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At least 91 records · Page 5

A computer architecture for intelligent machines

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Lefebvre, D. R.↗

Quantum Gravity and Laser Interferometry: Towards Observable Predictions

Understanding quantum gravity remains one of the deepest challenges in modern physics, as direct experimental access to Planck-scale effects is beyond current technological reach. However, recent theoretical advances indicate that quantum fluctuations of spacetime may produce measurable effects in precision experiments, particularly near causal horizons. This opens new avenues for testing quantum gravity phenomena through high-precision measurement techniques. This dissertation develops multiple theoretical models to characterize these effects and examines their potential observational signatures in future gravitational wave interferometers. We begin by investigating the role of quantum fluctuations in near-horizon geometries through the lens of the AdS/CFT correspondence, which provides a powerful framework for understanding the interplay between quantum field theory and general relativity via holographic principles. By modeling stochastic energy-momentum sources in Rindler-AdS spacetime, we demonstrate that vacuum fluctuations transform the Einstein equations into a Langevin-type stochastic differential equation, leading to potentially observable fluctuations in photon traversal times. Extending this approach to Minkowski spacetime, we establish a correspondence between gravitational shockwaves and fluid dynamics, showing that near-horizon perturbations satisfy an equation analogous to that governing incompressible fluids, thereby reinforcing the membrane paradigm and hydrodynamic analogies in the context of the fluid/gravity duality. Furthermore, we construct the covariant phase space of a spherically symmetric causal diamond in Minkowski spacetime, identifying two fundamental charges that govern its evolution. These results provide a foundation for quantizing causal horizons and understanding their microscopic degrees of freedom. Building upon these theoretical developments, we further examine a related stochastic phenomenon: the gravitational wave memory background arising from the cumulative memory steps produced by supermassive black hole mergers. After reviewing the standard stochastic gravitational wave background, gravitational memory effects, and BMS symmetries, we model the stochastic memory background using a Brownian motion framework. We show that while the cumulative memory background initially appears above the sensitivity curve of space-based interferometers like LISA, the realistic subtraction of individually resolvable merger events substantially suppresses the residual signal, making its detection more challenging. This highlights the critical importance of source subtraction when evaluating the detectability of gravitational memory effects. By bridging fundamental theory with experimental prospects, this dissertation contributes to the ongoing effort to uncover the quantum nature of spacetime through precision measurement techniques. Whether through detecting quantum spacetime fluctuations, gravitational memory backgrounds, or probing the symmetries of causal horizons, the pursuit of observable quantum gravity phenomena continues to expand the frontiers of both theory and experiment.

Zhang, Yiwen [Caltech] (ORCID:0000000323559416)↗

Theoretical perspective on phase stability and polarization switching in ferroelectric hafnia

Fluorite-based ferroelectric materials are revolutionizing the application space of polar semiconductors. These materials leverage robust polarization of extremely thin films, compatibility with the silicon chip processing, and decades of manufacturing experience to enable a new generation of ferroelectric memory devices. As a new paradigm for ferroelectrics, understanding of phase transitions and the switching mechanism in fluorites is essential both for advancing applications and for fundamental science. In this article, we outline the recent progress that has been made to understand the relative phase stability, phase transition and order parameter coupling, ferroelectric switching through unique nucleation and growth processes, and how defects affect these phases and processes. The main challenges, opportunities, and next steps for leveraging these materials for next-generation devices are reviewed.

Condensed Matter Physics↗

Folded network and structural transition in molten tin

The fundamental relationships between the structure and properties of liquids are far from being well understood. For instance, the structural origins of many liquid anomalies still remain unclear, but liquid-liquid transitions (LLT) are believed to hold a key. However, experimental demonstrations of LLTs have been rather challenging. Here, we report experimental and theoretical evidence of a second-order-like LLT in molten tin, one which favors a percolating covalent bond network at high temperatures. The observed structural transition originates from the fluctuating metallic/covalent behavior of atomic bonding, and consequently a new paradigm of liquid structure emerges. The liquid structure, described in the form of a folded network, bridges two well-established structural models for disordered systems, i.e., the random packing of hard-spheres and a continuous random network, offering a large structural midground for liquids and glasses. Our findings provide an unparalleled physical picture of the atomic arrangement for a plethora of liquids, shedding light on the thermodynamic and dynamic anomalies of liquids but also entailing far-reaching implications for studying liquid polyamorphism and dynamical transitions in liquids.

36 MATERIALS SCIENCE↗

Enhanced two-dimensional ferromagnetism in van der Waals β-UTe 3 monolayers

The discovery of local-moment magnetism in van der Waals (vdW) semiconductors down to the single-layer limit has led to a paradigm shift in the understanding of two-dimensional (2D) magnets. The incorporation of strong electronic and magnetic correlations in 2D vdW metals remains a sought-after platform to enable control of emergent quantum phases and to achieve more theoretically tractable microscopic models of complex materials. To date, however, there is limited success in the discovery of such metallic vdW platforms, and f-electron monolayers remain out of reach. Here, we demonstrate that strongly correlated β–uranium tritelluride (β-UTe 3 ) can be exfoliated to the monolayer limit. Unexpectedly, β-UTe 3 remains ferromagnetic in this limit with an enhanced ordering temperature of 35 kelvin, a factor of two larger than its bulk counterpart. Our work establishes β-UTe 3 as a materials platform for investigating and modeling correlated behavior in the monolayer limit and opens numerous avenues for quantum control with, e.g., strain engineering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A computer architecture for intelligent machines

The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Lefebvre, D. R.↗

Timing analysis by model checking

The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.

Naydich, Dimitri↗

Prominence Mass Supply and the Cavity

A prevalent but untested paradigm is often used to describe the prominence-cavity system; the cavity is under-dense because it it evacuated by supplying mass to the condensed prominence. The thermal non-equilibrium (TNE) model of prominence formation offers a theoretical framework to predict the thermodynamic evolutin of the prominence and the surrounding corona. We examine the evidence for a prominence-cavity connection by comparing the TNE model and diagnostics of dynamic extreme ultraviolet (EUV) emission surrounding the prominence, specifically prominence horns. Horns are correlated extensions of prminence plasma and coronal plasma which appear to connect the prominence and cavity. The TNE model predicts that large-scale brightenings will occur in the Solar Dynamics Observatory Atmospheric Imaging Assembly 171 A badpass near he prominence that are associated with the cooling phase of condensation formation. In our simulations, variations in the magnitude of footpoint heating lead to variations in the duration, spatial scale, and temporal offset between emission enhancements in the other EUV bandpasses. While these predictions match well a subset of the horn observations, the range of variations in the observed structures is not captured by the model. We discuss the implications of one-dimensional loop simulations for the three-dimensional time-averaged equilibrium in the prominence and the cavity. Evidence suggests that horns are likely caused by condensing prominence plasma, but the larger question of whether this process produces a density-depleted cavity requires a more tightly constrained model of heating and better knowledge of the associated magnetic structure.

PROMINENCES↗

The basics of quantum computing for chemists

The rapid and successful strides in quantum chemistry in the past decades can be largely credited to a conspicuous synergy between theoretical and computational advancements. However, the architectural computer archetype that enabled such a progress is approaching a state of more stagnant development. One of the most promising technological avenues for the continuing progress of quantum chemistry is the emerging quantum computing paradigm. This revolutionary proposal comes with several challenges, which span a wide array of disciplines. In chemistry, it implies, among other things, a need to reformulate some of its long established cornerstones in order to adjust to the operational demands and constraints of quantum computers. Due to its relatively recent emergence, much of quantum computing may still seem fairly nebulous and largely unknown to most chemists. It is in this context that here we review and illustrate the basic aspects of quantum information and their relation to quantum computing insofar as enabling simulations of quantum chemistry. As a result, we consider some of the most relevant developments in light of these aspects and discuss the current landscape when of relevance to quantum chemical simulations in quantum computers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts

Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study presents a multistage machine learning (ML) approach to streamline the discovery and optimization of complex multimetallic catalysts. Our method integrates data mining, active learning, and domain adaptation throughout the materials discovery process. Unlike traditional trial-and-error methods, this approach systematically narrows the exploration space using domain knowledge with minimized reliance on subjective intuition. Then, the active learning module efficiently refines element composition and synthesis conditions through iterative experimental feedback. The process culminated in the discovery of a promising Ru-Mn-Ca-Pr oxide catalyst. Our workflow also enhances theoretical simulations with domain adaptation strategy, providing deeper mechanistic insights aligned with experimental findings. By leveraging diverse data sources and multiple ML strategies, we demonstrate an efficient pathway for electrocatalyst discovery and optimization. This comprehensive, data-driven approach represents a paradigm shift and potentially benchmark in electrocatalysts research.

Science & Technology - Other Topics↗

Modeling the performance of the human (pilot) interaction in a synthetic flight domain: Information theoretic approach

Current advances in computing technology are devoid of formal methods that describe the theories of how information is shared between humans and machines. Specifically, in the domain of human-machine interaction, a common mathematical foundation is lacking. The aim of this paper is to propose a formal method of human-machine (H-M) interaction paradigm from the information view point. The methods presented are interpretation- and context-free and can be used both in experimental analysis as well as in modeling problems.

Ntuen, Celestine A.↗

Theory and modeling group

The primary purpose of the Theory and Modeling Group meeting was to identify scientists engaged or interested in theoretical work pertinent to the Max '91 program, and to encourage theorists to pursue modeling which is directly relevant to data which can be expected to result from the program. A list of participants and their institutions is presented. Two solar flare paradigms were discussed during the meeting -- the importance of magnetic reconnection in flares and the applicability of numerical simulation results to solar flare studies.

Holman, Gordon D.↗

Stabilization of [(N 5 ) 2 BX] 2– and [(N 5 ) 2 B 2 X 2 ] 2– (X = H, F, Cl, Br) by Conjugation and Hyperconjugation Effects

The isolation of nucleophilic boron bases has led to a paradigm shift in boron chemistry. Previous studies of the bis(carbene) borylene complexes revealed that these compounds possess strong donor abilities, and their reaction inertness is due to the large steric hindrance between boron reagents and reactant. In the present study, we have theoretically studied the [(N 5 ) 2 BX] 2– and [(N 5 ) 2 B 2 X 2 ] 2– compounds (X = H, F, Cl, Br). Their electronic structures and properties are discussed by using the NBO, LOL, and ELF methods. We found that both π-conjugation and hyperconjugation effects can effectively stabilize the substituted nucleophilic anionic boron compounds [(N 5 ) 2 BX] 2– and [(N 5 ) 2 B 2 X 2 ] 2– . Substituents, especially X = H, stabilize the boron center through highly delocalized π-bonding, involving the formally “empty” in-plane p orbitals of the boron atom. While the halogen substituents have high electron withdrawal ability, leading to systems being less stable, we suggest the borinium anions [(N 5 ) 2 BH] 2– and [(N 5 ) 2 B 2 H 2 ] 2– as possible synthetic targets of novel environmentally friendly catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

How the birth and death of shear layers determine confinement evolution: from the L → H transition to the density limit

Electric field profile structure—especially its shear—is a natural order parameter for the edge plasma, and characterizes confinement regimes ranging from the H-mode (Wagner et al. 1982 Phys. Rev. Lett.49, 1408–1412 (doi:10.1103/PhysRevLett.49.1408)) to the density limit (DL) (Greenwald et al. 1988 Nucl. Fusion28, 2199–2207 (doi:10.1088/0029-5515/28/12/009)). The theoretical developments and lessons learned during 40 years of H-mode studies (Connor & Wilson 1999 Plasma Phys. Control. Fusion42, R1–R74 (doi:10.1088/0741-3335/42/1/201); Wagner 2007 Plasma Phys. Control. Fusion49, B1–B33 (doi:10.1088/0741-3335/49/12b/s01)) are applied to the shear layer collapse paradigm (Hong et al. 2017 Nucl. Fusion58, 016041 (doi:10.1088/1741-4326/aa9626)) for the onset of DL phenomena. Results from recent experiments on edge shear layers and DL phenomenology are summarized and discussed in the light of L → H transition physics. The theory of shear layer collapse is then developed. In this work, we demonstrate that shear layer physics captures both the well known current (Greenwald) scaling of the DL (Greenwald 2002 Plasma Phys. Control. Fusion44, R27–R53 (doi:10.1088/0741-3335/44/8/201); Greenwald et al. 2014 Phys. Plasmas21, 110501 (doi:10.1063/1.4901920)), as well as the emerging power scaling (Zanca, Sattin, JET Contributors 2019 Nucl. Fusion59, 126011 (doi:10.1088/1741-4326/ab3b31)). The derivation of the power scaling theory exploits an existing model, originally developed for the L → H transition (Diamond, Liang, Carreras, Terry 1994 Phys. Rev. Lett.72, 2565–2568 (doi:10.1103/PhysRevLett.72.2565); Kim & Diamond 2003 Phys. Rev. Lett.90, 185006 (doi:10.1103/PhysRevLett.90.185006)). We describe the enhanced particle transport events that occur following shear layer collapse. Open problems and future directions are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rare Lepton Decays and Differentiable Hadronization Models - From Signatures of New Physics to Data-driven Event Generation

This dissertation is partitioned into two parts: phenomenological studies focused on rare lepton decays as probes of heavy and light new physics, and the development of differentiable, data-driven hadronization models. Part I develops the phenomenology of new physics signatures stemming from rare charged lepton flavor violating decays probed by experiments at the intensity frontier. These include interactions mediated by both high-scale effective operators and light new physics, manifesting in multi-lepton final states ($\mu \to 5e$), elastic nuclear transitions ($\mu \to e$ conversion), baryon-number-violating muon capture, and time-dependent signals from ultralight dark matter ($\mu \to e \phi, \tau \to \ell \phi$). Part II develops two distinct strategies for advancing differentiable and data-driven hadronization models. One involves comprehensive reweighting frameworks for hadronization that enable efficient uncertainty estimation, facilitate parameter tuning, and interface naturally with differentiable programming paradigms. The other introduces machine-learning-based methods for extracting microscopic fragmentation dynamics directly from macroscopic observables through the deformation of existing models -- effectively providing solutions to the inverse problem of hadronization. Altogether, these studies advance the interpretability, flexibility, and precision of theoretical predictions for both high-intensity and high-energy experiments.

Menzo, Tony [Cincinnati U.] (ORCID:000000022013457↗

Using interfaces to: create strongly-coupled magnetic-ferroelectrics

Starting at the level of electrons and atoms our long-term goal is to rationally design complex oxide heterostructures and interface-materials with targeted emergent behaviors. This is not a matter of simply optimizing material parameters, but rather begins with understanding a mechanism to control the interplay between the diverse microscopic degrees of freedom prevalent in complex oxides in order to create targeted macroscopic phenomena and ends with the design of new material realizations. These realizations are in turn created with atomic-layer precision, structurally assessed to see that they are the intended realization, and finally their relevant properties are measured. During this program we have developed the scientific ideas necessary to apply this materials-by-design paradigm to the creation of materials offering electrical control of magnetism. At the heart of our approach lies a partnership between theory, synthesis, and characterization. These are the areas of expertise of the three co-PIs, who have worked closely together since their arrival at Cornell. During this project bold ideas on where to put the atoms to provide electrical control of magnetism were met with the latest methods of synthesis science and electron microscopy in an attempt create targeted new multiferroics. Our work applying this materials-by-design methodology to multiferroics has enjoyed multiple successes. The Co-PIs have invented new mechanisms for multiferroics, which provide strong coupling between polarization and magnetism, and reduced them to practice. Specifically, we pioneered multiferroics based on spin-phonon coupling, rotation-driven multiferroicity, and novel geometric multiferroics. Importantly, the latter two of these mechanisms enable the deterministic switching of magnetism by an applied electric field, which is key to the application of multiferroics to future device technologies. Most recently, we performed detailed theoretical analysis on a system involving the combination of magnetoelectric and colossal magnetoresistance behaviors and predict that electrical control of a metal-insulator transition is possible in appropriately strained SmBaMn2O6. The research enabled by this grant led to 63 publications in leading refereed journals including Nature, Nature Materials, Physical Review Letters, and Advanced Materials demonstrating a materials-by-design paradigm to the creation of materials offering electrical control of magnetism.

36 MATERIALS SCIENCE↗

A software tool for dataflow graph scheduling

A graph-theoretic design process and software tool is presented for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described using a dataflow graph and are intended to be executed repetitively on multiple processors. The dataflow paradigm is very useful in exposing the parallelism inherent in algorithms. It provides a graphical and mathematical model which describes a partial ordering of algorithm tasks based on data precedence.

Jones, Robert L., III↗

Why cutting respiratory CO 2 loss from crops is possible, practicable, and prudential

Abstract Plants release back to the atmosphere about half of the CO 2 they capture by photosynthesis. Decreasing the rate of crop respiration could therefore potentially increase yields, store more carbon in the soil and draw down atmospheric CO 2 . However, decreasing respiration rate has had very little research effort compared to increasing photosynthesis, the historically dominant metabolic paradigm for crop improvement. Conceptual and technical advances, particularly in protein turnover and directed enzyme evolution, have now opened ways to trim the large fraction of respiration that fuels proteome maintenance by lowering the breakdown and resynthesis rates of enzymes and other proteins. In addition to being theoretically possible and practicable, exploring the reduction of respiration is prudential, given that it (i) has barely yet been tried and (ii) could help meet the challenges of sustaining crop productivity and managing atmospheric carbon.

Joshi, Jaya↗