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Nambu and Compositeness

The Nambu--Jona-Lasinio model is the simplest field theory of a composite scalar boson, consisting of a pair of chiral fermions. A bound state emerges from an assumed point-like 4-fermion interaction and is described by local effective field, $\Phi(x)$. We review this in the context of the renormalization group and show some its phenomenological successes, such as the QCD chiral dynamics and the prediction of stable heavy-light resonances that reveal the single light quark chiral dynamics. We also review some NJL--inspired composite Higgs models. We then describe a novel UV completion of the NJL model, to an extended interaction, where the solution is described by a bilocal effective, Yukawa field, $\Phi(x,y)$. I conclude with a personal recollection of Yoichiro Nambu.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Particle configurations in the $NN\bar K$ system

Three-body AAB model for the $NN\bar K$(s NN = 0) kaonic cluster is considered based on the configuration space Faddeev equations. Within a single channel approach, the difference between masses of nucleons and kaons and the charge independence breaking of nucleon-nucleon interaction are taken into consideration. We definite the particle configurations in the system according to the particle masses and pair potentials. There are two sets of the particle configurations, ppK¯, npK¯ 0 and nnK¯ 0 , npK¯, charged and neutral. The three-body calculations are performed by applying NN and NK¯ phenomenological isospin-dependent potentials. The mass and energy spectra related to the particle configurations are presented. We evaluate the mass and energy uncertainties for the NNK¯ model. As a result, an analogy to NNN model for the 3 H and 3 He nuclei is proposed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Energy deposition in a gaseous mixture

Existing models in planetary aeronomy involve a variety of possible gaseous mixtures subjected to charged particle bombardment. In the present paper, a phenomenological approach to electron degradation in such mixtures is proposed to facilitate analysis of such problems. Existing parameterized yield spectra for a variety of gases, computed by a discrete energy bin method, are used as a basis for constructing a parameterized composite yield spectrum for an arbitrary mixture. The approach proposed is an improvement over the continuous slow-down approximation in that discreteness is taken into account phenomenologically. The advantages are in the ease of application to aeronomical problems involving variable mixtures.

Peterson, L. R.↗

A life prediction model for laminated composite structural components

A life prediction methodology for laminated continuous fiber composites subjected to fatigue loading conditions was developed. A summary is presented of research completed. A phenomenological damage evolution law was formulated for matrix cracking which is independent of stacking sequence. Mechanistic and physical support was developed for the phenomenological evolution law proposed above. The damage evolution law proposed above was implemented to a finite element computer program. And preliminary predictions were obtained for a structural component undergoing fatigue loading induced damage.

Allen, David H.↗

Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics

Data-driven constitutive modeling with neural networks has received increased interest in recent years due to its ability to easily incorporate physical and mechanistic constraints and to overcome the challenging and time-consuming task of formulating phenomenological constitutive laws that can accurately capture the observed material response. However, even though neural network-based constitutive laws have been shown to generalize proficiently, the generated representations are not easily interpretable due to their high number of trainable parameters. Sparse regression approaches exist that allow for obtaining interpretable expressions, but the user is tasked with creating a library of model forms which by construction limits their expressiveness to the functional forms provided in the libraries. Here, in this work, we propose to train regularized physics-augmented neural network-based constitutive models utilizing a smoothed version of $L^0$-regularization. This aims to maintain the trustworthiness inherited by the physical constraints, but also enables interpretability which has not been possible thus far on any type of machine learning-based constitutive model where model forms were not assumed a priori but were actually discovered. During the training process, the network simultaneously fits the training data and penalizes the number of active parameters, while also ensuring constitutive constraints such as thermodynamic consistency. We show that the method can reliably obtain interpretable and trustworthy constitutive models for compressible and incompressible hyperelasticity, yield functions, and hardening models for elastoplasticity, using synthetic and experimental data. This work aims to set a new paradigm for interpretable machine learning models in the broad area of solid mechanics where low and limited data is available along with prior knowledge of physical constraints that the learned maps need to obey. This paradigm can potentially be extended to a broader spectrum of scientific exploration.

Data-driven constitutive models↗

Thermomechanical deformation testing and modeling in the presence of metallurgical instabilities

A number of viscoplastic constitutive models were developed to describe deformation behavior under complex combinations of thermal and mechanical loading. Questions remain, however, regarding the validity of procedures used to characterize these models for specific structural alloys. One area of concern is that the majority of experimental data available for this purpose are determined under isothermal conditions. This experimental study is aimed at determining whether viscoplastic constitutive theories characterized using an isothermal data base can adequately model material response under the complex thermomechanical loading conditions typical of power generation service. The approach adopted was to conduct a series of carefully controlled thermomechanical experiments on a nickel-based superalloy, Hastelloy Alloy X. Previous investigations had shown that this material experiences metallurgical instabilities leading to complex hardening behavior, termed dynamic strain aging. Investigating this phenomenon under full thermomechanical conditions leads to a number of challenging experimental difficulties which up to the present work were unresolved. To correct this situation, a number of advances were made in thermomechanical testing techniques. Advanced methods for dynamic temperature gradient control, phasing control and thermal strain compensation were developed and incorporated into real time test control software. These advances allowed the thermomechanical data to be analyzed with minimal experimental uncertainty. The thermomechanical results were evaluated on both a phenomenological and microstructural basis. Phenomenological results revealed that the thermomechanical hardening trends were not bounded by those displayed under isothermal conditions. For the case of Hastelloy Alloy X (and similar dynamic strain aging materials), this strongly suggests that some form of thermomechanical testing is necessary when characterizing a thermoviscoplastic deformation model. Transmission electron microscopy was used to study the microstructural physics, and analyze the unique phenomenological behavior.

Castelli, Michael G.↗

Spatially inhomogeneous magnetic superconductors

Here we consider a problem of superconductivity coexistence with the spin-density-wave order in disordered multiband metals. It is assumed that random variations of the disorder potential on short length scales render the interactions between electrons to become spatially correlated. As a consequence, both superconducting and magnetic order parameters become spatially inhomogeneous and are described by the universal phenomenological quantities, whereas all the microscopic details are encoded in the correlation function of the coupling strength fluctuations. We consider a minimal model with two nested two-dimensional Fermi surfaces and disorder potentials which include both intra- and interband scattering. The model is analyzed using the quasiclassical approach to show that short-scale pairing-potential disorder leads to a broadening of the coexistence region.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microscopic origin of ultranodal superconducting states in spin- 1 2 systems

Several unconventional superconductors show indications of zero-energy excitations in the superconducting state consistent with the existence of a so-called Bogoliubov-Fermi surface (BFS). In particular, FeSe isovalently substituted with S seems to acquire a nonzero density of states at zero energy at low temperatures as the system goes into the tetragonal phase, consistent with a previously proposed phenomenological theory assuming an anisotropic spin singlet pairing gap coexisting with a nonunitary interband triplet component. Here we search for a microscopic model that can support the coexistence of singlet pairing with other orders, including interband nonunitary triplet pairing with magnetization, and discuss several candidates that indeed stabilize ground states with BFS. We show that with proper choice of the coupling strength of the various orders in our model, spontaneous breaking of C 4 rotational symmetry is realized at low temperatures. This feature resembles the findings of recent angle-resolved photoemission experiments in Fe(Se,S) in the tetragonal phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

UV massive resonance from IR double copy consistency

From the perspective of effective field theory (EFT), Wilson coefficients of the low energy theory are determined by integrating out modes of the full ultraviolet (UV) theory. The spectrum can be in principle resummed if one has access to all available infrared (IR) coefficients at low energies. In this work we show that there exists a general class of consistent massive resonance double-copy (CMRDC) models where UV massive residues are reconstructed through double-copy consistency conditions between the IR Wilson coefficients of the full EFT expansion. Through a color-dual bootstrap, we find surprisingly that double-copy consistency alone introduces the kinematic factors of CMRDC models that soften high energy behavior by exponentiating color-dual contacts. This bootstrap suggests that our massive resonance paradigm is an inevitable consequence of the duality between color and kinematics, thereby providing a path towards emergent UV structure directly from the IR. We then demonstrate how CMRDC models can capture a spectrum of massive modes compatible with general multiplicity, and use Padé extrapolation to solve the inverse problem of identifying massive UV resonance from a small number of IR Wilson coefficients. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Extracting transition generalized parton distributions from hard exclusive pion-nucleon scattering

We study the extraction of transition generalized parton distributions (GPDs) from production of two back-to-back high transverse momentum photons ( γ γ ) and a massive pair of leptons ( ℓ + ℓ − ) in hard exclusive pion-nucleon scattering. We argue that the exclusive scattering amplitude of both processes could be factorized into nonperturbative pion distribution amplitude and nucleon transition GPDs that are convoluted with perturbatively calculable short-distance matching coefficients. We demonstrate that the exclusive diphoton production not only is complementary to the Drell-Yan-type dilepton production for extracting the GPDs but also provides enhanced sensitivities for extracting the parton momentum fraction x dependence of the GPDs. We show that both exclusive observables are physically measurable at the J-PARC and AMBER experiment energies. If the target nucleon can be polarized, corresponding spin asymmetries can offer additional sensitivities for extracting transition GPDs. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dynamical Scaling as a Signature of Multiple Phase Competition in Yb 2⁢ Ti 2 ⁢O 7

Yb 2 ⁢Ti 2 ⁢O 7 is a celebrated example of a pyrochlore magnet with highly frustrated, anisotropic exchange interactions. To date, attention has largely focused on its unusual, static properties, many of which can be understood as coming from the competition between different types of magnetic order. Here, in this work, we use inelastic neutron scattering with exceptionally high energy resolution to explore the dynamical properties of Yb 2 ⁢Ti 2 ⁢O 7 . We find that spin correlations exhibit dynamical scaling, analogous to behavior found near to a quantum critical point. We show that the observed scaling collapse can be explained within a phenomenological theory of multiple-phase competition, and confirm that a scaling collapse is also seen in semiclassical simulations of a microscopic model of Yb 2 ⁢Ti 2 ⁢O 7 . These results suggest that dynamical scaling may be general to systems with competing ground states.

74 ATOMIC AND MOLECULAR PHYSICS↗

High current hollow cathode phenomena

Experimental results show that the energies of ions produced near a hollow cathode orifice can be several times the anode-to-cathode potential difference generally considered available to accelerate them. These energies (of order 50 eV) are sufficient to induce substantial sputter erosion rates. Increases in discharge current (to 60 A) cause the energies and current densities of these jet ions to increase substantially. A model describing jet ion generation is proposed. The effects of discharge current on cathode internal pressure are also examined experimentally and described phenomenologically.

Friedly, Verlin J.↗

On the theory of silicon spectra in O and B stars

Results of a previous calculation of a grid of predicted line profiles for 36 multiplets of Si II, III, and IV over a range of model atmospheres corresponding roughly to B0-B5 in spectral type and III-IV in luminosity class are analyzed and applied to observed spectra. The overall properties of the grid of Si line equivalent widths are reviewed, the diagnostic capability of this grid is discussed, and some results are presented for the parameters of 11 B stars derived from observed Si lines. The general fit of the predictions to the observations is evaluated, and test calculations are performed to examine the effect of varying a number of important parameters. Some systematic trends in the computational results are noted which can be expressed as phenomenological 'laws'. Special attention is given to problems arising from non-LTE effects as well as to the self-consistency of analytical results obtained from unblanketed models. It is found that the Si line calculations yield good agreement in two tests for main-sequence stars between B0 and B2, but both tests give somewhat negative results for spectral types later than B2.

Kamp, L. W.↗

Dripping handrails and the quasi-periodic oscillations of the AM Herculis objects

AM Her objects exhibit periodic, quasi-periodic, and aperiodic variability on timescales ranging from seconds to years. Here, we investigate a process for the production of aperiodic and quasi-periodic accretion rate fluctuations. We consider the nonlinear dynamical model known as the dripping handrail (DHR). The DHR, basically a model for certain types of spatially extended systems and loosely based on water condensing on and dripping off a handrail, has recently been used as a model for the quasi-periodic oscillations (QPO) and very low frequency noise of the low-mass X-ray binary Sco X-1. Here, we show that (1) the DHR is a robust QPO generation process in that it leads to QPO production under a wide range of conditions and assumptions; (2) the phenomenology of the DHR is consistent with the observed aperiodic and quasi-periodic varibility of the AM Her QPO source VV Pup over timescales ranging from 16 ms to 20 s; and (3) a single DHR model can produce both broadband QPOs and features with quality Q greater than 20 as observed in several AM Her QPO sources.

Steiman-Cameron, Thomas Y.↗

The role of computerized modeling and simulation in the development of life support system technologies

Computerized modeling and simulation (CMAS) is a tool that can greatly reduce both the time and cost of technology development. CMAS refers to computer methods for correlating, storing, and retrieving property data for chemical species and for solving the phenomenological equations of physical/chemical processes. Furthermore, process conditions based on properties of materials, mass, and energy balances; equipment sizing based on rate processes; and the governing equations for unit operations can be determined using CMAS. CMAS systems can be used to evaluate an LSS process with minimal requirements for laboratory experimentation. A CMAS model is presented for a vapor compression distillation system(VCD) for reclaiming water from urine.

Modell, Michael↗

Breaking mirror twin color

We investigate simple extensions of the Mirror Twin Higgs model in which the twin color gauge symmetry and the discrete Z2 mirror symmetry are spontaneously broken. This is accomplished in a minimal way by introducing a single new colored triplet, sextet, or octet scalar field and its twin along with a suitable scalar potential. This spontaneous Z2 breaking allows for a phenomenologically viable alignment of the electroweak vacuum, and leads to dramatic differences between the visible and mirror sectors with regard to the residual gauge symmetries at low energies, color confinement scales, and particle spectra. In particular, several of our models feature a remnant SU(2) or SO(3) twin color gauge symmetry with a very low confinement scale in comparison to ΛQCD. Furthermore, couplings between the colored scalar and matter provide a new dynamical source of twin fermion masses, and due to the mirror symmetry, these lead to a variety of correlated visible sector effects that can be probed through precision measurements and collider searches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable, when interacting with its surroundings. The combined law of thermodynamics derived by Gibbs about 150 years ago laid the foundation of thermodynamics. In Gibbs combined law, the entropy production due to internal processes was not included, and the 2nd law was thus practically removed from the Gibbs combined law, so it is only applicable to systems under equilibrium, thus commonly termed as equilibrium or Gibbs thermodynamics. Gibbs further derived the classical statistical thermodynamics in terms of the probability of configurations in a system in the later 1800's and early 1900's. With the quantum mechanics (QM) developed in 1920's, the QM-based statistical thermodynamics was established and connected to classical statistical thermodynamics at the classical limit as shown by Landau in the 1940's. In 1960's the development of density functional theory (DFT) by Kohn and co-workers enabled the QM prediction of properties of the ground state of a system. On the other hand, the entropy production due to internal processes in non-equilibrium systems was studied separately by Onsager in 1930's and Prigogine and co-workers in the 1950's. In 1960's to 1970's the digitization of thermodynamics was developed by Kaufman in the framework of the CALculation of PHAse Diagrams (CALPHAD) modeling of individual phases with internal degrees of freedom. CALPHAD modeling of thermodynamics and atomic transport properties has enabled computational design of complex materials in the last 50 years. Our recently termed zentropy theory integrates DFT and statistical mechanics through the replacement of the internal energy of each individual configuration by its DFT-predicted free energy. The zentropy theory is capable of accurately predicting the free energy of individual phases, transition temperatures and properties of magnetic and ferroelectric materials with free energies of individual configurations solely from DFT-based calculations and without fitting parameters, and is being tested for other phenomena including superconductivity, quantum criticality, and black holes. Those predictions include the singularity at critical points with divergence of physical properties, negative thermal expansion, and the strongly correlated physics. Furthermore, those individual configurations may thus be considered as the genomic building blocks of individual phases in the spirit of the materials genome®. This has the potential to shift the paradigm of CALPHAD modeling from being heavily dependent on experimental inputs to becoming fully predictive with inputs solely from DFT-based calculations and machine learning models built on those calculations and existing experimental data through newly developed and future open-source tools. Furthermore, through the combined law of thermodynamics including the internal entropy production, it is shown that the kinetic coefficient matrix of independent internal processes is diagonal with respect to the conjugate potentials in the combined law, and the cross phenomena that the phenomenological Onsager flux and reciprocal relationships are due to the dependence of the conjugate potential of a molar quantity on nonconjugate molar quantities and other potentials, which can be predicted by the zentropy theory and CALPHAD modeling.

42 ENGINEERING↗

Incorporating Physical Priors into Weakly Supervised Anomaly Detection

We propose a new machine-learning-based anomaly detection strategy for comparing data with a background-only reference (a form of weak supervision). The sensitivity of previous strategies degrades significantly when the signal is too rare or there are many unhelpful features. Our prior-assisted weak supervision (PAWS) method incorporates information from a class of signal models to significantly enhance the search sensitivity of weakly supervised approaches. As long as the true signal is in the prespecified class, PAWS matches the sensitivity of a dedicated, fully supervised method without specifying the exact parameters ahead of time. On the benchmark LHC Olympics anomaly detection dataset, our mix of semisupervised and weakly supervised learning is able to extend the sensitivity over previous methods by a factor of 10 in cross section. Furthermore, if we add irrelevant (noise) dimensions to the inputs, classical methods degrade by another factor of 10 in cross section while PAWS remains insensitive to noise. This new approach could be applied in a number of scenarios and pushes the frontier of sensitivity between completely model-agnostic approaches and fully model-specific searches.

artificial neural networks↗