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In this paper an extensive database of SPARC H-modes confinement predictions has been provided, to assess its variability with respect to few input assumptions. The simulations have been performed within the ASTRA framework, using the quasi-linear model TGLF SAT2, including electromagnetic effects, for the core transport, and a neural network trained on EPED simulations to predict the pedestal height and width self-consistently. The database has been developed starting from two SPARC H-mode discharges (12.2 T, i.e. Primary Reference Discharge or PRD, and 8 T, i.e. reduced field) and permuting 4 input parameters (W concentration, DT mixture concentration, temperature ratio at top of pedestal and deviation of pedestal pressure from the EPED prediction), to perform a sensitivity study. For the PRD a scan of auxiliary input power (ion cyclotron heating) has been performed up to 25MW, to keep highly radiative plasmas above the LH power threshold as predicted by Martin and Schmidtmayr power scalings. A scan of pedestal density has then been performed for both PRD and 8T databases. ptop/pEPED and Ti/Te at top of pedestal showed the biggest impact on the fusion gain. Significant variation is observed across the database, highlighting the importance of sensitivity studies. Below a certain W concentration, the 12T database shows that Q > 5 is consistently achieved for full-field H-modes with 11 MW of auxiliary power, and values of Q > 2 are assured when increasing the input power to keep the plasma in H-mode. The 8T database demonstrates that SPARC can access a Q > 1 operational window with low W concentration, making it a potentially interesting scenario for obtaining breakeven conditions.

The development of advanced materials with high specific energy is crucial for enabling sustainable energy storage solutions, particularly in applications such as lithium-air batteries. Lithium peroxide (Li$_{2}$O$_{2}$) is a key discharge product in non-aqueous lithium-air systems, where its structural and electronic properties significantly influence battery performance. In this work, we investigate the atomic structure, electronic band structure, and Wannier functions of bulk Li$_{2}$O$_{2}$ using density functional theory. The performance of different basis sets of numerical atomic orbitals are compared with respect to a converged plane-wave basis results. We analyze the material's ionic characteristics, the formation of molecular orbitals in oxygen dimers, and the band gap discrepancies between various computational approaches. Furthermore, we develop a localized Wannier basis to model electron-vibration interactions and explore their implications for polaron formation. Our findings provide a chemically intuitive framework for understanding electron-lattice coupling and offer a basis for constructing reduced models that accurately describe the dynamics of polarons in Li$_{2}$O$_{2}$. These insights contribute to the broader goal of improving energy storage technologies and advancing the field of materials design., Comment: 9 pages, 7 figures

As cloud services continue to expand, the security of private data stored and processed in these environments has become paramount. This work delves into quantum homomorphic encryption (QHE), an emerging technology that facilitates secure computation on encrypted quantum data without revealing the underlying information. We reinterpret QHE schemes through classical-quantum circuits, enhancing efficiency and addressing previous limitations related to key computations. Our approach eliminates the need for exponential key preparation by calculating keys in real-time during simulation, leading to a linear complexity in classically controlled gates. We also investigate the $T/T^{\dagger}$-gate complexity associated with various quantum walks, particularly Szegedy quantum and semiclassical algorithms, demonstrating efficient homomorphic implementations across different graph structures. Our simulations, conducted in Qiskit, validate the effectiveness of QHE for both standard and semiclassical walks. The rules for the homomorphic evaluation of the reset and intermediate measurement operations have also been included to perform the QHE of semiclassical walks. Additionally, we introduce the CQC-QHE library, a comprehensive tool that simplifies the construction and simulation of classical-quantum circuits tailored for quantum homomorphic encryption. Future work will focus on optimizing classical functions within this framework and exploring broader graph types to enhance QHE applications in practical scenarios., Comment: RevTex 4.2, 29+7 pages, 19+12 color figures

Transition metal dichalcogenides (TMDs) exhibit unique properties and potential applications when reduced to one-dimensional (1D) nanoribbons (NRs), owing to quantum confinement and high edge densities. However, effective growth methods for self-aligned TMD NRs are still lacking. We demonstrate a versatile approach for lattice-guided growth of dense, aligned MoS2 NR arrays via chemical vapor deposition (CVD) on anisotropic sapphire substrates, without tailored surface steps. This method enables the synthesis of NRs with widths below 10 nm and longitudinal axis parallel to the zigzag direction, being also extensible to the growth of WS2 NRs and MoS2-WS2 hetero-nanoribbons. Growth is influenced by both substrate and CVD temperature, indicating the role of anisotropic precursor diffusion and substrate interaction. The 1D nature of the NRs was asserted by the observation of Coulomb blockade at low temperature. Pronounced catalytic activity was observed at the edges of the NRs, indicating their promise for efficient catalysis., Comment: 41 pages, 27 figures

Preceding a core-collapse supernova, various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande via inverse beta decay interactions. Once these pre-supernova neutrinos are observed, an early warning of the upcoming core-collapse supernova can be provided. In light of this, KamLAND and Super-Kamiokande, both located in the Kamioka mine in Japan, have been monitoring pre-supernova neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and Super-Kamiokande on pre-supernova neutrino detection. A pre-supernova alert system combining the KamLAND detector and the Super-Kamiokande detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-supernova neutrino signal from a 15 M$_{\odot}$ star within 510 pc of the Earth, at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hours in advance., Comment: Resubmitted to ApJ. 22 pages, 16 figures, for more information about the combined pre-supernova alert system, see https://www.lowbg.org/presnalarm/

Extending the classical Dirichlet's density theorem on coprime pairs, in this paper we describe completely the probability distribution of the number of coprime pairs in random squares of fixed side length in the lattice $\mathbb{N}^2$. The limit behaviour of this distribution as the side length of the random square tends to infinity is also considered.

We apply quantum homomorphic encryption (QHE) schemes suitable for circuits with a polynomial number of $T/T^{\dagger}$-gates to Grover's algorithm, performing a simulation in Qiskit of a Grover circuit that contains 3 qubits. The $T/T^{\dagger}$ gate complexity of Grover's algorithm is also analysed in order to show that any Grover circuit can be evaluated homomorphically in an efficient manner. We discuss how to apply these QHE schemes to allow for the efficient homomorphic evaluation of any Grover circuit composed of $n$ qubits using $n-2$ extra ancilla qubits. We also show how the homomorphic evaluation of the special case where there is only one marked item can be implemented using an algorithm that makes the decryption process more efficient compared to the standard Grover algorithm.

Domain reduction techniques are at the core of any global optimization solver for NLP or MINLP problems. In this paper, we delve into several of these techniques and assess the impact they may have in the performance of an RLT-based algorithm for polynomial optimization problems. These techniques include i) the use of (nonlinear) conic relaxations for optimality-based bound tightening, ii) the use of Lagrangian dual information to enhance feasibility-based bound tightening, and iii) different strategies for branching point selection. We also explore how a solver equipped with these domain reduction enhancements can further improve its performance by using machine learning to better choose the best domain reduction approach to use on a given instance.

In this letter, we study the potential of boosting the atmospheric neutrino experiments sensitivity to the neutrino mass ordering (NMO) sensitivity by incorporating inelasticity measurements. We show how this observable improves the sensitivity to the NMO and the precision of other neutrino oscillation parameters relevant to atmospheric neutrinos, specifically in the IceCube-Upgrade and KM3NeT-ORCA detectors. Our results indicate that an oscillation analysis of atmospheric neutrinos including inelasticity information has the potential to enhance the ordering discrimination by several units of $\chi^2$ in the assumed scenario of 5 and 3 years of running of IceCube-Upgrade and KM3NeT-ORCA detectors, respectively., Comment: 8 pages (6 + 2), 7 figures (5 + 2)

Any power series with nonnegative coefficients has an associated family of probability distributions supported on the nonnegative integers. There is a close connection between the function theoretic properties of the power series and the moments of the family of distributions. In this paper, we describe that interplay, provide simpler proofs of some known results by emphasizing the probabilistic perspective, and present some new theorems.

APIs are increasingly becoming new business assets for organizations and consequently, API functionality and its pricing should be precisely defined for customers. Pricing is typically composed by different plans that specify a range of limitations, e.g., a Free plan allows 100 monthly requests while a Gold plan has 10000 requests per month. In this context, the OpenAPI Specification (OAS) has emerged to model the functional part of an API, becoming a de facto industry standard and boosting a rich ecosystem of vendor-neutral tools to assist API providers and consumers. In contrast, there is no proposal for modeling API pricings (i.e. their plans and limitations) and this lack hinders the creation of tools that can leverage this information. To deal with this gap, this paper presents a pricing modeling framework that includes: (a) Pricing4APIs model, a comprehensive and rigorous model of API pricings, along SLA4OAI, a serialization that extends OAS; (b) an operation to validate the description of API pricings, with a toolset (sla4oai-analyzer) that has been developed to automate this operation. Additionally, we analyzed 268 real-world APIs to assess the expressiveness of our proposal and created a representative dataset of 54 pricing models to validate our framework.

Using first-principles DFT calculations, we analyze the origin of the different crystal structures, optical and magnetic properties of two basic families of layered fluoride materials with formula A2MF4 (M = Ag, Cu, Ni, Mn; A = K, Cs, Rb). On one hand, Cs2AgF4 and K2CuF4 compounds (both with d9 metal cations) crystallize in an orthorhombic structure with Cmca space group and MA - F - MB bridge angle of 180, and they exhibit a weak ferromagnetism (FM) in the layer plane. On the other hand, K2NiF4 or K2MnF4 compounds (with d8 and d5 metal cations, respectively) have a tetragonal I4/mmm space group with 180 bridge angle and exhibit antiferromagnetism (AFM) in the layer plane. Firstly, we show that, contrary to what is claimed in the literature, the Cmca structure of Cs2AgF4 and K2CuF4 is not related to a cooperative Jahn-Teller effect among elongated MF64- units. Instead, first-principles calculations carried out in the I4/mmm parent phase of these two compounds show that MF64- units are axially compressed because the electrostatic potential from the rest of lattice ions force the hole to lie in the 3z2 - r2 molecular orbital (z being perpendicular to the layer plane). This fact increases the metal-ligand distance in the layer plane and makes that covalency in the bridging ligand has a residual character (clearly smaller than in K2NiF4 or KNiF3) stabilizing for only a few meV (7.9 meV for Cs2AgF4) an AFM order. However, this I4/mmm parent phase of Cs2AgF4 is unstable thus evolving towards the experimental Cmca structure with an energy gain of 140 meV, FM ordering and orthorhombic MF64- units., Comment: 33 pages, special issue in Journal of Physical Chemistry C

We studied the interlayer coupling and decoupling of bilayer graphene (BLG) by using spatially resolved electron energy loss spectroscopy (EELS) with a monochromated electron source. We correlated the twist-angle-dependent energy band hybridization with Moire superlattices and the corresponding optical absorption peaks. The optical absorption peak originates from the excitonic transition between the hybridized van Hove singularities (vHSs), which shifts systematically with the twist angle. We then proved that the BLG decouples when a monolayer of metal chloride is intercalated in its van der Waals (vdW) gap, and results in the elimination of the vHS peak.

The nonrecursive Bernstein-Vazirani algorithm was the first quantum algorithm to show a superpolynomial improvement over the corresponding best classical algorithm. Here we define a class of circuits that solve a particular case of this problem for second-level recursion. This class of circuits simplifies the number of gates $T$ required to construct the oracle by making it grow linearly with the number of qubits in the problem. We find an application of this scheme to quantum homomorphic encryption (QHE) which is an important cryptographic technology useful for delegated quantum computation. It allows a remote server to perform quantum computations on encrypted quantum data, so that the server cannot know anything about the client's data. Liang developed QHE schemes with perfect security, $\mathcal{F}$-homomorphism, no interaction between server and client, and quasi-compactness bounded by $O(M)$ where M is the number of gates $T$ in the circuit. Precisely these schemes are suitable for circuits with a polynomial number of gates $T/T^{\dagger}$. Following these schemes, the simplified circuits we have constructed can be evaluated homomorphically in an efficient way., Comment: Revtex file, color figures

Context. Software Engineering (SE) has low female representation due to gender bias that men are better at programming. Pair programming (PP) is common in industry and can increase student interest in SE, especially women; but if gender bias affects PP, it may discourage women from joining the field. Objective. We explore gender bias in PP. In a remote setting where students cannot see their peers' gender, we study how perceived productivity, technical competency and collaboration/interaction behaviors of SE students vary by perceived gender of their remote partner. Method. We developed an online PP platform (twincode) with a collaborative editing window and a chat pane. Control group had no gender information about their partner, while treatment group saw a gendered avatar as a man or woman. Avatar gender was swapped between tasks to analyze 45 variables on collaborative coding behavior, chat utterances and questionnaire responses of 46 pairs in original study at the University of Seville and 23 pairs in the replication at the University of California, Berkeley. Results. No significant effect of gender bias treatment or interaction between perceived partner's gender and subject's gender in any variable in original study. In replication, significant effects with moderate to large sizes in four variables within experimental group comparing subjects' actions when partner was male vs female.

We report second-principles simulations on the structural and energetic properties of domains in (PbTiO$_{3}$)$_{n}$/(SrTiO$_{3}$)$_{n}$ superlattices. For the explored layer thickness ($n$ ranging between 8 and 16 unit cells) and lateral sizes of the domains, the most stable configuration corresponds to polar domains separated by a sequence of counter-rotating vortices (clockwise/counterclockwise) perpendicular to the stacking direction and acting as domain walls. The balance between the domain wall energy and the electrostatic energy yields to an optimal domain period $\omega$ that is proportional to the square-root of the thickness of the PbTiO$_{3}$ layer, following the Kittel law. For a given lateral size of the simulation box, suboptimal domain structures (with a width larger than the one predicted by the Kittel law) can be obtained in a metastable form. However, at finite temperature, molecular dynamics simulations show the spontaneous change of periodicity, which implies the formation of new domains whose generation is initiated by the nucleation of vortices and antivortices at the interface between the SrTiO$_{3}$ and the PbTiO$_{3}$ layers. The vortices progressively elongate and eventually annihilate with the antivortices yielding the formation of new domains to comply the Kittel law via a topological phase transition., Comment: 7 pages, 6 Figures

We study the emergence of Berezinskii-Kosterlitz-Thouless (BKT) phases in (PbTiO$_3$)$_3$/(SrTiO$_3$)$_3$ superlattices by means of second-principles simulations. Beyond a threshold tensile epitaxial strain of $\epsilon = 0.25 \%$ the local dipole moments within the superlattices are confined to the film-plane, and thus the polarization can be effectively considered as two-dimensional. The analysis of the decay of the dipole-dipole correlation with the distance, together with the study of the density of defects and its distribution as function of temperature, supports the existence of a BKT phase in a range of temperature mediating the ordered ferroelectric (stable at low $T$), and the disordered paraelectric phase that appears beyond a critical temperature $T_{\rm BKT}$. This BKT phase is characterized by quasi-long-range order (whose signature is a power-law decay of the correlations with the distance), and the emergence of tightly bounded vortex-antivortex pairs whose density is determined by a thermal activation process. The proposed PbTiO$_{3}$/SrTiO$_{3}$ superlattice model and the imposed mechanical boundary conditions are both experimentally feasible, opening the door for the first experimental observation of these new topological phases in ferroelectric materials., Comment: 11 pages, 6 Figures

In this paper, we give a simple criterion to verify that functions of the form $e^g$ are in the Hayman class when $g$ is a power series with nonnegative coefficients. Thus, using the Hayman and B\'aez-Duarte formulas, we obtain asymptotics for the coefficients of generating functions that arise in many examples of set construction in analytic combinatorics. This new criterion greatly simplifies that obtained previously by the authors.

We study the equilibrium arrangements of polarization vortices in (PbTiO$_3$)$_n$/(SrTiO$_3$)$_n$ superlattices by means of second-principles simulations. We find that, at low temperatures, polarization vortices organize in a regular arrangement in which clockwise and counter-clockwise vortices alternate positions, leading to a crystal-like structure with well defined handedness. This chiral crystal melts at a critical temperature $T_\mathrm{M}$ into a chiral liquid, where long-range order is lost but handedness is preserved. At even higher temperatures, $T_\mathrm{C}$, a second phase transition occurs, at which the chiral liquid of polarization vortices loses its handedness. Both phase transitions can be readily identified by the adequate choices of order parameters., Comment: 7 pages, 4 figures

Following Hales (2018), the evolution of P\'olya's urn may be interpreted as a walk, a P\'olya walk, on the integer lattice $\mathbb{N}^2$. We study the visibility properties of P\'olya's walk or, equivalently, the divisibility properties of the composition of the urn. In particular, we are interested in the asymptotic average time that a P\'olya walk is visible from the origin, or, alternatively, in the asymptotic proportion of draws so that the resulting composition of the urn is coprime. Via de Finetti's exchangeability theorem, P\'olya's walk appears as a mixture of standard random walks. This paper is a follow-up of Cilleruelo-Fern\'andez-Fern\'andez (2019), where similar questions were studied for standard random walks.

With the increasing interest in twisted bilayer graphene (tBLG) of the past years, fast, reliable, and non-destructive methods to precisely determine the twist angle are required. Raman spectroscopy potentially provides such method, given the large amount of information about the state of the graphene that is encoded in its Raman spectrum. However, changes in the Raman spectra induced by the stacking order can be very subtle, thus making the angle identification tedious. In this work, we propose the use of machine learning (ML) analysis techniques for the automated classification of the Raman spectrum of tBLG into a selected range of twist angles. The ML classification proposed here is low computationally demanding, providing fast and accurate results with ~99 % of agreement with the manual labelling of the spectra. The flexibility and non-invasive nature of the Raman measurements, paired with the predictive accuracy of the ML, is expected to facilitate the exploration of the nascent research of tBLG. Moreover, the present work showcases how the currently available open-source tools facilitate the study and integration of ML-based techniques., Comment: 38 pages, 21 figures

Context. Pair programming (PP) has been found to increase student interest in Computer Science, particularly so for women, and would therefore appear to be a way to help remedy their under-representation, which could be partially motivated by gender stereotypes applied to software engineers, assuming that men perform better than their women peers. If this same bias is present in pair programming, it could work against the goal of improving gender balance. Objective. In a remote setting in which students cannot directly observe their peers, we aim to explore whether they behave differently when the perceived gender of their remote PP partners changes, searching for differences in (i) the perceived productivity compared to solo programming; (ii) the partner's perceived technical competency compared to their own; (iii) the partner's perceived skill level; (iv) the interaction behavior, such as the frequency of source code additions, deletions, etc.; and (v) the type and relative frequencies of dialog messages in a chat window. Method. Using the twincode platform, several behaviors are automatically measured during the remote PP process, together with two questionnaires and a semantic tagging of the pairs' chats. A series of experiments to identify the effect, if any, of possible gender bias shall be performed. The control group will have no information about their partner's gender, whereas the treatment group will receive such information but will be selectively deceived about their partner's gender. For each response variable we will (i) compare control and experimental groups for the score distance between two in-pair tasks; then, using the data from the experimental group only, we will (ii) compare scores using the partner's perceived gender as a within-subjects variable; and (iii) analyze the interaction between the partner's perceived gender and the subject's gender., Comment: Accepted at the ESEM 2021 Registered Report track