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Date:14SundayDecember 2025Lecture
The Clore Center for Biological Physics
More information Time 13:15 - 14:30Title Self-organized hyperuniformity in population dynamicsLocation Nella and Leon Benoziyo Physics LibraryLecturer Dr. Tal Agranov
Lunch at 12:45Contact Abstract Show full text abstract about Living systems often operate at critical states – poised on ...» Living systems often operate at critical states – poised on the border between two distinct dynamical behaviours, where unique functionality emerges [1]. A striking example is the ear’s sensory hair cells, which amplify faint sounds by operating on the verge of spontaneous oscillations [2]. How such finely tuned states are maintained, and what statistical signatures characterise them, remain major open questions.In this talk, I will present a generic mechanism for critical tuning in population dynamics [3]. In our model, the consumption of a shared resource drives the population towards a critical steady state characterised by prolonged individual lifetimes. Remarkably, we find that in its spatially extended form, the model exhibits hyperuniform density correlations. In contrast to previously studied hyperuniform systems, our model lacks conservation laws even arbitrarily close to criticality. Through explicit coarse-graining, we derive a hydrodynamic theory that clarifies the underlying mechanism for this striking statistical behaviour. I will highlight several biological contexts in which this mechanism is expected to operate, including biomolecular complex assembly in the developing C. elegans embryo. Here, together with experimental collaborators, we identify signatures of critical tuning that may arise from resource competition.More broadly, our framework motivates future work on how living systems harness resource-mediated interactions to regulate their dynamical states.[1] T. Mora, W. Bialek, J Stat Phys (2011)[2] S. Camalet, T. Duke, F. Jülicher and J. Prost, PNAS (1999)[3] T Agranov, N. Wiegenfeld,O. Karin and B. D. Simons arXiv:2509.08077 (2025)FOR THE LATEST UPDATES AND CONTENT ON SOFT MATTER AND BIOLOGICAL PHYSICS AT THE WEIZMANN, VISIT OUR WEBSITE: https://www.bio -
Date:14SundayDecember 202515MondayDecember 2025Conference
Symposium in honor of Rafi Malach - The Mind's Eye: A Quest from Vision to Consciousness
More information Time 14:00 - 19:00Title Symposium in honor of Rafi Malach - The Mind's Eye: A Quest from Vision to ConsciousnessLocation The David Lopatie Conference CentreChairperson Michal RamotHomepage Contact -
Date:16TuesdayDecember 2025Lecture
Recent Advances in Understanding Arenaviral Cell Entry and Immune Recognition
More information Time 11:15 - 12:15Location Gerhard M.J. Schmidt Lecture HallLecturer Prof. Ron Diskin Organizer Department of Chemical and Structural Biology -
Date:18ThursdayDecember 2025Colloquia
Physics Colloquium
More information Time 11:15 - 12:30Title The quest for the Nonlinear Breit-Wheeler Pair Production MeasurementLocation Weissman AuditoriumLecturer Dr. Noam Tal-Hod Abstract Show full text abstract about The nonlinear Breit-Wheeler process — electron-positron pair...» The nonlinear Breit-Wheeler process — electron-positron pair creation from high-energy photons in an intense electromagnetic field — is one of the most fundamental yet experimentally elusive predictions of strong-field quantum electrodynamics. Reaching the regime where this process becomes measurable requires not only extreme light-matter interaction conditions, but also detecting technologies capable of resolving rare signatures amid complex backgrounds. Beyond its intrinsic importance for testing quantum electrodynamics in the strongest fields accessible on Earth, this process is also relevant for understanding environments such as magnetars, where similarly intense fields and abundant pair production naturally occur. I will present the ongoing international effort to realize a definitive measurement of the process and highlight how advanced particle-tracking methods, commonly used in High-Energy Physics experiments, are contributing to this goal. I will discuss the running E320 experiment at SLAC, where our tracking detector is used to characterize collisions of 10 GeV electrons and 10 TW laser pulses in unprecedented detail, and give an outlook on the upcoming LUXE experiment at DESY, which aims to operate at the intensity frontier. I will also describe new opportunities at high-power multi-PW laser facilities — including our recent all-laser campaigns at ELI-NP and APOLLON — that open complementary routes to probe strong-field physics in complementary parameter spaces. Together, these efforts bring accelerator-based, laser-based and particle physics approaches closer to a definitive measurement of the nonlinear Breit-Wheeler process. -
Date:18ThursdayDecember 2025Lecture
Vision and AI
More information Time 12:15 - 13:15Title Bridging Generative Models and Physical Priors for 3D ReconstructionLocation Jacob Ziskind Building
Lecture Hall - Room 1 - אולם הרצאות חדר 1Lecturer Dor Verbin
Google DeepMindOrganizer Department of Computer Science and Applied MathematicsContact Abstract Show full text abstract about Recent years have brought remarkable progress in 3D vision p...» Recent years have brought remarkable progress in 3D vision problems like view synthesis and inverse rendering. Despite these advancements, substantial challenges remain in material and lighting decomposition, geometry estimation, and view synthesis—particularly when handling a wide range of materials. In this talk, I will outline a few of these problems and present solutions that combine the principled structure and efficiency of physics-based rendering with the strong priors encoded in generative image and video models.
Bio:
Dor Verbin is a research scientist at Google DeepMind in San Francisco, where he works on computer vision, computer graphics, and machine learning. He received his Ph.D. in computer science from Harvard University. Previously, he received a double B.Sc. in physics and in electrical engineering from Tel Aviv University, after which he worked as a researcher at Camerai, developing real-time computer vision algorithms for mobile devices. He received the Best Student Paper Honorable Mention award at CVPR 2022. -
Date:18ThursdayDecember 2025Lecture
Geometric Functional Analysis and Probability Seminar
More information Time 13:30 - 14:30Title Metric smoothnessLocation Jacob Ziskind Building
Room 155 - חדר 155Lecturer Assaf Naor
PrincetonOrganizer Department of Computer Science and Applied MathematicsContact Abstract Show full text abstract about A foremost longstanding open problem in the Ribe program is ...» A foremost longstanding open problem in the Ribe program is to find a purely metric reformulation of the Banach space property of having an equivalent norm whose modulus of uniform smoothness has a given power type. In this talk we will present a solution of this problem. All of the relevant background and concepts will be explained, and no prerequisites will be assumed beyond rudimentary undergraduate functional analysis and probability. Based on joint work with Alexandros Eskenazis. -
Date:21SundayDecember 202522MondayDecember 2025Academic Events
Hanukkah STAR - workshop 2025
More information Time All dayLocation Jacob Ziskind Building
Room 1Homepage -
Date:22MondayDecember 2025Lecture
Seminar for PhD thesis Defense by Yahel Cohen
More information Time 11:00 - 12:00Title “miRNA isoforms as biomarkers for amyotrophic lateral sclerosis prognosis”Location Benoziyo Biochemistry auditorium room 191c-new -
Date:22MondayDecember 2025Lecture
Foundations of Computer Science Seminar
More information Time 11:15 - 12:15Title Corners and Communication ComplexityLocation Jacob Ziskind Building
Lecture Hall - Room 1 - אולם הרצאות חדר 1Lecturer Shachar Lovett
UCSDOrganizer Department of Computer Science and Applied MathematicsContact Abstract Show full text abstract about The corners problem is a classical problem in additive combi...» The corners problem is a classical problem in additive combinatorics. A corner is a triple of points (x,y), (x+d,y), (x,y+d). It can be viewed as a 2-dimensional analog of a (one-dimensional) 3-term arithmetic progression. An old question of Ajtai and Szemeredi is: how many points can there be in the n x n integer grid without containing a corner? They proved a qualitative bound of o(n^2), but no effective quantitative bounds.
This question has an equivalent description in the language of communication complexity. Given 3 players with inputs x,y,z which are integers in the range 1 to n, what is the most efficient Number-On-Forehead (NOF) deterministic protocol to check if they sum to n. This connection was first observed in the seminal paper of Chandra, Furst and Lipton that introduced the NOF model back in 1983.
In the language of communication complexity, the trivial protocol sends log(n) bits, but there is a better NOF protocol (based on constructions in additive combinatorics) which only sends (log n)^{1/2} bits. However, the best lower bound until our work was double exponentially far off - of the order of log log log n. In this work, we close this gap, and prove a lower bound of (log n)^c for some absolute constant c.
The work is based on combining the high-level approach of Shkredov, who obtained the previous lower bound, which was based on Fourier analysis; with the recent breakthrough of Kelley and Meka on the 3-term arithmetic progression problem, and the ensuing developments. The main message is that "spreadness" based techniques (a notion that I will explain in the talk) give significantly better quantitative bounds compared to classical Fourier analysis.
Joint work with Michael Jaber, Yang P. Liu, Anthony Ostuni and Mehtaab Sawhney
Paper will appear in FOCS 2025
https://arxiv.org/abs/2504.07006 -
Date:23TuesdayDecember 2025Lecture
Climate modeling in the era of AI
More information Time 11:30 - 12:30Location Gerhard M.J. Schmidt Lecture HallLecturer Laure Zanna Organizer Department of Earth and Planetary SciencesAbstract Show full text abstract about While AI has been disrupting conventional weatherforecasting...» While AI has been disrupting conventional weatherforecasting, we are only beginning to witness theimpact of AI on long-term climate simulations. Thefidelity and reliability of climate models have beenlimited by computing capabilities. These limitationslead to inaccurate representations of key processessuch as convection, cloud, or mixing or restrict theensemble size of climate predictions. Therefore, theseissues are a significant hurdle in enhancing climatesimulations and their predictions.Here, I will discuss a new generation of climatemodels with AI representations of unresolved oceanphysics, learned from high-fidelity simulations, andtheir impact on reducing biases in climatesimulations. The simulations are performed withoperational ocean model components. I will furtherdemonstrate the potential of AI to accelerate climatepredictions and increase their reliability through thegeneration of fully AI-driven emulators, which canreproduce decades of climate model output in secondswith high accuracy -
Date:24WednesdayDecember 2025Lecture
2025-2026 Spotlight on Science Seminar Series - Dr. Jacques Pienaar (Department of Physics Core Facilities)
More information Time 12:30 - 14:00Title Illuminating the Dark: The Search for Dark MatterLocation Gerhard M.J. Schmidt Lecture HallLecturer Jacques Pienaar Contact Abstract Show full text abstract about Cosmological observations suggest that about 85% of the univ...» Cosmological observations suggest that about 85% of the universe’s mass is made up of matter that neither emits nor absorbs light. The existence of this mysterious component—dark matter—is inferred from its gravitational effects and is theorized to interact only very weakly with ordinary matter. The XENON detector, located deep underground in Italy’s Gran Sasso Laboratory, employs a large reservoir of ultrapure liquid xenon to search for the faint signals produced when a dark matter particle collides with a xenon atom. By suppressing background radiation and using highly sensitive sensors, the experiment strives to observe these extremely rare events. Although dark matter remains undetected, XENON continues to search while also shaping future searches. -
Date:25ThursdayDecember 2025Lecture
Geometric Functional Analysis and Probability Seminar
More information Time 13:30 - 14:30Title TBDLocation Jacob Ziskind Building
Room 155 - חדר 155Lecturer Yeor Hafouta
FloridaOrganizer Faculty of Mathematics and Computer ScienceContact -
Date:25ThursdayDecember 2025Lecture
Apoptotic Pathways as Molecular Switches of Tumor Initiation and Reversion
More information Time 14:00 - 15:00Location Candiotty
AuditoriumLecturer Prof. Sarit Larisch Organizer Dwek Institute for Cancer Therapy Research -
Date:25ThursdayDecember 2025Lecture
Tracking the emergence of intentions in the human motor cortex- evidence from intracranial neuronal recordings
More information Time 14:00 - 15:00Location Gerhard M.J. Schmidt Lecture HallLecturer Uri Maoz, PhD Organizer Department of Brain SciencesContact Abstract Show full text abstract about Abstract: How voluntary, self-paced intentions emerge in the...» Abstract: How voluntary, self-paced intentions emerge in the brain and translate into action remains one of the most fundamental open questions in neuroscience. Leveraging rare access to intracranial neuronal recordings from human motor cortex, we built a real-time, online closed-loop system that allowed us to study the formation of voluntary actions under competitive conditions.We show that participants have only limited capacity to voluntarily steer their motor-cortex activity when doing so is strategically advantageous-revealing tight constraints on intentional control at the neural population level. Yet the commitment to act can be decoded reliably from motor-cortex activity roughly 250 ms before movement onset, at a time point when participants report already being consciously aware of their decision. We also find that brain–computer interfaces trained in one cognitive context transfer seamlessly to another, despite substantial differences in neural trajectories and force profiles-suggesting a shared underlying representational structure for volitional actions in motor cortex.Offline analyses further uncovered the specific neural patterns that signal commitment to action, shedding new light on how early voluntary actions can be reliably predicted from motor-cortex activity. We will conclude by discussing how these and related results inform emerging efforts to track and interpret intentions in advanced AI systems (ai-intentions.org). -
Date:28SundayDecember 2025Academic Events
Scientific Council Meeting
More information Time 09:38 - 10:38Title PhD hcהנשיא - בהשתתפות Ceremony for new members of the SC + Council of Prof.Location The David Lopatie Conference Centre
KIMELContact -
Date:28SundayDecember 2025Lecture
The Clore Center for Biological Physics
More information Time 13:15 - 14:30Title Anticipatory and Responsive Regulation of Blood Glucose LevelsLocation Nella and Leon Benoziyo Physics LibraryLecturer Dr. Danny Ben-Zvi
Lunch at 12:45Contact Abstract Show full text abstract about Glucose can enter the blood following a meal, and/or can be ...» Glucose can enter the blood following a meal, and/or can be produced by the liver and kidneys at times of need such as fasting. An elevation in blood glucose beyond steady state levels leads to secretion of the hormone insulin, leading to increase in glucose uptake into muscle and adipose tissues. Diabetes Mellitus arises when insufficient levels of insulin are secreted into the blood, manifesting as a chronic elevation in blood glucose levels. A reduction in glucose levels can lead to secretion of a large number of hormones, such as glucagon, cortisol and adrenaline, which cause endogenous glucose production and secretion into the blood, maintaining homeostasis of glucose levels. In this talk we will use mathematical modeling and biochemical measurements to study the dynamics of hormone secretion in healthy individuals and Diabetes patients, and (hopefully) provide an answer to a key question: does the "body" measure glucose levels and regulates glucose levels accordingly by secreting insulin/glucose, as expected by a standard negative feedback system, or does it estimate future glucose levels and secretes hormones/glucose in a feedforward mechanism?Students interested in meeting the speaker after the seminar may sign up here:LINKFOR THE LATEST UPDATES AND CONTENT ON SOFT MATTER AND BIOLOGICAL PHYSICS AT THE WEIZMANN, VISIT OUR WEBSITE: https://www.bio -
Date:29MondayDecember 2025Lecture
PhD Defense Seminar- Ofir Kuperman
More information Time 10:00 - 11:00Title Deciphering Sugar Uptake, Transport and Incorporation Mechanisms by Plant Tissues in the Context of Material FarmingLocation Nella and Leon Benoziyo Building for Plant and Environmental Sciences
691Contact -
Date:30TuesdayDecember 2025Lecture
iSCAR Seminar
More information Time 09:00 - 10:00Title Wicked Lymphatics Shape the Epigenetic Landscape of Epithelial Stem Cell PlasticityLocation Max and Lillian Candiotty Building
AuditoriumLecturer Dr. Shiri Gur-Cohen Organizer Department of Immunology and Regenerative BiologyContact -
Date:30TuesdayDecember 2025Lecture
Chemical Evolution: How Can Chemistry Invent Biology?
More information Time 11:15 - 12:15Location Gerhard M.J. Schmidt Lecture HallLecturer Dr. Moran Frenkel-Pinter Organizer Department of Chemical and Structural Biology -
Date:30TuesdayDecember 2025Lecture
Vision and AI
More information Time 11:15 - 12:15Title Efficient representations for dense reasoning with long videosLocation Jacob Ziskind Building
Room 155 - חדר 155Lecturer Greg Shakhnarovich
TTI-COrganizer Department of Computer Science and Applied MathematicsContact Abstract Show full text abstract about In some video understanding scenarios, it is important to ca...» In some video understanding scenarios, it is important to capture details that exist at fine temporal resolution, over a significant length of context (hundreds, thousands and even tens of thousands of frames). This poses a computational challenge for many existing video encoders. I will discuss our recent efforts on developing models for video representation that address this challenge in two ways, each with a different kind of video task in mind. In our work on sign language understanding we extract information from each video frame in a highly selective way, and train the long context encoder from a large video corpus without any labels. The resulting video model, SHuBERT, is a "foundation model" for American Sign Language achieving state of the art performance on multiple sign language understanding tasks. In another, ongoing effort, we focus on the task of nonlinear movie editing, and develop an autoregressive model that relies on a highly compressed representation of video frames. This model, trained on an unlabeled corpus of movies, yields state of the art results on complex movie editing tasks and on editing-related video understanding benchmarks.
