# SPEAKERS

Ludovic Berthier

Université de Montpellier

##### Resume:

Ludovic Berthier received his Ph.D. in Theoretical Physics in 2001 at the Ecole Normale Supérieure in Lyon, France. He was a Marie Curie Postdoctoral Fellow at the Department of Theoretical Physics at Oxford University until 2003. In 2004 he was appointed as a CNRS researcher at the Laboratoire Charles Coulomb at University of Montpellier (France), where he is now Director of Research. In 2007, he was a visiting scientist at the James Franck Institute of the University of Chicago, US. He works on the statistical mechanics of disordered materials, nonequilibrium systems, and soft matter. He performs theoretical research and computer simulations to develop a fundamental understanding of the structure and dynamics of a broad range of materials that we use on a daily basis, from sandpiles, emulsions, pastes and to window glasses and simple molecular fluids.

##### The topic of the talk is waiting to be announced.

Juan P. Garrahan

University of Nottingham

##### Resume:

Juan P. Garrahan is an academic researcher from University of Nottingham. The author has contributed to research in topic(s): Phase transition & Quantum. The author has an hindex of 55, co-authored 260 publication(s) receiving 10600 citation(s). Previous affiliations of Juan P. Garrahan include University of Buenos Aires & University of Bath.

##### The topic of the talk is waiting to be announced.

Gian Giacomo Guerreschi

Intel

##### Resume:

Gian Giacomo Guerreschi is a research scientist at Intel Labs where he focuses on theoretical and numerical aspects of Quantum Computing. Gian Giacomo received his Ph.D. degree in Theoretical Physics from the University of Innsbruck (Austria) and the Institute for Quantum Information and Quantum Optics (IQOQI). Before joining Intel he was a post-doctoral researcher at Harvard University where he investigated restricted models of quantum computation: adiabatic quantum optimization and boson sampling.

Gian Giacomo’s research interests include: large scale simulations of quantum algorithms, compilers for quantum circuits, the extension of neural networks to the quantum regime. His research has been presented in conferences and featured in journals like Nature Photonics, Physical Review Letters and Quantum Science and Technology, among others.

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Hilbert J. Kappen

Radbout Universiteit (The Neederlands)

##### Resume:

Bert Kappen’s research focuses on neural networks and machine learning, and the development of self-learning intelligent systems, which, among other things, can assist in locating missing persons. He also explores how quantum technology can be used for machine learning.

##### Why adiabatic quantum annealing is unlikely to yield speed-up
LyX Document
We study quantum annealing for combinatorial optimization with Hamiltonian $H=z{H}_{f}+{H}_{0}$ where ${H}_{f}$ is diagonal, ${H}_{0}=-|\varphi ⟩⟨\varphi |$ is the equal superposition state projector and $z$ the annealing parameter. We analytically compute the minimal spectral gap as $O\left(1}{\sqrt{N}}\right)$ with $N$ the total number of states and its location ${z}_{\ast }$. We show that quantum speed-up requires an annealing schedule which demands a precise knowledge of ${z}_{\ast }$, which can be computed only if the density of states of the optimization problem is known. However, in general the density of states is intractable to compute, making quadratic speed-up unfeasible for any practical combinatoric optimization problems. We conjecture that it is likely that this negative result also applies for any other instance independent transverse Hamiltonians such as ${H}_{0}=-\sum _{i=1}^{n}\sigma _{i}^{x}$.

Lucas Lamata

##### Resume:

I am an Associate Professor (Profesor Titular de Universidad) at Universidad de Sevilla, Spain (3 sexenios, 1 quinquenio, 4 trienios). My research is focused on quantum optics and quantum information, including proposals for quantum simulations with trapped ions and superconducting circuits. I am also interested in quantum artificial intelligence and quantum machine learning, as well as in the emulation of biological behaviours with quantum controllable systems. I enjoy working with experimentalists, and have made proposals and participated in 16 experiments in collaboration with up to 17 prominent experimental groups in quantum science.

Before Sevilla, I worked in Bilbao, at the University of the Basque Country, as a Marie Curie postdoctoral fellow and subsequently with a Ramón y Cajal position and a Staff Scientist position. Earlier, I was a Humboldt Fellow and a Max Planck postdoctoral fellow for 3 and a half years at the Max Planck Institute for Quantum Optics in Garching, Germany. Previously, I carried out my PhD at CSIC, Madrid, and Universidad Autónoma de Madrid. I have 19-year research experience in centers of Spain and Germany, having performed research as well with scientific collaborations in several one- or two-week stays in centers from all continents as Harvard University, ETH Zurich, Google/University of California Santa Barbara, Shanghai University, Tsinghua University, Macquarie University, Walther-Meissner Institut Garching, IQOQI Innsbruck, among others.

Seth Lloyd

MIT

##### Resume:

His research area is the interplay of information with complex systems, especially quantum systems. He has performed seminal work in the fields of quantum computation, quantum communication and quantum biology, including proposing the first technologically feasible design for a quantum computer, demonstrating the viability of quantum analog computation, proving quantum analogs of Shannon’s noisy channel theorem, and designing novel methods for quantum error correction and noise reduction.

##### The topic of the talk is waiting to be announced.

Cristina Masoller

Universitat Politècnica de Catalunya (UPC)

##### Resume:

Cristina Masoller is a Professor in the Physics Department at the Universitat Politecnica de Catalunya (UPC), where she teaches graduate and undergrad courses, and performs research on nonlinear dynamics, complex systems and data analysis, specifically, laser dynamics, neuronal dynamics, extreme events, rogue waves, tipping points, climate data and biomedical signals. Prior to joining UPC in 2004, she spent 18 years at the Physics Department, Faculty of Sciences, University of the Republic, Uruguay, where she was first Assistant and then Associated Professor. She is an expert in the analysis of complex systems, with more than 190 refereed publications, 1 book, 1 issued EU/US patent, 12 PhD supervised thesis and 45 invited talks. Prof. Masoller has coordinated two European Projects (ITNs LINC and BE-OPTICAL) and has been the principal investigator of Spanish and international projects. She has served on the program committee of international conferences, including CLEO-Europe, Nonlinear Optics, NetSci, CCS, Complex Networks, among others. She is a section editor of Chaos, Solitons and Fractals, topical editor of Optics Letters, editor of Scientific Reports and serves as an associate editor of the Journal of Physics Complexity. She is a fellow of Optica, the leading professional society in optics and photonics, a member of the European Physical Society (EPS) and a founding member of the Catalan complexity network, complexitat.cat. She received three ICREA Academia Awards from the Catalan Institution for Research and Advanced Studies (2010, 2016 and 2021). She holds a Ph. D. in physics from Bryn Mawr College, Pennsylvania, USA.

##### Signal processing and image classification with an array of nanolasers

Photonic artificial neural networks are causing a revolution in artificial intelligence systems because they have the potential to be much faster and more energy efficient than current silicon technology. In these big data days where data centers and high-performance computing systems consume enormous amounts of energy, energy-efficient systems are urgently needed. A most attractive candidate for photonic neural networks is a nanolaser, because nanolaser arrays are scalable and can provide high performance with ultra-low power consumption. In this talk, I will discuss a novel protocol that exploits the symmetry properties of the collective modes of an array of nanolasers, for binary image classification. Through simulation of a simple model, I will show that, under appropriate conditions, when spatially modulated pump patterns are applied to the laser array via a computer-based linear transformation of an input image, only a given class of images efficiently excites a zero mode of the array. As a proof-of-concept demonstration, we analyzed images of handwritten digits and obtained overall accuracies of 98% for one-versus-all classifiers (G. Tirabassi et al, APL Photon. 7, 090801 2022; doi: 10.1063/5.0100049).

Pankaj Mehta

Boston University

##### Resume:

I am interested in theoretical problems at the interface of physics and biology. I want to understand how large-scale, collective behaviors observed in biological systems emerge from the interaction of many individual molecular elements, and how these interactions allow cells to perform complex computations in response to environmental cues. I am also a part of the BU Bioinformatics Program and the BUMC Center for Regenerative Medicine (CReM) , and the BU Biological Design Center.

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Tomaso Poggio

McGovern Institute MIT

##### Resume:

Dr. Tomaso A. Poggio is the Eugene McDermott professor in the Department of Brain and Cognitive Sciences, an investigator at the McGovern Institute for Brain Research, a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and director of both the Center for Biological and Computational Learning at MIT and the Center for Brains, Minds, and Machina multi-institutional collaboration headquartered at the McGovern Institute since 2013.

##### The topic of the talk is waiting to be announced.

K. Birgitta Whaley

University of California (Berkeley)