Abstract:
\r\nOlfactory navigation emerges from dynamic interactions among sensory input, brain activity, and the animal’s own movements. In C. elegans, a compact nervous system enables brain-wide imaging in behaving animals exposed to controlled olfactory environments, and undulatory locomotion reduces navigation to transitions among forward runs, reversals, and turns. Here, we used brain-wide tracking microscopy to record neural activity in freely crawling worms navigating spatial odor gradients or isotropic environments, and in immobilized worms responding to temporal odor pulses. Across conditions, we identified strongly correlated brain-wide activity patterns spanning olfactory sensory neurons, interneurons, and premotor neurons. Motor-state transitions and brain-wide correlation structure differed between freely moving and immobilized animals, demonstrating that olfactory sensory representations depend jointly on sensory input, motor activity, and behavioral context. Together, these findings show that brain-wide representations of olfactory behavior are extensively reconfigured by sensory input, self-motion, and behavioral context.
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Thesis Director: Prof. B. E. Ferreira De Sousa Correia,
\r\nChemistry and Chemical Engineering doctoral program
\r\nThesis Nr. 11408
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\r\nTo take part in the public defense, please contact directly the speaker
Thesis Director: Prof. W. Gerstner,
\r\nNeuroscience doctoral program
\r\nThesis Nr. 11158
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\r\nTo take part in the public defense, please contact directly the speaker
Current research indicates that the role of generative AI in education is a double-edged sword: on one hand it can assist teachers for designing effective learning tasks and resources, on the other hand it can have negative effects on student learning and raises a range of ethical questions.
\r\nIn our new workshop series “Responsible AI skills for education” we will try to navigate these questions by focusing on specific teaching and learning activities and identifying practical skills you can develop for your everyday practice. Through a blend of concise theoretical input and hands-on activities, we will explore both the benefits and the risks of generative AI in education in short 1-hour sessions on campus. The first two workshops in the series focus on quiz design and critical analysis skills.
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\r\nEffective quiz design:
\r\nIn this 1-hour workshop, we will focus on the design of effective quiz questions for your class with the assistance of LLM tools. We will explore both the ethical and practical questions associated with LLM use for this task through theoretical inputs and hands-on activities.
Current research indicates that the role of generative AI in education is a double-edged sword: on one hand it can assist teachers for designing effective learning tasks and resources, on the other hand it can have negative effects on student learning and raises a range of ethical questions.
\r\nIn our new workshop series “Responsible AI skills for education” we will try to navigate these questions by focusing on specific teaching and learning activities and identifying practical skills you can develop for your everyday practice. Through a blend of concise theoretical input and hands-on activities, we will explore both the benefits and the risks of generative AI in education in short 1-hour sessions on campus. The first two workshops in the series focus on quiz design and critical analysis skills.
\r\n
\r\nTeaching critical analysis:
\r\nIn this 1-hour workshop, we will focus on how to help students develop critical analysis skills for reviewing LLM outputs in the context of learning tasks. The workshop will combine theoretical inputs and hands-on activities, drawing on your disciplinary expertise and fact-checking strategies.
\r\n
Current research indicates that the role of generative AI in education is a double-edged sword: on one hand it can assist teachers for designing effective learning tasks and resources, on the other hand it can have negative effects on student learning and raises a range of ethical questions.
\r\nIn our new workshop series “Responsible AI skills for education” we will try to navigate these questions by focusing on specific teaching and learning activities and identifying practical skills you can develop for your everyday practice. Through a blend of concise theoretical input and hands-on activities, we will explore both the benefits and the risks of generative AI in education in short 1-hour sessions on campus. The first two workshops in the series focus on quiz design and critical analysis skills.
\r\n
\r\nEffective quiz design:
\r\nIn this 1-hour workshop, we will focus on the design of effective quiz questions for your class with the assistance of LLM tools. We will explore both the ethical and practical questions associated with LLM use for this task through theoretical inputs and hands-on activities.
\r\n
Please join us for the Junior Quantum Seminar with Gaia Bolognini from the Laboratory for Quantum Gases (LQG), IPHYS, EPFL who will give the talk \"Density Wave Ordering in Strongly Interacting Fermi Gases\" and Emanuele Tirrito from the Laboratory of Theoretical Physics of Nanosystems (LTPN), IPHYS, EPFL who will give the talk \"Quantum Complexity in Many-Body Systems: From Entanglement to Magic\" on Tuesday June 2nd from 9h30-11h.
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\r\nPLEASE NOTE: The Junior Quantum Series are for gathering the junior quantum community of master's students, PhDs and post-docs at EPFL, to create a non-judgmental space were scientific ideas can be shared between peers. This event is not for Professors or senior researchers.
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\r\nABTRACT:
\r\n1. Density Wave Ordering in Strongly Interacting Fermi Gases
\r\nAnalog quantum simulations using ultracold atoms offer exciting opportunities to investigate many-body systems in highly controllable and tunable settings. While most studies have focused on simulation of systems with short-range interactions, their interplay with long-range interactions remains largely unexplored.
\r\nIn our experimental platform, the atomic ensemble is strongly coupled to a high finesse optical resonator, whose photons mediate an effective long-range interaction among the particles. Upon reaching a critical long-range interaction strength, the system undergoes a phase transition into a density wave ordered state, characterized by the superradiant build-up of the cavity field and the atomic self-organisation into a crystalline lattice. While this phenomenon has been extensively studied in bosonic quantum gases, we explore the effect of this transition in a degenerate two-component Fermi gas with tunable short-range interactions.
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\r\nI will present our recent experimental results, where high-resolution microscopy yields the first real-space observation of the periodic density modulation characterizing the density-wave ordered state. Moreover, the micrometer-scale resolution gives access to high-frequency spatial correlations of the gas in both the density and magnetization observables, and enables precise shaping of the trapping potential - significantly expanding the degree of control over the many-body state.
\r\nWe make use of this versatile platform to explore the interplay between the cavity field and the atomic ordering and to investigate how the many-body state of the paired Fermi gas is reshaped by the cavity mediated long-range interactions.
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\r\n2. Quantum Complexity in Many-Body Systems: From Entanglement to Magic
\r\nUnderstanding what makes a quantum many-body state complex is a central question in quantum information, quantum computation, and condensed matter physics. Traditionally, entanglement has played a central role in this discussion: it captures genuinely quantum correlations, constrains classical simulability, and provides a powerful diagnostic of phases of matter and out-of-equilibrium dynamics. However, entanglement alone does not fully characterize the computational complexity of quantum states. In particular, highly entangled states can sometimes be efficiently simulated, while universal quantum computation requires an additional resource known as magic, or non-stabilizerness.
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\r\nIn this talk, I will give a broad introduction to quantum complexity in many-body systems, focusing on the complementary roles of entanglement and magic. I will explain the physical meaning of magic, its connection to stabilizer states and Clifford circuits, and why it is necessary for quantum computational advantage. I will then discuss how magic can be generated and diagnosed in many-body dynamics, and how it provides new insight into questions such as thermalization, quantum chaos, transport, and classical simulability.
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\r\nBIO:
\r\nGaia Bolognini is currently a third year PhD student in the Laboratory for Quantum Gases (LQG) at EPFL under the supervision of professor Jean-Philippe Brantut. Her research focuses on atomic interacting matter, quantum gases and cavity quantum electrodynamics. She obtained her Master's degree at EPFL, where she focused on the assembly and the design of a new technology for quantum gas experiments, the 'cavity-microscope'. She obtained her Bachelor's degree at University of Milano-Bicocca, in my hometown.
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\r\nEmanuele Tirrito obtained his Master’s degree in Physics from the University of Pisa, working on relaxation and prethermalization in one-dimensional quantum systems. He then completed his PhD at ICFO in Barcelona, where he studied topological phases of matter and developed tensor-network methods for strongly correlated systems. After postdoctoral positions at SISSA, the University of Trento, and ICTP, his research has progressively moved toward quantum information aspects of many-body physics, with a particular focus on entanglement, non-stabilizerness or “magic”, measurement-induced transitions, and quantum simulation. He is currently an SNSF Postdoctoral Fellow at EPFL.
\r\n
Current research indicates that the role of generative AI in education is a double-edged sword: on one hand it can assist teachers for designing effective learning tasks and resources, on the other hand it can have negative effects on student learning and raises a range of ethical questions.
\r\nIn our new workshop series “Responsible AI skills for education” we will try to navigate these questions by focusing on specific teaching and learning activities and identifying practical skills you can develop for your everyday practice. Through a blend of concise theoretical input and hands-on activities, we will explore both the benefits and the risks of generative AI in education in short 1-hour sessions on campus. The first two workshops in the series focus on quiz design and critical analysis skills.
\r\n
\r\nTeaching critical analysis:
\r\nIn this 1-hour workshop, we will focus on how to help students develop critical analysis skills for reviewing LLM outputs in the context of learning tasks. The workshop will combine theoretical inputs and hands-on activities, drawing on your disciplinary expertise and fact-checking strategies.
\r\n