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06/04/2022, 14:00
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Andrea Rinaldo, Samir Suweiss (University of Padova), flavio seno (università di Padova)06/04/2022, 14:30
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Anna Levina (University of Tuebingen)06/04/2022, 14:45
Timescales characterize how fast the observables change in time. In neuro science, they can be estimated from the measured activity and can be used, for example, as a signature of the memory trace in the activations. Inferring the
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timescales seems to be an easy task; however, I will show you how the timescales are subject to a statistical bias that is impossible to remove by a simple... -
Elisa Omodei (Central European University)06/04/2022, 15:30
In a rapidly changing world, facing an increasing number of socioeconomic, health and environmental crises, physics of data and complex systems can help us to assess and quantify
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vulnerabilities, and to monitor and achieve the UN Sustainable Development Goals. In this talk, I will provide an overview of the main areas of applications where physics of data and
complex systems has shown its... -
Umberto Tomasini (EPFL)06/04/2022, 16:45
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Nicola Dainese (Aalto University)06/04/2022, 17:00
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Jeff Byers (Naval Research Laboratory)06/04/2022, 17:15
In physics the data that is acquired in experiments are highly-controlled and often taken with specific goals in mind. However, the notion of a “Physics of Data” is about using mathematical tools developed in physics to understand data acquired in more open-ended and uncontrolled environments. As the data acquisition process becomes more opaque and distant from any particular purpose, we have...
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Laura Lupi (Roma Tre University)07/04/2022, 09:00
Many interesting physical processes occur on timescales that are very long compared to the shortest significant timescale involved. For example, timescales for folding the smallest of proteins are in the range of microseconds to milliseconds, while small-amplitude motions of amino acid side chains occur within 1 fs.
This large difference of timescales can present serious computational...
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Grill Jacopo (ICTP)07/04/2022, 09:45
Microbial communities are high-dimensional systems, with many co-evolving heterogeneous species and many environmental factors, that vary across time and space. Due to the sequencing advancements of the last 30 years, ecology, a traditionally data-poor discipline, has transitioned to become a data-rich one. In the first part of the talk, I will discuss some open questions that drive modern...
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Anna Braghetto (University of Padova)07/04/2022, 11:00
One of the fundamental open problems in knot theory is their classification, which aims to discriminate whether two given closed curves are topologically equivalent or not. The
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problem might be tackled with knot invariants, such as the Alexander polynomial, quantities that are the same for equivalent knots. Nevertheless, algorithms implementing
knot recognition through invariants might take... -
Luca Baroni (Charles University)07/04/2022, 11:15
The visual cortex is the sensory area of the brain responsible for the information processing that underlies our visual perceptions. The first part of the cortex that receives input from visual stimuli is called primary visual cortex, or V1. It is the most studied area of the visual cortex, and probably the most studied sensory area of the brain in general.
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Since the Nobel prize works of... -
Johannes Zierenberg (Max Planck Institute for Dynamics and Self-Organization)07/04/2022, 11:30
I will present a data-driven approach to identify from physical proximity data features of human contact patterns that determine crucial properties of epidemic outbreaks. From the physical proximity data, we construct for each individual
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a point-process-like representation of their contacts, from which we estimate the distribution of potential secondary infections for different disease... -
Ilaria Siloi (University of Padua)07/04/2022, 14:45
The promise of quantum computing is to provide new methods to unveil the physics of molecules and materials that has been inaccessible to the conventional numerical modeling. Over the past few years, quantum annealers have grown in complexity to the point that the computation of molecular energies has
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become a feasible application. Whilst typical approaches use quantum annealers to extract... -
Guido Caldarelli (University of Venice)07/04/2022, 15:30
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Samuele Cavinato (IOV)07/04/2022, 16:45
The development of quantum computers is one of the most intriguing and motivating challenges of the current century. Thanks to their inborn quantum nature, these machines are expected to offer an unprecedented computational advantage over classical machines in solving highly complex
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computational problems that span from the simulation of quantum systems to quantum chemistry and material... -
Vincenzo Maria Schimmenti (Univ. Paris-Saclay)07/04/2022, 17:00
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Stefano Campese (stefano.campese.90@gmail.com)07/04/2022, 17:15
Natural language processing (NLP) is the ability of a computer to understand human languages. In both the academic and the industrial world, NLP has been widely used for different purposes such as Sentiment Analysis, Semantic
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Text Similarity (STS), Text Translation, and Question Answering (QA), to cite a few.
With the advent of the Transformer model architectures like BERT, the performances... -
Carlo Albert (Eawag Institute)08/04/2022, 09:30
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Floor Broekgaarden08/04/2022, 10:15
The rapidly increasing population of detected gravitational wave sources carries valuable information about the properties of black holes and neutron stars, such as their rates,
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masses and spins, that we aim to use to probe their progenitors and answer two of the big open questions in Astronomy today: “How do these sources form?” and “What can we learn from their gravitational waves about the... -
Giuliano Iorio (University of Padua)08/04/2022, 11:30
In 2015, the LIGO/VIRGO interferometers detected the first gravitational wave (GW) signal coming from the merger of two black holes. Since then, about 90 merging binary compact
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objects (BCOs), namely binary neutron stars and black holes, have been detected through GW signals. This wealth of new data provides us with crucial insight on the populations
of BCOs. For this reason, numerical tools... -
Cecilia Sgalletta (SISSA)08/04/2022, 12:15
Pulsars are powerful probes of our universe: thanks to their extraordinary long-term rotational stability and their fast rotation, they allow extremely precise timing measurements. However, the physics behind their spins and magnetic fields evolution is still poorly understood. A particular interest resides in the process of spin-up: neutron stars in binary systems
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can be spun-up by accreting... -
Jacopo Tissino (GSSI)08/04/2022, 12:30
The LIGO-Virgo collaboration has detected dozens of gravitational wave signals so far, and will do so at an increasing rate in the following years with detector
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upgrades. These signals are extremely faint and arrive to us buried in noise; measuring and analyzing them is a hard computational challenge.
I will discuss how machine learning can help in this task, mostly focusing on the... -
Nicholas Wardle (Imperial College of London)08/04/2022, 14:35
The Large Hadron Collider (LHC) at CERN is one of our most powerful tools to probe the fundamental particles of nature and their interactions. By colliding protons at extremely high energies (13 TeV centre of mass), the LHC can probe conditions of the early universe just after the Big Bang. Particle detectors, such as the Compact Muon Solenoid (CMS) experiment are designed to reconstruct the...
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Sofia Vallecorsa (CERN)08/04/2022, 15:20
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Gaia Grosso (University of Padua, CERN)08/04/2022, 16:20
Experimental observations and convincing conceptual arguments indicate that the present understanding of fundamental physics is not complete, motivating the search for physics beyond the Standard Model at collider experiments. The most common searching strategy is to test the data for the presence of one candidate new theory at a time and therefore optimise the data analysis to be sensitive to...
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Marco Zanetti (DFA, Università di Padova)08/04/2022, 16:40
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