The reviewed record of science sign in
Pith

arxiv: 0707.3168 · v1 · pith:ZU46GU7A · submitted 2007-07-21 · hep-th

Wormholes in Maximal Supergravity

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:ZU46GU7Arecord.jsonopen to challenge →

classification hep-th
keywords maximalsolutionssupergravityarguebecausebriefcontributedimensions
0
0 comments X
read the original abstract

In this brief note, we reconsider the problem of finding Euclidean wormhole solutions to maximal supergravity in d dimensions. We find that such solutions exists for all d less than or equal to 9. However, we argue that, in toroidally-compactified string theories, these saddle points never contribute to the path integral because of a tension with U-duality.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 16 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Simultaneously Efficient Allocation of Indivisible Items Across Multiple Dimensions

    cs.GT 2026-06 unverdicted novelty 7.0

    The MDEA model admits tight 1/ℓ-approximations for simultaneous USW and ESW efficiency across ℓ dimensions with NP-hardness for exact simultaneous optimization even with binary valuations, plus characterizations of th...

  2. Beyond Detection: A Structure-Aware Framework for Scene Text Tracking

    cs.CV 2026-05 unverdicted novelty 7.0

    SymTrack is the first systematic detection-free framework for scene text tracking that constructs benchmarks from video text spotting datasets and reports up to 11.97% AUC gains over prior trackers.

  3. Cascade Pipeline for Leading-Order Matrix Element Evaluation on AMD Versal AI Engine Arrays

    hep-ex 2026-05 unverdicted novelty 7.0

    A cascade pipeline architecture on AMD Versal AI Engine tiles projects 1 million matrix element evaluations per second at 54.8 W for gg→ttg, delivering 34× CPU speedup and 7.7× better energy efficiency with parts-per-...

  4. Ravines in quantum cost landscapes: opportunities for improved VQA predictions

    quant-ph 2026-07 unverdicted novelty 6.0

    NEB-adapted ravine ensembles for QNNs classifying concentratable entanglement outperform naive methods when local-prediction variability is high and reduce costs, with ravines persisting under depth and qubit scaling.

  5. Physics-conforming Latent Twins

    cs.LG 2026-06 unverdicted novelty 6.0

    Physics-conforming Latent Twins learns encoder-decoder pairs and latent flow maps that satisfy physical principles by design via constraint transfer and algebraic conditions on invariants and dissipation.

  6. Implicit Multi-Camera System Calibration Using Gaussian Processes

    cs.CV 2026-05 unverdicted novelty 6.0

    Gaussian process regression enables implicit multi-camera calibration by learning 2D-to-3D mappings with built-in uncertainty and active learning for efficient data use.

  7. A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning

    cs.LG 2026-05 unverdicted novelty 6.0

    Mean curvature estimated from local k-NN patches acts as a descriptor for boundary, outlier, and transition points, enabling curvature-driven data decomposition that improves clustering separability.

  8. Hallucination Early Detection in Diffusion Models

    cs.CV 2026-04 unverdicted novelty 6.0

    HEaD+ detects object hallucinations early in diffusion generation via cross-attention maps, text, and a Predicted Final Image, raising complete image rates by 6-8% for four-object prompts and reducing time by up to 32%.

  9. Towards Entanglement-Enhanced Atom Interferometry Using Bow-Tie Cavities

    quant-ph 2026-06 unverdicted novelty 5.0

    A monolithic bow-tie cavity with finesse 5.7e4 is realized for homogeneous coupling to Sr atoms at 689 nm, projected to enable up to 28 dB spin squeezing for quantum-enhanced interferometry.

  10. Measuring Tail Dependence in Linear Processes: Theory and Empirics

    math.ST 2026-05 unverdicted novelty 5.0

    A new tail dependence measure for linear processes with regularly varying distributions is introduced, incorporating persistence effects and validated via simulations and cryptocurrency data analysis.

  11. Measuring Tail Dependence in Linear Processes: Theory and Empirics

    math.ST 2026-05 unverdicted novelty 5.0

    A dependence measure is introduced for joint extremes in linear processes with regularly varying tails, informed by cryptocurrency data and confirmed via simulations.

  12. A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning

    cs.LG 2026-05 unverdicted novelty 5.0

    MCBP detects boundaries by computing discrete mean curvature from k-nearest neighbor patches on the data manifold, then decomposes data into low-curvature smooth and high-curvature boundary subsets to improve clustering.

  13. Cascade Pipeline for Leading-Order Matrix Element Evaluation on AMD Versal AI Engine Arrays

    hep-ex 2026-05 unverdicted novelty 5.0

    A cascade pipeline on 400 AIE tiles evaluates gg→ttg leading-order matrix elements at 1 million per second with parts-per-million accuracy to MadGraph, delivering 34× CPU speedup and 7.7× better energy efficiency at 54.8 W.

  14. ProMoTA: a model-driven framework for end-to-end traceability analysis

    cs.SE 2026-05 unverdicted novelty 4.0

    ProMoTA integrates process modeling with automated end-to-end traceability generation and analysis for model transformation chains in MDE, demonstrated on a wireless sensor network IoT application.

  15. A Hybrid Approach For Malware Classification Using Secondary Features Fusion

    cs.CR 2026-06 unverdicted novelty 3.0

    Hybrid feature fusion of API calls and n-grams with voting-based classifier fusion achieves 99.72% accuracy and 0.989 AUC for malware family classification on Microsoft dataset.

  16. Outstanding Questions in Giant Planet Theory

    astro-ph.EP 2026-05 unverdicted novelty 2.0

    The paper identifies key unresolved questions in giant planet formation, interiors, and their role in planetary systems.