Researchers examine various causal structures for spacetimes with continuous metrics.
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We demonstrate the breakdown of several fundamentals of Lorentzian causality theory in low regularity. Most notably, chronological futures (defined naturally using locally Lipschitz curves) may be non-open, and may differ from the corresponding sets defined via piecewise -curves. By refining the notion of a causal…
We solve a lifecycle model in which the consumer's chronological age does not move in lockstep with calendar time. Instead, biological age increases at a stochastic non-linear rate in time like a broken clock that might occasionally move backwards. In other words, biological age could actually decline. Our paper is ins…
Chronologically consistent models maintain accuracy with time-restricted data.
New models avoid lookahead bias by training on past data only.
On the Geroch-Kronheimer-Penrose future completion of a spacetime , there are two frequently used topologies. We systematically examine , the stronger (metrizable) of them, which is the coarsest causally continuous topology, obtaining a variety of novel results, among them a complete characterization of…
Chronological Causal Bandits (CCB) tackles dynamic causal decision-making.
IMPaCT improves node classification in chronological split temporal graphs.
Study causal structure of warped spacetimes using novel pre-length spaces.
Defines doubling conditions for Lorentzian spaces linked to curvature bounds.
CODA simulates future data to generalize models across different datasets.
Probabilistic programming aids in automatically dating ice cores, reducing manual error and uncertainty.
A new method extracts features from time series data using iterated sums and improves classification accuracy.
Study uses reinforcement learning to optimize portfolios under recursive utility.
The paper characterizes global hyperbolicity in Lorentzian manifolds without relying on manifold topology.
Chronnet models spatiotemporal data using chronological networks.
Recently, the intervention calculus when the DAG is absent (IDA) method was developed to estimate lower bounds of causal effects from observational high-dimensional data. Originally it was introduced to assess the effect of baseline biomarkers which do not vary over time. However, in many clinical settings, measurement…
Surveying nonparametric inference with shape constraints, past and future.
Recently ({\em Class. Quant. Grav.} {\bf 20} 625-664) the concept of {\em causal mapping} between spacetimes --essentially equivalent in this context to the {\em chronological map} one in abstract chronological spaces--, and the related notion of {\em causal structure}, have been introduced as new tools to study causal…
The paper analyzes gold, oil, and bitcoin futures volatility and basis.
We create a framework for odd Khovanov homology in the spirit of Bar-Natan's construction for the ordinary Khovanov homology. Namely, we express the cube of resolutions of a link diagram as a diagram in a certain 2-category of chronological cobordisms and show that it is 2-commutative: the composition of 2-morphisms al…
Reconstruct spacetime from order and number of points.
The paper examines how timing of observations affects causal discovery methods.
This is not in any way meant to be a complete survey on positive curvature. Rather it is a short essay on the fascinating changes in the landscape surrounding positive curvature. In particular, details and many results and references are not included, and things are not presented in chronological order.
The study proves timelike Ricci bounds for low regularity spacetimes using optimal transport.
There are two categorifications of the Jones polynomial: "even" discovered by M.Khovanov in 1999 and "odd" dicovered by P.Ozsvath, J.Rasmussen and Z.Szabo in 2007. The first one can be fully constructed in the category of cobordisms (strictly: in the additive closure of that category), where we can build a complex for …
Comparing data defined over space and time is notoriously hard, because it involves quantifying both spatial and temporal variability, while at the same time taking into account the chronological structure of data. Dynamic Time Warping (DTW) computes an optimal alignment between time series in agreement with the chrono…
This study examines how DEXs impact traders' behavior in perpetual futures contracts.
There are various algorithms and methodologies used for automated screening of cervical cancer by segmenting and classifying cervical cancer cells into different categories. This study presents a critical review of different research papers published that integrated AI methods in screening cervical cancer via different…
Cosmological singularity theorems such as that of Hawking and Penrose assume local curvature conditions as well as global ones like the existence of a compact (achronal) slice. Here, we prove a new singularity theorem for chronological spacetimes that satisfy what we call a `past null focusing' condition. Such a condit…
The 2007 Midwest Geometry Conference included a panel discussion devoted to open problems and the general direction of future research in fields related to the main themes of the conference. This paper summarizes the comments made during the panel discussion.
Quarter-hour market bursts predict algorithmic trading and returns in crypto futures.
This paper reviews information theory in open-world machine learning.
Study finds no statistically significant trading edge in MNQ futures signals from OHLCV data.
We study the optimal trading policies for a wind energy producer who aims to sell the future production in the open forward, spot, intraday and adjustment markets, and who has access to imperfect dynamically updated forecasts of the future production. We construct a stochastic model for the forecast evolution and deter…
Irrespective of local conditions imposed on the metric, any extendible spacetime U has a maximal extension containing no closed causal curves outside the chronological past of U. We prove this fact and interpret it as impossibility (in classical general relativity) of the time machines, insofar as the latter are define…
We survey the known existence and non-existence results for -instantons on non-compact cohomogeneity-1 -manifolds and their consequences, including an explicit example of a family of -instantons where bubbling, removable singularities and conservation of energy phenomena occur. We also describe several o…
This survey aims to cover the motivation for and history of the study of local rigidity of group actions. There is a particularly detailed discussion of recent results, including outlines of some proofs. The article ends with a large number of conjectures and open questions and aims to point to interesting directions f…
Estimates financial market impacts of COVID-19 using time-varying kernel density.
Survey of financial LLMs in finance.
In a recent paper, Eichmair, Galloway and Pollack have proved a Gannon-Lee-type singularity theorem based on the existence of marginally outer trapped surfaces (MOTS) on noncompact initial data sets for globally hyperbolic spacetimes. However, one might wonder whether the corresponding incomplete geodesics could still …
Blockchain is a distributed database that keeps a chronologically-growing list (chain) of records (blocks) secure from tampering and revision. While computerisation has changed the nature of a ledger from clay tables in the old days to digital records in modern days, blockchain technology is the first true innovation i…
We analyze the time series of overnight returns for the bund and btp futures exchanged at LIFFE (London). The overnight returns of both assets are mapped onto a one-dimensional symbolic-dynamics random walk: The `bond walk'. During the considered period (October 1991 - January 1994) the bund-future market opened earlie…
Estimates the rational homological dimension of Riemann surfaces with boundary and marked points.
Causal classification of three Misner-type spacetimes.
Study introduces new curvature conditions for Lorentzian spaces using Rényi entropy.
This review classifies electricity price models for risk management.
Visualizes futures markets using particle physics tools.