Open Contents

arXivThermal Extraction of Volatiles from Lunar and Asteroid Regolith in Axisymmetric CrankNicholson Modeling Philip T. Metzger, Kris Zacny, Phillip Morrison... more(3) 20230606 A physicsbased computer model has been developed to support the development of volatile extraction from regolith of the Moon and asteroids. The model is based upon empirical data sets for extraterrestrial soils and simulants, including thermal conductivity of regolith and mixed composition ice, heat capacity of soil and mixed composition ice, hydrated mineral volatile release patterns, and sublimation of ice. A new thermal conductivity relationship is derived that generalizes cases of regolith with varying temperature, soil porosity, and pore vapor pressure. Ice composition is based upon measurements of icy ejecta from the Lunar CRater Observation and Sensing Satellite (LCROSS) impact and it is shown that thermal conductivity and heat capacity equations for water ice provide adequate accuracy at the present level of development. The heat diffusion equations are integrated with gas diffusion equations using multiple adaptive timesteps. The entire model is placed into a CrankNicholson framework where the finite difference formalism was extended to two dimensions in axisymmetry. The onedimensional version of the model successfully predicts heat transfer that matches lunar and asteroid data sets. The axisymmetric model has been used to study heat dissipation around lunar drills and water extraction in asteroid coring devices.
Subject Source arXiv URL https://arxiv.org/abs/2306.03776view Article Title Thermal Extraction of Volatiles from Lunar and Asteroid Regolith in Axisymmetric CrankNicholson ModelingAuthors Philip T. Metzger; Kris Zacny; Phillip MorrisonAbstract A physicsbased computer model has been developed to support the development of volatile extraction from regolith of the Moon and asteroids. The model is based upon empirical data sets for extraterrestrial soils and simulants, including thermal conductivity of regolith and mixed composition ice, heat capacity of soil and mixed composition ice, hydrated mineral volatile release patterns, and sublimation of ice. A new thermal conductivity relationship is derived that generalizes cases of regolith with varying temperature, soil porosity, and pore vapor pressure. Ice composition is based upon measurements of icy ejecta from the Lunar CRater Observation and Sensing Satellite (LCROSS) impact and it is shown that thermal conductivity and heat capacity equations for water ice provide adequate accuracy at the present level of development. The heat diffusion equations are integrated with gas diffusion equations using multiple adaptive timesteps. The entire model is placed into a CrankNicholson framework where the finite difference formalism was extended to two dimensions in axisymmetry. The onedimensional version of the model successfully predicts heat transfer that matches lunar and asteroid data sets. The axisymmetric model has been used to study heat dissipation around lunar drills and water extraction in asteroid coring devices.Is Part Of J. Aerospace Engineering 33, no.6 (Nov. 2020): 04020075 20230606 Identifier ISSN: DOI 10.1061/(ASCE)AS.19435525.0001165Category astroph.EP physics.appph physics.spacephLicense 
arXivEmbracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach Michael Gelfond, Jorge Fandinno, Evgenii Balai... more(3) 20230606 This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. This language is used for accurately and directly formalizing common benchmark examples from the literature of actual causality. A definition of cause is presented and used to analyze the actual causes of changes with respect to sequences of actions representing those examples.
Subject Source arXiv URL https://arxiv.org/abs/2306.03874view Article Title Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming ApproachAuthors Michael Gelfond; Jorge Fandinno; Evgenii BalaiAbstract This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. This language is used for accurately and directly formalizing common benchmark examples from the literature of actual causality. A definition of cause is presented and used to analyze the actual causes of changes with respect to sequences of actions representing those examples.Is Part Of 20230606 Identifier ISSN: Category cs.AI cs.LOLicense 
arXivEnabling Efficient Interaction between an Algorithm Agent and an LLM: A Reinforcement Learning Approach Bin Hu, Chenyang Zhao, Pu Zhang, ... more(7) 20230606 Large language models (LLMs) encode a vast amount of world knowledge acquired from massive text datasets. Recent studies have demonstrated that LLMs can assist an algorithm agent in solving complex sequential decision making tasks in embodied environments by providing highlevel instructions. However, interacting with LLMs can be timeconsuming, as in many practical scenarios, they require a significant amount of storage space that can only be deployed on remote cloud server nodes. Additionally, using commercial LLMs can be costly since they may charge based on usage frequency. In this paper, we explore how to enable efficient and costeffective interactions between the agent and an LLM. We propose a reinforcement learning based mediator model that determines when it is necessary to consult LLMs for highlevel instructions to accomplish a target task. Experiments on 4 MiniGrid environments that entail planning subgoals demonstrate that our method can learn to solve target tasks with only a few necessary interactions with an LLM, significantly reducing interaction costs in testing environments, compared with baseline methods. Experimental results also suggest that by learning a mediator model to interact with the LLM, the agent's performance becomes more robust against both exploratory and stochastic environments.
Subject Source arXiv URL https://arxiv.org/abs/2306.03604view Article Title Enabling Efficient Interaction between an Algorithm Agent and an LLM: A Reinforcement Learning ApproachAuthors Bin Hu; Chenyang Zhao; Pu Zhang; Zihao Zhou; Yuanhang Yang; Zenglin Xu; Bin LiuAbstract Large language models (LLMs) encode a vast amount of world knowledge acquired from massive text datasets. Recent studies have demonstrated that LLMs can assist an algorithm agent in solving complex sequential decision making tasks in embodied environments by providing highlevel instructions. However, interacting with LLMs can be timeconsuming, as in many practical scenarios, they require a significant amount of storage space that can only be deployed on remote cloud server nodes. Additionally, using commercial LLMs can be costly since they may charge based on usage frequency. In this paper, we explore how to enable efficient and costeffective interactions between the agent and an LLM. We propose a reinforcement learning based mediator model that determines when it is necessary to consult LLMs for highlevel instructions to accomplish a target task. Experiments on 4 MiniGrid environments that entail planning subgoals demonstrate that our method can learn to solve target tasks with only a few necessary interactions with an LLM, significantly reducing interaction costs in testing environments, compared with baseline methods. Experimental results also suggest that by learning a mediator model to interact with the LLM, the agent's performance becomes more robust against both exploratory and stochastic environments.Is Part Of 20230606 Identifier ISSN: Category cs.AILicense 
arXivTowards Adaptable and Interactive Image Captioning with Data Augmentation and Episodic Memory Aliki Anagnostopoulou, Mareike Hartmann, Daniel Sonntag... more(3) 20230606 Interactive machine learning (IML) is a beneficial learning paradigm in cases of limited data availability, as human feedback is incrementally integrated into the training process. In this paper, we present an IML pipeline for image captioning which allows us to incrementally adapt a pretrained image captioning model to a new data distribution based on user input. In order to incorporate user input into the model, we explore the use of a combination of simple data augmentation methods to obtain larger data batches for each newly annotated data instance and implement continual learning methods to prevent catastrophic forgetting from repeated updates. For our experiments, we split a domainspecific image captioning dataset, namely VizWiz, into nonoverlapping parts to simulate an incremental input flow for continually adapting the model to new data. We find that, while data augmentation worsens results, even when relatively small amounts of data are available, episodic memory is an effective strategy to retain knowledge from previously seen clusters.
Subject Source arXiv URL https://arxiv.org/abs/2306.03500view Article Title Towards Adaptable and Interactive Image Captioning with Data Augmentation and Episodic MemoryAuthors Aliki Anagnostopoulou; Mareike Hartmann; Daniel SonntagAbstract Interactive machine learning (IML) is a beneficial learning paradigm in cases of limited data availability, as human feedback is incrementally integrated into the training process. In this paper, we present an IML pipeline for image captioning which allows us to incrementally adapt a pretrained image captioning model to a new data distribution based on user input. In order to incorporate user input into the model, we explore the use of a combination of simple data augmentation methods to obtain larger data batches for each newly annotated data instance and implement continual learning methods to prevent catastrophic forgetting from repeated updates. For our experiments, we split a domainspecific image captioning dataset, namely VizWiz, into nonoverlapping parts to simulate an incremental input flow for continually adapting the model to new data. We find that, while data augmentation worsens results, even when relatively small amounts of data are available, episodic memory is an effective strategy to retain knowledge from previously seen clusters.Is Part Of 20230606 Identifier ISSN: Category cs.CL cs.CVLicense 
arXivVector calculus on weighted reflexive Banach spaces Enrico Pasqualetto, Tapio Rajala 20230606 We study firstorder Sobolev spaces on reflexive Banach spaces via relaxation, test plans, and divergence. We show the equivalence of the different approaches to the Sobolev spaces and to the related tangent bundles.
Subject 수학 Source arXiv URL https://arxiv.org/abs/2306.03684view Article Title Vector calculus on weighted reflexive Banach spacesAuthors Enrico Pasqualetto; Tapio RajalaAbstract We study firstorder Sobolev spaces on reflexive Banach spaces via relaxation, test plans, and divergence. We show the equivalence of the different approaches to the Sobolev spaces and to the related tangent bundles.Is Part Of 20230606 Identifier ISSN: Category math.FA math.CA math.MGLicense 
arXivUnderstanding Progressive Training Through the Framework of Randomized Coordinate Descent Rafał Szlendak, Elnur Gasanov, Peter Richtárik... more(3) 20230606 We propose a Randomized Progressive Training algorithm (RPT)  a stochastic proxy for the wellknown Progressive Training method (PT) (Karras et al., 2017). Originally designed to train GANs (Goodfellow et al., 2014), PT was proposed as a heuristic, with no convergence analysis even for the simplest objective functions. On the contrary, to the best of our knowledge, RPT is the first PTtype algorithm with rigorous and sound theoretical guarantees for general smooth objective functions. We cast our method into the established framework of Randomized Coordinate Descent (RCD) (Nesterov, 2012; Richt\'arik & Tak\'a\v{c}, 2014), for which (as a byproduct of our investigations) we also propose a novel, simple and general convergence analysis encapsulating stronglyconvex, convex and nonconvex objectives. We then use this framework to establish a convergence theory for RPT. Finally, we validate the effectiveness of our method through extensive computational experiments.
Subject 수학 Source arXiv URL https://arxiv.org/abs/2306.03626view Article Title Understanding Progressive Training Through the Framework of Randomized Coordinate DescentAuthors Rafał Szlendak; Elnur Gasanov; Peter RichtárikAbstract We propose a Randomized Progressive Training algorithm (RPT)  a stochastic proxy for the wellknown Progressive Training method (PT) (Karras et al., 2017). Originally designed to train GANs (Goodfellow et al., 2014), PT was proposed as a heuristic, with no convergence analysis even for the simplest objective functions. On the contrary, to the best of our knowledge, RPT is the first PTtype algorithm with rigorous and sound theoretical guarantees for general smooth objective functions. We cast our method into the established framework of Randomized Coordinate Descent (RCD) (Nesterov, 2012; Richt\'arik & Tak\'a\v{c}, 2014), for which (as a byproduct of our investigations) we also propose a novel, simple and general convergence analysis encapsulating stronglyconvex, convex and nonconvex objectives. We then use this framework to establish a convergence theory for RPT. Finally, we validate the effectiveness of our method through extensive computational experiments.Is Part Of 20230606 Identifier ISSN: Category cs.LG math.OCLicense 
arXivLarge effective magnetic fields from chiral phonons in rareearth halides Jiaming Luo, Tong Lin, Junjie Zhang, ... more(8) 20230606 Timereversal symmetry (TRS) is pivotal for materials optical, magnetic, topological, and transport properties. Chiral phonons, characterized by atoms rotating unidirectionally around their equilibrium positions, generate dynamic lattice structures that break TRS. Here we report that coherent chiral phonons, driven by circularly polarized terahertz light pulses, can polarize the paramagnetic spins in CeF3 like a quasistatic magnetic field on the order of 1 Tesla. Through timeresolved Faraday rotation and Kerr ellipticity, we found the transient magnetization is only excited by pulses resonant with phonons, proportional to the angular momentum of the phonons, and growing with magnetic susceptibility at cryogenic temperatures, as expected from the spinphonon coupling model. The timedependent effective magnetic field quantitatively agrees with that calculated from phonon dynamics. Our results may open a new route to directly investigate modespecific spinphonon interaction in ultrafast magnetism, energyefficient spintronics, and nonequilibrium phases of matter with broken TRS.
Subject Source arXiv URL https://arxiv.org/abs/2306.03852view Article Title Large effective magnetic fields from chiral phonons in rareearth halidesAuthors Jiaming Luo; Tong Lin; Junjie Zhang; Xiaotong Chen; Elizabeth R. Blackert; Rui Xu; Boris I. Yakobson; Hanyu ZhuAbstract Timereversal symmetry (TRS) is pivotal for materials optical, magnetic, topological, and transport properties. Chiral phonons, characterized by atoms rotating unidirectionally around their equilibrium positions, generate dynamic lattice structures that break TRS. Here we report that coherent chiral phonons, driven by circularly polarized terahertz light pulses, can polarize the paramagnetic spins in CeF3 like a quasistatic magnetic field on the order of 1 Tesla. Through timeresolved Faraday rotation and Kerr ellipticity, we found the transient magnetization is only excited by pulses resonant with phonons, proportional to the angular momentum of the phonons, and growing with magnetic susceptibility at cryogenic temperatures, as expected from the spinphonon coupling model. The timedependent effective magnetic field quantitatively agrees with that calculated from phonon dynamics. Our results may open a new route to directly investigate modespecific spinphonon interaction in ultrafast magnetism, energyefficient spintronics, and nonequilibrium phases of matter with broken TRS.Is Part Of 20230606 Identifier ISSN: Category condmat.mtrlsciLicense 
arXivA Generalization of Mersenne and Thabit Numerical Semigroups Feihu Liu, Guoce Xin, Suting Ye, ... more(4) 20230606 Let $A=(a_1, a_2, ..., a_n)$ be relative prime positive integers with $a_i\geq 2$. The Frobenius number $F(A)$ is the largest integer not belonging to the numerical semigroup $\langle A\rangle$ generated by $A$. The genus $g(A)$ is the number of positive integer elements that are not in $\langle A\rangle$. The Frobenius problem is to find $F(A)$ and $g(A)$ for a given sequence $A$. In this paper, we study the Frobenius problem of $A=(a,2a+d,2^2a+3d,...,2^ka+(2^k1)d)$ and obtain formulas for $F(A)$ and $g(A)$ when $a+d\geq k$. Our formulas simplifies further for some special cases, such as Mersenne and Thabit numerical semigroups. We obtain explicit formulas for generalized Mersenne and Thabit numerical semigroups and some more general numerical semigroups.
Subject 수학 Source arXiv URL https://arxiv.org/abs/2306.03459view Article Title A Generalization of Mersenne and Thabit Numerical SemigroupsAuthors Feihu Liu; Guoce Xin; Suting Ye; Jingjing YinAbstract Let $A=(a_1, a_2, ..., a_n)$ be relative prime positive integers with $a_i\geq 2$. The Frobenius number $F(A)$ is the largest integer not belonging to the numerical semigroup $\langle A\rangle$ generated by $A$. The genus $g(A)$ is the number of positive integer elements that are not in $\langle A\rangle$. The Frobenius problem is to find $F(A)$ and $g(A)$ for a given sequence $A$. In this paper, we study the Frobenius problem of $A=(a,2a+d,2^2a+3d,...,2^ka+(2^k1)d)$ and obtain formulas for $F(A)$ and $g(A)$ when $a+d\geq k$. Our formulas simplifies further for some special cases, such as Mersenne and Thabit numerical semigroups. We obtain explicit formulas for generalized Mersenne and Thabit numerical semigroups and some more general numerical semigroups.Is Part Of 20230606 Identifier ISSN: Category math.NT math.COLicense 
arXivAn alternative explanation for the unnatural tiny scale of the dark energy density and the phantom cutoff from the nonuniqueness of Lagrangian Suppanat Supanyo, Monsit Tanasittikosol, Sikarin YooKong... more(3) 20230606 Employing the inverse problem of the calculus of variation, the homogeneous phantom Lagrangian can be expressed in the multiplicative form, while the equation of motion of the canonical phantom field is still intact. According to the nonuniqueness principle, the standard and the multiplicative Lagrangian can be linearly combined. This linear combination of Lagrangian can be used as a guideline to add the higher dimension operators and, consequently, the energy scale discrepancy between the particle physics and the cosmology could possibly be resolved.
Subject Source arXiv URL https://arxiv.org/abs/2306.03396view Article Title An alternative explanation for the unnatural tiny scale of the dark energy density and the phantom cutoff from the nonuniqueness of LagrangianAuthors Suppanat Supanyo; Monsit Tanasittikosol; Sikarin YooKongAbstract Employing the inverse problem of the calculus of variation, the homogeneous phantom Lagrangian can be expressed in the multiplicative form, while the equation of motion of the canonical phantom field is still intact. According to the nonuniqueness principle, the standard and the multiplicative Lagrangian can be linearly combined. This linear combination of Lagrangian can be used as a guideline to add the higher dimension operators and, consequently, the energy scale discrepancy between the particle physics and the cosmology could possibly be resolved.Is Part Of 20230606 Identifier ISSN: Category hepthLicense 
arXivDispersive determination of neutrino mass orderings Hsiangnan Li 20230606 We argue that the mixing phenomenon of a neutral meson formed by a fictitious massive quark will disappear, if the electroweak symmetry of the Standard Model (SM) is restored at a high energy scale. This disappearance is taken as the highenergy input for the dispersion relation, which must be obeyed by the width difference between two meson mass eigenstates. The solution to the dispersion relation at low energy, i.e., in the symmetry broken phase, then connects the CabibboKobayashiMaskawa (CKM) matrix elements to the quark masses involved in the box diagrams responsible for meson mixing. It is demonstrated via the analysis of the $D$ meson mixing that the typical $d$, $s$ and $b$ quark masses demand the CKM matrix elements in agreement with measured values. In particular, the known numerical relation $V_{us}\approx \sqrt{m_s/m_b}$ with the $s$ ($b$) quark mass $m_s$ ($m_b$) can be derived analytically from our solution. Next we apply the same formalism to the mixing of the $\mu^ e^+$ and $\mu^+ e^$ states through similar box diagrams with intermediate neutrino channels. It is shown that the neutrino masses in the normal hierarchy (NH), instead of in the inverted hierarchy or quasidegenerate spectrum, match the observed PontecorvoMakiNakagawaSakata matrix elements. The lepton mixing angles larger than the quark ones are explained by means of the inequality $m_2^2/m_3^2\gg m_s^2/m_b^2$, $m_{2,3}$ being the neutrino masses in the NH. At last, the solution for the $\tau^e^+$$\tau^+e^$ mixing specifies the mixing angle $\theta_{23}\approx 45^\circ$ with slight preference for the first octant. Our work suggests that the fermion masses and mixing parameters are constrained dynamically, and the neutrino mass orderings can be discriminated by the internal consistency of the SM.
Subject Source arXiv URL https://arxiv.org/abs/2306.03463view Article Title Dispersive determination of neutrino mass orderingsAuthors Hsiangnan LiAbstract We argue that the mixing phenomenon of a neutral meson formed by a fictitious massive quark will disappear, if the electroweak symmetry of the Standard Model (SM) is restored at a high energy scale. This disappearance is taken as the highenergy input for the dispersion relation, which must be obeyed by the width difference between two meson mass eigenstates. The solution to the dispersion relation at low energy, i.e., in the symmetry broken phase, then connects the CabibboKobayashiMaskawa (CKM) matrix elements to the quark masses involved in the box diagrams responsible for meson mixing. It is demonstrated via the analysis of the $D$ meson mixing that the typical $d$, $s$ and $b$ quark masses demand the CKM matrix elements in agreement with measured values. In particular, the known numerical relation $V_{us}\approx \sqrt{m_s/m_b}$ with the $s$ ($b$) quark mass $m_s$ ($m_b$) can be derived analytically from our solution. Next we apply the same formalism to the mixing of the $\mu^ e^+$ and $\mu^+ e^$ states through similar box diagrams with intermediate neutrino channels. It is shown that the neutrino masses in the normal hierarchy (NH), instead of in the inverted hierarchy or quasidegenerate spectrum, match the observed PontecorvoMakiNakagawaSakata matrix elements. The lepton mixing angles larger than the quark ones are explained by means of the inequality $m_2^2/m_3^2\gg m_s^2/m_b^2$, $m_{2,3}$ being the neutrino masses in the NH. At last, the solution for the $\tau^e^+$$\tau^+e^$ mixing specifies the mixing angle $\theta_{23}\approx 45^\circ$ with slight preference for the first octant. Our work suggests that the fermion masses and mixing parameters are constrained dynamically, and the neutrino mass orderings can be discriminated by the internal consistency of the SM.Is Part Of 20230606 Identifier ISSN: Category hepphLicense