TALES School I

16 Feb 2026, 09:00 → 20 Feb 2026, 18:00 Europe/Rome

Room B (Centro Congressi Federico II)

Rationale

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The first TALES school aims at providing an introductory but comprehensive overview to the study of AGN physics and demography using a variety of time-domain analysis methods and tools. The lectures will cover the activities of all TALES work packages form both an observational and theoretical perspective. The program includes a first part dedicated to AGN studies in the time-domain, one day of consortium activities, and a final part dedicated to lectures on machine learning, with hands-on sessions and examples of applications to astrophysical studies. The lectures will be offered by the TALES consortium members as well as by research and industrial partners, with contributions from the Doctoral candidates themselves.

 

Participants

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Tutors:

1. M. Paolillo
2. A. Georgakakis
3. I. Papadakis
4. E. Costantini
5. F. Tombesi
6. A. Rau
7. A. Young
8. A. Różańska
9. D. Ilic
10. A. Kovacevic
11. A. Gomboc
12. C. Raiteri
13. C. Feruglio
14. D. Gronkiewicz 

 

Students:

1. Nicolò Belgiovine
2. Natale De Bonis
3. Amie-Louise Doherty
4. Prathamesh Ingale
5. Marios Kouzis
6. Tianying Lian
7. V. Madurga Favieres
8. Valerio Pandolfi
9. Michail Polioudakis
10. Shashanth Sriramanathan
11. Erin Umuzigazuba

 

Additional attendees:

• Pierpaolo Condò
• Lorenzo Santo
• Vincenzo Petrecca
• Nikolas Vasilas
• Francesco Montenigro
• Orsini Luca Menichini
• Marta Fatovic
• Demetra De Cicco

Monday 16 February

09:15 → 09:30 Welcome

09:30 → 11:00 Introduction to timing analysis and X-ray variability in AGN

Content: This lecture will introduce the concept of random processes, and in particular stationary random processes, which are of significant importance in the study of variable phenomena in Astrophysics. I will give the definition of the auto-covariance and of the power spectral density function of a random process. I will then discuss how we estimate these random functions, and why it is preferable to work in the frequency rather than in the time domain.

Speaker: Prof. I. Papadakis

11:00 → 11:30 coffee break

11:30 → 12:15 X-ray reflection and reverberation in AGN

Content: in the very innermost regions of accretion flows onto supermassive black holes the hot corona, located somewhere above the accretion disc, produces X-rays which illuminate the accretion disc. The back-scattered, “reflection”, spectrum contains spectral features that are affected by strong Doppler and relativistic effects close to the black hole, as well as “reverberation” echoes due to the light travel time between the corona and the disc. I will summarise the theoretical, numerical, and observational frameworks used to study these systems, and outline the limitations of standard models that we hope to address with TALES.

Speaker: Prof. A. Young

12:15 → 13:00 Estimators of stohastic flux variability

Content: the lecture will present the statistical tools observational astronomers are using to measure the stochastic variability of light curves, with emphsasis on Active Galactic Nuclei. I will describe the benefits and shortcomings of different methods and also briefly discuss challenges associated with the Poisson nature of X-ray observations.

Speaker: Dr A. Georgakakis

13:00 → 14:30 lunch break

14:30 → 15:15 Characterizing optical/UV variability of AGN

Content: the lecture will discuss the behaviour of AGN variability in the optical/UV band, and its link with X-ray variability, as well as the link between variability physical properties of AGN (mass, accretion rate). Finally we will discuss the eDectiveness of optical variability to identify AGN in next generation optical surveys.

Speaker: Prof. M. Paolillo

15:15 → 16:00 Accretion flow properties through ML modeling

this lecture illustrates how we can build an AI-driven framework that reconstructs accretion flow transfer functions, SMBH physical parameters, and red-noise variability directly from AGN light curves without assuming stationarity or predefined parametric models. We will show how a data-riven approach allows to infer accretion flow structure and variability mechanisms across diverse AGN populations, enabling scalable characterization of SMBH accretion across millions of AGN in upcoming large time-domain surveys.

Speakers: Prof. A. Kovacevic, Prof. D. Ilic

16:00 → 16:30 coffee break

16:30 → 17:15 TDE, QPE and transient variability: characterization and modeling in X-rays

Content: the lecture will provide an introduction to Tidal Disruption Events (history, basic theory, emission models), of the X-ray properties studies from ROSAT to eROSITA and Einstein Probe, te challenges in identifying TDEs in wide-field X-ray surveys, the nature of Quasi Periodic Eruptions, and their link to TDEs.

Speaker: Dr A. Rau

17:15 → 18:00 TDE, QPE and transient variability: characterization and modeling in optical/UV

Content: the lecture will review the basic picture of TDEs, hydrodynamical simulations of TDEs, current status of optical/UV observations, what we can expect from Rubin LSST and the need for classification based solely on photometry. I will also briefly describe also QPE phenomenon.

Speaker: Prof. A. Gomboc

Tuesday 17 February

09:30 → 10:15 Modeling the temporal and dynamical behavior of multi-phase accretion flows

Content: the lecture will discuss timescales that are an outcome of multi-phase modelling of an inner accretion flow. In the model we consider the division of a total accretion energy is dissipated partially in an accretion disk, a warm corona responsible for soft X-ray excess and a hot corona where most hard X-ray radiation is emitted in radio quiet AGN. It will overview those timescales and put predictions on the multiwavelength observations of AGN variability.

Speaker: Prof. A. Rozanska

10:15 → 11:00 Exploring the realm of winds in AGN

Content: the lecture will review the state-of-the-art of our understanding of the nature of powerful winds, outflowing from the innermost parts of accretion disks in Active Galactic Nuclei (AGN). Winds are the likely messengers to explain how the central black hole may influence the host galaxy growth and ultimately explain galaxy evolution across cosmic time. Through high-energy resolution observations in the UV and X-rays, our view of winds evolved enormously. The high energy band provide a privileged view of the most energetic and massive multi-phases of the outflowing material.

Speaker: Dr E. Constantini

11:00 → 11:30 coffee break

11:30 → 12:15 Feeding the Storm: Probing the Power and Impact of Black Hole Winds

Content: the lecture will focus on the most extreme forms of AGN feedback: ultra-fast outflows (UFOs), highly ionized winds moving at relativistic speeds, exploring the physical processes that launch and accelerate these winds, the diagnostics provided by high-resolution X-ray spectroscopy, and the modeling techniques used to interpret their properties. Special attention will be given to recent results from XRISM, which reveal complex multi-velocity structures and rich absorption features. Finally, we will discuss the implications of UFOs for galaxy evolution and the challenges that remain for theory and observation.

Speaker: Prof. F. Tombesi

12:15 → 13:00 Student presentations

13:00 → 14:30 lunch break

14:30 → 16:00 Student presentations

16:00 → 16:30 coffee break

16:30 → 17:00 Student presentations

17:00 → 17:30 TBA

Speaker: Dr C. Ratieri

17:30 → 18:00 TBA

Speaker: Dr C. Feruglio

Wednesday 18 February

09:00 → 11:00 Consortium/Student Meeting

11:00 → 11:30 coffee break

11:30 → 13:00 WP splinter meetings

13:00 → 22:00 Free afternoon - Social event

Thursday 19 February

09:30 → 11:00 PROMITY: Introduction to machine learning: lecture

09:30 Introduction to machine learning: lecture

An introductory, non-technical review lecture about what machine learning is: the basic tasks, concepts, methods, followed by a practical workshop. A laptop with internet access and a web browser is required!

11:00 → 11:30 coffee break

11:30 → 13:00 PROMITY: Introduction to machine learning: hands-on workshop

13:00 → 14:30 lunch break

14:30 → 16:00 PROMITY: Introduction to deep learning and GPU computing: lecture

14:30 Introduction to deep learning and GPU computing: lecture

Content: Short introduction to deep learning and its challenges, followed by an extended more technical workshop. Participants will learn the building blocks of modern ML: using GPU for computation, tensor operations, building deep neural networks in Pytorch, loading data, traning the model, saving and retrieving models. A laptop with internet access and a web browser is required!

16:00 → 16:30 coffee break

16:30 → 18:00 PROMITY: Introduction to deep learning and GPU computing: hands-on workshop

Friday 20 February

09:30 → 11:00 PROMITY: ML project from scratch: lecture

09:30 ML project from scratch: lecture

Content: Participants will use skills from day 1 to train a custom deep network from start to finish using recommended tools and practices. Additionally, they learn about tools to observe training, managing ML models and results and how to optimize your model if performance is of issue. A laptop with internet access and a web browser is required!

11:00 → 11:30 coffee break

11:30 → 13:00 PROMITY: ML project from scratch: hands-on workshop

13:00 → 14:30 lunch break

14:30 → 16:00 ML applications in Astronomy

14:30 Strengthening leverage of Artificial Intelligence in interdisciplinary Science: Astrophysics use cases

Content: Most domains of science are experiencing a paradigm shift due to the availability data streams at an unprecedented rate. The scientific exploitation of these data, namely Data Driven Discovery, requires interoperability, massive and optimal use of Artificial Intelligence methods in all steps of the data acquisition, processing and analysis, the access to large and distributed computing HPC facilities, the implementation and access to large simulations and interdisciplinary skills that usually are not provided by standard academic curricula. Through the presentation of several astrophysical use cases, we show how the Data Driven based solutions could represent the optimal playground to achieve the multi-disciplinary methodological approach.

Speaker: M. Brescia

15:15 Leveraging Transfer Learning for Astronomical Image Analysis

Content: This lecture explores some applications of transfer learning in astronomical image analysis, focusing on the usage of a pretrained model. We discuss methods for identifying active galactic nuclei, extracting physical parameters, and detecting anomalies in time series data. Additionally, we present some potential future applications, demonstrating the versatility of this approach, even without a training phase.

Speaker: S. Cavuoti (INAF- Capodimonte)

16:00 → 16:30 coffee break

16:30 → 18:00 Final discussion and future activities