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Josephson junctions containing ferromagnetic materials are under consideration for applications in digital superconducting logic and memory. Some memory applications rely on the ability to reverse the magnetization direction of a "soft" magnetic layer within the junction using a small local magnetic field generated on the chip. It is crucial, therefore, to find a suitable soft magnetic material with a low switching field and low switching energy. A popular magnetic material for such applications is Ni$_{80}$Fe$_{20}$, also known as Permalloy, however Permalloy has a rather large magnetization, leading to large magnetic switching energies. In this work we explore Cr-doped Permalloy, specifically Ni$_{73}$Fe$_{18}$Cr$_{9}$, which has a saturation magnetization just under two-thirds that of Permalloy. Josephson junctions containing this NiFeCr alloy undergo a 0-$\pi$ transition at a NiFeCr thickness of 2.3 nm, and the critical supercurrent decays in the alloy over a short characteristic length of 0.36 nm. Switching fields of a few millitesla are promising, but the short decay length and overall small values of the critical current in the Josephson junctions may preclude the use of NiFeCr in current cryogenic memory technologies., Comment: 7 pages, 4 figures

Attestation of documents like legal papers, professional qualifications, medical records, and commercial documents is crucial in global transactions, ensuring their authenticity, integrity, and trustworthiness. Companies expanding operations internationally need to submit attested financial statements and incorporation documents to foreign governments or business partners to prove their businesses and operations' authenticity, legal validity, and regulatory compliance. Attestation also plays a critical role in education, overseas employment, and authentication of legal documents such as testaments and medical records. The traditional attestation process is plagued by several challenges, including time-consuming procedures, the circulation of counterfeit documents, and concerns over data privacy in the attested records. The COVID-19 pandemic brought into light another challenge: ensuring physical presence for attestation, which caused a significant delay in the attestation process. Traditional methods also lack real-time tracking capabilities for attesting entities and requesters. This paper aims to propose a new strategy using decentralized technologies such as blockchain and self-sovereign identity to overcome the identified hurdles and provide an efficient, secure, and user-friendly attestation ecosystem.

We present a simplified derivation of the optimal checkpoint interval in Young_1974 [1]. The optimal checkpoint interval derivation in [1] is based on minimizing the total lost time as an objective-function. Lost time is a function of checkpoint interval, checkpoint save time, and average failure time. This simplified derivation yields lost-time-optimal that is identical to the one derived in [1]. For large scale-out super-computer or datacenter systems, what is important is the selection of optimal checkpoint interval that maximizes availability. We show that availability-optimal checkpoint interval is different from the one derived in [1]. However, availability-optimal checkpoint interval is asymptotically same as lost-time-optimal checkpoint interval for certain conditions on checkpoint save and recovery time. We show that these optimal checkpoint intervals hold in situations where the error detection latency is significantly smaller than any selected checkpoint interval. However, in cases where the error detection latency is very large then the optimal checkpoint interval is greater than or equal to the error detection latency., Comment: 10 pages, 5 figures

Residential rooftop solar adoption is considered crucial for reducing carbon emissions. The lack of photovoltaic (PV) data at a finer resolution (e.g., household, hourly levels) poses a significant roadblock to informed decision-making. We discuss a novel methodology to generate a highly granular, residential-scale realistic dataset for rooftop solar adoption across the contiguous United States. The data-driven methodology consists of: (i) integrated machine learning models to identify PV adopters, (ii) methods to augment the data using explainable AI techniques to glean insights about key features and their interactions, and (iii) methods to generate household-level hourly solar energy output using an analytical model. The resulting synthetic datasets are validated using real-world data and can serve as a digital twin for modeling downstream tasks. Finally, a policy-based case study utilizing the digital twin for Virginia demonstrated increased rooftop solar adoption with the 30\% Federal Solar Investment Tax Credit, especially in Low-to-Moderate-Income communities., Comment: 41 pages including references and supplementary

The capability of standard Geant4 PhysicsLists to address the fragmentation of $^{12}$C$-^{12}$C was assessed through a comparative analysis with experimental cross sections reported by Divay et al. and Dudouet et al. The standard PhysicsLists were found to be inadequate in explaining the fragmentation systematics. To address this limitation, the breakup component of fragmentation was systematically integrated into the standard PhysicsList, which successfully replicated the differential and double differential cross sections for $\alpha$ production. This breakup component was modeled using fresco CDCC-CRC calculations. This novel physics process was then incorporated into the Geant4 framework, facilitating the calculation of dose distributions in water and tissue. The application of this method demonstrated a precise reproduction of the dose deposited at the Bragg peak region, corroborating the experimental data from Liedner et al., thereby enhancing the accurate visibility of dose tailing.

The generation of $S_z=1$ triplet Cooper pairs has been predicted theoretically in superconducting-ferromagnetic hybrid heterostructures in the presence of spin-orbit coupling [F. S. Bergeret and I. V. Tokatly, Phys. Rev. B 89, 134517 (2014) and Jacobsen et al., Sci. Rep. 6, 23926 (2016)]. In this study, we experimentally investigate vertical Josephson junctions where the weak link is formed from a ferromagnetic layer with perpendicular magnetic anisotropy sandwiched by two non-magnetic layers with weak or strong spin-orbit coupling. We find that the decay of the Josephson coupling is reduced in the latter case, possibly indicating the presence of $S_z=1$ spin-triplet correlations. We speculate that the canted magnetization required for these correlations is provided by the interaction of magnetization with Meissner effect in the superconducting layers.

The cross sections for the $^{12}\mathrm{C}(\gamma,\alpha)^{8}\mathrm{Be}\rightarrow 3\alpha$ reaction have been successfully measured using exclusive coincidence between three $\alpha$ particles, minimizing Compton background. Sequential breakup kinematics are evident, and the cross sections are presented as locally averaged histogram values. Theoretical \textsc{Fresco} CDCC-CRC calculations reproduce the experimental data, showing that the process involves electromagnetic coupling to both $^{8}\mathrm{Be}^{0^+}$ and $^{8}\mathrm{Be}^{2^+}$ states. This study confirms that the $^{12}\mathrm{C}(\gamma,\alpha)^{8}\mathrm{Be}\rightarrow 3\alpha$ reaction proceeds via a sequential mechanism, crucial for understanding its significance in radiotherapy dosimetry.

We consider the dimensional reduction to two dimensions of certain gravitational theories in $D \geq 4$ dimensions at the two-derivative level. It is known that the resulting field equations describe an integrable system in two dimensions which can also be obtained by a dimensional reduction of the self-dual Yang-Mills equations in four dimensions. We use this relation to construct a single copy prescription for classes of gravitational solutions in Weyl-Lewis-Papapetrou coordinates. In contrast with previous proposals, we find that the gauge group of the Yang-Mills single copy carries non-trivial information about the gravitational solution. We illustrate our single copy prescription with various examples that include the extremal Reissner-Nordstrom solution, the Kaluza-Klein rotating attractor solution, the Einstein-Rosen wave solution and the self-dual Kleinian Taub-NUT solution., Comment: 54 pages; v2: references added

Natural language generation tools are powerful and effective for generating content. However, language models are known to display bias and fairness issues, making them impractical to deploy for many use cases. We here focus on how fairness issues impact automatically generated test content, which can have stringent requirements to ensure the test measures only what it was intended to measure. Specifically, we review test content generated for a large-scale standardized English proficiency test with the goal of identifying content that only pertains to a certain subset of the test population as well as content that has the potential to be upsetting or distracting to some test takers. Issues like these could inadvertently impact a test taker's score and thus should be avoided. This kind of content does not reflect the more commonly-acknowledged biases, making it challenging even for modern models that contain safeguards. We build a dataset of 601 generated texts annotated for fairness and explore a variety of methods for classification: fine-tuning, topic-based classification, and prompting, including few-shot and self-correcting prompts. We find that combining prompt self-correction and few-shot learning performs best, yielding an F1 score of 0.79 on our held-out test set, while much smaller BERT- and topic-based models have competitive performance on out-of-domain data., Comment: 19 pages, 4 figures, accepted to the 19th Workshop on Innovative Use of NLP for Building Educational Applications

The ISMR profoundly impacts over a billion people across the region. ISMR extremes have been linked to the ENSO and modulated by the Indian Ocean Dipole (IOD). ISMR of 2022 displayed intriguing spatial patterns: above-normal precipitation over the south peninsula and central India, normal over Northwest India, and below-normal over East and NE India. In 2022, La Nina conditions associated with a negative IOD (nIOD), were prevalent over the equatorial Pacific Ocean (PO) and IO. This study investigates the often-overlooked Oceanic subsurface contribution to large-scale atmospheric convection over the tropical IO. By undertaking a comprehensive analysis, we find that strong equatorial westerly wind anomalies prevailed over the equatorial IO during co-occurring years generating eastward propagating downwelling Kelvin waves which deepens the D20 in the eastern equatorial IO. The Kelvin waves then propagates into BoB and gets reflected from southern tip of India as westward propagating Rossby waves deepening the D20 and causing low level wind convergence in the Northern Arabian Sea(NAS). We identify two centres of low-level wind convergence, one over NAS and another over Maritime Continent during co-occurrence years. These wind convergence centres play a pivotal role in channeling moisture towards their core, also, significantly deepen D20, increase the Ocean heat content and thus maintaining warmer SSTs over area of conversions. Together, these interrelated factors create an environment that is conducive for enhanced convective activity over the zone of convergence, enhancing and sustaining the convective conditions. This study underscores the significant contribution of ocean dynamics in shaping large-scale atmospheric convection during the co-occurrence years, highlighting the significance of considering broader Oceanic variables in comprehending and forecasting monsoonal variability., Comment: 47 pages, 10 main figures, 08 supplementary figures; under review in Climate Dynamics

The Smart home possesses the capability of facilitating home services to their users with the systematic advance in The Internet of Things (IoT) and information and communication technologies (ICT) in recent decades. The home service offered by the smart devices helps the users in utilize maximized level of comfort for the objective of improving life quality. As the user and smart devices communicate through an insecure channel, the smart home environment is prone to security and privacy problems. A secure authentication protocol needs to be established between the smart devices and the user, such that a situation for device authentication can be made feasible in smart home environments. Most of the existing smart home authentication protocols were identified to fail in facilitating a secure mutual authentication and increases the possibility of lunching the attacks of session key disclosure, impersonation and stolen smart device. In this paper, Secure Supervised Learning-based Smart Home Authentication Framework (SSL-SHAF) is proposed as are liable mutual authentication that can be contextually imposed for better security. The formal analysis of the proposed SSL-SHAF confirmed better resistance against session key disclosure, impersonation and stolen smart device attacks. The results of SSL-SHAF confirmed minimized computational costs and security compared to the baseline protocols considered for investigation.