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Two-dimensional van der Waals heterostructures are potential game changers both in understanding the fundamental physics and in the realization of various devices that exploit magnetism at the nanoscale. Multiferroic heterostructures comprising a two-dimensional ferroelectric and a two-dimensional ferromagnet are ideal candidates for electrical control of properties of the ferromagnets that can lead to non-volatile memory devices, for example. Relatively new but immensely promising two-dimensional materials, MXene and transition metal dichalcogenides, can be effectively combined to achieve the goal as both have flexibilities in their structures and compositions that are tunable. In this work, using Density Functional Theory, we have investigated the magneto-electric coupling driven transitions in the electronic ground states of VSe$_{2}$-Sc$_{2}$CO$_{2}$ bi-layer and tri-layer heterostructures. Our results demonstrate that the change in the ferroelectric polarisation in the MXene layer leads to changes in the spin-polarized band structures of the magnetic component VSe$_{2}$ enabling a semiconductor to half-metal transition in these heterostructures. We propose several applications of this magneto-electric coupling in these multiferroic heterostructures that can lead to the efficient operation of Field Effect transistors and achieve non-volatility in memory devices at the nanoscale.

1D superconductor-semiconductor nanowires are leading candidates for topological quantum computation due to their ability to host Majorana zero modes (MZMs). However, standard methods for identifying MZMs are often inadequate, particularly in the presence of disorder, where many properties considered to be heralds of MZMs are often generated by trivial disorder induced Andreev bound states. Recent works clearly indicate the need for developing new techniques for identifying and diagnosing MZMs. In this study, we utilize a Vision Transformer-based neural network to predict using tunnel conductance measurements, both whether a device manifests a topological MZMs phase, and also to map out the entire topological phase diagram. We show the ability of our method up to arbitrary confidence ($P>0.9998$) classify a device as possessing a non-trivial MZM-carrying topological phase for a wide variety of disorder parameters. Further, within these regimes we demonstrate an ability to predict from conductance measurements alternative (to the extensively used scattering-matrix-invariant topological indicator) Majorana indicators based on local density of states (LDOS). This work serves as a significant advance offering a step towards the practical realization of Majorana-based quantum devices, enabling a deep-learning understanding of the topological properties in disordered nanowire systems. We validate our method using extensive simulated Majorana results in the presence of disorder, and suggest using this technique for the analysis of experimental data in superconductor-semiconductor hybrid Majorana platforms., Comment: 21 pages, 12 Figures

On High-Performance Computing (HPC) systems, several hyperparameter configurations can be evaluated in parallel to speed up the Hyperparameter Optimization (HPO) process. State-of-the-art HPO methods follow a bandit-based approach and build on top of successive halving, where the final performance of a combination is estimated based on a lower than fully trained fidelity performance metric and more promising combinations are assigned more resources over time. Frequently, the number of epochs is treated as a resource, letting more promising combinations train longer. Another option is to use the number of workers as a resource and directly allocate more workers to more promising configurations via data-parallel training. This article proposes a novel Resource-Adaptive Successive Doubling Algorithm (RASDA), which combines a resource-adaptive successive doubling scheme with the plain Asynchronous Successive Halving Algorithm (ASHA). Scalability of this approach is shown on up to 1,024 Graphics Processing Units (GPUs) on modern HPC systems. It is applied to different types of Neural Networks (NNs) and trained on large datasets from the Computer Vision (CV), Computational Fluid Dynamics (CFD), and Additive Manufacturing (AM) domains, where performing more than one full training run is usually infeasible. Empirical results show that RASDA outperforms ASHA by a factor of up to 1.9 with respect to the runtime. At the same time, the solution quality of final ASHA models is maintained or even surpassed by the implicit batch size scheduling of RASDA. With RASDA, systematic HPO is applied to a terabyte-scale scientific dataset for the first time in the literature, enabling efficient optimization of complex models on massive scientific data. The implementation of RASDA is available on https://github.com/olympiquemarcel/rasda, Comment: submitted to Future Generation Computer Systems

Natural faults often contain a fluid-saturated, granular fault-gouge layer, whose failure and sliding processes play a central role in earthquake dynamics. Using a two-dimensional discrete element model coupled with fluid dynamics, we simulate a fluid-saturated granular layer, where fluid pressure is incrementally raised. At a critical fluid pressure level, the layer fails and begins to accelerate. When we gradually reduce fluid pressure, a distinct behavior emerges: slip-rate decreases linearly until the layer halts at a fluid pressure level below that required to initiate failure. During this pressure cycle the system exhibits (1) velocity-strengthening friction and (2) frictional hysteresis. These behaviors, well established in dry granular media, are shown to extend here to shear of dense fluid-saturated granular layers. Additionally, we observe a delay between fluid pressure increase and failure, associated with pre-failure dilative strain and "dilational-hardening". During the delay period, small, arrested slip events dilate the layer in preparation for full-scale failure. Our findings may explain (i) fault motion that continues even after fluid pressure returns to pre-injection levels, and (ii) delayed failure in fluid-injection experiments, and (iii) pre-failure arrested slip events observed prior to earthquakes.

A partition is said to be $\ell$-regular if none of its parts is a multiple of $\ell$. Let $b^\prime_5(n)$ denote the number of 5-regular partitions into distinct parts (equivalently, into odd parts) of $n$. This function has also close connections to representation theory and combinatorics. In this paper, we study arithmetic properties of $b^\prime_5(n)$. We provide full characterization of the parity of $b^\prime_5(2n+1)$, present several congruences modulo 4, and prove that the generating function of the sequence $(b^\prime_5(5n+1))$ is lacunary modulo any arbitrary positive powers of 5., Comment: To appear in the International Journal of Number Theory

This work solves an open problem regarding the rate of time-bounded Kolmogorov complexity and polynomial-time dimension, conditioned on a hardness assumption. Hitchcock and Vinodchandran (CCC 2004) show that the polynomial-time dimension of infinite sequences (denoted ${\mathrm{cdim}}_\mathrm{P}$) defined using betting algorithms called gales, is lower bounded by the asymptotic lower rate of polynomial-time Kolmogorov complexity (denoted $\mathcal{K}_\text{poly}$). Hitchcock and Vindochandran and Stull asked whether the converse relationship also holds. This question has thus far resisted resolution. The corresponding unbounded notions, namely, the constructive dimension and the asymptotic lower rate of unbounded Kolmogorov complexity are equal for every sequence. Analogous notions are equal even at finite-state level. In view of these results, it is reasonable to conjecture that the polynomial-time quantities are identical for every sequence and set of sequences. However, under a plausible assumption which underlies modern cryptography - namely the existence of one-way functions, we refute the conjecture thereby giving a negative answer to the open question posed by Hitchcock and Vinodchandran and Stull . We show the following, conditioned on the existence of one-way functions: There are sets $\mathcal{F}$ of infinite sequences whose polytime dimension strictly exceeds $\mathcal{K}_\text{poly}(\mathcal{F})$, that is ${\mathrm{cdim}}_\mathrm{P}(\mathcal{F}) > \mathcal{K}_\text{poly}(\mathcal{F})$. We establish a stronger version of this result, that there are individual sequences $X$ whose poly-time dimension strictly exceeds $\mathcal{K}_\text{poly}(X)$, that is ${\mathrm{cdim}}_\mathrm{P}(X) > \mathcal{K}_\text{poly}(X)$. Further, we show that the gap between these quantities can be made arbitrarily close to 1. We also establish similar bounds for strong poly-time dimension

In this work, we explore the entanglement structure of two $N = Z$ nuclei, $^{20}$Ne and $^{22}$Na using single-orbital entanglement entropy within the No-Core Shell Model (NCSM) framework for two realistic interactions, INOY and N$^3$LO. We begin with the determination of the optimal frequencies based on the variation of ground-state (g.s.) binding energy with NCSM parameters, $N_{max}$ and $\hbar \Omega$, followed by an analysis of the total single-orbital entanglement entropy, $S_{tot}$, for the g.s. of $^{20}$Ne and $^{22}$Na. Our results show that $S_{tot}$ increases with $N_{max}$ and decreases with $\hbar \Omega$ after reaching a maximum. We use $S_{tot}$ to guide the selection of an additional set of optimal frequencies that can enhance electromagnetic transition strengths. We also calculate the low-energy spectra and $S_{tot}$ for four low-lying states of $^{20}$Ne and six low-lying states of $^{22}$Na. Finally, we calculate a few $E2$ and one $M1$ transition strengths, finding that N$^3$LO provides better results for $B(E2; 5^+_1 \to 3^+_1$) and INOY performs well for the $B(M1; 0_1^+ \to 1_1^+)$ transition in the $^{22}$Na nucleus while considering the first set of optimal frequencies. We also observe that the second set of optimal frequencies enhances electromagnetic transition strengths, particularly for the states with large and comparable $S_{tot}$. Also, for both nuclei, the $S_{tot}$ for INOY and N$^3$LO are close while considering the second set of optimal frequencies, suggesting that the calculated $S_{tot}$ are more dependent on $\hbar \Omega$ than the interactions employed for the same model space defined by the $N_{max}$ parameter., Comment: 15 pages, 5 figures

The sustainability of open source software (OSS) projects hinges on contributor retention. Interpersonal challenges can inhibit a feeling of welcomeness among contributors, particularly from underrepresented groups, which impacts their decision to continue with the project. How much this impact is, varies among individuals, underlining the importance of a thorough understanding of their effects. Here, we investigate the effects of interpersonal challenges on the sense of welcomeness among diverse populations within OSS, through the diversity lenses of gender, race, and (dis)ability. We analyzed the large-scale Linux Foundation Diversity and Inclusion survey (n = 706) to model a theoretical framework linking interpersonal challenges with the sense of welcomeness through Structural Equation Models Partial Least Squares (PLS-SEM). We then examine the model to identify the impact of these challenges on different demographics through Multi-Group Analysis (MGA). Finally, we conducted a regression analysis to investigate how differently people from different demographics experience different types of interpersonal challenges. Our findings confirm the negative association between interpersonal challenges and the feeling of welcomeness in OSS, with this relationship being more pronounced among gender minorities and people with disabilities. We found that different challenges have unique impacts on how people feel welcomed, with variations across gender, race, and disability groups. We also provide evidence that people from gender minorities and with disabilities are more likely to experience interpersonal challenges than their counterparts, especially when we analyze stalking, sexual harassment, and doxxing. Our insights benefit OSS communities, informing potential strategies to improve the landscape of interpersonal relationships, ultimately fostering more inclusive and welcoming communities., Comment: Accepted by 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025)

We develop a light-front model of the proton to investigate the twist-3 chiral-even generalized parton distributions (GPDs) of light sea quarks. In this model, the sea quarks are treated as spin-\(\frac{1}{2}\) active partons, while the remaining proton constituents are modeled as spin-1 spectators. The momentum wave function, predicted by the soft-wall AdS/QCD, is fitted to the unpolarized parton distribution functions (PDFs) from the CETQ global analysis. Using this fitted distribution, we determine the unknown model parameters. We calculate the twist-3 GPDs and analyze their dependence on the transverse momentum transfer, \(\Delta_T^2\), and the longitudinal momentum fraction, \(x\). Additionally, we explore the Mellin moments and the twist-3 chiral-even PDF, \(g_T(x)\), within this theoretical framework., Comment: 13 pages, 7 figures

In this short note, we prove several new congruences for the overcubic partition triples function, using both elementary techniques and the theory of modular forms. These extend the recent list of such congruences given by Nayaka, Dharmendra, and Kumar (2024). We also generalize overcubic partition triples to overcubic partition $k$-tuples and prove a few arithmetic properties for these type of partitions., Comment: 12 pages, to appear in the Bulletin of the Australian Mathematical Society

Large language models (LLMs) have demonstrated impressive performance on several tasks and are increasingly deployed in real-world applications. However, especially in high-stakes settings, it becomes vital to know when the output of an LLM may be unreliable. Depending on whether an answer is trustworthy, a system can then choose to route the question to another expert, or otherwise fall back on a safe default behavior. In this work, we study the extent to which LLMs can reliably indicate confidence in their answers, and how this notion of confidence can translate into downstream accuracy gains. We propose Self-REF, a lightweight training strategy to teach LLMs to express confidence in whether their answers are correct in a reliable manner. Self-REF introduces confidence tokens into the LLM, from which a confidence score can be extracted. Compared to conventional approaches such as verbalizing confidence and examining token probabilities, we demonstrate empirically that confidence tokens show significant improvements in downstream routing and rejection learning tasks.

This work presents a theoretical framework for enhancing quantum correlations in a hybrid double-cavity optomechanical system that hosts an atomic ensemble. We investigate the role of the coupling phase $\phi$ between cavity 1 and the atomic ensemble in optimizing quantum correlations, i.e., bipartite/tripartite quantum entanglement and quantum discord. By employing metrics such as logarithmic negativity for bipartite entanglement and minimum residual contangle for genuine tripartite entanglement, we demonstrate that tuning the phase $\phi$ is essential for maximizing photon-phonon entanglement. Specifically, we find that optimal entanglement occurs at $\phi=n\pi$, with distinct conditions for odd and even integers $n$. Our results also indicate that the quantum entanglement achieved in this system is robust against thermal fluctuations, making it a promising candidate for applications in quantum information processing and quantum computing. Furthermore, this research highlights the significance of phase tuning in controlling quantum correlations, paving the way for advancements in quantum technologies.

In this study, we developed and tested various isospin symmetry-breaking (ISB) versions of the microscopic DJ16A interaction. Starting with the isospin symmetric DJ16A interaction, we introduced two different Coulomb interactions-Coulomb-CD and Coulomb-w/SRC-along with phenomenological charge symmetry breaking (CSB) and charge independence breaking (CIB) effects. We also considered CSB and CIB parts of the Argonne v18 (AV18) interaction. We examined two sets of interactions for each Coulomb interaction and employed these interactions to calculate $b$- and $c$-parameters of the isobaric multiplet mass equation for $|T_z| = 1/2$ and $|T_z| = 1$ nuclei across the $sd$-shell. Our results indicate that the DJ16A$^\dagger$+CD interaction provides the most accurate $b$-parameter predictions up to $A = 33$ mirror pairs. Additionally, we explored mirror energy differences (MEDs) in low-energy spectra around $A = 20$ and demonstrated that large MEDs are primarily associated with high occupancies of the $1s_{1/2}$ orbital. Furthermore, $E2$ transition strengths were calculated using all four DJ16A-based ISB interactions agreed with the experimental data, with minimal ISB effects observed on these transitions. Overall, the DJ16A$^\dagger$+CD interaction serves as a complementary set to the newly developed USD-family interactions, USDC, and USDCm and can be further tested for other mirror nuclei across the $sd$-shell to study nuclear structure properties and ISB effects in nuclear $\beta$-decay., Comment: 18 pages, 14 figures

Nonlinear metasurfaces offer a new paradigm to realize optical nonlinear devices with new and unparalleled behavior compared to nonlinear crystals, due to the interplay between photonic resonances and materials properties. The complicated interdependency between efficiency and emission directionality of the nonlinear optical signal on the existence, localization, and lifetimes of photonic resonances, as well as on the nonlinear susceptibility, makes it extremely difficult to design optimal metasurfaces using conventional materials and geometries. Inverse design using topology optimization is a powerful design tool for photonic structures, but traditional approaches developed for linear photonics are not suitable for such high dimensional nonlinear problems. Here, we use a topology optimization approach to inverse-design a fabrication-robust nonlinear metasurface that includes quantum-engineered resonant nonlinearities in semiconductor heterostructures for efficient and directional second harmonic generation. Furthermore, we also demonstrate that under practical constraints, among all the parameters, the nonlinear modal overlap emerges as the dominant parameter that enhances conversion efficiency, a finding that contrasts with intuition-driven studies that often emphasize Purcell enhancement. Our results open new opportunities for optimizing nonlinear processes in nanophotonic structures for novel light sources, quantum information applications, and communication.

We study a Kerr-modified cavity magnomechanical system with a focus on its bistable regime. We identify a distinct parametric condition under which bistability appears, featuring two stable branches and one unstable branch in the middle. Interestingly, our study reveals a unique transition where the upper branch loses its stability under a sufficiently strong drive, giving rise to limit cycle oscillation. Consequently, we report a rich phase diagram consisting of both bistable and periodic solutions and study quantum correlations around them. While in the bistable regime, we find the entanglement reaching different steady state value, in the unstable regime, entanglement oscillates in time. This study is especially important in understanding quantum entanglement at different stable and unstable points arising in a Kerr-modified cavity magnomechanical system.

The discrete-time Hawkes process (DTHP) is a sub-class of $g$-functions that serves as a discrete-time version of the continuous-time Hawkes process (CTHP). Like the CTHP, the DTHP also has the self-exciting property and its intensity depends on the entire history. In this paper, we study the asymptotic behaviour of the DTHP and its compensator. We further analyse the moment generating function (MGF) of the DTHP and obtain some bounds and convergence results on the scaled logarithmic MGF of the DTHP., Comment: 13 pages, This paper has been published in "Statistics & Probability Letters", DOI: https://doi.org/10.1016/j.spl.2024.110192

We investigate the reduction of measurement-added noise in force sensing by analyzing its power spectral density (PSD) within a hybrid optomechanical system. The setup comprises of an optomechanical cavity equipped with a movable mirror which acts as the mechanical oscillator, a stationary semi-transparent mirror, a superconducting qubit, and an optical parametric amplifier (OPA). By utilizing the concept of coherent quantum noise cancellation (CQNC), we derive the conditions necessary for complete cancellation of back-action force, thereby enhancing force sensitivity. Furthermore, with the gradual increase in the OPA pump gains, we suppress the sensitivity beyond the standard quantum limit (SQL) at a lower value of laser power. The removal of back-action noise, along with the reduction of shot noise, improves force detection capabilities, thereby surpassing the standard quantum limit associated with weak force detection.

We numerically study zeroes of the partition function for trimers ($k = 3$) on $3 \times L$ strip. While such results for dimers ($k = 2$) on 2D lattices are well known to always lie on the negative real axis and are unbounded, here we see that the zeroes are bounded on branches in a finite-sized region and with a considerable number of them being complex. We analyze this result further to numerically study the density of zeroes on such branches, estimating the critical power-law exponents, and make interesting observations on density of filled sites in the lattice as a function of activity $z$., Comment: 12 pages, 13 figures

Designing algorithms for space bounded models with restoration requirements on the space used by the algorithm is an important challenge posed about the catalytic computation model introduced by Buhrman et al. (2014). Motivated by the scenarios where we do not need to restore unless is useful, we define $ACL(A)$ to be the class of languages that can be accepted by almost-catalytic Turing machines with respect to $A$ (which we call the catalytic set), that uses at most $c\log n$ work space and $n^c$ catalytic space. We show that if there are almost-catalytic algorithms for a problem with catalytic set as $A \subseteq \Sigma^*$ and its complement respectively, then the problem can be solved by a ZPP algorithm. Using this, we derive that to design catalytic algorithms, it suffices to design almost-catalytic algorithms where the catalytic set is the set of strings of odd weight ($PARITY$). Towards this, we consider two complexity measures of the set $A$ which are maximized for $PARITY$ - random projection complexity (${\cal R}(A)$) and the subcube partition complexity (${\cal P}(A)$). By making use of error-correcting codes, we show that for all $k \ge 1$, there is a language $A_k \subseteq \Sigma^*$ such that $DSPACE(n^k) \subseteq ACL(A_k)$ where for every $m \ge 1$, $\mathcal{R}(A_k \cap \{0,1\}^m) \ge \frac{m}{4}$ and $\mathcal{P}(A_k \cap \{0,1\}^m)=2^{m/4}$. This contrasts the catalytic machine model where it is unclear if it can accept all languages in $DSPACE(\log^{1+\epsilon} n)$ for any $\epsilon > 0$. Improving the partition complexity of the catalytic set $A$ further, we show that for all $k \ge 1$, there is a $A_k \subseteq \{0,1\}^*$ such that $\mathsf{DSPACE}(\log^k n) \subseteq ACL(A_k)$ where for every $m \ge 1$, $\mathcal{R}(A_k \cap \{0,1\}^m) \ge \frac{m}{4}$ and $\mathcal{P}(A_k \cap \{0,1\}^m)=2^{m/4+\Omega(\log m)}$., Comment: 22 pages, A new lower bound on the subcube partition complexity of Hamming balls (Proposition 2.6 and Lemma 2.7), improving the bound and fixing an error in the previous version

We study the intravalley spin-polarized superconductivity in rhombohedral tetralayer graphene, which has been discovered experimentally in Han $et$ $al$ arXiv:2408.15233. We construct a minimal model for the intravalley spin-polarized superconductivity, assuming a simplified anisotropic interaction that depends only on the angle between the incoming and outgoing momenta. Despite the absence of Fermi surface nesting, we show that the superconductivity appears near the Van Hove singularity with the maximal $T_c$ near a bifurcation point of the peaks in the density of states. We identify the topological $p+ip$, topological $h+ih$, and the non-topological nodal $f$-wave pairings as the possible states, which are all pair density wave orders due to the intravalley nature. Furthermore, these pair density wave orders require a finite attractive threshold for superconductivity, resulting in narrow superconducting regions, consistent with experimental findings. We discuss the possible pairing mechanisms and point out that the Kohn-Luttinger mechanism is a plausible explanation for the intravalley spin-polarized superconductivity in the rhombohedral tetralayer graphene., Comment: 7+5 pages, 3+2 figures

Analogous to Andrews' and Newman's discovery and work on the minimal excludant or "mex" of partitions, we define four new classes of minimal excludants for overpartitions and unearth relations to certain functions due to Ramanujan., Comment: 14 pages. Comments are welcome!

Generative AI (genAI) tools, such as ChatGPT or Copilot, are advertised to improve developer productivity and are being integrated into software development. However, misaligned trust, skepticism, and usability concerns can impede the adoption of such tools. Research also indicates that AI can be exclusionary, failing to support diverse users adequately. One such aspect of diversity is cognitive diversity -- variations in users' cognitive styles -- that leads to divergence in perspectives and interaction styles. When an individual's cognitive style is unsupported, it creates barriers to technology adoption. Therefore, to understand how to effectively integrate genAI tools into software development, it is first important to model what factors affect developers' trust and intentions to adopt genAI tools in practice? We developed a theoretically grounded statistical model to (1) identify factors that influence developers' trust in genAI tools and (2) examine the relationship between developers' trust, cognitive styles, and their intentions to use these tools in their work. We surveyed software developers (N=238) at two major global tech organizations: GitHub Inc. and Microsoft; and employed Partial Least Squares-Structural Equation Modeling (PLS-SEM) to evaluate our model. Our findings reveal that genAI's system/output quality, functional value, and goal maintenance significantly influence developers' trust in these tools. Furthermore, developers' trust and cognitive styles influence their intentions to use these tools in their work. We offer practical suggestions for designing genAI tools for effective use and inclusive user experience., Comment: 13 pages, Accepted by 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025)

The recent experimental observation of fractional quantum anomalous Hall (FQAH) states in rhombohedral multilayer graphene has attracted significant attention. One of the most intriguing observations is that the FQAH states at various fractional fillings give way to IQAH states as the temperature is lowered. In this work, we propose a mechanism for the appearance of FQAH states within a finite temperature range in a toy model. The model consists of a flat Chern band and impurities, and we analyze the effects of impurities on the system's behavior at finite temperatures. We believe that the crossover may arise from the competition between the energy penalty for thermal excitations and the increase in entropy. We support our theoretical argument with numerical calculations using exact diagonalization. Our results suggest that impurities may play a crucial role in the crossover from the FQAH to IQAH states in rhombohedral pentalayer graphene., Comment: 5 pages, 4 figures. Comments are welcome

We report on the first experimental characterization of a laser-wakefield accelerator able to deliver, in a single pulse, doses in excess of \unit[1]{Gy} on timescales of the order of a hundred femtoseconds, reaching unprecedented average dose-rates up to \unit[10$^{13}$]{Gy/s}. The irradiator is demonstrated to deliver doses tuneable up to \unit[2.2]{Gy} in a cm$^2$ area and with a high degree of longitudinal and transverse uniformity in a single irradiation. In this regime, proof-of-principle irradiation of patient-derived glioblastoma stem-like cells and human skin fibroblast cells show indications of a differential cellular response, when compared to reference irradiations at conventional dose-rates. These include a statistically significant increase in relative biological effectiveness ($1.40\pm0.08$ at 50\% survival for both cell lines) and a significant reduction of the relative radioresistance of tumour cells. Data analysis provides preliminary indications that these effects might not be fully explained by induced oxygen depletion in the cells but may be instead linked to a higher complexity of the damages triggered by the ultra-high density of ionising tracks of femtosecond-scale radiation pulses. These results demonstrate an integrated platform for systematic radiobiological studies at unprecedented beam durations and dose-rates, a unique infrastructure for translational research in radiobiology at the femtosecond scale., Comment: 29 pages, 11 figures, Paper submission

We predict large regions of the charge stability diagram using a multi-band and multi-electron configuration interaction model of a double quantum dot system. We account for many-body interactions within each quantum dot using full configuration interaction and solve for single-particle density operators. This allows charge states to be predicted more accurately than the extensively used classical capacitance model or the single-band Hubbard model. The resulting single-particle mixed states then serve as inputs into an atomic orbital picture that allows for the explicit calculation of the underlying Hubbard model parameters by performing the appropriate integrals. This numerical approach allows for arbitrary choices of electrostatic potential and gate geometry. A common assumption when calculating charge stability diagrams from the Hubbard model is that the charge stability diagrams are periodic, but we find that the tunnel couplings for valence electrons in dots with $N=3$ electrons are significantly enhanced when compared to single-electron dots. This difference is apparent in the charge stability diagram for higher occupancy Coulomb diamonds. We also quantitatively explore how the barrier gate strength and dot pitch impact this behavior. Our work should help improve the future realistic modeling of semiconductor-dot-based quantum circuits., Comment: Published version. 13 pages, 13 figures

The exploration of deep neural networks for optimal control has gathered a considerable amount of interest in recent years. Here, we utilize deep reinforcement learning to control individual evolutions of coupled harmonic oscillators in an oscillator network. Our work showcases a numerical approach to actively cool internal oscillators to their thermal ground states through modulated forces imparted to the external oscillators in the network. We present our results for thermal cooling of all oscillators in multiple network configurations and introduce the utility of our scheme in the quantum regime., Comment: The submission contains 6 (main text) + 8 (supplementary) pages with (5 + 6) figures and 1 table. For a demonstration of the cooling, see https://youtu.be/Pu-sReKY1KY

Recently, Drema and N. Saikia (2023) and M. P. Saikia, Sarma, and Sellers (2023) proved several congruences modulo powers of $2$ for overpartition triples with odd parts. In this paper, we study further divisibility properties of overpartition $k$-tuples with odd parts using elementary means as well as properties of modular forms. In particular, we prove several congruences modulo multiples of $3$, and an infinite family of congruences modulo powers of $3$; we also prove some cases of a conjecture of Saikia, Sarma, and Sellers., Comment: 21 pages

By theoretically analyzing the recent temperature dependent transport data in pentalayer graphene [Lu et al., arXiv:2408.10203], we establish that the experimentally observed transition from low-temperature quantum anomalous Hall effect to higher-temperature fractional quantum anomalous Hall effect is a crossover phenomenon arising from the competition between interaction and disorder energy scales, with the likely zero temperature ground state of the system being either a localized insulator or a Chern insulator with a quantized anomalous Hall effect. In particular, the intriguing suppression of FQAHE in favor of QAHE with decreasing temperature is explained as arising from the low-temperature localization of the carriers where disorder overcomes the interaction effects. We provide a detailed analysis of the data in support of the crossover scenario., Comment: Published version

Hole spin qubits in Ge, investigated for all-electrical spin manipulation because of its large spin-orbit coupling, are exposed to charge noise leading to decoherence. Here we construct a model of $1/f$ noise from individual fluctuators and determine the dephasing time $T_2^*$ as a function of qubit properties. $T_2^*$ decreases with increasing magnetic field and is an order of magnitude longer for out-of-plane than for in-plane fields for the same Zeeman energy. $T_2^*$ shows little variation as a function of the top gate field and is a complex function of the dot radius. Our results should help experiments to enhance coherence in hole qubit architectures., Comment: 5 pages, 5 figures

We investigate the fractional quantum anomalous Hall (FQAH) effect in rhombohedral multilayer graphene (RnG) in the presence of a strong applied displacement field. We first introduce the interacting model of RnG, which includes the noninteracting continuum model and the many-body Coulomb interaction. We then discuss the integer quantum anomalous Hall (IQAH) effect in RnG and the role of the Hartree-Fock approach in understanding its appearance. Next, we explore the FQAH effect in RnG for $n=3$--$6$ using a combination of constrained Hartree-Fock and exact diagonalization methods. We characterize the stability of the FQAH phase by the size of the FQAH gap and find that RnG generally has a stable FQAH phase, although the required displacement field varies significantly among different $n$ values. Our work establishes the theoretical universality of both IQAH and FQAH in RnG., Comment: 6 pages, 3 figures. Comments are welcome

Studies show that the model-independent, fully non-perturbative covariant cosmographic approach is suitable for analyzing the local Universe $(z\lesssim 0.1)$. However, accurately characterizing large and inhomogeneous mass distributions requires the fourth-order term in the redshift expansion of the covariant luminosity distance $d_L(z,\boldsymbol{n})$. We calculate the covariant snap parameter $\mathbb{S}$ and its spherical harmonic multipole moments using the matter expansion tensor and the evolution equations for lightray bundles. The fourth-order term adds 36 degrees of freedom, since the highest independent multipole of the snap is the 32-pole (dotriacontapole) $(\ell=5)$. Including this term helps to de-bias estimations of the covariant deceleration parameter. Given that observations suggest axially symmetric anisotropies in the Hubble diagram for $z \lesssim 0.1$ and theory shows that only a subset of multipoles contributes to the signal, we demonstrate that only 12 degrees of freedom are needed for a model-independent description of the local universe. We use an analytical axisymmetric model of the local Universe, with data that matches the Zwicky Transient Facility survey, in order to provide a numerical example of the amplitude of the snap multipoles and to forecast precision., Comment: 13 + 7 pages

Electrochemical cells employing Sodium (Na) and Zinc (Zn) electrodes and a chloride salt electrolyte have been imaged by neutron radiography during cycling. The use of such abundant raw materials confers a very low energy-normalised cost to the Na-Zn system, but its operation requires them to be entirely molten, and therefore to be operated at 600 {\deg}C. To suppress the self-discharge that results from this all-molten configuration, porous ceramic diaphragms are used to partition the electrolyte and thereby impede the movement of the Zn2+ ions responsible towards the Na electrode. Neutron images reveal large gas bubbles trapped beneath these diaphragms, formed during the cell fabrication process due to the large volume change that accompanies melting/solidifying of the electrolyte. Cycling data confirm that these bubbles interfere with cell operation by substantially increasing ohmic resistance. They indicate the need for either a new diaphragm design, or a cell fabrication process that prevents their formation in the first instance., Comment: 8 pages, 3 figures

The Kitaev chain can be engineered within a quantum dot-superconductor array, hosting Majorana zero modes at fine-tuned sweet spots. In this work, we propose and simulate the occurrence of Rabi and Ramsey oscillations to feasibly construct a minimal Majorana qubit in the quantum dot setup. Our real-time results incorporate realistic effects, e.g., charge noise and leakage, reflecting the latest experimental progress. We demonstrate that Majorana qubits with larger energy gaps exhibit significantly enhanced performance -- longer dephasing times, higher quality factors, reduced leakage probabilities, and improved visibilities -- compared to those with smaller gaps and with conventional quantum dot-based charge qubits. We introduce a method for reading out Majorana qubits via quantum capacitance measurements. Our work paves the way for future experiments on realizing Majorana qubits in quantum dot-superconductor arrays., Comment: 7 Pages, 4 figures

Hand gesture recognition allows humans to interact with machines non-verbally, which has a huge application in underwater exploration using autonomous underwater vehicles. Recently, a new gesture-based language called CADDIAN has been devised for divers, and supervised learning methods have been applied to recognize the gestures with high accuracy. However, such methods fail when they encounter unseen gestures in real time. In this work, we advocate the need for zero-shot underwater gesture recognition (ZSUGR), where the objective is to train a model with visual samples of gestures from a few ``seen'' classes only and transfer the gained knowledge at test time to recognize semantically-similar unseen gesture classes as well. After discussing the problem and dataset-specific challenges, we propose new seen-unseen splits for gesture classes in CADDY dataset. Then, we present a two-stage framework, where a novel transformer learns strong visual gesture cues and feeds them to a conditional generative adversarial network that learns to mimic feature distribution. We use the trained generator as a feature synthesizer for unseen classes, enabling zero-shot learning. Extensive experiments demonstrate that our method outperforms the existing zero-shot techniques. We conclude by providing useful insights into our framework and suggesting directions for future research., Comment: Accepted to ICPR 2024. 15 pages, 6 figures. Project page: https://github.com/sandipan211/ZSUGR

Quantum Parameter Estimation (QPE) is important from the perspective of both fundamental quantum research and various practical applications of quantum technologies such as for developing optimal quantum control strategies. Standard and traditional methods for QPE involve projective measurements on thousands of identically prepared quantum systems. However, these methods face limitations, particularly in terms of the required number of samples and the associated experimental resources. In this work, we present a novel method for precise QPE that diverges from conventional techniques, employs continuous measurements, and enables accurate QPE with a single quantum trajectory. In an application, we demonstrate the use of the method for the task of parameter estimation and force sensing of a levitated nanoparticle., Comment: 6 pages, 4 figures

The design and synthesis of masked cryptographic hardware implementations that are secure against power side-channel attacks (PSCAs) in the presence of glitches is a challenging task. High-Level Synthesis (HLS) is a promising technique for generating masked hardware directly from masked software, offering opportunities for design space exploration. However, conventional HLS tools make modifications that alter the guarantee against PSCA security via masking, resulting in an insecure RTL. Moreover, existing HLS tools can't place registers at designated places and balance parallel paths in a cryptographic design which is needed to stop glitch propagation. This paper introduces a domain-specific HLS approach tailored to obtain a PSCA secure masked hardware implementation directly from a masked software implementation. It places the registers at specific locations required by the glitch-robust masking gadgets, resulting in a secure RTL. Moreover, our tool automatically balances parallel paths and facilitates a reduction in latency while preserving the PSCA security guaranteed by masking. Experimental results with the PRESENT Cipher's S-box and AES Canright's S-box masked with four state-of-the-art gadgets, show that MaskedHLS produces RTLs with 73.9% decrease in registers and 45.7% decrease in latency on an average} compared to manual register insertions. The PSCA security of the MaskedHLS generated RTLs is also shown with TVLA test.

Single-stranded RNA viruses co-assemble their capsid with the genome and variations in capsid structures can have significant functional relevance. In particular, viruses need to respond to a dehydrating environment to prevent genomic degradation and remain active upon rehydration. Theoretical work has predicted low-energy buckling transitions in icosahedral capsids which could protect the virus from further dehydration. However, there has been no direct experimental evidence, nor molecular mechanism, for such behaviour. Here we observe this transition using X-ray single particle imaging of MS2 bacteriophages after aerosolization. Using a combination of machine learning tools, we classify hundreds of thousands of single particle diffraction patterns to learn the structural landscape of the capsid morphology as a function of time spent in the aerosol phase. We found a previously unreported compact conformation as well as intermediate structures which suggest an incoherent buckling transition which does not preserve icosahedral symmetry. Finally, we propose a mechanism of this buckling, where a single 19-residue loop is destabilised, leading to the large observed morphology change. Our results provide experimental evidence for a mechanism by which viral capsids protect themselves from dehydration. In the process, these findings also demonstrate the power of single particle X-ray imaging and machine learning methods in studying biomolecular structural dynamics., Comment: 10 pages, 4 figures plus 9 pages supplementary information

The fractional quantum anomalous Hall (FQAH) effect in rhombohedral pentalayer graphene (PLG) has attracted significant attention due to its potential for observing exotic quantum states. In this work, we present a self-consistent Hartree-Fock theory for the FQAH effect in rhombohedral PLG. In particular, we focus on the convergence of the Hartree-Fock calculation with various reference fields and discuss the stability of the FQAH states in PLG. We show that the so-called charge neutrality scheme provides an unambiguous result for the Hartree-Fock calculation, as it ensures a convergence with respect to the momentum cutoff. Based on the Hartree-Fock band structure, we further carry out exact diagonalization calculations to explore the stability of the FQAH states in PLG. Our work provides an improved and unified (minimal) theoretical framework to understand the FQAH effect in rhombohedral PLG and paves the way for future experimental and theoretical studies., Comment: 19 pages, 12 figures. Comments are welcome

We show a transition from a bound state to a continuum resonance in a shallow quantum well (QW) by electrostatic gating to bend the conduction band edge. This bound state-continuum resonance (BSCR) transition is particularly relevant in topological quantum computing platforms where shallow InAs QWs are used. We predict the observed capacitance jump and the parallel metal-insulator transition accompanied the BSCR transition. An experimental puzzle in shallow InAs QWs is the mobility drop at an electron density smaller than expected for the bound-state second subband occupation. We explain this puzzle as a result of intersubband scattering involving a level-broadened continuum resonance, mediated by screened Coulomb impurities., Comment: Main text: 5 pages, 3 figures, 1 table. Supplemental materials: 6 pages, 3 figures, 2 tables

We consider the well-known phonon scattering induced high-temperature linear-in-$T$ metallic resistivity, showing that a naive extrapolation of the effective linearity from high temperatures to $T=0$ leads to an apparent zero-temperature negative resistivity. The precise magnitude of this extrapolated $T=0$ negative resistivity depends on the temperature regime from where the extrapolation is carried out, and approaches the correct physical result of zero resistivity at $T=0$ only if the extrapolation starts from $T\gg T_D$, where $T_D$ is the Debye temperature. We establish a theoretical relationship between the negative intercept and the slope of the linear-in-$T$ resistivity as a function of the temperature $T$ from where the extrapolation is carried out. Experimental implications of our finding are discussed for the much-discussed Planckian behavior of the transport scattering rate., Comment: 7 pages, 6 figures

For the first time, robust superconductivity has been independently observed in twisted WSe$_2$ bilayers by two separate groups [Y. Xia et al., arXiv:2405.14784; Y. Guo et al., arXiv:2406.03418.]. In light of this, we explore the possibility of a universal superconducting pairing mechanism in twisted WSe$_2$ bilayers. Using a continuum band structure model and a phenomenological boson-mediated effective electron-electron attraction, we find that intervalley intralayer pairing predominates over interlayer pairing. Notably, despite different experimental conditions, both twisted WSe$_2$ samples exhibit a comparable effective attraction strength. This consistency suggests that the dominant pairing glue is likely independent of the twist angle and layer polarization, pointing to a universal underlying boson-induced pairing mechanism.

We investigate magic-angle twisted bilayer graphene (MATBG) with proximity-induced Ising and Rashba spin-orbit couplings (SOC) in the top layer, as recently achieved experimentally. Utilizing the Bistritzer-MacDonald model with SOCs, we reveal a rich single-particle topological phase diagram featuring topological flat bands across different twist angles and interlayer hopping energies. The evolution of Dirac cones and Chern numbers is examined to understand the topological phase transitions. We find that all phases can be achieved with an experimentally accessible SOC strength ($\sim$1 meV) in systems with angles very close to the magic angle. Furthermore, the van Hove singularity for each topological flat band splits in the presence of SOC, significantly altering the electronic properties. Additionally, we investigate the spin textures of each band in momentum space, discovering a skyrmion-like spin texture in the center of the moir\'e Brillouin zone, which is correlated with the topological phase transitions and can be tuned via the SOCs and an out-of-plane electric field. Our findings provide a comprehensive understanding of the topological flat bands, establishing a foundation for grasping the intrinsic and rich roles of SOCs in MATBG., Comment: 19 pages, 20 figures

Recent experiments have measured flux dependent capacitance at radio frequencies leading to the potential for a fast parity read-out of a Majorana qubit. In this work we argue that the quantum dot used in the capacitance measurement can be reasonably approximated by a non-interacting weakly coupled orbital. We then predict the measured flux and parity dependent capacitance for several parameter regimes of the disordered Majorana nanowire model that are both topological and trivial. Following this we study how such a fast capacitance read-out can be used to characterize the quantum coherence of a Majorana nanowire-based qubit using Rabi oscillations. We additionally show that such measurements, if made possible by coherent inter-wire tunneling, would provide a valuable way of characterizing the low energy states in the frequency domain., Comment: 7 pages, 6 figures

We give combinatorial interpretations of two residual cranks of overpartitions defined by Bringmann, Lovejoy and Osburn in 2009 analogous to the crank of partitions given by Andrews and the first author in 1988. As a consequence, we give new versions of their definitions without adjusted weights. Furthermore, we investigate the combinatorial interpretation of an $M_2$-crank of partitions without repeated odd parts and explore connections of these statistics with their companion rank counterparts and the tenth order mock theta functions of Ramanujan.

We study an interacting composite $(1+1/n)$ Abelian helical edge state made of a regular helical liquid carrying charge $e$ and a (fractionalized) helical liquid carrying charge $e/n$. A systematic framework is developed for these composite $(1+1/n)$ Abelian helical edge states with $n=1,2,3$. For $n=2$, the composite edge state consists of a regular helical Luttinger liquid and a fractional topological insulator (the Abelian $Z_4$ topological order) edge state arising from half-filled conjugated Chern bands. The composite edge state with $n=2$ is pertinent to the recent twisted MoTe$_2$ experiment, suggesting a possible fractional topological insulator with conductance $\frac{3}{2}\frac{e^2}{h}$ per edge. Using bosonization, we construct generic phase diagrams in the presence of $weak$ Rashba spin-orbit coupling. In addition to a phase of free bosons, we find a time-reversal symmetry-breaking localized insulator, two perfect positive drag phases, a perfect negative drag phase (for $n=2,3$), a time-reversal symmetric Anderson localization (only for $n=1$), and a disorder-dominated metallic phase analogous to the $\nu=2/3$ disordered fractional quantum Hall edges (only for $n=3$). We further compute the two-terminal edge-state conductance, the primary experimental characterization for the (fractional) topological insulator. Remarkably, the negative drag phase gives rise to an unusual edge-state conductance, $(1-1/n)\frac{e^2}{h}$, not directly associated with the filling factor. We further investigate the effect of an applied in-plane magnetic field. For $n>1$, the applied magnetic field can result in a phase with edge-state conductance $\frac{1}{n}\frac{e^2}{h}$, providing another testable signature. Our work establishes a systematic understanding of the composite $(1+1/n)$ Abelian helical edge, paving the way for future experimental and theoretical studies., Comment: 22 pages and 6 figures. Published version

We present an efficient physics-informed neural networks (PINNs) framework, termed Adaptive Interface-PINNs (AdaI-PINNs), to improve the modeling of interface problems with discontinuous coefficients and/or interfacial jumps. This framework is an enhanced version of its predecessor, Interface PINNs or I-PINNs (Sarma et al.; https://dx.doi.org/10.2139/ssrn.4766623), which involves domain decomposition and assignment of different predefined activation functions to the neural networks in each subdomain across a sharp interface, while keeping all other parameters of the neural networks identical. In AdaI-PINNs, the activation functions vary solely in their slopes, which are trained along with the other parameters of the neural networks. This makes the AdaI-PINNs framework fully automated without requiring preset activation functions. Comparative studies on one-dimensional, two-dimensional, and three-dimensional benchmark elliptic interface problems reveal that AdaI-PINNs outperform I-PINNs, reducing computational costs by 2-6 times while producing similar or better accuracy., Comment: 17 pages, 8 figures, 6 tables