Spatial duration-augmented SPEI modeling over Italy reveals a strong south–north drought-memory gradient and shows BATs distributions dominate standard SPEI candidates while RET choice barely moves the signal.
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The SSTN detects non-normality by tracking how the standardized empirical characteristic function changes under repeated self-similarity transformations, with the null distribution calibrated by Monte Carlo simulation.
A quantum Monte Carlo algorithm solves multidimensional Black-Scholes PDEs for option pricing with polynomial complexity in dimension d and accuracy 1/ε, with rigorous error bounds and a claimed speedup over classical Monte Carlo for bounded payoffs.
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citing papers explorer
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A spatial duration-augmented framework for drought persistence
Spatial duration-augmented SPEI modeling over Italy reveals a strong south–north drought-memory gradient and shows BATs distributions dominate standard SPEI candidates while RET choice barely moves the signal.
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New insights into Elo algorithm for practitioners and statisticians
Elo's heuristic and MLE perspectives coincide for binary logistic cases but demand closed-form noise corrections to scale and home-field parameters for accurate prediction, outperforming the standard approach and showing non-convergence in FIFA rankings.
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A test for normality based on self-similarity
The SSTN detects non-normality by tracking how the standardized empirical characteristic function changes under repeated self-similarity transformations, with the null distribution calibrated by Monte Carlo simulation.
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Quantum Monte Carlo algorithm for option pricing and its complexity analysis
A quantum Monte Carlo algorithm solves multidimensional Black-Scholes PDEs for option pricing with polynomial complexity in dimension d and accuracy 1/ε, with rigorous error bounds and a claimed speedup over classical Monte Carlo for bounded payoffs.
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Persona-Trained Monte Carlo: Estimating Market-Outcome Distributions via Swarms of Persona-Conditioned Neural Policy Bots in a Limit Order Book
PTMC is a proposed Monte Carlo estimator that generates market-outcome distributions by simulating continuous double-auction interactions among persona-conditioned neural-policy bots whose heterogeneity is drawn from a learned distribution.
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Magnetic field alignment with dense cores in the transition between cloud and core scales
Core-scale magnetic fields in star-forming regions are more disordered than cloud-scale fields and align randomly with core orientations and velocity gradients.
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IceCube Second Track Data Release IceTracks-DR2: Data from 2008-2022 for Neutrino Source Searches
IceCube publishes its second public muon track data release covering 14 years with updated event selection, calibration, and instrument response functions for neutrino point-source analyses.
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Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit
DQRbuild toolkit automates data quality vetting for gravitational-wave events, recovering 96% of human-identified issues from O3 with a 24% false alarm rate.