Abstract We generalize a magnetogram-matching Biot–Savart law (BSl) from planar to spherical geometry. For a given coronal current densityJ, this law determines the magnetic field whose radial component vanishes at the surface. The superposition of with a potential field defined by a given surface radial field,Br, provides the entire configuration whereBrremains unchanged by the currents. Using this approach, we (1) upgrade our regularized BSls for constructing coronal magnetic flux ropes (MFRs) and (2) propose a new method for decomposing a measured photospheric magnetic field as , where the potential,Bpot, toroidal,BT, and poloidal, , fields are determined byBr,Jr, and the surface divergence ofB–Bpot, respectively, all derived from magnetic data. OurBTis identical to the one in the alternative Gaussian decomposition by P. W. Schuck et al., whileBpotand are different from their poloidal fields and , which arepotentialin the infinitesimal proximity to the upper and lower side of the surface, respectively. In contrast, our has no such constraints and, asBpotandBT, refers to thesameupper side of the surface. In spite of these differences, for a continuousJdistribution across the surface,Bpotand are linear combinations of and . We demonstrate that, similar to the Gaussian method, our decomposition allows one to identify the footprints and projected surface-location of MFRs in the solar corona, as well as the direction and connectivity of their currents.
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Numerical Fuzz: A Type System for Rounding Error Analysis
Algorithms operating on real numbers are implemented as floating-point computations in practice, but floatingpoint operations introduceroundoff errorsthat can degrade the accuracy of the result. We propose , a functional programming language with a type system that can express quantitative bounds on roundoff error. Our type system combines a sensitivity analysis, enforced through a linear typing discipline, with a novel graded monad to track the accumulation of roundoff errors. We prove that our type system is sound by relating the denotational semantics of our language to the exact and floating-point operational semantics. To demonstrate our system, we instantiate with error metrics proposed in the numerical analysis literature and we show how to incorporate rounding operations that faithfully model aspects of the IEEE 754 floating-point standard. To show that can be a useful tool for automated error analysis, we develop a prototype implementation for that infers error bounds that are competitive with existing tools, while often running significantly faster. Finally, we consider semantic extensions of our graded monad to bound error under more complex rounding behaviors, such as non-deterministic and randomized rounding.
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- PAR ID:
- 10612719
- Publisher / Repository:
- Association for Computing Machinery (ACM)
- Date Published:
- Journal Name:
- Proceedings of the ACM on Programming Languages
- Volume:
- 8
- Issue:
- PLDI
- ISSN:
- 2475-1421
- Format(s):
- Medium: X Size: p. 1954-1978
- Size(s):
- p. 1954-1978
- Sponsoring Org:
- National Science Foundation
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