Federica Rescigno

About Me

Education
2020 - Present
PhD in Astrophysics at the University of Exeter, UK
Supervisors: Dr. Raphaelle Haywood, Dr. Tim Naylor
Title: Breaking the stellar activity barrier to determining robust masses of small exoplanets

2016 - 2020
MPhys in Physics and Astronomy at Durham University, UK
Master Project Advisor: Prof. Cedric Lacey
Title: Study of the galaxy merger rate in the EAGLE simulation

Research Interests
I focus on understanding the stellar activity signal in radial velocity surveys for the detection of exoplanets. I have developed a python3 pipeline called MAGPy, a Gaussian process regression tool with MCMC paramter search algorithm. I am using this new pipeline in the detection and characterisations of two systems with the HARPS-N Science Team.

I am also involved in "Sun as an exoplanet-hosting distant star" studies. In particular, I am looking at the solar longitudinal, line-of-sight magnetic flux, measured with the SDO/HMI, and to whether it can be a good proxy for detecting the stellar rotational period and for modeling stellar activity.

I am a member of the High Accuracy Rocky Planet Search for the Northern Hemisphere, Guaranteed Time Observation Consortium (HARPS-N GT) Science Team and Solar Team, as well as a collaborator for the Terra Hunting Experiment Consortium in the Science Team, the Solar Team and the Polarimetry Team.

I am passionate about scientific dissemination and am therefore very active in public outreach. I especially love working with younger students and children, from visiting schools, exchanging letters to direct pastoral mentoring in highschool.

Publications:
ADS Library of all papers

Research

A hot mini-Neptune and a temperate, highly eccentric sub-Saturn around the bright K-dwarf TOI-2134
Including radial velocity data by HARPS—N and SOPHIE and transit photometry by TESS, LCOGT, WASP and NEOSSat.
To be publushed in: Rescigno et al. in review
Included in the following poster: MAGPy pipeline, TOI2134.01 and .02 detection

MAGPy Pipeline
MAGPy: a pipeline for Gaussian Process regression with MCMC parameter space searching algorithm, developed in the context of stellar activity reduction for planet detection. It is developed to be self-contained and flexible enough to fit any Gaussian process need. Kernels and models can be modified or added. It has a affine invariant MCMC algorithm, which can optionally be parallelized. It includes publication level plotting. It is the process of being packaged for public release, with extended API.
Published in: Rescigno, F et al. b (in prep)
To be released on GitHub: MAGPy
Included in the following poster: MAGPy pipeline and TOI2134.01 and .02 detection

Longitudinal, line-of-sight magnetic flux as a proxy for stellar activity: SDO/HMI and HARPS-N data
I am investigating the efficacy of the longitudinal, line-of-sight magnetic flux as a proxy to detect the stellar rotational period of solar-like star and to model stellar activity-induced variations in radial velocity surveys. Preliminary analysis shows that, while it is not directly correlated to the RVs, when used in a Gaussian Process regression framwork it consistently outperforms other proxies, especially in the low-activity regime.
To be published in: Rescigno, F et al. a (in prep)
Included in the following poster: The Longitudinal, line-of-sight magnetic flux as aproxy for stellar activity

Rocky Planet Search: HDxxxxx planetary system detection
Non—transiting planet detection of an Earth—like planet and a mini—Neptune using HARPS-N radial velocity data.
HARPS-N GTO Collaboration, RPS Team. Under the lead of Dr. Shweta Dalal (University of Exeter, UK).
To be published in: Dalal, S et al. (in prep)

Other Current Projects

• Disentangling supergranulation in Sun-as-a-star observations from SDO/HMI data. Collaboration with Ben Lakeland (University of Exeter, UK)
  
• Deriving point-source-like line profiles and bisector analysis using GRASS of the resolved SDO/HMI data. Collaboration with Michael Palumbo (Penn State University, US)
  
• Applying Gaussian Process regression analysis to formation temperature-dependent stellar activity RVs across spectral types. Collaboration with Khaled Al Moulla (University of Geneva, CH)
  
• Resolved Sun—like star simulations using SDO data with Dr. Steve Saar (Harvard University, US), Dr. Raphaelle Haywood (University of Exeter, UK) and Michael Palumbo (Penn State University, US).
  

Past Projects

• SolAster: 'Sun-as-a-star' radial velocity variations analysis python pipeline. A tool to analyse SDO/HMI data to study the Sun as a non-resolved star, including magnetic activity and filling factors computations. Lead by Tama Ervin.
  Published in: Ervit et al. 2022
  Simple use tutoral (developed for the Sun-as-a-star workshop, CCA, 2023): SolAster Jupyter Tutorial

Teaching and Outreach

Contact

Email: fr307@exeter.ac.uk

Address: Physics Building, Streatham Campus, University of Exeter, North Park Road, Exeter UK EX4 4QL

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