Our Work

accomp allows one to connect atmospheric composition measurements to the planet's building blocks and make inferences about the planet's formation history. It can take results of atmospheric retrieval…

accomp allows one to connect atmospheric composition measurements to the planet's building blocks and make inferences about the planet's formation history. It can take results of atmospheric retrievals and calculate the implied metal mass fraction and absolute metal mass for planets orbiting host stars with arbitrary composition. One can also infer the different sources of the metals if the abundance of a sufficient number of elements is known, especially if these elements include both refractories (elements that trace solids) and volatiles. The calculated metal mass can be easily compared to simple predictions from formation models. This is the first release of the repository accomp. This version was used for interpreting the composition of the HR 8799 planets and AF Lep b and the scientific content of this code is described in Chachan, Murray-Clay & Fortney 2026. Any feedback is appreciated.

We prove both Erdős–Ulam conjectures on monochromatic union-closed families (Erdős Problem 1183). Every two-colouring of the subsets of a finite set contains a monochromatic union-closed family whose …

We prove both Erdős–Ulam conjectures on monochromatic union-closed families (Erdős Problem 1183). Every two-colouring of the subsets of a finite set contains a monochromatic union-closed family whose size grows faster than any fixed power of the size of the set, while suitable colourings admit no monochromatic union-closed family of exponential size. Both results hold for any number of colours and are verified in Lean.This record contains the paper (PDF and LaTeX source with TikZ figures) and the Lean 4 formalisation with Mathlib. Every theorem, proposition, corollary and lemma of the paper is checked in Lean with no sorry, and each audited statement uses only the standard axioms propext, Classical.choice and Quot.sound. Claude (Anthropic) assisted with the coding.

This review evaluates the article "Computational Hermeneutics: Machine Reading and the Epistemology of Literary Interpretation," situating it within the emerging interdisciplinary discourse on artific…

This review evaluates the article "Computational Hermeneutics: Machine Reading and the Epistemology of Literary Interpretation," situating it within the emerging interdisciplinary discourse on artificial intelligence and literary studies. The article advances a theoretically ambitious thesis: that machine reading constitutes not a positivist or anti-hermeneutic practice but a distinctive form of interpretation that both challenges and enriches traditional humanistic hermeneutics. The software code, and even quantified models, has, the article develops three interlocking arguments: that the hermeneutic-positivistic divide in digital humanities is a false dichotomy; that machine reading operates through "interpretive lenses" that shape interpretive attention; and that machine-generated interpretations require renewed engagement with the hermeneutic concepts of situatedness, plurality, and ambiguity. The article's most significant contributions are its rigorous articulation of the epistemological stakes of computational hermeneutics and its nuanced treatment of the "simulated hermeneutic." However, three limitations constrain its impact: an uneven empirical foundation, particularly in its comparative study of human and machine readings; a limited engagement with non-Western and multilingual contexts; and an underdeveloped treatment of power, ideology, and material conditions. The review identifies Habermas's emancipatory interest of hermeneutics of suspicion, and political economy of AI as theoretical resources capable of addressing these gaps. The article ultimately stands as both an important intervention and an invitation to develop an emancipatory computational hermeneutics that integrates critical theory with computational practice.

Python scripts that reproduce the XPS Studio analysis of X-ray photoelectron spectra from plain data files: energy calibration, background subtraction (Shirley, linear, Tougaard), peak fitting, peak a…

Python scripts that reproduce the XPS Studio analysis of X-ray photoelectron spectra from plain data files: energy calibration, background subtraction (Shirley, linear, Tougaard), peak fitting, peak areas and atomic-% quantification with relative sensitivity factors, including statistical uncertainties, 3σ detection limits and an extended uncertainty budget. Templates (fit_region.py, quantify.py) with documented settings; the science modules are included in science/. See README.md for the maths, CHANGELOG.md for versions and REFERENCES.md for the literature.

Companion code for Word-Processing-based Routing: A Fault-tolerant Routing Scheme for Cayley Graphs (D. Aguirre-Guerrero, L. Fàbrega, P. Vilà). It reproduces every figure reported in the…

Companion code for Word-Processing-based Routing: A Fault-tolerant Routing Scheme for Cayley Graphs (D. Aguirre-Guerrero, L. Fàbrega, P. Vilà). It reproduces every figure reported in the tables of the paper.Version 2.1.0 (revised manuscript) refines the revised forwarding rule so that the failure trace carries only the failures that block the path of a message (the whole-table rule of 2.0.0 is kept as trace-full) and regenerates the multi-failure results. Version 2.0.0 added: wpr_faults.py, a simulation engine for node and link failures with sequential or concurrent notification (Algorithms 5–8) and the two forwarding rules (the rule of the original submission and the revised rule with a failure trace in the message header, Algorithms 11–12), plus a greedy failure-oblivious baseline; wpr_experiments.py, the new experiments (exhaustive two-failure verification, k concurrent failures, minimality mitigation with the affected set and blind-spot radius, instances of up to 362,880 nodes, the RCRR scenario on the 1081-node Borel Cayley graph, greedy baseline) with CSV output and a self-test; wda_cost.g and run_wda.py, which measure the size of the shortLex automatic structures (word acceptor and word-difference automata) with GAP/kbmag; and results/, the CSV files behind every table of the paper. wpr_verify.py (single failure, Tables 5, 8 and 9) and edge_transitivity.g are unchanged.Requirements: Python ≥ 3.6 (standard library only) for the Python scripts; GAP ≥ 4.15 with the GRAPE and kbmag packages for the GAP scripts.

This record contains an exportation of the Docker image colomoto/colomoto-docker:2026-10-02 (see release notes and source record).  The image contains a Jupyter lab and notebook environment with …

This record contains an exportation of the Docker image colomoto/colomoto-docker:2026-10-02 (see release notes and source record).  The image contains a Jupyter lab and notebook environment with pre-installed software related to modeling, analysis, simulation, and inference of qualitative models of biological networks. See https://colomoto.github.io/colomoto-docker for more information. The image can be executed directly using the colomoto-docker command line utility  [swh:1:dir:1a643c45c1e8e73a55b4da355e7a858b95824026]  (requires Python and Docker): pip install -U colomoto-dockercolomoto-docker --doi [DOI] See further colomoto-docker usage instructions. Alternatively, the image can be imported using the command docker load with the attached image file: docker load -i image.tar.gz or with the donodo command available at https://github.com/pauleve/donodo [swh:1:dir:3c23b84c86526b41333c09093e56593028e3873b]: pip install -U donodo donodo pull [DOI]

Scripts and data reproducing all numerical results in Papers A and B of the Modular Entanglement-Induced Gravity (MEIG) program: node spectra, lattice modular flow, Gauss projection, and Bisognano&nda…

Scripts and data reproducing all numerical results in Papers A and B of the Modular Entanglement-Induced Gravity (MEIG) program: node spectra, lattice modular flow, Gauss projection, and Bisognano–Wichmann tests for the lattice Schwinger and SU(2) gauge models.