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Rotation of Polarization Angle in Gamma-Ray Burst Prompt Phase. III. The Influence of the Magnetic Field Orientation
Xing-Yao Wang, Jia-Sheng Li, Mi-Xiang Lan
https://arxiv.org/abs/2510.11971

Rotation of Polarization Angle in Gamma-Ray Burst Prompt Phase. III. The Influence of the Magnetic Field Orientation
Polarization is very sensitive to the configuration of the magnetic field in the radiation region. In addition to polarization curve and polarization spectrum, studies of polarization angle (PA) rotation spectrum is also crucial. In this paper, we use a simple parametric magnetic reconnection model with a large-scale aligned magnetic field in the radiation region to study the effects of field orientation on the PA rotations. Under different field orientations, variations of the PA rotation with…

Beyond Revenue and Welfare: Counterfactual Analysis of Spectrum Auctions with Application to Canada's 3800MHz Allocation
Sara Jalili Shani, Kris Joseph, Michael B. McNally, James R. Wright
https://arxiv.org/abs/2512.08106 https://arxiv.org/pdf/2512.08106 https://arxiv.org/html/2512.08106
arXiv:2512.08106v1 Announce Type: new
Abstract: Spectrum auctions are the primary mechanism through which governments allocate scarce radio frequencies, with outcomes that shape competition, coverage, and innovation in telecommunications markets. While traditional models of spectrum auctions often rely on strong equilibrium assumptions, we take a more parsimonious approach by modeling bidders as myopic and straightforward: in each round, firms simply demand the bundle that maximizes their utility given current prices. Despite its simplicity, this model proves effective in predicting the outcomes of Canada's 2023 auction of 3800 MHz spectrum licenses. Using detailed round-by-round bidding data, we estimate bidders' valuations through a linear programming framework and validate that our model reproduces key features of the observed allocation and price evolution. We then use these estimated valuations to simulate a counterfactual auction under an alternative mechanism that incentivizes deployment in rural and remote regions, aligning with one of the key objectives set out in the Canadian Telecommunications Act. The results show that the proposed mechanism substantially improves population coverage in underserved areas. These findings demonstrate that a behavioral model with minimal assumptions is sufficient to generate reliable counterfactual predictions, making it a practical tool for policymakers to evaluate how alternative auction designs may influence future outcomes. In particular, our study demonstrates a method for counterfactual mechanism design, providing a framework to evaluate how alternative auction rules could advance policy goals such as equitable deployment across Canada.
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Incoherent repumping scheme in the $^{88}$Sr$^{ }$ five-level manifold
Valentin Martimort, Sacha Guesne, Derwell Drapier, Vincent Tugaye, Lilay Gros-Desormeaux, Valentin Cambier, Albane Douillet, Luca Guidoni, Jean-Pierre Likforman
https://arxiv.org/abs/2512.08710 https://arxiv.org/pdf/2512.08710 https://arxiv.org/html/2512.08710
arXiv:2512.08710v1 Announce Type: new
Abstract: Laser-cooled trapped ions are at the heart of modern quantum technologies and their cooling dynamics often deviate from the simplified two-level atom model. Doppler cooling of the $^{88}$Sr$^{ }$ ion involves several electronic levels and repumping channels that strongly influence fluorescence.In this work, we study a repumping scheme for the $^{88}$Sr$^{ }$ ion by combining precision single-ion spectroscopy with comprehensive numerical modeling based on optical Bloch equations including 18 Zeeman sublevels. We show that, although the observed fluorescence spectra retain a Lorentzian lineshape, their width and amplitude cannot be explained by a two-level atom description. Moreover, we find the optimal repumping conditions for maximizing the photon scattering rate.
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Learning Paths to Multi-Sector Equilibrium: Belief Dynamics Under Uncertain Returns to Scale
Stefano Nasini, Rabia Nessah, Bertrand Wigniolle
https://arxiv.org/abs/2512.07013 https://arxiv.org/pdf/2512.07013 https://arxiv.org/html/2512.07013
arXiv:2512.07013v1 Announce Type: new
Abstract: This paper explores the dynamics of learning in a multi-sector general equilibrium model where firms operate under incomplete information about their production returns to scale. Firms iteratively update their beliefs using maximum a-posteriori estimation, derived from observed production outcomes, to refine their knowledge of their returns to scale. The implications of these learning dynamics for market equilibrium and the conditions under which firms can effectively learn their true returns to scale are the key objects of this study. Our results shed light on how idiosyncratic shocks influence the learning process and demonstrate that input decisions encode all pertinent information for belief updates. Additionally, we show that a long-memory (path-dependent) learning which keeps track of all past estimations ends up having a worse performance than a short-memory (path-independent) approach.
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