Creating Metric Describing Large Disk

  • #1
Onyx
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TL;DR Summary
How can I create a metric describing the space outside a large disk, like an elliptical galaxy?
How can I create a metric describing the space outside a large disk, like an elliptical galaxy? In cylindrical coordinates, ##\phi## would be the angle restricted the the plane, as ##\rho## would be the radius restricted to the plane. I think that if ##z## is suppressed to create an embedding function with just ##\rho## and ##\phi##, it would look very much like the Schwarzschild case, since it is a circle in the plane. But if I suppressed ##\phi##, I think the embedding function of that plane would have arguments of both ##\rho## and ##z##, and it would look more oblong. So I feel like the metric must have these features, but I'm not sure specifically in what arrangment.
 
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  • #2
Onyx said:
TL;DR Summary: How can I create a metric describing the space outside a large disk, like an elliptical galaxy?
Take a look at this 1996 Helvetica Physica Acta paper and its references:

Relativistically rotating dust
by G. Neugebauer, A. Kleinwachter and R. Meinel
Abstract: Dust configurations play an important role in astrophysics and are the simplest models for rotating bodies. The physical properties of the general–relativistic global solution for the rigidly rotating disk of dust, which has been found recently as the solution of a boundary value problem, are discussed.

Available here: https://arxiv.org/pdf/gr-qc/0301107.pdf
 
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  • #3
This seems right if considering a significantly rotating disk, but unless I'm mistaken most galaxies don't rotate very fast in proportion to their disk radius. I found another metric describing a stationary and static ellipse, as described in this paper. However, I don't understand why the ##g_{tt}## term is still the same as in the Schwarzschild case; since this metric does not have spherical symmetry, I would have thought it would be different.
 

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  • #4
Onyx said:
I found another metric describing a stationary and static ellipse, as described in this paper.
I wouldn't rely on this paper. It appears in International Journal of the Physical Sciences from "Academic Journals", which is on Beall's list of predatory publishers. Can you find this same metric in a proper journal or textbook?
 
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FAQ: Creating Metric Describing Large Disk

What is a "large disk" in the context of creating metrics?

A "large disk" typically refers to a substantial storage device, often used in data centers or for large-scale data storage applications. These disks are characterized by their high capacity, often in terabytes or petabytes, and are used to store vast amounts of data efficiently.

Why is it important to create metrics for large disks?

Creating metrics for large disks is important for monitoring performance, reliability, and utilization. Metrics help in understanding how the disk is being used, identifying potential issues, optimizing performance, and ensuring data integrity and availability. They are crucial for maintaining the health of storage systems and for planning future storage needs.

What types of metrics are typically used to describe large disks?

Common metrics for describing large disks include capacity (total, used, and free space), IOPS (Input/Output Operations Per Second), latency, throughput, error rates, and temperature. These metrics provide a comprehensive view of the disk's performance and health.

How can I collect and analyze metrics for large disks?

Metrics for large disks can be collected using various tools and software, such as monitoring agents, SNMP (Simple Network Management Protocol), and specialized storage management solutions. Once collected, these metrics can be analyzed using analytic tools, dashboards, and reporting systems to gain insights and make data-driven decisions.

What challenges might arise when creating metrics for large disks?

Challenges in creating metrics for large disks include handling the sheer volume of data, ensuring accuracy and consistency of metrics, dealing with the complexity of modern storage systems, and integrating data from different sources. Additionally, maintaining the performance of the disk while collecting metrics can be a concern, as extensive monitoring can sometimes impact system performance.

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