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Prospecting for New Physics through Flavor, Dark Matter, and Machine Learning

US/Mountain
Aspen Center for Physics

Aspen Center for Physics

Aspen Center for Physics 700 West Gillespie Street Aspen, CO 81611
David Shih (Rutgers University), Mike Williams (MIT), Patrick Fox (Fermilab), Stefania Gori (UC Santa Cruz), Wolfgang Altmannshofer (UC Santa Cruz)
Description

We have entered a new and exciting decade of particle physics. The field of Beyond the Standard Model (BSM) physics has rapidly transformed into a diverse program of new physics (NP) searches, including: high-pT searches at the LHC; precision tests of the SM, especially in the Higgs and flavor sectors; searches for new light particles at high intensity experiments; and direct and indirect searches for Dark Matter across an increasingly broad range of masses and couplings.  In addition, exciting developments in the field of machine learning are inspiring new and innovative methods to search for NP across this broad program.

The goal of this Aspen Winter Conference is to bring together theorists and experimentalists, both to discuss the latest experimental results in all of these areas and their various theoretical implications, as well as to explore novel techniques for the future exploration of BSM physics, including the prospects for NP searches at the High-Luminosity LHC and future colliders. Key topics that will be covered include: results from the first run of the Belle II flavor factory; the status of the flavor anomalies; new ideas to probe Dark Matter and dark sectors; direct and indirect searches for new physics at high energy experiments; precision measurements at small scale high-intensity experiments, e.g. g-2 and rare kaon decay experiments; and machine learning in particle physics.

 

Application deadline is September 30,  2022

Please complete your application at http://www.aspenphys.org/physicists/winter/winterapps.html

This event is sponsored by  

    • 5:00 PM 7:00 PM
      Opening Welcome Reception
    • 8:00 AM 9:25 AM
      Muon g-2
    • 9:25 AM 9:45 AM
      Coffee Break 20m
    • 9:45 AM 11:00 AM
      Neutrinos
      • 9:45 AM
        BSM in the Neutrino Sector 25m
        Speaker: Pedro Machado (Fermilab)
      • 10:10 AM
        Machine Learning for Neutrinos 25m
        Speakers: Kazuhiro Terao (SLAC National Accelerator Laboratory), Kazuhiro Terao
      • 10:35 AM
        Neutrinos at the LHC 25m
        Speakers: Tao Han (University of Wisconsin), Tao Han (University of Pittsburgh)
    • 4:30 PM 4:55 PM
      Neutrinos
      • 4:30 PM
        Signatures for New Physics in Short-Baseline Liquid Argon Neutrino Experiments 25m
        Speakers: Ornella Palamara (Fermilab), Ornella Palamara (Fermilab)
    • 4:55 PM 5:45 PM
      LHC 1
    • 5:45 PM 6:15 PM
      Coffee Break 30m
    • 6:15 PM 7:30 PM
      Dark Sectors 1
      • 6:15 PM
        Dark Matter Misalignment Through the Higgs Portal 25m
        Speakers: Brian Batell (CERN), Brian Batell (Perimeter Institute), Brian Batell (University of Pittsburgh)
      • 6:40 PM
        FASER and the FPF 25m
        Speaker: Jonathan Feng (UC Irvine)
      • 7:05 PM
        Spacetime fluctuations in quantum gravity and the experiment GQuEST 25m
        Speaker: Kathryn Zurek (Berkeley Lab)
    • 8:00 AM 9:15 AM
      Dark Sectors 2
      • 8:00 AM
        Dark Sector Theory 25m
        Speaker: Maxim Pospelov (University of Minnesota)
      • 8:25 AM
        Darkquest 25m
        Speaker: Yongbin Feng (Fermilab)
      • 8:50 AM
        LDMX 25m
        Speaker: Cristina Ana Mantilla Suarez (FNAL)
    • 9:15 AM 9:45 AM
      Coffee Break 30m
    • 9:45 AM 11:25 AM
      Machine Learning 1
      • 9:45 AM
        Uncertainties in the era of ML 25m
        Speaker: Aishik Ghosh
      • 10:10 AM
        Machine Learning for Event Generation and Fast Simulation 25m

        LHC run 3 has just started and in the years leading up to 2040, we will see a 20-fold increase in available data. This forthcoming dataset will have enormous potential for a deeper understanding of the Standard Model and possible physics beyond it. At the same time, the endless possibilities of new physics hiding in this dataset pose a challenge, both for our analyses and also our simulation algorithms.
        Modern machine learning has become a standard tool in our numerical tool box. In recent years, we have not only seen applications to boost the performance of existing algorithms, but also new analysis or simulation strategies. I will highlight how advancements in modern Machine Learning, especially using invertible networks also known as normalizing flows, help speed up crucial bottlenecks in event generation and detector simulation.

        Speaker: Claudius Krause (ITP Heidelberg)
      • 10:35 AM
        Anomaly Detection 25m
        Speaker: Vinicius Massami Mikuni (Universitaet Zuerich (CH))
      • 11:00 AM
        Machine Learning for Triggering 25m
        Speaker: Javier Duarte (University of California San Diego)
    • 4:30 PM 5:45 PM
      Axion Like Particles
      • 4:30 PM
        ALP theory 25m
        Speaker: Jeff Dror (UC Santa Cruz)
      • 4:55 PM
        Hybrid Cosmological Collider of Axion 25m

        If a light axion is present during inflation and becomes part of dark matter afterwards, its quantum fluctuations contribute to dark matter isocurvature. In this article, we introduce a whole new suite of cosmological observables for axion isocurvature, which could help test the presence of axions, as well as its coupling to the inflaton and other heavy spectator fields during inflation such as the radial mode of the Peccei-Quinn field. They include correlated clock signals in the curvature and isocurvature spectra, and mixed cosmological-collider non-Gaussianities involving both curvature and isocurvature fluctuations with shapes and running unconstrained by the current data. Taking into account of the existing strong constraints on axion isocurvature fluctuations from the CMB, these novel signals could still be sizable and potentially observable. In some models, the signals, if observed, could even help us significantly narrow down the range of the inflationary Hubble scale, a crucial parameter difficult to be determined in general, independent of the tensor mode.

        Speaker: Lingfeng Li (Brown U.)
      • 5:20 PM
        ADMX 25m
        Speakers: Nick Du (Lawrence Livermore National Labs), Nick Du (University of Washington)
    • 5:45 PM 6:15 PM
      Coffee Break 30m
    • 6:15 PM 7:30 PM
      Heavy Flavor Physics 1
      • 6:15 PM
        Heavy Flavors at LHCb 25m
        Speaker: Rafael Silva Coutinho (Syracuse University)
      • 6:40 PM
        Heavy Flavors at ATLAS and CMS 25m
        Speaker: Peter Onyisi (University of Texas at Austin)
      • 7:05 PM
        Heavy Flavors Theory 25m
        Speaker: Darius Faroughy (Rutgers University)
    • 8:00 AM 9:15 AM
      Dark Matter Direct Detection
      • 8:00 AM
        Five predictions for the next five years 25m
        Speaker: Peter Sorensen (LBL)
      • 8:25 AM
        Sensors for DM Detection at the meV Scale 25m
        Speaker: Noah Kurinsky
      • 8:50 AM
        Seeing the invisible: the search for low-mass axion dark matter 25m
        Speakers: Chiara Salemi (MIT), Chiara Salemi (UNC Chapel Hill)
    • 9:15 AM 9:45 AM
      Coffee Break 30m
    • 9:45 AM 11:00 AM
      Dark Matter Indirect Detection
      • 9:45 AM
        Indirect Detection 25m
        Speaker: Rebecca Leane (SLAC)
      • 10:10 AM
        Astrophysical searches for particle dark matter using neural simulation-based inference 25m

        The complexity of astrophysical data and presence of unknowable systematics poses significant challenges to robustly characterizing signatures of dark matter in many datasets using conventional methods. I will describe how overcoming these challenges will require a qualitative shift in our approach to statistical inference, bringing together several recent advances in probabilistic machine learning, differentiable programming, and simulation-based inference. I will showcase applications of these methods to the analysis of Fermi gamma-ray data, with implications for the Galactic Center Excess, and the analysis of stellar kinematics of stars bound to dwarf galaxies, aiming to uncover the latent dark matter density profiles with implications for the nature of self-interactions in the dark sector.

        Speaker: Siddharth Mishra Sharma (New York University)
      • 10:35 AM
        Machine Learning for Particle Astrophysics 25m
        Speaker: Matthew Buckley (Fermilab)
    • 11:00 AM 11:25 AM
      LHC 1
    • 5:30 PM 6:30 PM
      Public Lecture
      • 5:30 PM
        Public Lecture: Casting a Wide Net for Dark Matter 1h
        Speaker: Tim Tait (UC Irvine)
    • 8:00 AM 9:15 AM
      Kaons
    • 9:15 AM 9:45 AM
      Coffee Break 30m
    • 9:45 AM 11:25 AM
      LHC 2 + Machine Learning 2
      • 9:45 AM
        Higgs Theory 25m
        Speakers: Carlos Wagner (Argonne National Laboratory), Carlos Wagner (University of Chicago and Argonne National Laboratory), Carlos Wagner (ANL and University of Chicago)
      • 10:10 AM
        Higgs at ATLAS and CMS 25m
        Speakers: Jacobo Konigsberg (University of Florida), jacobo konigsberg (univ of florida)
      • 10:35 AM
        Machine Learning at CMS 25m
        Speakers: Jennifer Ngadiuba (FNAL), Jennifer Ngadiuba (Caltech)
      • 11:00 AM
        Machine Learning at ATLAS 25m
        Speaker: Daniel Whiteson (UC Irvine)
    • 4:30 PM 5:20 PM
      Cosmology
      • 4:30 PM
        Cosmological Considerations for Dark Sectors with Light Mediators 25m
        Speaker: Julia (Jessie) Shelton (UIUC)
      • 4:55 PM
        Particle physics models that predict dark matter in the form of primordial black holes 25m

        Primordial black hole is a dark matter candidate in a variety of existing models of physics beyond the standard model, including supersymmetry models and models with asymmetric dark matter. I will review the formation of black holes in such scenarios, as well as the effects of predicted PBHs on astrophysics and cosmology.

        Speaker: Alexander Kusenko (UCLA)
    • 5:20 PM 5:50 PM
      Coffee Break 30m
    • 5:50 PM 7:05 PM
      Dark Sectors 3
    • 7:05 PM 8:30 PM
      Poster Session
      • 7:05 PM
        Poster: Manifesting hidden dynamics of a sub-component dark matter 5m
        Speaker: Seodong Shin (Jeonbuk National University)
      • 7:10 PM
        Poster: A Cookbook of Flavorful Modifications to the Froggatt-Nielsen Mechanism 5m
        Speaker: Katie Fraser (Harvard)
      • 7:15 PM
        Composite states in the Standard Model and beyond 5m
        Speaker: Benoit Assi (Fermilab)
      • 7:20 PM
        Poster 5m
        Speaker: Manuel Szewc (University of Cincinnati)
      • 7:25 PM
        Poster 5m
        Speaker: Elias Bernreuther (Fermilab)
      • 7:30 PM
        Poster: milliQan - A search for milli-charged particles at the LHC Run3 5m
        Speaker: Andrew Haas (NYU)
      • 7:35 PM
        Poster 5m
        Speaker: Henning Bahl
    • 8:00 AM 9:15 AM
      Heavy Flavor Physics 2
      • 8:00 AM
        Heavy Flavors at Belle II: Prospecting for New Physics with b & c quarks and tau leptons 25m
        Speaker: Michael Roney (University of Victoria)
      • 8:25 AM
        Machine Learning at LHCb 25m
        Speaker: Niklas Nolte (MIT)
      • 8:50 AM
        Precision Theory for Heavy Flavor Physics 25m
        Speaker: Mikolaj Misiak
    • 9:15 AM 9:45 AM
      Coffee Break 30m
    • 9:45 AM 11:25 AM
      LHC 3 + Snowmass