Brans-Dicke Theory in Anisotropic Model with Viscous Fluid

In this paper we have considered an anisotropic space-time model of the Universe in presence of Brans-Dicke (BD) scalar field $\phi$, causal viscous fluid and barotropic fluid. We have shown that irrespective of fluid the causality theory provides late time acceleration of the Universe. If the deceleration occurs in radial direction and acceleration occurs in transverse direction then the anisotropic Universe will accelerate for a particular condition of the power law representation of the scale factors.Comment: 5 page

Role of Chameleon Field in presence of Variable Modified Chaplygin gas in Brans-Dicke Theory

In this work, we have considered FRW model of the universe for Brans-Dicke (BD) theory with BD scalar field as a Chameleon field. First we have transformed the field equations and conservation equation from Jordan's frame to Einstein's frame. We have shown in presence of variable modified Chaplygin gas, the potential function $V$ and another analytic function $f$ always increase with respect to BD-Chameleon scalar field $\phi$.Comment: 9 pages, 2 figure

Towards Generating Functionally Correct Code Edits from Natural Language Issue Descriptions

Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential to generate code from natural language descriptions across a wide range of programming tasks. Several benchmarks have recently emerged to evaluate the ability of LLMs to generate functionally correct code from natural language intent with respect to a set of hidden test cases. This has enabled the research community to identify significant and reproducible advancements in LLM capabilities. However, there is currently a lack of benchmark datasets for assessing the ability of LLMs to generate functionally correct code edits based on natural language descriptions of intended changes. This paper aims to address this gap by motivating the problem NL2Fix of translating natural language descriptions of code changes (namely bug fixes described in Issue reports in repositories) into correct code fixes. To this end, we introduce Defects4J-NL2Fix, a dataset of 283 Java programs from the popular Defects4J dataset augmented with high-level descriptions of bug fixes, and empirically evaluate the performance of several state-of-the-art LLMs for the this task. Results show that these LLMS together are capable of generating plausible fixes for 64.6% of the bugs, and the best LLM-based technique can achieve up to 21.20% top-1 and 35.68% top-5 accuracy on this benchmark

Correspondence between Electro-Magnetic Field and other Dark Energies in Non-linear Electrodynamics

In this work, we have considered the flat FRW model of the universe filled with electro-magnetic field. First, the Maxwell's electro-magnetic field in linear form has been discussed and after that the modified Lagrangian in non-linear form for accelerated universe has been considered. The corresponding energy density and pressure for non-linear electro-magnetic field have been calculated. We have found the condition such that the electro-magnetic field generates dark energy. The correspondence between the electro-magnetic field and the other dark energy candidates namely tachyonic field, DBI-essence, Chaplygin gas, hessence dark energy, k-essenece and dilaton dark energy have been investigated. We have also reconstructed the potential functions and the scalar fields in this scenario.Comment: 11 pages, 7 figure

Ranking LLM-Generated Loop Invariants for Program Verification

Synthesizing inductive loop invariants is fundamental to automating program verification. In this work, we observe that Large Language Models (such as gpt-3.5 or gpt-4) are capable of synthesizing loop invariants for a class of programs in a 0-shot setting, yet require several samples to generate the correct invariants. This can lead to a large number of calls to a program verifier to establish an invariant. To address this issue, we propose a {\it re-ranking} approach for the generated results of LLMs. We have designed a ranker that can distinguish between correct inductive invariants and incorrect attempts based on the problem definition. The ranker is optimized as a contrastive ranker. Experimental results demonstrate that this re-ranking mechanism significantly improves the ranking of correct invariants among the generated candidates, leading to a notable reduction in the number of calls to a verifier.Comment: Findings of The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP-findings 2023

Finding Inductive Loop Invariants using Large Language Models

Loop invariants are fundamental to reasoning about programs with loops. They establish properties about a given loop's behavior. When they additionally are inductive, they become useful for the task of formal verification that seeks to establish strong mathematical guarantees about program's runtime behavior. The inductiveness ensures that the invariants can be checked locally without consulting the entire program, thus are indispensable artifacts in a formal proof of correctness. Finding inductive loop invariants is an undecidable problem, and despite a long history of research towards practical solutions, it remains far from a solved problem. This paper investigates the capabilities of the Large Language Models (LLMs) in offering a new solution towards this old, yet important problem. To that end, we first curate a dataset of verification problems on programs with loops. Next, we design a prompt for exploiting LLMs, obtaining inductive loop invariants, that are checked for correctness using sound symbolic tools. Finally, we explore the effectiveness of using an efficient combination of a symbolic tool and an LLM on our dataset and compare it against a purely symbolic baseline. Our results demonstrate that LLMs can help improve the state-of-the-art in automated program verification

Higher Dimensional Cosmology with Some Dark Energy Models in Emergent, Logamediate and Intermediate Scenarios of the Universe

We have considered N-dimensional Einstein field equations in which four-dimensional space-time is described by a FRW metric and that of extra dimensions by an Euclidean metric. We have chosen the exponential forms of scale factors a and d numbers of b in such a way that there is no singularity for evolution of the higher dimensional Universe. We have supposed that the Universe is filled with K-essence, Tachyonic, Normal Scalar Field and DBI-essence. Here we have found the nature of potential of different scalar field and graphically analyzed the potentials and the fields for three scenario namely Emergent Scenario, Logamediate Scenario and Intermediate Scenario. Also graphically we have depicted the geometrical parameters named statefinder parameters and slow-roll parameters in the higher dimensional cosmology with the above mentioned scenarios.Comment: 21 pages, 36 figure

Observational Constraints of Modified Chaplygin Gas in Loop Quantum Cosmology

We have considered the FRW universe in loop quantum cosmology (LQC) model filled with the dark matter (perfect fluid with negligible pressure) and the modified Chaplygin gas (MCG) type dark energy. We present the Hubble parameter in terms of the observable parameters $\Omega_{m0}$, $\Omega_{x0}$ and $H_{0}$ with the redshift $z$ and the other parameters like $A$, $B$, $C$ and $\alpha$. From Stern data set (12 points), we have obtained the bounds of the arbitrary parameters by minimizing the $\chi^{2}$ test. The best-fit values of the parameters are obtained by 66%, 90% and 99% confidence levels. Next due to joint analysis with BAO and CMB observations, we have also obtained the bounds of the parameters ($B,C$) by fixing some other parameters $\alpha$ and $A$. From the best fit of distance modulus $\mu(z)$ for our theoretical MCG model in LQC, we concluded that our model is in agreement with the union2 sample data.Comment: 14 pages, 10 figures, Accepted in EPJC. arXiv admin note: text overlap with arXiv:astro-ph/0311622 by other author