About

Dr. Phil G. Campbell is a Research Professor in the Department of Biomedical Engineering and the Institute for Complex Engineered Systems at the Carnegie Institute of Technology (School of Engineering) at Carnegie Mellon University in Pittsburgh. He also holds courtesy appointments in CMU's Departments of Biological Sciences and Materials Science and Engineering, and is a Faculty Member of the Molecular Biosensor and Imaging Center at CMU. With over 25 years of experience in multidisciplinary research, Dr. Campbell has collaborated with engineers and clinicians to develop solutions for complex biomedical problems, including the development of natural-based biomaterials, implant biocompatibility, and tissue engineering. His overarching research theme involves understanding and engineering the cellular microenvironment from an endocrine perspective, both in vitro and in vivo. His work encompasses growth factor interstitial transport, interactions with receptors and non-receptor binding proteins, immobilization and proteolytic processing of extracellular matrix-bound signaling molecules, and live cell and animal imaging. Dr. Campbell's research utilizes biopatterned microenvironments to spatially deliver signaling molecules, controlling cell behavior in vitro and tissue formation in vivo, with applications in musculoskeletal, cardiac, immunological, and cancer fields.

Research topics

• Astrophysics
• Physics
• Astronomy
• Computer Science
• Geography

Selected publications

• Halotools: A New Release Adding Intrinsic Alignments to Halo-Based Methods

  The Journal of Open Source Software · 2025-03-11

  articleOpen access
  PublisherOA PDFDOI

• An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

  The Open Journal of Astrophysics · 2024-06-04 · 6 citations

  articleOpen access

  We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to . We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

  PublisherDOI

• Delivering scientific evidence for global policy and management to ensure ocean sustainability

  Sustainability Science · 2024-10-07 · 7 citations

  articleOpen access

  Abstract Life depends on the ocean, with societal health, cultural systems and national economies reliant on ocean processes and resources. As ocean resources are used, and humans continue to drive climate change, the benefits from the ocean to society are being diminished. Science must meet the needs of policy and deliver to decision makers the information and tools for identifying pathways that support continued delivery of the benefits society derives from the ocean, whilst minimising impacts. This is crucial if the world’s nations are to meet the goals and targets they have set under international agreements. Here, we outline how a global assessment that focuses specifically on the ocean, the World Ocean Assessment, is linking science to the governments of the world and their policies within an internationally mandated framework. In doing so, we identify key elements that are needed for facilitating engagement by decision makers and uptake of knowledge, and the pathways taken by the assessment in implementing them. We also provide insights into the evolution that the World Ocean Assessment has undertaken over its first three cycles to progress its goal of enhancing the scientific basis of policymaking. We identify the challenges in delivering science to policy at a global scale and the work that still needs to be done in filling gaps to achieve a coordinated, comprehensive mechanism for connecting science with policy and ensuring future sustainability of the ocean.

  PublisherOA PDFDOI

• An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

  arXiv (Cornell University) · 2023-11-13 · 1 citations

  preprintOpen access

  We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the IllustrisTNG suite. We create an HOD mock with TNG-like correlations using our method, constraining the associated IA model parameters, with the $χ^2_{\rm dof}$ between our model's correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation--position and orientation--orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to $0.1~h^{-1}{\rm Mpc}$. We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

  PublisherOA PDFDOI

• Galaxies and haloes on graph neural networks: Deep generative modelling scalar and vector quantities for intrinsic alignment

  Monthly Notices of the Royal Astronomical Society · 2022 · 9 citations

  Senior authorCorresponding
  • Physics
  • Astrophysics

  ABSTRACT In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency of galaxies to naturally align towards overdensities, an effect called intrinsic alignments (IA), can be a major source of systematics in the weak lensing analysis. As the details of galaxy formation and evolution relevant to IA cannot be simulated in practice on such volumes, we propose as an alternative a Deep Generative Model. This model is trained on the IllustrisTNG-100 simulation and is capable of sampling the orientations of a population of galaxies so as to recover the correct alignments. In our approach, we model the cosmic web as a set of graphs, where the graphs are constructed for each halo, and galaxy orientations as a signal on those graphs. The generative model is implemented on a Generative Adversarial Network architecture and uses specifically designed Graph-Convolutional Networks sensitive to the relative 3D positions of the vertices. Given (sub)halo masses and tidal fields, the model is able to learn and predict scalar features such as galaxy and dark matter subhalo shapes; and more importantly, vector features such as the 3D orientation of the major axis of the ellipsoid and the complex 2D ellipticities. For correlations of 3D orientations the model is in good quantitative agreement with the measured values from the simulation, except for at very small and transition scales. For correlations of 2D ellipticities, the model is in good quantitative agreement with the measured values from the simulation on all scales. Additionally, the model is able to capture the dependence of IA on mass, morphological type, and central/satellite type.

  PublisherOA PDFDOI

• Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era

  The Open Journal of Astrophysics · 2022-01-17 · 16 citations

  articleOpen access

  Large simulation efforts are required to provide synthetic galaxy catalogs for ongoing and upcoming cosmology surveys. These extragalactic catalogs are being used for many diverse purposes covering a wide range of scientific topics. In order to be useful, they must offer realistically complex information about the galaxies they contain. Hence, it is critical to implement a rigorous validation procedure that ensures that the simulated galaxy properties faithfully capture observations and delivers an assessment of the level of realism attained by the catalog. We present here a suite of validation tests that have been developed by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). We discuss how the inclusion of each test is driven by the scientific targets for static ground-based dark energy science and by the availability of suitable validation data. The validation criteria that are used to assess the performance of a catalog are flexible and depend on the science goals. We illustrate the utility of this suite by showing examples for the validation of cosmoDC2, the extragalactic catalog recently released for the LSST DESC second Data Challenge.

  PublisherOA PDFDOI

• Probabilistic model for dynamic galaxy decomposition

  Monthly Notices of the Royal Astronomical Society · 2021-10-27

  preprintOpen access

  ABSTRACT In the era of precision cosmology and ever-improving cosmological simulations, a better understanding of different galaxy components such as bulges and discs will give us new insight into galactic formation and evolution. Based on the fact that the stellar populations of the constituent components of galaxies differ by their dynamical properties, we develop two simple models for galaxy decomposition using the TNG100 cosmological hydrodynamical simulation from the IllustrisTNG project. The first model uses a single dynamical parameter and can distinguish four components: thin disc, thick disc, counter-rotating disc, and bulge. The second model uses one more dynamical parameter, was defined in a probabilistic manner, and distinguishes two components: bulge and disc. We demonstrate the improved robustness of these models compared to a widely used method in literature involving cuts on the circularity parameter. The number fraction of disc-dominated galaxies at a given stellar mass obtained by our models agrees well with observations for masses exceeding log10(M*/M⊙) = 10. The galaxies classified as bulge-dominated by the second model are mostly red; however, the population classified as disc-dominated contains significant number of red galaxies alongside the blue population. The contributions of the different galaxy components to the total stellar mass budget exhibits similar trends with stellar mass compared to the observational data, although there is a quantitative disagreement at high and low masses. The Sérsic indices and half-mass radii for the bulge and disc components agree well with those of real galaxies.

  PublisherOA PDFDOI

• Void Galaxies Follow a Distinct Evolutionary Path in the Environmental COntext Catalog

  The Astrophysical Journal · 2021 · 30 citations

  • Physics
  • Astrophysics
  • Astronomy

  Abstract We measure the environmental dependence, where environment is defined by the distance to the third nearest neighbor, of multiple galaxy properties inside the Environmental COntext (ECO) catalog. We focus primarily on void galaxies, which we define as the 10% of galaxies having the lowest local density. We compare the properties of void and non-void galaxies: baryonic mass, color, fractional stellar mass growth rate (FSMGR), morphology, and gas-to-stellar-mass ratio (estimated from a combination of H i data and photometric gas fractions calibrated with the REsolved Spectroscopy Of a Local VolumE survey). Our void galaxies typically have lower baryonic masses than galaxies in denser environments, and they display the properties expected of a lower mass population: they have more late types, are bluer, have a higher FSMGR, and are more gas-rich. We control for baryonic mass and investigate the extent to which void galaxies are different at fixed mass. Void galaxies are bluer, more gas-rich, and more star-forming at fixed mass than non-void galaxies, which is a possible signature of galaxy assembly bias. Furthermore, we show that these trends persist even at fixed mass and morphology, and we find that voids host a distinct population of early types that are bluer and more star-forming than the typical red and quenched early types. In addition to these empirical observational results, we also present theoretical results from mock catalogs with built-in galaxy assembly bias. We show that a simple matching of galaxy properties to (sub)halo properties, such as mass and age, can recover the observed environmental trends in ECO galaxies.

  PublisherOA PDFDOI

• Generating synthetic cosmological data with GalSampler

  Monthly Notices of the Royal Astronomical Society · 2020 · 22 citations

  Senior authorCorresponding
  • Computer Science
  • Physics
  • Astrophysics

  ABSTRACT As part of the effort to meet the needs of the Large Synoptic Survey Telescope Dark Energy Science Collaboration (LSST DESC) for accurate, realistically complex mock galaxy catalogues, we have developed galsampler, an open-source python package that assists in generating large volumes of synthetic cosmological data. The key idea behind galsampler is to recast hydrodynamical simulations and semi-analytic models as physically motivated galaxy libraries. galsampler populates a new, larger volume halo catalogue with galaxies drawn from the baseline library; by using weighted sampling guided by empirical modelling techniques, galsampler inherits statistical accuracy from the empirical model and physically motivated complexity from the baseline library. We have recently used galsampler to produce the cosmoDC2 extragalactic catalogue made for the LSST DESC Data Challenge 2. Using cosmoDC2 as a guiding example, we outline how galsampler can continue to support ongoing and near-future galaxy surveys such as the Dark Energy Survey, the Dark Energy Spectroscopic Instrument, WFIRST, and Euclid.

  PublisherOA PDFDOI

• How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

  Monthly Notices of the Royal Astronomical Society · 2019-06-25 · 32 citations

  articleOpen accessSenior author

  ABSTRACT Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analysed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy–halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function $w$p(rp), the galaxy–galaxy lensing signal ΔΣ(rp), the void probability function VPF(r), the distributions of counts-in-cylinders P(NCIC), and counts-in-annuli P(NCIA), and the distribution of the ratio of counts in cylinders of different sizes P(N2/N5). We find that despite the frequent use of the combination $w$p(rp) + ΔΣ(rp) in interpreting galaxy data, the count statistics, P(NCIC) and P(NCIA), are generally more efficient in constraining galaxy assembly bias when combined with $w$p(rp). Constraints based upon $w$p(rp) and ΔΣ(rp) share common degeneracy directions in the parameter space, while combinations of $w$p(rp) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy–halo connection.

  PublisherOA PDFDOI

Frequent coauthors

• François Lanusse

  Centre National de la Recherche Scientifique

  22 shared

• Andrew P. Hearin

  Argonne National Laboratory

  16 shared

• Yao-Yuan Mao

  11 shared

• Rachel Mandelbaum

  Carnegie Mellon University

  9 shared

• Frank C. van den Bosch

  8 shared

• J. Lange

  The University of Texas at Austin

  7 shared

• Manodeep Sinha

  Australian Research Council

  7 shared

• Andrew R. Zentner

  University of Pittsburgh

  7 shared

Labs

• Exosome Research LabPI

Education

• B.S., Animal Science

  Auburn University

• M.S., Animal Science

  Auburn University

• Ph.D., Physiology

  Pennsylvania State University

  1985

Awards & honors

• Benjamin Richard Teare Teaching Award, 2018