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TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Execution
arXiv:2606.08379v1 Announce Type: new Abstract: This study addresses the optimal execution of large stock sell programs by introducing TT-DAC-PS (Twin-Target Deterministic Actor-Critic with Policy Smoothing), a deterministic actor-critic architecture that combines twin exponential-moving-average critic targets with pessimistic min backup, TD3-style target policy smoothing noise, delayed actor updates, and conservative Q regularisation to curb overestimation. Exploration uses...
The MuFusE Large-Volume Diamond Anvil Cell for Exploring Muon-Catalyzed Fusion at Higher Pressures and Temperatures
Announce Type: new Abstract: A new large-volume diamond anvil cell (DAC) has been developed for the Muon-catalyzed Fusion ($\mu$CF) Experiment (MuFusE), enabling the compression and heating of deuterium-tritium (d-t) mixtures to pressures and temperatures needed to advance $\mu$CF research. The MuFusE DAC achieves the large sample volumes necessary for high-precision fusion measurements while integrating cryogenic loading, all-metal sealing, and flexible bellows to maintain a secure...
LPG supply stable, but oil firms still losing nearly Rs 700 on every cylinder sold
Oil Marketing Companies (OMCs) continue to face under-recoveries of nearly Rs 700 on every domestic LPG cylinder despite a range of measures taken by the government to strengthen supplies, ministry of petroleum and natural gas said on Thursday. Addressing an inter-ministerial briefing, Sujata Sharma, joint secretary in the ministry of petroleum and natural gas, said that the government has stepped up domestic LPG production and secured imports to ensure adequate availability across the...
Developing Distance-Aware Physics-Constrained Probabilistic Frameworks for Industrial Prognostics
arXiv:2512.08499v3 Announce Type: replace Abstract: Development of reliable and physically interpretable probabilistic frameworks for industrial prognostics remain nascent, and existing literature is often insensitive as inputs move away from the training manifold. In this paper, we develop two sampling-free, distance-aware physics-constrained probabilistic frameworks: (i) PC-SNGP and (ii) PC-SNER. Both apply spectral normalization to hidden layer weights, enforcing bi-Lipschitz...