Search NASA⌕ Search

SEARCH · Search NASA

Results for “group representations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

IrRep: Symmetry eigenvalues and irreducible representations of ab initio band structures

Here, we present IrRep – a Python code that calculates the symmetry eigenvalues of electronic Bloch states in crystalline solids and the irreducible representations under which they transform. As input it receives bandstructures computed with state-of-the-art Density Functional Theory codes such as VASP, Quantum Espresso, or Abinit, as well as any other code that has an interface to Wannier90. Our code is applicable to materials in any of the 230 space groups and double groups preserving time-reversal symmetry with or without spin-orbit coupling included, for primitive or conventional unit cells. This makes IrRep a powerful tool to systematically analyze the connectivity and topological classification of bands, as well as to detect insulators with non-trivial topology, following the Topological Quantum Chemistry formalism: IrRep can generate the input files needed to calculate the (physical) elementary band representations and the symmetry-based indicators using the [CheckTopologicalMat: https://www.cryst.ehu.es/cgi-bin/cryst/programs/magnetictopo.pl] routine of the Bilbao Crystallographic Server. It is also particularly suitable for interfaces with other plane-waves based codes, due to its flexible structure.

97 MATHEMATICS AND COMPUTING↗

Deeply conserved synteny and the evolution of metazoan chromosomes

Animal genomes show networks of deeply conserved gene linkages whose phylogenetic scope and chromosomal context remain unclear. Here, we report chromosome-scale conservation of synteny among bilaterians, cnidarians, and sponges and use comparative analysis to reconstruct ancestral chromosomes across major animal groups. Comparisons among diverse metazoans reveal the processes of chromosome evolution that produced contemporary karyotypes from their Precambrian progenitors. On the basis of these findings, we introduce a simple algebraic representation of chromosomal change and use it to establish a unified systematic framework for metazoan chromosome evolution. We find that fusion-with-mixing, a previously unappreciated mode of chromosome change, has played a central role. We find that relicts of several metazoan chromosomal units are preserved in unicellular eukaryotes. These conserved pre-metazoan linkages include the chromosomal unit that encodes the most diverse set of metazoan homeobox genes, suggesting a candidate genomic context for the early diversification of this key gene family.

59 BASIC BIOLOGICAL SCIENCES↗

Illuminating the pathways to carbon liberation: a systems approach to characterizing the consequential unknowns of carbon transformation and loss from thawing permafrost peatlands (Final Report)

The IsoGenie3 Project delivered new systems-level insights into carbon cycling in thawing permafrost landscapes, with an emphasis on methane and carbon dioxide emissions. From >200 samples from the site collected over a decade, co-analyzed for geochemistry and microbiology, the team recovered ~1,500 assembled microbial genomes and ~1,900 viral population genomes, revealing appreciable genetic novelty - from a new highly abundant bacterial phylum, to novel methane consumers and their activities, to rampant viral novelty. IsoGenie3 linked these organisms to carbon compound transformations (which define the cycling of organic matter in soils, and the loss of the greenhouse gases carbon dioxide and methane), and saw that the microbes at each stage of permafrost thaw had different genetic potential to degrade categories of compounds, expressed that genetic potential differently, and actually transformed carbon compounds into greenhouse gases in different ways. IsoGenie 3 identified that some of the thaw-stage differences were due to plant-microbiome relationships; the plant species across the thaw gradient contributed different carbon compounds into the soil, and hosted distinct microbiota (differing among parts of plants as well as species). Lastly, microbes in the saturated post-thaw conditions appeared likely to contribute to the mobilization and toxification of mercury released during thaw. In parallel with ongoing field sampling and analysis, hypotheses arising from field observations were tested via lab incubation experiments. When communities are taken out of their native habitats, they behave differently, and the team first rigorously quantified the magnitude of this effect on microbiome composition and functional capacity, organic matter composition, and gas production; overall the main system processes were maintained in the lab incubations under the conditions tested. Further, the microbial data could inform geochemical reaction network models of those processes. Then, the team ran experiments with additions of compounds, varying temperature, and “live” vs. “dead” peat (the latter having been gamma irradiated, with a few additional variants to control for methodological artifacts). From these, we (a) determined the importance of plant-derived soluble phenolic compounds in bogs’ extraordinary recalcitrance of organic matter, and carbon gas emissions skewed to carbon dioxide; (b) proposed an abiotic ‘tanning’ mechanism, which could contribute to Sphagnum’s inhibitory effect on anaerobic decomposition through alteration of N availability. IsoGenie3 illuminated longer-term and landscape-scale interactions of permafrost thaw and carbon cycling, advancing knowledge of the drivers of methane dynamics not only across in the permafrost-associated peatland (where hydrology and plant communities dictate microbiomes) but also their interconnected lakes (where sediment carbon quality and resident microbiota are determined by position within lake, and lake features). By leveraging observations of site methane dynamics extending well before this project, the team was able to construct a 44-year portrait of the interplay of permafrost thaw, hydrology, vegetation dynamics, and carbon gas emissions, and the doubling of the fully-thawed fens over this time. From the detailed study of this focal site, IsoGenie3 also aimed to improve model representation of these kinds of sites and processes. To improve predictions of methane transformations, we incorporated acetate and isotope dynamics into the ‘DNDC’ biogeochemistry model. In addition, recovered genomes were grouped into ‘functional groups’, i.e. the genomes that perform a specific function of interest, then used to parameterize maximum growth rate and optimum growth temperature (via signatures in their sequence composition) for the BioCrunch model. The BioCrunch model was then in turn used to test the impact of increasing functional resolution of the microbes, on the carbon gas emissions. Lastly for modeling, the ecosys model was parameterized from the microbial and other data, and used to evaluate drivers of e.g. change in methane emissions. Finally, this project also led to the development of a range of new methods and tools, a new metric of organic matter decomposability, as well as a graph-database solution to multidisciplinary data storage and querying. This project’s ongoing analyses at our focal site also contributed to broader advancements in understanding elements of genetic plasticity and methane metabolism, climate change microbiology and community assembly, global peatland geochemistry and Arctic lakes’ roles in climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

The hazard components of representative key risks. The physical climate perspective

The framework of Representative Key Risks (RKRs) has been adopted by the Intergovernmental Panel on Climate Change Working Group II in order to categorize, assess and communicate a wide range of regional and sectoral key risks, expected to become severe as a consequence of the potentially detrimental convergence of changing climate conditions, exposure and vulnerability of human and natural systems, and responses through (mal)adaptation measures. Other papers in this special issue treat each of eight RKRs by holistically assessing their current status and future evolution as a result of this convergence. However, their treatment cannot always organize such assessment according to a systematic gradation of climatic changes, often times having to extrapolate the big-picture evolution of risk from either qualitative effects of “low” medium” and “high” warming, or limited/focused analysis of the consequences of particular mitigation choices (e.g., benefits of limiting warming to 1.5 or 2C). In this study we offer as systematic a representation as possible – given current literature and assessments – of the future evolution of the hazard components of RKRs. We draw on the assessment of changes in climatic impact-drivers relevant to RKRs described in the 6th Assessment Report by Working Group 1 (WGI) supplemented when needed by more recent literature. We identify the relevant hazards for each RKR, based upon the WGII authors’ assessment, and we report on their current state and expected future changes in magnitude, intensity and/or frequency, linking these changes to Global Warming Levels to the extent possible. For some of these quantities - like regional trends in oceanic and atmospheric temperature and precipitation, some heat and precipitation extremes, permafrost thaw and Northern Hemisphere snow cover - a strong and quantitative relationship with global average temperature change has been assessed. For others - like frequency and intensity of tropical cyclones and extra-tropical storms, and fire weather - the link to increasing global temperatures can only be described qualitatively. For some processes - like the behavior of ice-sheets, or changes in circulation dynamics - large uncertainties about the effects of different levels of warming remain, and for a few others - like ocean pH and air pollution - the composition of the scenario of anthropogenic emissions is most relevant, rather than the warming reached. In almost all cases, however, the basic message remains that every small increment in CO2 concentration in the atmosphere and associated warming will bring changes in climate phenomena that will contribute to increasing risk of impacts on human and natural systems when these changes happen in conjunction with these systems’ conditions of exposure and vulnerability, and in lack of effective adaptation. Our picture of the evolution of RKR-relevant climatic impact-drivers complements and enriches the treatment of RKRs in the other papers in at least two ways: by filling in an often only cursory or limited representation of the physical climate aspects driving impacts, and by providing a fuller representation of their future possible evolution which represents an important component – if never the only one – of the potential future evolution of risk severity.

54 ENVIRONMENTAL SCIENCES↗

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems towards either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services towards some human end. We trace the salient features of modeled representations of human systems by organizing the typology around three key questions: 1) Who are the modeled actors in MSD systems? 2) What are their modeled actions? 3) How and for what purpose are these actors and actions operationalized in a computational model? The typology is used to critically examine existing models and chart the frontier of future human systems modeling for MSD research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Porflow Implementation of Vadose Zone Conceptual Model for Slit and Engineered Trenches in the E-Area Low Level Waste Facility Performance Assessment

A summary of the conceptual models to be used in representing slit (ST) and engineered trenches (ET) in PORFLOW (ACRi 2018) simulations as part of the performance assessment (PA) of the E-Area Low Level Waste Facility (ELLWF) is presented. Key details that are discussed include: model geometries, spatially dependent hydro-stratigraphic representations, model dimensionality, and boundary conditions (i.e., infiltration rates, cover overhangs, subsidence). Accounting for differences in the percent of non-crushable materials, eighteen unique models, defined by seven hydro-stratigraphic groupings, will be used to represent slit and engineered trenches.

42 ENGINEERING↗

Dynamic Binary Complexes (DBC) as Super-Adjustable Viscosity Modifiers for Hydraulic Fracturing Fluids

In the preceding project year two, we refined three DBC formulations from a selection of over 50 different chemistries. The optimization study primarily encompassed testing for (i) reversibility extent, (ii) performance in the presence of chemical additives, (iii) adhesion and friction behavior during displacement in wellbores and pipelines, (iv) corrosion protection performance, and (v) injection performance with model fracture systems at the laboratory scale. Highly promising results obtained from all these tests signify the significant potential of DBCs in enhancing hydrocarbon recovery from unconventional reservoirs. The primary activities in the third project year included publishing experimental findings across multiple articles and conducting outreach initiatives. Throughout the year, we undertook tasks such as replicating experimental results, further optimizing various formulations and their associated experimental sets, and conducting additional tests to address missing components based on reviewer feedback and suggestions. We also explored the surfactant and friction-reduction aspects of selected formulations through drag reduction tests. In addition, we constructed an improved fracturing performance setup and performed flow injection tests. The specific DBC formulations focused on during this project period were A8/B1, A12/B5, and A10/B12. We also obtained results for additional DBC formulations and a select few commercial fracturing fluids for the purpose of comparison. Within the project's scope, we aim to enhance the experimental findings with the development of various models. The first two years focused on two key aspects: (i) the creation of a high-fidelity hydraulic fracturing model for non-Newtonian fluids to gain insights into the implementation of DBC fluids in fracking environments, and (ii) the development of a multiphase flow simulator for estimating total production, fluid saturation in the reservoir, and the creation of a fracture propagation model and kinetic Monte Carlo (kMC) models for diverse applications. In the third year, we delved into the fundamental nanostructural properties of DBCs, exploring aspects such as material chemistry, pH tunability, and control of DBC formation and stability. Subsequently, in the extension year, we conducted a systematic investigation of various building blocks containing primary, secondary, and tertiary amine functional groups to understand their impact on rheological and viscoelastic properties. Furthermore, we explored a Dissipative Particle Dynamics (DPD) model to simulate self-assembly processes with precision, creating a high-fidelity representation of relevant nanostructures. The tasks performed this year with the significant results obtained have been discussed in Section 2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward a coordinated understanding of hydro‐biogeochemical root functions in tropical forests for application in vegetation models

Summary Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest–climate feedbacks for these carbon‐rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine‐root strategies for soil resource exploration, (2) coupling and trade‐offs in fine‐root water vs nutrient acquisition, and (3) aboveground–belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground–belowground hydro‐nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO 2 . The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.

Plant Sciences↗

Characters, quasinormal modes, and Schwinger pairs in dS 2 with flux

An integral representation of the 1-loop partition function for charged scalars and spinors, minimally coupled to a uniform U(1) field on S 2 , is given in terms of SO(1, 2) Harish-Chandra group characters and evaluated exactly in terms of Hurwitz ζ-functions. Analytically continuing the U(1) field, we interpret the path integrals as quasicanonical partition functions in dS 2 with an electric field. The character itself is obtained as a trace over states living at the future boundary of de Sitter and has a quasinormal mode expansion. The imaginary part of the partition function captures Schwinger pair creation in the static patch at finite temperature. The thermal enhancement is most noticeable for scalar masses below Hubble and leads to non-monotonicity of the current as a function of the field. This parameter range, when dimensionally reducing from a charged or rotating Nariai spacetime, is excluded by Swampland-inspired bounds. Around the AdS 2 black hole, in contrast to dS 2 , there is a threshold to pair creation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fermion mass, axion dark matter, and leptogenesis in SO(10) GUT

SO(10) grand unified theory with minimum parameters in the Yukawa sector employs the Peccei-Quinn symmetry that solves the strong C P problem. Such an economical Yukawa sector is highly appealing and has been extensively studied in the literature. However, when the running of the renormalization group equations of the Yukawa couplings are considered, this scenario shows some tension with the observed fermion masses and mixing. In this work, we propose an extension of the minimal framework that utilizes lower dimensional representations and alleviates this tension by introducing only a few new parameters. The proposed model consists of a fermion in the fundamental and a scalar in the spinorial representations. While the latter is needed to implement the Peccei-Quinn symmetry successfully, the presence of both is essential in obtaining an excellent fit to the fermion mass spectrum. In our model, axions serve the role of dark matter, and the out-of-equilibrium decays of the right-handed neutrinos successfully generate the matter-antimatter symmetry of the Universe. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs With Physics‐Informed Neural Networks

Accurate representation of pumping wells is essential for reliable reservoir characterization and simulation of operational scenarios in subsurface flow models. Physics-informed neural networks (PINNs) are emerging as a promising alternative to numerical models for reservoir modeling, offering seamless integration of monitoring data and governing physical equations. However, existing PINN-based studies face major challenges in capturing fluid pressure near wells when using a source/sink term, particularly during the early stages after pumping begins. We address this problem by introducing WellPINN, a workflow in which an initially trained PINN infers fluid pressure across the entire reservoir domain using a large equivalent well radius. This initial PINN solution is then locally refined around the well by a set of subdomain PINNs that are trained for smaller equivalent well radii. Continuity across these subdomain interfaces as well as at the initial condition is ensured by hard-constraining each PINN on its subdomain boundary. Our results demonstrate WellPINN as the first workflow of its kind to focus on accurate inference of fluid pressure from pumping rates throughout the entire injection period, significantly advancing the potential of PINNs for inverse modeling and operational scenario simulations. All data and code for this paper are openly available at https://doi.org/10.20350/DIGITALCSIC/17260.

58 GEOSCIENCES↗

Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity

The newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known. Results Here, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of >600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group.

59 BASIC BIOLOGICAL SCIENCES↗

Implementation of an Orographic Drag Scheme Considering Orographic Anisotropy in All Flow Directions in the Earth System Model CAS‐ESM 2.0

Abstract A reasonable representation of orographic anisotropy in earth system models is vital for improving weather and climate modeling. In this study, we implement the orographic drag scheme, including 3‐D orographic anisotropy (3D‐AFD), into the Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM 2.0). Three groups of simulations named sensitivity run, medium‐range forecast, and seasonal forecast respectively are conducted using the updated CAS‐ESM model and validated against station observation and reanalysis data. These simulations are run using the three schemes—3D‐AFD scheme, the 3D orographic anisotropy scheme for the eight‐direction (3D‐8x), and the 2D isotropic scheme (2D)—to compare their performance in CAS‐ESM 2.0. Sensitivity runs show that the 3D‐AFD provide more continuous transition of calculated drag as function of wind direction than the 3D‐8x, while the drag calculated using the 2D scheme show no variation with change of wind direction. Enhanced drag in the medium range and seasonal forecast using the updated CAS‐ESM alleviates part of the winter wind speed bias over the Tibetan Plateau (TP) and the cold bias over TP and the Siberian polar region. It is shown that the 3D‐AFD scheme alleviates more bias than that of the 3D‐8x scheme (by wind speed reduction of 1 ∼ 2 m/s and temperature of 1 ∼ 2 K) especially in the seasonal forecast. The results suggest that reasonable representation of the orographic anisotropy is important in climate modeling.

Xie, Jinbo↗

Coupling and recoupling coefficients for Wigner’s U(4) supermultiplet symmetry

A novel procedure for evaluating Wigner coupling coefficients and Racah recoupling coefficients for U(4) in two group–subgroup chains is presented. The canonical U(4) > U(3) > U(2) > U(1) coupling and recoupling coefficients are applicable to any system that possesses U(4) symmetry, while the physical U(4) coupling coefficients are more specific to nuclear structure studies that utilize Wigner’s supermultiplet symmetry concept. The procedure that is proposed sidesteps the use of binomial coefficients and alternating sum series and consequently enables fast and accurate computation of any and all U(4)-underpinned features. The inner multiplicity of a (S, T) pair within a single U(4) > SU S (2) Ⓧ SU T (2) irreducible representation is obtained from the dimension of the null space of the SU(2) raising generators, while the resolution for the outer multiplicity follows from the work of Alex et al. on U(N) . It is anticipated that a C++ library will ultimately be available for determining generic coupling and recoupling coefficients associated with both the canonical and the physical group–subgroup chains of U(4).

Cross-Coupling Reaction↗

Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer

Cervical lymph node metastasis is the leading cause of poor prognosis in oral tongue squamous cell carcinoma and also occurs in the early stages. The current clinical diagnosis depends on a physical examination that is not enough to determine whether micrometastasis remains. The transcriptome profiling technique has shown great potential for predicting micrometastasis by capturing the dynamic activation state of genes. However, there are several technical challenges in using transcriptome data to model patient conditions: (1) An Insufficient number of samples compared to the number of genes, (2) Complex dependence between genes that govern the cancer phenotype, and (3) Heterogeneity between patients between cohorts that differ geographically and racially. We developed a computational framework to learn the subnetwork representation of the transcriptome to discover network biomarkers and determine the potential of metastasis in early oral tongue squamous cell carcinoma. Our method achieved high accuracy in predicting the potential of metastasis in two geographically and racially different groups of patients. The robustness of the model and the reproducibility of the discovered network biomarkers show great potential as a tool to diagnose lymph node metastasis in early oral cancer.

59 BASIC BIOLOGICAL SCIENCES↗

Evolutionary lineage explains trait variation among 75 coexisting grass species

Summary Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C 3 vs C 4 plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity. We measured 11 structural and physiological traits in situ from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species. Critically, we found evidence that grass traits varied among lineages, including independent origins of C 4 photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics. Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C 4 species. These results indicate that further assessment of lineage‐based differences at other sites and across other grass species distributions may improve representation of C 4 species in trait comparison analyses and modeling investigations.

Donnelly, Ryan C.↗

Color symmetry and confinement as an underlying superconformal structure in holographic QCD

Dedicated to the memory of our colleague, Harald Fritzsch, who, together with Murray Gell-Mann, introduced the color quantum number as the exact symmetry responsible for the strong interaction, thus establishing quantum chromodynamics (QCD) as a fundamental non-Abelian gauge theory. A basic understanding of hadron properties, however, such as confinement and the emergence of a mass scale, from first principles QCD has remained elusive: Hadronic characteristics are not explicit properties of the QCD Lagrangian and perturbative QCD, so successful in the large transverse momentum domain, is not applicable at large distances. In this article, we shall examine how this daunting obstacle is overcome in holographic QCD with the introduction of a superconformal symmetry in anti de Sitter (AdS) space which is responsible for confinement and the introduction of a mass scale within the superconformal group. When mapped to light-front coordinates in physical spacetime, this approach incorporates supersymmetric relations between the Regge trajectories of meson, baryon and tetraquark states which can be visualized in terms of specific SU(3) C color representations of quarks. Finally, we will also briefly discuss here the implications of holographic models for QCD color transparency in view of the present experimental interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Entropy-Assisted Quality Pattern Identification in Finance

Short-term patterns in financial time series form the cornerstone of many algorithmic trading strategies, yet extracting these patterns reliably from noisy market data remains a formidable challenge. In this paper, we propose an entropy-assisted framework for identifying high-quality, non-overlapping patterns that exhibit consistent behavior over time. We ground our approach in the premise that historical patterns, when accurately clustered and pruned, can yield substantial predictive power for short-term price movements. To achieve this, we incorporate an entropy-based measure as a proxy for information gain: patterns that lead to high one-sided movements in historical data yet retain low local entropy are more “informative” in signaling future market direction. Compared to conventional clustering techniques such as K-means and Gaussian Mixture Models (GMMs), which often yield biased or unbalanced groupings, our approach emphasizes balance over a forced visual boundary, ensuring that quality patterns are not lost due to over-segmentation. By emphasizing both predictive purity (low local entropy) and historical profitability, our method achieves a balanced representation of Buy and Sell patterns, making it better suited for short-term algorithmic trading strategies. This paper offers an in-depth illustration of our entropy-assisted framework through two case studies on Gold vs. USD and GBPUSD. While these examples demonstrate the method’s potential for extracting high-quality patterns, they do not constitute an exhaustive survey of all possible asset classes.

Physics↗