and Language Recognition Workshop. arXiv admin note: text overlap with arXiv:2306.03664

We demonstrate a design for a high-performance $2 \times 2$ splitter meeting the essential requirements of broadband coupling, support for arbitrary coupling ratio, ultra low-loss, high fabrication tolerance, and a compact footprint. This is achieved based on a rigorous coupled mode theory analysis of the broadband response of the bent directional coupler (DC) and by demonstrating a full coupling model, with measured broadband values of 0.4, 0.5, 0.6, and 0.7. As a benchmark, we demonstrate a 0.5:0.5 splitter that significantly reduces coupling variation from 0.391 in the traditional DC to just 0.051 over an 80 nm wavelength span. This represents a remarkable 7.67 times reduction in coupling variation. Further, newly-invented low-loss bends were used in the proposed design leading to an ultra low-loss design with negligible excess loss ($\mathrm{0.003 \pm 0.013 \ dB}$). The proposed 0.5:0.5 silicon strip waveguide-based design is tolerant and shows consistently low coupling variation over a full 300 mm wafer showcasing a maximum cross coupling variation of 0.112 over 80 nm wavelength range, at the extreme edge of the wafer. Futhermore, we augmented the wafer mapping with a waveguide width fabrication tolerance study, confirming the tolerance of the device with a mere 0.061 maximum coupling variation with a waveguide width deviation of $\pm 20$ nm over 80 nm wavelength range. These specs make the proposed splitter an attractive component for practical applications with mass production.

Hallucinations and delusions are often grouped together within the positive symptoms of psychosis. However, recent evidence suggests they may be driven by distinct computational and neural mechanisms. Examining the time course of their emergence may provide insights into the relationship between these underlying mechanisms. Participants from the second (N = 719) and third (N = 699) iterations of the North American Prodrome Longitudinal Study (NAPLS 2 and 3) were assessed for timing of CHR-P-level delusion and hallucination onset. Pre-onset symptom patterns in first-episode psychosis patients (FEP) from the Prevention and Early Intervention Program for Psychosis (PEPP-Montreal; N = 694) were also assessed. Symptom onset was determined at baseline assessment and the evolution of symptom patterns examined over 24 months. In all three samples, participants were more likely to report the onset of delusion-spectrum symptoms prior to hallucination-spectrum symptoms (odds ratios (OR): NAPLS 2 = 4.09; NAPLS 3 = 4.14; PEPP, Z = 7.01, P < 0.001) and to present with only delusions compared to only hallucinations (OR: NAPLS 2 = 5.6; NAPLS 3 = 11.11; PEPP = 42.75). Re-emergence of delusions after remission was also more common than re-emergence of hallucinations (Ps < 0.05), and hallucinations more often resolved first (Ps < 0.001). In both CHR-P samples, ratings of delusional ideation fell with the onset of hallucinations (P = 0.007). Delusions tend to emerge before hallucinations and may play a role in their development. Further work should examine the relationship between the mechanisms driving these symptoms and its utility for diagnosis and treatment.

The objective of this paper is to describe the study on speech interaction mode for home automation control of equipment by impaired people for an inclusive housing. The study is related to the HIP HOPE project concerning a building of 19 inclusive housing units. 7 participants with different types of disabilities were invited to carry out use cases using voice and touch control. Only the results obtained on the voice interaction mode through the Amazon voice assistant are reported here. The results show, according to the type of handicap, the success rates in the speech recognition of the command emitted on the equipment and highlight the errors related to the formulation, the noisy environment, the intelligible speech, the speech segmentation and the bad synchronization of the audio channel opening.

We study how to use the surface states in a Bi$_{2}$Se$_{3}$ topological insulator ultra-thin film that are affected by finite size effects for the purpose of quantum computing. We demonstrate that: (i) surface states under the finite size effect can effectively form a two-level system where their energy levels lie in between the bulk energy gap and a logic qubit can be constructed, (ii) the qubit can be initialized and manipulated using electric pulses of simple forms, (iii) two-qubit entanglement is achieved through a $\sqrt{\text{SWAP}}$ operation when the two qubits are in a parallel setup, and (iv) alternatively, a Floquet state can be exploited to construct a qubit and two Floquet qubits can be entangled through a Controlled-NOT operation. The Floquet qubit offers robustness to background noise since there is always an oscillating electric field applied, and the single qubit operations are controlled by amplitude modulation of the oscillating field, which is convenient experimentally., Comment: 12 pages, 9 figures, submitted to the journal Frontiers of Physics

To the best of our knowledge, this paper has achieved the lowest thermal tuning power (5.85 mW/pi) for silicon rings with FSR>=3.2 THz, and the first silicon ring-based WDM-32x100 GHz filter., Comment: 3 pages submitted for conference

Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods In this multinational retrospective observational study we enrolled adult participants (aged $\ge$18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year followup after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75$\bullet$3%) were female, 2530 (24$\bullet$7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2$\bullet$8 kg/m${}^2$ (95% CI 2$\bullet$6-3$\bullet$0) and mean RMSE BMI was 4$\bullet$7 kg/m${}^2$ (4$\bullet$4-5$\bullet$0), and the mean difference between predicted and observed BMI was-0$\bullet$3 kg/m${}^2$ (SD 4$\bullet$7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. InterpretationWe developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions., Comment: The Lancet Digital Health, 2023

We explain how to calculate link homology for a Lie algebra $\mathfrak{g}$ using the Fukaya category associated to a 2d A-model. Links are represented as configurations of particular A-branes and link homology is given by Homs between these A-branes. In the case of $\mathfrak{g}=\mathfrak{su}_2$, we explain how to explicitly construct projective resolutions of the relevant A-branes in terms of thimbles, whose algebra is known. This gives an explicit algorithm for computing Khovanov homology. This algorithm can be extended to all Lie algebras., Comment: 16 pages, 15 figures, contribution to the proceedings of String Math 2022

Given two hyperbolic curves over p-adic local fields, the absolute anabelian conjecture claims that any isomorphism between their \'etale fundamental group comes from an isomorphism of schemes. This conjecture was proven by S. Mochizuki for curves of quasi-Belyi type. The goal of this paper is to extend the result to a wider family of curves, that includes for example hyperbolic Mumford curves., Comment: 12 pages

Most state-of-the-art self-supervised speaker verification systems rely on a contrastive-based objective function to learn speaker representations from unlabeled speech data. We explore different ways to improve the performance of these methods by: (1) revisiting how positive and negative pairs are sampled through a "symmetric" formulation of the contrastive loss; (2) introducing margins similar to AM-Softmax and AAM-Softmax that have been widely adopted in the supervised setting. We demonstrate the effectiveness of the symmetric contrastive loss which provides more supervision for the self-supervised task. Moreover, we show that Additive Margin and Additive Angular Margin allow reducing the overall number of false negatives and false positives by improving speaker separability. Finally, by combining both techniques and training a larger model we achieve 7.50% EER and 0.5804 minDCF on the VoxCeleb1 test set, which outperforms other contrastive self supervised methods on speaker verification., Comment: accepted at INTERSPEECH 2023, 20th-24th August 2023, Dublin, Ireland

This paper introduces a new challenge for image similarity search in the context of fashion, addressing the inherent ambiguity in this domain stemming from complex images. We present Referred Visual Search (RVS), a task allowing users to define more precisely the desired similarity, following recent interest in the industry. We release a new large public dataset, LRVS-Fashion, consisting of 272k fashion products with 842k images extracted from fashion catalogs, designed explicitly for this task. However, unlike traditional visual search methods in the industry, we demonstrate that superior performance can be achieved by bypassing explicit object detection and adopting weakly-supervised conditional contrastive learning on image tuples. Our method is lightweight and demonstrates robustness, reaching Recall at one superior to strong detection-based baselines against 2M distractors. The dataset is available at https://huggingface.co/datasets/Slep/LAION-RVS-Fashion ., Comment: 29 pages, 14 figures, 5 tables

There is a generalization of Heegaard-Floer theory from ${\mathfrak{gl}}_{1|1}$ to other Lie (super)algebras $^L{\mathfrak{g}}$. The corresponding category of A-branes is solvable explicitly and categorifies quantum $U_q(^L{\mathfrak{g}})$ link invariants. The theory was discovered in \cite{A1,A2}, using homological mirror symmetry. It has novel features, including equivariance and, if $^L{\mathfrak{g}} \neq {\mathfrak{gl}}_{1|1}$, coefficients in categories. In this paper, we describe the theory and how it is solved in detail in the two simplest cases: the ${\mathfrak{gl}}_{1|1}$ theory itself, categorifying the Alexander polynomial, and the ${\mathfrak{su}}_{2}$ theory, categorifying the Jones polynomial. Our approach to solving the theory is new, even in the familiar ${\mathfrak{gl}}_{1|1}$ case., Comment: 146 pages

We calculate the decay rates for $\eta_c \to \gamma \gamma$, $J/\psi \to \gamma \eta_c$ and $J/\psi \to \eta_c e^+e^-$ in lattice QCD with $u$, $d$, $s$ and $c$ quarks in the sea for the first time. We improve significantly on previous theory calculations to achieve accuracies of 1--2\%, giving lattice QCD results that are now more accurate than the experimental values. In particular our results transform the theoretical picture for $\eta_c\to\gamma\gamma$ decays. We use gluon field configurations generated by the MILC collaboration that include $n_f=2+1+1$ flavours of Highly Improved Staggered (HISQ) sea quarks at four lattice spacing values from 0.15 fm to 0.06 fm and with sea u/d masses down to their physical value. We also implement the valence $c$ quarks using the HISQ action. We find ${\Gamma (\eta_c \to \gamma \gamma) = 6.788(45)_{\text{fit}}(41)_{\text{syst}} \: \mathrm{keV}}$, in good agreement with experimental results using $\gamma\gamma \to \eta_c \to K\overline{K}\pi$ but in 4$\sigma$ tension with the Particle Data Group global fit result; we suggest this fit is revisited. We also calculate $\Gamma (J/\psi \to \gamma \eta_c) = 2.219(17)_{\text{fit}}(18)_{\text{syst}}(24)_{\text{expt}}(4)_{\text{QED}} \; \mathrm{keV}$, in good agreement with results from CLEO, and predict the Dalitz decay rate $\Gamma (J/\psi \to \eta_c e^+ e^-) = 0.01349(21)_{\text{latt}}(13)_{\text{QED}} \; \mathrm{keV}$. We use our results to calibrate other theoretical approaches and to test simple relationships between the form factors and $J/\psi$ decay constant expected in the nonrelativistic limit., Comment: 26 pages, 19 figures. Updated Figure 7, added 3 references and made further small changes to clarify the presentation. Further small changes to text, version accepted by Physical Review D

As part of the Digital Working Group (GTnum) #Scol_IA "Renewal of digital practices and creative uses of digital and AI" we are pleased to present the white paper "Teaching and learning in the era of Artificial Intelligence, Acculturation, integration and creative uses of AI in education". The white paper edited by Margarida Romero, Laurent Heiser and Alexandre Lepage aims to provide the various educational actors with a diversified perspective both on the issues of acculturation and training in AI and on the resources and feedback from the various research teams and organisations. of scientific culture in the French-speaking countries. A multidisciplinary approach makes it possible to consider the perspectives of researchers in computer science as well as those of education and training sciences, information and communication sciences and the expertise of teaching professionals. and scientific mediation., Comment: in French language

We present a numerically-optimized multipulse framework for the quantum control of a single-electron charge qubit. Our framework defines a set of pulse sequences, necessary for the manipulation of the ideal qubit basis, that avoids errors associated with excitations outside the computational subspace. A novel control scheme manipulates the qubit adiabatically, while also retaining high speed and ability to perform a general single-qubit rotation. This basis generates spatially localized logical qubit states, making readout straightforward. We consider experimentally realistic semiconductor qubits with finite pulse rise and fall times and determine the fastest pulse sequence yielding the highest fidelity. We show that our protocol leads to improved control of a qubit. We present simulations of a double quantum dot in a semiconductor device to visualize and verify our protocol. These results can be generalized to other physical systems since they depend only on pulse rise and fall times and the energy gap between the two lowest eigenstates., Comment: 9 pages, 9 figures

The specific activity of the beta decay of $^{39}$Ar in atmospheric argon is measured using the DEAP-3600 detector. DEAP-3600, located 2 km underground at SNOLAB, uses a total of (3269 $\pm$ 24) kg of liquid argon distilled from the atmosphere to search for dark matter. This detector with very low background uses pulseshape discrimination to differentiate between nuclear recoils and electron recoils and is well-suited to measure the decay of $^{39}$Ar. With 167 live-days of data, the measured specific activity at the time of atmospheric extraction is [0.964 $\pm$ 0.001 (stat) $\pm$ 0.024 (sys)] Bq/kg$_{\rm atmAr}$ which is consistent with results from other experiments. A cross-check analysis using different event selection criteria provides a consistent result.