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Auto-SPICE is the first fully automated framework leveraging large language models (LLMs) to generate Simulation Programs with Integrated Circuit Emphasis (SPICE) netlists. It addresses a long-standing challenge in automating netlist generation for analog circuits within circuit design automation. Automating this workflow could accelerate the creation of finetuned LLMs for analog circuit design and verification. We identify key challenges in this automation and evaluate the multi-modal capabilities of state-of-the-art LLMs, particularly GPT-4, to address these issues. We propose a three-step workflow to overcome current limitations: labeling analog circuits, prompt tuning, and netlist verification. This approach aims to create an end-to-end SPICE netlist generator from circuit schematic images, tackling the long-standing hurdle of accurate netlist generation. Our framework demonstrates significant performance improvements, tested on approximately 2,100 schematics of varying complexity. We open-source this solution for community-driven development.

Here we present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first bootstrap a model based on simulation with access to the full statevector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

The majority of atomic nuclei have deformed shapes and nearly all these shapes are symmetric with respect to reflection. There are only a few reflection asymmetric pear-shaped nuclei that have been found in actinide and lanthanide regions, which have static octupole deformation. These nuclei possess an intrinsic electric dipole moment due to the shift between the center of charge and the center of mass. This manifests in the enhancement of the electric dipole transition rates. In this article, we report on the measurement of the lifetimes of the high spin levels of the two alternate parity bands in $^{100}$Ru through the Doppler Shift Attenuation Method. The estimated electric dipole transition rates have been compared with the calculated transition rates using the triaxial projected shell model without octupole deformation, and are found to be an order of magnitude enhanced. Thus, the observation of seven inter-leaved electric dipole transitions with enhanced rates establish $^{100}$Ru as possibly the first octupole deformed nucleus reported in the A $\approx$ 100 mass region.

We focus on a sample of 42 sources in the vicinity of the bow-shock source IRS 1W (N-sources), located at the distance of $6.05''$ north-east of the supermassive black hole (SMBH) Sagittarius A* (Sgr A*), within the radius of $1.35''$. We present the first proper motion measurements of N-sources and find that a larger subset of N-sources (28 sources) exhibit a north-westward flying angle. These sources can be bound by an intermediate mass black hole (IMBH) or the concentration that we observe is due to a disk-like distribution projection along the line of sight. We detect the N-sources in $H$, $K_s$, and $L$' bands. The north-westward flying sources could be a bound collection of stars. We discuss a tentative existence of an IMBH or an inclined disk distribution to explain a significant overdensity of stars. The first scenario of having an IMBH implies the lower limit of $\sim 10^4~M_\odot$ for the putative IMBH. Our measurements for the first time reveal that the dense association of stars containing IRS 1W is a co-moving group of massive, young stars. This stellar association might be the remnant core of a massive stellar cluster that is currently being tidally stripped as it inspirals towards Sgr A*. The second scenario suggests that the appearance of the N-sources might be influenced by the projection of a disk-like distribution of younger He-stars and/or dust-enshrouded stars., Comment: 21 pages, 17 figures; published in the Astrophysical Journal

Let $D$ be a digraph of order $n$ with adjacency matrix $A(D)$. For $\alpha\in[0,1)$, the $A_{\alpha}$ matrix of $D$ is defined as $A_{\alpha}(D)=\alpha {\Delta}^{+}(D)+(1-\alpha)A(D)$, where ${\Delta}^{+}(D)=\mbox{diag}~(d_1^{+},d_2^{+},\dots,d_n^{+})$ is the diagonal matrix of vertex outdegrees of $D$. Let $\sigma_{1\alpha}(D),\sigma_{2\alpha}(D),\dots,\sigma_{n\alpha}(D)$ be the singular values of $A_{\alpha}(D)$. Then the trace norm of $A_{\alpha}(D)$, which we call $\alpha$ trace norm of $D$, is defined as $\|A_{\alpha}(D)\|_*=\sum_{i=1}^{n}\sigma_{i\alpha}(D)$. In this paper, we study the variation in $\alpha$ trace norm of a digraph when a vertex or an arc is deleted. As an application of these results, we characterize oriented trees and unicyclic digraphs with maximum $\alpha$ trace norm.

We explore the consequences of varying the pump beam waist that illuminates a nonlinear crystal, realizing spontaneous parametric down-conversion (SPDC). The coherence is transferred from the marginal one-photon wavefunction to the two-photon wavefunction where it manifests into entanglement in the form of spatial correlation. We interpret this as a consequence of the number of independent emitters, called the biphoton birth zones, targeted by the pump beam on the crystal. The birth zone number $N$ characterises the number of such birth zones that fit along a diameter of the region illuminated by the pump waist. To experimentally observe the duality between the one- and two-photon interference, we employ a double slit and analyse their visibilities $V_m$ and $V_\text{12}$ respectively. We demonstrate the conservation of the quantity $V_m^2+V_\text{12}^2$. Finally, we identify three regimes of entanglement of the down-converted photons based on $N$. We show that changing the pump waist lets us actively control the degree of entanglement letting us access these regimes. We provide implications of each regime, and mention experimental use cases thereof., Comment: 11 pages, 5 figures

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mis-modeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

Ferroelectric field-effect transistors integrated on 2D semiconducting platforms are extremely relevant for low power electronics. Here, we propose and demonstrate a novel phase-change ferroelectric field effect transistor (PCFE-FET) for steep switching applications. Our gate stack is engineered as a ferroelectric Lanthanum doped hafnium oxide (LHO) proximity coupled with Mott insulator Ti$_x$O$_{2x-1}$(N$_y$) and is integrated onto a 2D MoS$_2$ channel. The interplay of partial polarization switching in the ferroelectric LHO layer and reversible field-tunable metal-insulator transition (MIT) in Ti$_x$O$_{2x-1}$(N$_y$) layer concomitantly triggers polar to non-polar phase transition in the LHO layer between 200 and 220 K. This results in distinctive step-like features in the channel current during DC measurements, and random current fluctuations in high-speed measurements with slim anticlockwise hysteresis. Our devices show subthreshold slopes as steep as 25 mV/dec at 210 K, breaking the Boltzmann limit. Our gate stack is also potentially tunable for operation at temperatures of interest, presenting innovative gate stack engineering approaches for low-power computing solutions.

The Vela pulsar (J0835-4510) is known to exhibit variations in Faraday rotation and dispersion on multi-decade timescales due to the changing sightline through the surrounding Vela supernova remnant and the Gum Nebula. Until now, variations in Faraday rotation towards Vela have not been studied on timescales less than around a decade. We present the results of a high-cadence observing campaign carried out with the Aperture Array Verification System 2 (AAVS2), a prototype SKA-Low station, which received a significant bandwidth upgrade in 2022. We collected observations of the Vela pulsar and PSR J0630-2834 (a nearby pulsar located outside the Gum Nebula), spanning $\sim 1\,\mathrm{yr}$ and $\sim 0.3\,\mathrm{yr}$ respectively, and searched for linear trends in the rotation measure (RM) as a function of time. We do not detect any significant trends on this timescale ($\sim$months) for either pulsar, but the constraints could be greatly improved with more accurate ionospheric models. For the Vela pulsar, the combination of our data and historical data from the published literature have enabled us to model long-term correlated trends in RM and dispersion measure (DM) over the past two decades. We detect a change in DM of $\sim 0.3\,\mathrm{cm}^{-3}\,\mathrm{pc}$ which corresponds to a change in electron density of $\sim 10^5\,\mathrm{cm}^{-3}$ on a transverse length scale of $\sim$1-2 au. The apparent magnetic field strength in the time-varying region changes from $240^{+30}_{-20}\,\mu\mathrm{G}$ to $-6.2^{+0.7}_{-0.9}\,\mu\mathrm{G}$ over the time span of the data set. As well as providing an important validation of polarimetry, this work highlights the pulsar monitoring capabilities of SKA-Low stations, and the niche science opportunities they offer for high-precision polarimetry and probing the microstructure of the magneto-ionic interstellar medium., Comment: 16 pages, 9 figures, 2 tables, published in PASA

We introduce Dynamic Information Sub-Selection (DISS), a novel framework of AI assistance designed to enhance the performance of black-box decision-makers by tailoring their information processing on a per-instance basis. Blackbox decision-makers (e.g., humans or real-time systems) often face challenges in processing all possible information at hand (e.g., due to cognitive biases or resource constraints), which can degrade decision efficacy. DISS addresses these challenges through policies that dynamically select the most effective features and options to forward to the black-box decision-maker for prediction. We develop a scalable frequentist data acquisition strategy and a decision-maker mimicking technique for enhanced budget efficiency. We explore several impactful applications of DISS, including biased decision-maker support, expert assignment optimization, large language model decision support, and interpretability. Empirical validation of our proposed DISS methodology shows superior performance to state-of-the-art methods across various applications.

Nonlinear superconducting circuits can be used as amplifiers, transducers, and qubits. Only a handful of superconducting circuits have been analyzed or built, so many high-performing configurations likely remain undiscovered. We seek to catalog this design space by enumerating all superconducting circuits -- up to five nodes in size -- built of capacitors, inductors, and Josephson junctions. Using graph isomorphism, we remove redundant configurations to construct a set of unique circuits. We define the concept of a ``Hamiltonian class'' and sort the resulting circuit Hamiltonians based on the types of variables present and the structure of their coupling. Finally, we search for novel superconducting qubits by explicitly considering all three node circuits, showing how the results of our enumeration can be used as a starting point for circuit design tasks., Comment: 16 pages, 11 figures, 11 tables

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low energy ($<$3 MeV) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV $^{208}$Tl decay $\gamma$ rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of $^{208}$Tl in the fiberglass composing these struts, $(11.7 \pm 0.2 ~\text{(stat)} \pm 2.8~\text{(syst)})~\text{Bq/kg}$. Cosmogenically-produced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated CORSIKA cosmic ray simulations, suggesting either incorrect CORSIKA modeling of incident cosmic fluxes or particle transport modeling issues in Geant4., Comment: 19 pages, 15 figures total including the supplementary material section, 1 table. CC BY license

Long and short baseline neutrino oscillation experiments, such as DUNE, ANNIE, SBND, demand high precision in reducing systematic errors, particularly those related to neutrino-nucleus interaction cross-sections. The stroboscopic approach offers a method to capture distinct neutrino energy spectra, aiding in the separation of flux and cross-section uncertainties. This report outlines the creation of short proton bunch lengths and the transport of a narrow beam down the Booster Neutrino Beamline, essential steps for the successful implementation of the stroboscopic approach.

Hypervelocity white dwarfs (HVWDs) are stellar remnants moving at speeds exceeding the Milky Way's escape velocity. The origins of the fastest HVWDs are enigmatic, with proposed formation scenarios facing challenges explaining both their extreme velocities and observed properties. Here we report a three-dimensional hydrodynamic simulation of a merger between two hybrid helium-carbon-oxygen white dwarfs (HeCO WDs with masses of 0.68 and 0.62 M$_\odot$). We find that the merger leads to a partial disruption of the secondary WD, coupled with a double-detonation explosion of the primary WD. This launches the remnant core of the secondary WD at a speed of $~2000$ km s$^{-1}$, consistent with observed HVWDs. The low mass of the ejected remnant and its heating from the primary WD's ejecta explain the observed luminosities and temperatures of hot HVWDs, which are otherwise difficult to reconcile with previous models. This discovery establishes a new formation channel for HVWDs and points to a previously unrecognized pathway for producing peculiar Type Ia supernovae and faint explosive transients., Comment: 13 pages, 6 figures. Comments welcome!

This paper presents a novel approach to solving convex optimization problems by leveraging the fact that, under certain regularity conditions, any set of primal or dual variables satisfying the Karush-Kuhn-Tucker (KKT) conditions is necessary and sufficient for optimality. Similar to Theory-Trained Neural Networks (TTNNs), the parameters of the convex optimization problem are input to the neural network, and the expected outputs are the optimal primal and dual variables. A choice for the loss function in this case is a loss, which we refer to as the KKT Loss, that measures how well the network's outputs satisfy the KKT conditions. We demonstrate the effectiveness of this approach using a linear program as an example. For this problem, we observe that minimizing the KKT Loss alone outperforms training the network with a weighted sum of the KKT Loss and a Data Loss (the mean-squared error between the ground truth optimal solutions and the network's output). Moreover, minimizing only the Data Loss yields inferior results compared to those obtained by minimizing the KKT Loss. While the approach is promising, the obtained primal and dual solutions are not sufficiently close to the ground truth optimal solutions. In the future, we aim to develop improved models to obtain solutions closer to the ground truth and extend the approach to other problem classes.

The linear canonical transform (LCT) serves as a powerful generalization of the Fourier transform (FT), encapsulating various integral transforms within a unified framework. This versatility has made it a cornerstone in fields such as signal processing, optics, and quantum mechanics. Extending this concept to quaternion algebra, the Quaternion Fourier Transform (QFT) emerged, enriching the analysis of multidimensional and complex-valued signals. The Quaternion Linear Canonical Transform (QLCT), a further generalization, has now positioned itself as a central tool across various disciplines, including applied mathematics, engineering, computer science, and statistics. In this paper, we introduce the Two Dimensional Quaternion Linear Canonical Transform (2DQLCT) as a novel framework for probability modeling. By leveraging the 2DQLCT, we aim to provide a more comprehensive understanding of probability distributions, particularly in the context of multi-dimensional and complex-valued signals. This framework not only broadens the theoretical underpinnings of probability theory but also opens new avenues for researchers

Context: The existence of intermediate-mass black holes (IMBHs) still poses challenges to theoretical and observational astronomers. Several candidates have been proposed, including the one in the IRS13 cluster in the Galactic centre, where the evidence is based on the velocity dispersion of its members, however, none have been confirmed to date. Aims: We aim to gain insights into the presence of an IMBH in the Galactic centre by a numerical study of the dynamical interplay between an IMBH and star clusters (SCs) in the vicinity of a supermassive black hole (SMBH). Methods: We use high-precision N-body models of IRS13-like SCs in the Galactic centre, and of more massive SCs that fall into the centre of the Galaxy from larger distances. Results: We find that at IRS13's physical distance of 0.4 pc, an IRS13-size SC cannot remain gravitationally bound even if it contains an IMBH of thousands $M_\odot$. Thus, IRS13 appears to be an incidental present-day clumping of stars. Furthermore, we show that the velocity dispersion of tidally disrupted SCs (the likely origin of IRS13) can be fully accounted for by the tidal forces of the central SMBH; the IMBH's influence is not essential., Comment: 7 pages, 1 table, 8 figures, accepted for publication in Astronomy & Astrophysics

Large Language Models (LLMs) are gaining significant popularity in recent years for specialized tasks using prompts due to their low computational cost. Standard methods like prefix tuning utilize special, modifiable tokens that lack semantic meaning and require extensive training for best performance, often falling short. In this context, we propose a novel method called Semantic Knowledge Tuning (SK-Tuning) for prompt and prefix tuning that employs meaningful words instead of random tokens. This method involves using a fixed LLM to understand and process the semantic content of the prompt through zero-shot capabilities. Following this, it integrates the processed prompt with the input text to improve the model's performance on particular tasks. Our experimental results show that SK-Tuning exhibits faster training times, fewer parameters, and superior performance on tasks such as text classification and understanding compared to other tuning methods. This approach offers a promising method for optimizing the efficiency and effectiveness of LLMs in processing language tasks., Comment: Accepted in Nature Scientific Reports

In this letter, we explore the $f(Q,T_{\mu\nu}T^{\mu \nu})$ gravity theory, building upon the foundations laid by the $f(Q)$ and $f(Q,T)$ gravity theories. Here, $Q$ represents non-metricity and $T_{\mu\nu}$ stands for the energy-momentum tensor. The proposed action encompasses an arbitrary function of both non-metricity $Q$ and the square of the energy-momentum tensor, specifically $T^2=T_{\mu\nu}T^{\mu \nu}$. We find the analytical solution for the barotropic fluid case $p=\omega \rho$ for the model $f(Q, T_{\mu \nu}T^{\mu \nu}) = Q + \eta(T_{\mu \nu}T^{\mu \nu}) $. We constrain parameters of the solution $H(z)$ utilizing CC, BAO, and latest Pantheon+SH0ES samples with the help of Monte Carlo Markov Chain sampling technique along with Bayesian statistical analysis. Further, from the Om diagnostic test, we find that the assumed cosmological model favors the quintessence regime., Comment: Physics Letters B published version

State space models (SSMs) have emerged as a powerful framework for modelling long-range dependencies in sequence data. Unlike traditional recurrent neural networks (RNNs) and convolutional neural networks (CNNs), SSMs offer a structured and stable approach to sequence modelling, leveraging principles from control theory and dynamical systems. However, a key challenge in sequence modelling is compressing long-term dependencies into a compact hidden state representation without losing critical information. In this paper, we develop a rigorous mathematical framework for understanding memory compression in selective state space models. We introduce a selective gating mechanism that dynamically filters and updates the hidden state based on input relevance, allowing for efficient memory compression. We formalize the trade-off between memory efficiency and information retention using information-theoretic tools, such as mutual information and rate-distortion theory. Our analysis provides theoretical bounds on the amount of information that can be compressed without sacrificing model performance. We also derive theorems that prove the stability and convergence of the hidden state in selective SSMs, ensuring reliable long-term memory retention. Computational complexity analysis reveals that selective SSMs offer significant improvements in memory efficiency and processing speed compared to traditional RNN-based models. Through empirical validation on sequence modelling tasks such as time-series forecasting and natural language processing, we demonstrate that selective SSMs achieve state-of-the-art performance while using less memory and computational resources., Comment: 27 Pages

This research explores refined boundary conditions for a traction-free surface in a non-local micropolar half-space, combining non-local and micropolar elasticity effects to study Rayleigh wave propagation in an isotropic, homogeneous medium. This study revisits the solution for Rayleigh waves obtained within the framework of Eringen's non-local differential model. It highlights that the equivalence between the non-local differential and integral formulations breaks down for a micropolar half-space and can only be restored under specific additional boundary conditions. For mathematical tractability, equivalence is assumed for a defined subset of stresses. Asymptotic analysis is further employed to capture the effects of the boundary layer within the non-local micropolar half-space. This technique finally derives the refined boundary conditions for micropolar media.

Spoken language assessment (SLA) systems restrict themselves to evaluating the pronunciation and oral fluency of a speaker by analysing the read and spontaneous spoken utterances respectively. The assessment of language grammar or vocabulary is relegated to written language assessment (WLA) systems. Most WLA systems present a set of sentences from a curated finite-size database of sentences thereby making it possible to anticipate the test questions and train oneself. In this paper, we propose a novel end-to-end SLA system to assess language grammar from spoken utterances thus making WLA systems redundant; additionally, we make the assessment largely unteachable by employing a large language model (LLM) to bring in variations in the test. We further demonstrate that a hybrid automatic speech recognition (ASR) with a custom-built language model outperforms the state-of-the-art ASR engine for spoken grammar assessment., Comment: 5 pages, 2 figures

This paper introduces the hypothetical track-length fitting algorithm, a novel method for measuring the kinetic energies of ionizing particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

We present a new approach to bootstrapping string-like theories by exploiting a local crossing symmetric dispersion relation and field redefinition ambiguities. This approach enables us to use mass-level truncation and to go beyond the dual resonance hypothesis. We consider both open and closed strings, focusing mainly on open tree-level amplitudes with integer-spaced spectrum, and two leading Wilson coefficients as inputs. Using entanglement minimization in the form of the minimum of the first finite moment of linear entropy or entangling power, we get an excellent approximation to the superstring amplitudes, including the leading and sub-leading Regge trajectories. We find other interesting S-matrices which do not obey the duality hypothesis, but exhibit a transition from Regge behaviour to power law behaviour in the high energy limit. Finally, we also examine Machine-Learning techniques to do bootstrap and discuss potential advantages over the present approach., Comment: 48 pages, 21 figures

The primary objective of this study is to develop novel interpolation operators that interpolate the boundary values of a function defined on a triangle. This is accomplished by constructing New Generalized Boolean sum neural network operator $\mathcal{B}_{n_1, n_2, \xi }$ using a class of activation functions. Its interpolation properties are established and the estimates for the error of approximation corresponding to operator $\mathcal{B}_{n_1, n_2, \xi }$ is computed in terms of mixed modulus of continuity. The advantage of our method is that it does not require training the network. Instead, the number of hidden neurons adjusts the weights and bias. Numerical examples are illustrated to show the efficacy of these newly constructed operators. Further, with the help of MATLAB, comparative and graphical analysis is given to show the validity and efficiency of the results obtained for these operators., Comment: 17 pages, 7 figures

Re-identification (ReID) is a critical challenge in computer vision, predominantly studied in the context of pedestrians and vehicles. However, robust object-instance ReID, which has significant implications for tasks such as autonomous exploration, long-term perception, and scene understanding, remains underexplored. In this work, we address this gap by proposing a novel dual-path object-instance re-identification transformer architecture that integrates multimodal RGB and depth information. By leveraging depth data, we demonstrate improvements in ReID across scenes that are cluttered or have varying illumination conditions. Additionally, we develop a ReID-based localization framework that enables accurate camera localization and pose identification across different viewpoints. We validate our methods using two custom-built RGB-D datasets, as well as multiple sequences from the open-source TUM RGB-D datasets. Our approach demonstrates significant improvements in both object instance ReID (mAP of 75.18) and localization accuracy (success rate of 83% on TUM-RGBD), highlighting the essential role of object ReID in advancing robotic perception. Our models, frameworks, and datasets have been made publicly available., Comment: 8 pages, 5 figures, 3 tables. Submitted to ICRA 2025

The rapid advancements in Large Language Models (LLMs) have revolutionized natural language processing (NLP) and related fields. However, fine-tuning these models for specific tasks remains computationally expensive and risks degrading pre-learned features. To address these challenges, we propose Propulsion, a novel parameter efficient fine-tuning (PEFT) method designed to optimize task-specific performance while drastically reducing computational overhead. Inspired by the concept of controlled adjustments in physical motion, Propulsion selectively re-scales specific dimensions of a pre-trained model, guiding output predictions toward task objectives without modifying the model's parameters. By introducing lightweight, trainable Propulsion parameters at the pre-trained layer, we minimize the number of parameters updated during fine-tuning, preventing overfitting or overwriting of existing knowledge. Our theoretical analysis, supported by Neural Tangent Kernel (NTK) theory, shows that Propulsion approximates the performance of full fine-tuning with far fewer trainable parameters. Empirically, Propulsion reduces the parameter count from 355.3 million to just 0.086 million, achieving over a 10x reduction compared to standard approaches like LoRA while maintaining competitive performance across benchmarks., Comment: 26 pages, 11 figures

Robots interacting with humans through natural language can unlock numerous applications such as Referring Grasp Synthesis (RGS). Given a text query, RGS determines a stable grasp pose to manipulate the referred object in the robot's workspace. RGS comprises two steps: visual grounding and grasp pose estimation. Recent studies leverage powerful Vision-Language Models (VLMs) for visually grounding free-flowing natural language in real-world robotic execution. However, comparisons in complex, cluttered environments with multiple instances of the same object are lacking. This paper introduces HiFi-CS, featuring hierarchical application of Featurewise Linear Modulation (FiLM) to fuse image and text embeddings, enhancing visual grounding for complex attribute rich text queries encountered in robotic grasping. Visual grounding associates an object in 2D/3D space with natural language input and is studied in two scenarios: Closed and Open Vocabulary. HiFi-CS features a lightweight decoder combined with a frozen VLM and outperforms competitive baselines in closed vocabulary settings while being 100x smaller in size. Our model can effectively guide open-set object detectors like GroundedSAM to enhance open-vocabulary performance. We validate our approach through real-world RGS experiments using a 7-DOF robotic arm, achieving 90.33\% visual grounding accuracy in 15 tabletop scenes. We include our codebase in the supplementary material.

We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839-10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less, and can detect 10x more FRBs than the current CRAFT incoherent sum system (i.e., 0.5-2 localised FRBs per day), enabling us to better constrain he models for FRBs and use them as cosmological probes., Comment: 26 pages, 19 figures, 9 tables, Accepted for publication in PASA

The moving target traveling salesman problem with obstacles (MT-TSP-O) is a generalization of the traveling salesman problem (TSP) where, as its name suggests, the targets are moving. A solution to the MT-TSP-O is a trajectory that visits each moving target during a certain time window(s), and this trajectory avoids stationary obstacles. We assume each target moves at a constant velocity during each of its time windows. The agent has a speed limit, and this speed limit is no smaller than any target's speed. This paper presents the first complete algorithm for finding feasible solutions to the MT-TSP-O. Our algorithm builds a tree where the nodes are agent trajectories intercepting a unique sequence of targets within a unique sequence of time windows. We generate each of a parent node's children by extending the parent's trajectory to intercept one additional target, each child corresponding to a different choice of target and time window. This extension consists of planning a trajectory from the parent trajectory's final point in space-time to a moving target. To solve this point-to-moving-target subproblem, we define a novel generalization of a visibility graph called a moving target visibility graph (MTVG). Our overall algorithm is called MTVG-TSP. To validate MTVG-TSP, we test it on 570 instances with up to 30 targets. We implement a baseline method that samples trajectories of targets into points, based on prior work on special cases of the MT-TSP-O. MTVG-TSP finds feasible solutions in all cases where the baseline does, and when the sum of the targets' time window lengths enters a critical range, MTVG-TSP finds a feasible solution with up to 38 times less computation time., Comment: Accepted to WAFR 2024

The ternary Goldbach conjecture states that every odd number $m \geqslant 7$ can be written as the sum of three primes. We construct a set of primes $\mathbb{P}$ defined by an expanding system of admissible congruences such that almost all primes are not in $\mathbb{P}$ and still, the ternary Goldbach conjecture holds true with primes restricted to $\mathbb{P}$., Comment: 22 pages

In next-generation wireless networks, low latency often necessitates short-length codewords that either do not use channel state information (CSI) or rely solely on CSI at the receiver (CSIR). Gaussian codes that achieve capacity for AWGN channels may be unsuitable for these no-CSI and CSIR-only cases. In this work, we design short-length codewords for these cases using an autoencoder architecture. From the designed codes, we observe the following: In the no-CSI case, the learned codes are mutually orthogonal when the distribution of the real and imaginary parts of the fading random variable has support over the entire real line. However, when the support is limited to the non-negative real line, the codes are not mutually orthogonal. For the CSIR-only case, deep learning-based codes designed for AWGN channels perform worse in fading channels with optimal coherent detection compared to codes specifically designed for fading channels with CSIR, where the autoencoder jointly learns encoding, coherent combining, and decoding. In both no-CSI and CSIR-only cases, the codes perform at least as well as or better than classical codes of the same block length.

Robust atomic resolution structural characterization of point defects in 3D is a longstanding challenge for electron microscopy. Here, we evaluate multislice electron ptychography as a tool to carry out 3D atomic resolution characterization of point defects in silicon carbide as a model. Through multislice electron scattering simulations, subsequent ptychographic reconstructions, and data analysis, we show that intrinsic defects such as vacancies and substitutions beyond transition metals can be detected with a depth precision of approximately 0.1 nm with realistic sample and microscope conditions. Furthermore, the dependence of contrast at defect sites on electron energy and dose, as well as optimal acquisition parameters, are described. Overall, these results serve as a guidepost to experiments aiming to analyze point defects beyond extremely thin specimens or only heavy elements.

Ion implantation is widely used to dope semiconductors for electronic device fabrication, but techniques to quantify point defects and induced damage are limited. While several techniques can measure dopant concentration profiles with high accuracy, none allow for simultaneous atomic resolution structural analysis. Here, we use multislice electron ptychography to quantify the damage induced by erbium implantation in a wide band gap semiconductor 4H-SiC over a 1,000 nm\textsuperscript{3} volume region. This damage extends further into the sample than expected from implantation simulations that do not consider crystallography. Further, the technique's sensitivity to dopants and vacancies is evaluated as a function of damage. As each reconstructed analysis volume contains approximately 10$^5$ atoms, sensitivity of 10\textsuperscript{18} cm\textsuperscript{-3} (in the order of 10 ppm) is demonstrated in the implantation tail region. After point defect identification, the local distortions surrounding \ch{Er_{Si}} and \ch{v_{Si}} defects are quantified. These results underscore the power of multislice electron ptychography to enable the investigation of point defects as a tool to guide the fabrication of future electronic devices.

We present the detection and analysis of GRB 231115A, a candidate extragalactic magnetar giant flare (MGF) observed by Fermi/GBM and localized by INTEGRAL to the starburst galaxy M82. This burst exhibits distinctive temporal and spectral characteristics that align with known MGFs, including a short duration and a high peak energy. Gamma-ray analyses reveal significant insights into this burst, supporting conclusions already established in the literature: our time-resolved spectral studies provide further evidence that GRB 231115A is indeed a MGF. Significance calculations also suggest a robust association with M82, further supported by a high Bayes factor that minimizes the probability of chance alignment with a neutron star merger. Despite extensive follow-up efforts, no contemporaneous gravitational wave or radio emissions were detected. The lack of radio emission sets stringent upper limits on possible radio luminosity. Constraints from our analysis show no fast radio bursts (FRBs) associated with two MGFs. X-ray observations conducted post-burst by Swift/XRT and XMM/Newton provided additional data, though no persistent counterparts were identified. Our study underscores the importance of coordinated multi-wavelength follow-up and highlights the potential of MGFs to enhance our understanding of short GRBs and magnetar activities in the cosmos. Current MGF identification and follow-up implementation are insufficient for detecting expected counterparts; however, improvements in these areas may allow for the recovery of follow-up signals with existing instruments. Future advancements in observational technologies and methodologies will be crucial in furthering these studies.

We present a complete analysis of Fermi Large Area Telescope (LAT) data of GRB 221009A, the brightest Gamma-Ray Burst (GRB) ever detected. The burst emission above 30 MeV detected by the LAT preceded by 1 s the low-energy (< 10 MeV) pulse that triggered the Fermi Gamma-Ray Burst Monitor (GBM), as has been observed in other GRBs. The prompt phase of GRB 221009A lasted a few hundred seconds. It was so bright that we identify a Bad Time Interval (BTI) of 64 seconds caused by the extremely high flux of hard X-rays and soft gamma rays, during which the event reconstruction efficiency was poor and the dead time fraction quite high. The late-time emission decayed as a power law, but the extrapolation of the late-time emission during the first 450 seconds suggests that the afterglow started during the prompt emission. We also found that high-energy events observed by the LAT are incompatible with synchrotron origin, and, during the prompt emission, are more likely related to an extra component identified as synchrotron self-Compton (SSC). A remarkable 400 GeV photon, detected by the LAT 33 ks after the GBM trigger and directionally consistent with the location of GRB 221009A, is hard to explain as a product of SSC or TeV electromagnetic cascades, and the process responsible for its origin is uncertain. Because of its proximity and energetic nature, GRB 221009A is an extremely rare event., Comment: 60 pages, 38 figures, 9 tables

Let $D$ be a digraph of order $n$ with adjacency matrix $A(D)$. For $\alpha\in[0,1)$, the $A_{\alpha}$ matrix of $D$ is defined as $A_{\alpha}(D)=\alpha {\Delta}^{+}(D)+(1-\alpha)A(D)$, where ${\Delta}^{+}(D)=\mbox{diag}~(d_1^{+},d_2^{+},\dots,d_n^{+})$ is the diagonal matrix of vertex outdegrees of $D$. Let $\sigma_{1\alpha}(D),\sigma_{2\alpha}(D),\dots,\sigma_{n\alpha}(D)$ be the singular values of $A_{\alpha}(D)$. Then the trace norm of $A_{\alpha}(D)$, which we call $\alpha$ trace norm of $D$, is defined as $\|A_{\alpha}(D)\|_*=\sum_{i=1}^{n}\sigma_{i\alpha}(D)$. In this paper, we find the singular values of some basic digraphs and characterize the digraphs $D$ with $\mbox{Rank}~(A_{\alpha}(D))=1$. As an application of these results, we obtain a lower bound for the trace norm of $A_{\alpha}$ matrix of digraphs and determine the extremal digraphs. In particular, we determine the oriented trees for which the trace norm of $A_{\alpha}$ matrix attains minimum. We obtain a lower bound for the $\alpha$ spectral norm $\sigma_{1\alpha}(D)$ of digraphs and characterize the extremal digraphs. As an application of this result, we obtain an upper bound for the $\alpha$ trace norm of digraphs and characterize the extremal digraphs., Comment: 19 pages, 1 figure with 11 digraphs

Context. Globular clusters (GCs) are suggested to host many stellar-mass black holes (BHs) at their centers, thus resulting in ideal testbeds for BH formation and retention theories. BHs are expected to play a major role in GC structural and dynamical evolution and their study has attracted a lot of attention. In recent years, several works attempted to constrain the BH mass fraction in GCs typically by comparing a single observable (for example mass segregation proxies) with scaling relations obtained from numerical simulations. Aims. We aim to uncover the possible intrinsic degeneracies in determining the BH mass fraction from single dynamical parameters and identify the possible parameter combinations that are able to break these degeneracies. Methods. We used a set of 101 Monte Carlo simulations sampling a large grid of initial conditions. In particular, we explored the impact of different BH natal kick prescriptions on widely adopted scaling relations. We then compared the results of our simulations with observations obtained using state-of-the-art HST photometric and astrometric catalogs for a sample of 30 Galactic GCs. Results. We find that using a single observable to infer the present-day BH mass fraction in GCs is degenerate, as similar values could be attained by simulations including different BH mass fractions. We argue that the combination of mass-segregation indicators with GC velocity dispersion ratios could help us to break this degeneracy efficiently. We show that such a combination of parameters can be derived with currently available data. However, the limited sample of stars with accurate kinematic measures and its impact on the overall errors do not allow us to discern fully different scenarios yet., Comment: 9 pages, 7 figures, accepted for publication by A&A

Let $A$ be an $m\times m$ complex matrix and let $\lambda _1, \lambda _2, \ldots , \lambda _m$ be the eigenvalues of $A$ arranged such that $|\lambda _1|\geq |\lambda _2|\geq \cdots \geq |\lambda _m|$ and for $n\geq 1,$ let $s^{(n)}_1\geq s^{(n)}_2\geq \cdots \geq s^{(n)}_m$ be the singular values of $A^n$. Then a famous theorem of Yamamoto (1967) states that $$\lim _{n\to \infty}(s^{(n)}_j )^{\frac{1}{n}}= |\lambda _j|, ~~\forall \,1\leq j\leq m.$$ Recently S. Nayak strengthened this result very significantly by showing that the sequence of matrices $|A^n|^{\frac{1}{n}}$ itself converges to a positive matrix $B$ whose eigenvalues are $|\lambda _1|,|\lambda _2|,$ $\ldots , |\lambda _m|.$ Here this theorem has been extended to arbitrary compact operators on infinite dimensional complex separable Hilbert spaces. The proof makes use of Nayak's theorem, Stone-Weirstrass theorem, Borel-Caratheodory theorem and some technical results of Anselone and Palmer on collectively compact operators. Simple examples show that the result does not hold for general bounded operators., Comment: 14 Pages

The IceCube neutrino observatory detects the diffuse astrophysical neutrino background with high significance, but the contribution of different classes of sources is not established. Because of their non-thermal spectrum, gamma-ray bursts (GRBs) are prime particle acceleration sites and one of the candidate classes for significant neutrino production. Exhaustive searches, based on stacking analysis of GRBs however could not establish the link between neutrinos and GRBs. Gamma-ray burst GRB 221009A had the highest time integrated gamma-ray flux of any detected GRB so far. The total fluence exceeds the sum of all Fermi Gamma-ray Burst Monitor (GBM) detected GRBs by a factor of two. Because it happened relatively nearby, it is one of the most favorable events for neutrino production from GRBs yet no neutrinos were detected. We calculate neutrino fluxes for this GRB in the TeV-PeV range using the most accurate, time-resolved spectral data covering the brightest intervals. We place limits on the physical parameters (Lorentz factor, baryon loading or emission radius) of the burst that are better by a factor of 2 compared to previous limits. The neutrino non-detection indicates a bulk Lorentz factor greater than 500 and possibly even 1000, consistent with other observations., Comment: 10 pages, 3 figures, 1 table. Submitted to AAS journals

Autism spectrum disorder (ASD) is characterized by significant challenges in social interaction and comprehending communication signals. Recently, therapeutic interventions for ASD have increasingly utilized Deep learning powered-computer vision techniques to monitor individual progress over time. These models are trained on private, non-public datasets from the autism community, creating challenges in comparing results across different models due to privacy-preserving data-sharing issues. This work introduces MMASD+, an enhanced version of the novel open-source dataset called Multimodal ASD (MMASD). MMASD+ consists of diverse data modalities, including 3D-Skeleton, 3D Body Mesh, and Optical Flow data. It integrates the capabilities of Yolov8 and Deep SORT algorithms to distinguish between the therapist and children, addressing a significant barrier in the original dataset. Additionally, a Multimodal Transformer framework is proposed to predict 11 action types and the presence of ASD. This framework achieves an accuracy of 95.03% for predicting action types and 96.42% for predicting ASD presence, demonstrating over a 10% improvement compared to models trained on single data modalities. These findings highlight the advantages of integrating multiple data modalities within the Multimodal Transformer framework.

Current observational evidence reveals that fast radio bursts (FRBs) exhibit bandwidths ranging from a few dozen MHz to several GHz. Traditional FRB searches primarily employ matched filter methods on time series collapsed across the entire observational bandwidth. However, with modern ultra-wideband receivers featuring GHz-scale observational bandwidths, this approach may overlook a significant number of events. We investigate the efficacy of sub-banded searches for FRBs, a technique seeking bursts within limited portions of the bandwidth. These searches aim to enhance the significance of FRB detections by mitigating the impact of noise outside the targeted frequency range, thereby improving signal-to-noise ratios. We conducted a series of Monte Carlo simulations, for the $400$-MHz bandwidth Parkes 21-cm multi-beam (PMB) receiver system and the Parkes Ultra-Wideband Low (UWL) receiver, simulating bursts down to frequency widths of about $100$\,MHz. Additionally, we performed a complete reprocessing of the high-latitude segment of the High Time Resolution Universe South survey (HTRU-S) of the Parkes-Murriyang telescope using sub-banded search techniques. Simulations reveal that a sub-banded search can enhance the burst search efficiency by $67_{-42}^{+133}$ % for the PMB system and $1433_{-126}^{+143}$ % for the UWL receiver. Furthermore, the reprocessing of HTRU led to the confident detection of eighteen new bursts, nearly tripling the count of FRBs found in this survey. These results underscore the importance of employing sub-banded search methodologies to effectively address the often modest spectral occupancy of these signals., Comment: Accepted for publication (A&A)

Astrophysical population simulations predict that a subset of dynamically formed binary black holes (BBHs) may possess eccentricity $\gtrsim 0.1$ at a gravitational wave (GW) frequency of $10 \,\text{Hz}$. Presently, the LIGO-Virgo-KAGRA (LVK) Collaboration tests general relativity (GR) assuming that the binary eccentricity has decayed well before it enters the detector's frequency band. Previous works have shown that binary eccentricity can bias GR tests if unaccounted for. Here we develop two methods to extend parametrized tests of GR to eccentric binaries. The first method extends the standard null parametrized test for quasicircular binaries by adding fractional deviations at each post-Newtonian (PN) order in the eccentric part of the GW phasing (assuming the small-eccentricity limit). Simultaneous measurement of the circular and eccentric deviation parameters ($\delta\hat{\varphi}, \delta\hat{\varphi}^e$) allows us to constrain deviations from GR for eccentric binaries. While strong constraints on the deviation parameters are not achievable with LIGO's projected sensitivity, the multibanding of LISA and CE observations can constrain these deviations to $|\delta\hat{\varphi}_2| \lesssim 3 \times 10^{-3}$ and $|\delta\hat{\varphi}^e_2|\lesssim 2\times 10^{-2}$. The second method looks for GR deviations in the rate of periastron advance ($\Delta\alpha$). The parameter $\Delta\alpha$ ($\Delta\alpha^{\rm GR} \to 0$) can be constrained with LIGO to $|\Delta\alpha|\lesssim 4 \times 10^{-2}$ (with $1 \sigma$ confidence). Multiband sources observed by LISA and CE provide an improved constraint of $|\Delta\alpha|\lesssim 3\times 10^{-5}$. The space-based detector DECIGO provides the best constraint on $\Delta\alpha$ with $|\Delta\alpha|\lesssim 8 \times 10^{-6}$., Comment: 32 pages, 7 figures

We establish a Wiener-type integral condition for first-order Sobolev functions defined on a complete, doubling metric measure space supporting a Poincar\'e inequality. It is stronger than the Lebesgue point property, except for a marginal increase in the capacity of the set of non-Lebesgue points.

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a "Module of Opportunity", aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.