REVIEW 4 cited by
Non-isometric codes for the black hole interior from fundamental and effective dynamics
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
We introduce a new holographic map for encoding black hole interiors by including both fundamental and effective dynamics. This holographic map is constructed by evolving a state in the effective, semiclassical gravity description of the interior backwards in time to pull the degrees of freedom outside the black hole, before evolving forwards in time in the fundamental description. We show this ``backwards-forwards'' map is equivalent to a post-selection map of the type introduced by Akers, Engelhardt, Harlow, Penington, and Vardhan, and in the case of trivial effective interactions reduces to their model, while providing a suitable generalization when those interactions are nontrivial. We show the map is equivariant with respect to time evolution, and independent of any interactions outside the black hole. This construction includes interactions with an infaller in a way that preserves the unitarity of black hole evolution exactly and does not allow for superpolynomial computational complexity.
Forward citations
Cited by 4 Pith papers
-
Deformed BTZ Radiance and Single Trace $T\bar{T}$ Holography
Long-string emission from rotating λ-deformed BTZ black holes forces a unique origin B-field that matches the value needed for the string spectrum to agree with the Z_w sector of single-trace T T-bar deformed orbifold...
-
THEME: Enhancing Thematic Investing with Semantic Stock Representations and Temporal Dynamics
A hierarchical contrastive learning framework that aligns stocks with theme descriptions and refines embeddings with short-term return signals improves thematic retrieval and backtested portfolio metrics.
-
Controllable diffusion-based generation for multi-channel biological data
A diffusion model with multi-resolution conditioning and channel-wise attention achieves state-of-the-art accuracy for protein and gene imputation in spatial and single-cell biological data.
-
HyBDM: Multi-Scale Hybrid Experts for Time Series Forecasting with Bidirectional Dependency Modeling
HyBDM combines a Mamba-style global-pattern expert with a local window transformer and a learned router to forecast multivariate time series, reporting state-of-the-art results on six benchmarks.
Discussion (0). Sign in to comment.