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Cosmology with persistent homology: a Fisher forecast

Abstract Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from theQuijotesimulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13–50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data.

Astronomy & Astrophysics

Dark Energy Survey Year 3 results: $w$CDM cosmology from simulation-based inference with persistent homology on the sphere

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite, specifically designed to mimic DES Y3 data properties, we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins. After neural network compression of these statistics, we estimate the likelihood function and validate our analysis against baryonic feedback effects, finding minimal biases (under $0.3σ$) in the $Ω_\mathrm{m}-S_8$ plane. Assuming the $w$CDM model, our combined Betti numbers and second moments analysis yields $S_8 = 0.821 \pm 0.018$ and $Ω_\mathrm{m} = 0.304\pm0.037$-constraints 70% tighter than those from cosmic shear two-point statistics in the same parameter plane. Our results demonstrate that topological methods provide a powerful and robust framework for extracting cosmological information, with our spherical methodology readily applicable to upcoming Stage IV wide-field galaxy surveys.

Prat, J. [Nordita; Royal Inst. Tech., Sodertalje;

Tusqh

SAND2025-00675O Tusqh is a software tool that generates cubical meshes in 2D and 3D and computes the homology of these meshes using persistent homology. It includes a grid cell in the output if its volume-fraction is above a selectable threshold, estimated by sampling points within the cell. Tusqh incorporates anti-aliasing algorithms to mitigate grid orientation and scale effects. It is designed for creating finite element meshes for simulations and can be used in various applications such as heat diffusion, mechanical simulations, and computer graphics rendering. The software outputs meshes in an open format compatible with downstream software. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC

Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images

This study utilizes satellite data to detect undocumented oil and gas wells, which pose significant environmental concerns, including greenhouse gas emissions. Three key findings emerge from the study. Firstly, the problem of imbalanced data is addressed by recommending oversampling techniques like Rotation–GaussianBlur–Solarization data augmentation (RGS), the Synthetic Minority Over-Sampling Technique (SMOTE), or ADASYN (an extension of SMOTE) over undersampling techniques. The performance of borderline SMOTE is less effective than that of the rest of the oversampling techniques, as its performance relies heavily on the quality and distribution of data near the decision boundary. Secondly, incorporating pre-trained models trained on large-scale datasets enhances the models’ generalization ability, with models trained on one county’s dataset demonstrating high overall accuracy, recall, and F1 scores that can be extended to other areas. This transferability of models allows for wider application. Lastly, including persistent homology (PH) as an additional input improves performance for in-distribution testing but may affect the model’s generalization for out-of-distribution testing. A careful consideration of PH’s impact on overall performance and generalizability is recommended. Overall, this study provides a robust approach to identifying undocumented oil and gas wells, contributing to the acceleration of a net-zero economy and supporting environmental sustainability efforts.

SMOTE

Topological Signatures of Adversaries in Multimodal Alignments

Topological Data Analysis for Adversarial Detection (LANL O4937) - Detects adversarial examples in vision-language models using persistent homology and two-sample testing. Combines TDA features from CLIP embeddings with statistical methods (ME, SCF, SAMMD, C2ST) for robust detection across ImageNet, CIFAR-10/100.

Bhattarai, Manish

A Fast Algorithm for Computing Zigzag Representatives

Zigzag filtrations of simplicial complexes generalize the usual filtrations by allowing simplex deletions in addition to simplex insertions. The barcodes computed from zigzag filtrations encode the evolution of homological features. Although one can locate a particular feature at any index in the filtration using existing algorithms, the resulting representatives may not be compatible with the zigzag: a representative cycle at one index may not map into a representative cycle at its neighbor. For this, one needs to compute compatible representative cycles along each bar in the barcode. It is known that the barcode for a zigzag filtration with m insertions and deletions can be computed $O(m^ω)$ in time, where $ω < 2.373$ is the matrix multiplication exponent. However, it is not known how to compute the compatible representatives so efficiently. For a non-zigzag filtration, the classical matrix-based algorithm provides representatives in $O(m^3)$ time, which can be improved to $O(m^ω)$. However, no known algorithm for zigzag filtrations computes the representatives with the $O(m^3)$ time bound. We present an $O(m^3 n)$ time algorithm for this problem, where $n ≤ m$ is the size of the largest complex in the filtration.

Persistent homology

Tracking the topology of neural manifolds across populations

Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising the possibility of studying how these manifolds relate across populations. However, when the manifolds are nonlinear and possibly code for multiple unknown variables, it is challenging to extract robust and falsifiable information about their relationships. We introduce a framework, called the method of analogous cycles, for matching topological features of neural manifolds using only observed dissimilarity matrices within and between neural populations. We demonstrate via analysis of simulations and in vivo experimental data that this method can be used to correctly identify multiple shared circular coordinate systems across both stimuli and inferred neural manifolds. Conversely, the method rejects matching features that are not intrinsic to one of the systems. Further, as this method is deterministic and does not rely on dimensionality reduction or optimization methods, it is amenable to direct mathematical investigation and interpretation in terms of the underlying neural activity. We thus propose the method of analogous cycles as a suitable foundation for a theory of cross-population analysis via neural manifolds.

97 MATHEMATICS AND COMPUTING

Cadmus v1.0

This software package is for distributed computation of persistent (co)homology. It is primarily intended for Topological Data Analysis (TDA) audience and scientists who use TDA methods and apply them to datasets that are too big to handle on a single machine. There are very few codes available for this; Cadmus outperforms DIPHA, if the user is interested in cohomology. The accompanying paper explaining the algorithm was accepted to ALENEX 26.

Nigmetov, Arnur [Lawrence Berkeley National Labora

Microbial species and intraspecies units exist and are maintained by ecological cohesiveness coupled to high homologous recombination

Abstract Recent genomic analyses have revealed that microbial communities are predominantly composed of persistent, sequence-discrete species and intraspecies units (genomovars), but the mechanisms that create and maintain these units remain unclear. By analyzing closely-related isolate genomes from the same or related samples and identifying recent recombination events using a novel bioinformatics methodology, we show that high ecological cohesiveness coupled to frequent-enough and unbiased (i.e., not selection-driven) horizontal gene flow, mediated by homologous recombination, often underlie these diversity patterns. Ecological cohesiveness was inferred based on greater similarity in temporal abundance patterns of genomes of the same vs. different units, and recombination was shown to affect all sizable segments of the genome (i.e., be genome-wide) and have two times or greater impact on sequence evolution than point mutations. These results were observed in bothSalinibacter ruber, an environmental halophilic organism, andEscherichia coli, the model gut-associated organism and an opportunistic pathogen, indicating that they may be more broadly applicable to the microbial world. Therefore, our results represent a departure compared to previous models of microbial speciation that invoke either ecology or recombination, but not necessarily their synergistic effect, and answer an important question for microbiology: what a species and a subspecies are.

Science & Technology - Other Topics

Reactive oxygen species control protein degradation at the mitochondrial import gate

While reactive oxygen species (ROS) have long been known to drive aging and neurodegeneration, their persistent depletion below basal levels also disrupts organismal function. Cells counteract loss of basal ROS via the reductive stress response, but the identity and biochemical activity of ROS sensed by this pathway remain unknown. Here, we show that the central enzyme of the reductive stress response, the E3 ligase Cullin 2-FEM1 homolog B (CUL2 FEM1B ), specifically acts at mitochondrial TOM complexes, where it senses ROS produced by complex III of the electron transport chain (ETC). ROS depletion during times of low ETC activity triggers the localized degradation of CUL2 FEM1B substrates, which sustains mitochondrial import and ensures the biogenesis of the rate-limiting ETC complex IV. As complex III yields most ROS when the ETC outpaces metabolic demands or oxygen availability, basal ROS are sentinels of mitochondrial activity that help cells adjust their ETC to changing environments, as required for cell differentiation and survival.

FEM1B

Anaerobic benzene oxidation in Geotalea daltonii involves activation by methylation and is regulated by the transition state regulator AbrB

ABSTRACT Benzene is a widespread groundwater contaminant that persists under anoxic conditions. The aim of this study was to more accurately investigate anaerobic microbial degradation pathways to predict benzene fate and transport. Preliminary genomic analysis of Geotalea daltonii strain FRC-32, isolated from contaminated groundwater, revealed the presence of putative aromatic-degrading genes. G. daltonii was subsequently shown to conserve energy for growth on benzene as the sole electron donor and fumarate or nitrate as the electron acceptor. The hbs gene, encoding for 3-hydroxybenzylsuccinate synthase (Hbs), a homolog of the radical-forming, toluene-activating benzylsuccinate synthase (Bss), was upregulated during benzene oxidation in G. daltonii , while the bss gene was upregulated during toluene oxidation. Addition of benzene to the G. daltonii whole-cell lysate resulted in toluene formation, indicating that methylation of benzene was occurring. Complementation of σ 54 - (deficient) E. coli transformed with the bss operon restored its ability to grow in the presence of toluene, revealing bss to be regulated by σ 54 . Binding sites for σ 70 and the transition state regulator AbrB were identified in the promoter region of the σ 54 -encoding gene rpoN, and binding was confirmed. Induced expression of abrB during benzene and toluene degradation caused G. daltonii cultures to transition to the death phase. Our results suggested that G. daltonii can anaerobically oxidize benzene by methylation, which is regulated by σ 54 and AbrB. Our findings further indicated that the benzene, toluene, and benzoate degradation pathways converge into a single metabolic pathway, representing a uniquely efficient approach to anaerobic aromatic degradation in G. daltonii . IMPORTANCE The contamination of anaerobic subsurface environments including groundwater with toxic aromatic hydrocarbons, specifically benzene, toluene, ethylbenzene, and xylene, has become a global issue. Subsurface groundwater is largely anoxic, and further study is needed to understand the natural attenuation of these compounds. This study elucidated a metabolic pathway utilized by the bacterium Geotalea daltonii capable of anaerobically degrading the recalcitrant molecule benzene using a unique activation mechanism involving methylation. The identification of aromatic-degrading genes and AbrB as a regulator of the anaerobic benzene and toluene degradation pathways provides insights into the mechanisms employed by G. daltonii to modulate metabolic pathways as necessary to thrive in anoxic contaminated groundwater. Our findings contribute to the understanding of novel anaerobic benzene degradation pathways that could potentially be harnessed to develop improved strategies for bioremediation of groundwater contaminants.

Bullows, James E.