Papers by Melissa Jacquart
Image credit：NASA Main viewpoints and conclusions: Cosmic Background (Cosmic ontology) and its to... more Image credit：NASA Main viewpoints and conclusions: Cosmic Background (Cosmic ontology) and its total energy, that is dark matter and dark energy. And the process of the origin of the Universe is a process of enthalpy conservation, entropy increase; and density reduction, volume increases; the essence of the expansion of the Universe is the principle of the increase of entropy-the Cosmic Background matter body (Cosmic ontology) is changing continuously from the highdensity, high-temperature, high-pressure and small-volume into a low-density, lowtemperature, low-pressure and large-volume state.
Synthese Library, 2023
This chapter examines some of the philosophical literature on idealizations in science and the ep... more This chapter examines some of the philosophical literature on idealizations in science and the epistemic challenges idealizations potentially pose for astrophysical methodology, particularly its use of computer simulations. We begin by surveying philosophical literature on idealization connected to (1) kinds of idealizations deployed in science, (2) the aims of idealization in science, and (3) various strategies for de-idealization. Using collisional ring galaxy simulations as a case study, we examine how these three themes play out in the context of astrophysical computer simulations. Ultimately, we argue that deploying deidealization strategies is central to bolstering epistemic confidence in simulations in astrophysics. We conclude with some remarks on the role of idealization in the context of astrophysical computer simulations more generally. 1 For the purposes of this chapter and philosophical issues that are examined we will consider computer simulations as a specification of a kind of model, that is, computational model. In this sense, a computer simulation is the process of running certain model(s) (typically mathematical in nature) on a computer program over some amount of time in order to study and/or visualize the behavior or performance of some system. As such, we use the terms models and computer simulations interchangeably in this paper.
American Astronomical Society Meeting Abstracts #213, 2009
We present the results of a deep search for fossil radio emission in a sample of X-ray luminous g... more We present the results of a deep search for fossil radio emission in a sample of X-ray luminous galaxy groups, NGC 383, with "radio-loud'' central sources. The data include new 235 and 610 MHz observations from the GMRT as well as archival data at 327 MHz from the VLA. Our goal is to directly measure the amount of energy that has been injected into the intragroup medium by individual active galactic nuclei (AGN) over the last 100-200Myr and compare it with the energy input by star formation as measured from H-alpha observations. We compare the radio luminosity to the amount of excess non-gravitational heating implied by the groups' X-ray properties. With our low frequency observations we show that AGN feedback must deposit significant amounts of energy into the intergalactic medium in galaxy groups.
Science & education, Aug 18, 2018
Scientific models, mathematical equations, and computer simulations are indispensable to scientif... more Scientific models, mathematical equations, and computer simulations are indispensable to scientific practice. Through the use of models, scientists are able to effectively learn about how the world works, and to discover new information. However, there is a challenge in understanding how scientists can generate knowledge from their use, stemming from the fact that models and computer simulations are necessarily incomplete representations, and partial descriptions, of their target systems. In order to construct a model, one must make idealizations, approximations, and abstractions. Given these constraints in constructing models, there is a question of whether they can provide new insight into how real systems actually work. So, how is it that highly abstract models inform us about the nature of the world, and more specifically, how do they provide explanatory knowledge? In Reconstructing Reality: Models, Mathematics, and Simulations, philosopher Margaret Morrison undertakes this task of examining the connection between the abstracted nature of mathematical models and computer simulations, and their ability to provide explanations and understanding of the world. Her philosophical project aims to develop an understanding of how we can learn about reality, even though it is acknowledged that the models being used in scientific investigations offer only incomplete representations of the systems under study. Morrison focuses on three central themes: how it is that mathematical models are developed, and how they then provide explanations and understanding (Part I); the nature of scientific representation via models (Part II), and how computer simulations can be understood as a successful method for providing experimental knowledge about reality (Part III). Rather than working to provide one overarching philosophical argument, each chapter stands somewhat alone, addressing a specific challenge central to the use of models in scientific practice. One of the takeaways for which Morrison advocates is the need to look Science & Education
Studies in History and Philosophy of Science, Oct 1, 2021
The debate between ΛCDM and MOND is often cast in terms of competing gravitational theories. Howe... more The debate between ΛCDM and MOND is often cast in terms of competing gravitational theories. However, recent philosophical discussion suggests that the ΛCDM-MOND debate demonstrates the challenges of multiscale modeling in the context of cosmological scales. I extend this discussion and explore what happens when the debate is thought to be about modeling rather than about theory, offering a model-focused interpretation of the ΛCDM-MOND debate. This analysis shows how a model-focused interpretation of the debate provides a better understanding of challenges associated with extension to a different scale or domain, which are tied to commitments about explanatory fit.
Bulletin of the American Physical Society, Apr 19, 2021
for an Invited Paper for the APR21 Meeting of the American Physical Society Computer simulations ... more for an Invited Paper for the APR21 Meeting of the American Physical Society Computer simulations and large-scale structure formation MELISSA JACQUART, University Of Cincinnati Scientific models and computer simulations are indispensable to scientific practice. Through their use, physicists are able to learn about how the world works, and to discover new information. However, there is a challenge in understanding how physicists can generate knowledge from their use, stemming from the fact that simulations are necessarily incomplete representations and partial descriptions of their target systems. In order to construct a simulation, one must make idealizations, approximations, and abstractions. In this talk, I focus on the role of idealization and representation in large-scale structure formation simulations. This case provides the opportunity to study the precise ways that idealization and representational trade-offs enter into the construction of simulations, and how they may determine values for simulation parameters. I argue that the use of simulation code that is flexible enough to de-idealize representations plays a specific role in reasoning about results in the context of astrophysics. This is particularly salient when the simulations aim to connect a vast array of independent astronomical observations/phenomena to cosmologists' more global arguments.
2017 AAAS Annual Meeting (February 16-20, 2017), Feb 19, 2017
Studies in History and Philosophy of Science, Jun 1, 2023
Philosophy of Science, Dec 1, 2020
Astrophysics faces methodological challenges as a result of being a predominantly observation-bas... more Astrophysics faces methodological challenges as a result of being a predominantly observation-based science without access to traditional experiments. In light of these challenges, astrophysicists frequently rely on computer simulations. Using collisional ring galaxies as a case study, I argue that computer simulations play three roles in reasoning in astrophysics: (1) hypothesis testing, (2) exploring possibility space, and (3) amplifying observations.
SAGE Publications, Inc. eBooks, May 15, 2012
Routledge eBooks, Aug 11, 2021
Dark Matter and Dark Energy Chapter for The Routledge Companion to Philosophy of Physics. Section... more Dark Matter and Dark Energy Chapter for The Routledge Companion to Philosophy of Physics. Sections include Observational Evidence for Dark Matter and Dark Energy; Realism; The Cosmological Constant Problem; Underdetermination of Theory by Evidence; Theory Change and Theory Choice; and Models and Computer Simulations
Philosophy of Science, Dec 1, 2018
Gravitational interactions allowed astronomers to conclude that dark matter rings all luminous ga... more Gravitational interactions allowed astronomers to conclude that dark matter rings all luminous galaxies in gigantic halos, but this only accounts for a fraction of the total mass of dark matter believed to exist. Where is the rest? We hypothesize that some of it resides in dark galaxies, pure dark matter halos that either never possessed or have totally lost their baryonic matter. This paper explores methodological challenges that arise due to the nature of observation in astrophysics, and examines how the blend of observation, simulation, and theory we call the Observing the Invisible approach might make detecting such dark objects possible. CORE Metadata, citation and similar papers at core.ac.uk
Teaching Philosophy, 2017
The problem of inadequate professional training for graduate students in teaching and pedagogy ha... more The problem of inadequate professional training for graduate students in teaching and pedagogy has recently come into sharp relief. Providing teacher training for philosophy graduate students through for-credit courses has been recommended as a solution to this problem. This paper provides an overview of the problem, identifies several aims such a course should have, and provides a detailed overview of a course satisfying those aims. By providing a detailed outline of the course, this paper can act as a resource for faculty tasked with teaching such a course. Finally, we justify the pedagogical decisions made in the design of this course to prepare facilitators to more effectively teach it, to allow facilitators to make informed and intentional decisions when adapting the course to their program, and as a demonstration of what we take to be some of the best practices in teaching and pedagogy. That is, the design of the course is informed by the very material covered in the course.
American Association of Philosophy Teachers Studies in Pedagogy
Bulletin of the American Physical Society, Apr 19, 2021
for an Invited Paper for the APR21 Meeting of the American Physical Society Computer simulations ... more for an Invited Paper for the APR21 Meeting of the American Physical Society Computer simulations and large-scale structure formation MELISSA JACQUART, University Of Cincinnati Scientific models and computer simulations are indispensable to scientific practice. Through their use, physicists are able to learn about how the world works, and to discover new information. However, there is a challenge in understanding how physicists can generate knowledge from their use, stemming from the fact that simulations are necessarily incomplete representations and partial descriptions of their target systems. In order to construct a simulation, one must make idealizations, approximations, and abstractions. In this talk, I focus on the role of idealization and representation in large-scale structure formation simulations. This case provides the opportunity to study the precise ways that idealization and representational trade-offs enter into the construction of simulations, and how they may determine values for simulation parameters. I argue that the use of simulation code that is flexible enough to de-idealize representations plays a specific role in reasoning about results in the context of astrophysics. This is particularly salient when the simulations aim to connect a vast array of independent astronomical observations/phenomena to cosmologists' more global arguments.
Studies in History and Philosophy of Science
Feminist Philosophy Quarterly
Empirical data show that members of underrepresented and historically marginalized groups in acad... more Empirical data show that members of underrepresented and historically marginalized groups in academia undertake many forms of undervalued or unnoticed labor. While the data help to identify that this labor exists, they do not provide a thick description of what the experience is like, nor do they offer a framework for understanding the different kinds of invisible labor that are being undertaken. We identify and analyze a distinct, undervalued, and invisible labor that the data have left unnamed and unmeasured: ontological labor, the work required to manage one’s identity and body if either or both do not fit into academic structures, norms, and demands. We argue that ontological labor efforts should be understood as a form of labor. We then provide a characterization of ontological labor, detailing the labor as navigating one’s obligations to give and managing entitlements to take. We also highlight the ontological labor that takes place through instances of resistance, such as thr...
Philosophy of Science, 2020
Astrophysics faces methodological challenges as a result of being a predominantly observation-bas... more Astrophysics faces methodological challenges as a result of being a predominantly observation-based science without access to traditional experiments. In light of these challenges, astrophysicists frequently rely on computer simulations. Using collisional ring galaxies as a case study, I argue that computer simulations play three roles in reasoning in astrophysics: (1) hypothesis testing, (2) exploring possibility space, and (3) amplifying observations.
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Papers by Melissa Jacquart