A5051781797- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
- Cosmology and Gravitation Theories
- Black Holes and Theoretical Physics
- Distributed and Parallel Computing Systems
- Computational Physics and Python Applications
- Scientific Computing and Data Management
- Superconducting Materials and Applications
- Neutrino Physics Research
- Big Data Technologies and Applications
- Particle Accelerators and Free-Electron Lasers
- Atomic and Subatomic Physics Research
- Medical Imaging Techniques and Applications
- Noncommutative and Quantum Gravity Theories
- Advanced Data Storage Technologies
- Generative Adversarial Networks and Image Synthesis
- Astronomy and Astrophysical Research
- Astrophysics and Cosmic Phenomena
- Quantum Computing Algorithms and Architecture
- International Science and Diplomacy
- Cold Atom Physics and Bose-Einstein Condensates
- Nuclear reactor physics and engineering
Massachusetts Institute of Technology
2016-2025
The NSF AI Institute for Artificial Intelligence and Fundamental Interactions
2021-2024
Georgia State University
2023
National Taiwan University
2019-2023
University of Colorado Boulder
2023
Rice University
2023
Istituto Nazionale di Fisica Nucleare
2023
Moscow Institute of Thermal Technology
2019-2022
Quantum Design (United States)
2022
Center for Theoretical Biological Physics
2019-2022
We introduce a new jet substructure technique called "soft drop declustering", which recursively removes soft wide-angle radiation from jet. The algorithm depends on two parameters--a threshold $z_\text{cut}$ and an angular exponent $\beta$--with the $\beta = 0$ limit corresponding roughly to (modified) mass procedure. To gain analytic understanding of highlight $\beta$ dependence, we perform resummed calculations for three observables soft-dropped jets: energy correlation functions, groomed...
Initial state radiation, multiple interactions, and event pileup can contaminate jets degrade reconstruction. Here we introduce a procedure, jet trimming, designed to mitigate these sources of contamination in initiated by light partons. This procedure is complimentary existing methods developed for boosted heavy particles. We find that trimming achieve significant improvements reconstruction, especially at high energy/luminosity hadron colliders like the LHC.
We show how generalized energy correlation functions can be used as a powerful probe of jet substructure. These are based on the energies and pair-wise angles particles within jet, with (N+1)-point correlators sensitive to N-prong Unlike many previous substructure methods, these do not require explicit identification subjet regions. In addition, better probes certain soft collinear features that masked by other methods. present three Monte Carlo case studies illustrate utility observables:...
When ultralight axion dark matter encounters a static magnetic field, it sources an effective electric current that follows the field lines and oscillates at Compton frequency. We propose new experiment to detect this current. In presence of matter, large toroidal magnet will act like oscillating ring, whose induced flux can be measured by external pickup loop inductively coupled SQUID magnetometer. consider both resonant broadband readout circuits show approach has advantages small masses....
In this paper, we review recent theoretical progress and the latest experimental results in jet substructure from Tevatron LHC. We status of outlook for calculation simulation tools studying substructure. Following up on report Boost 2010 workshop, present a new set benchmark comparisons techniques, focusing variables grooming methods that are collectively known as 'top taggers'. To facilitate further exploration, have attempted to collect, harmonize publish software implementations these techniques.
A key question for machine learning approaches in particle physics is how to best represent and learn from collider events. As an event intrinsically a variable-length unordered set of particles, we build upon recent efforts directly sets features or "point clouds". Adapting specializing the "Deep Sets" framework physics, introduce Energy Flow Networks, which respect infrared collinear safety by construction. We also develop Particle allow general energy dependence inclusion additional...
Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these are trained on imperfect simulations due a lack of truth-level information in the data, which risks model artifacts simulation. this paper, we introduce paradigm classification without labels (CWoLa) classifier is distinguish statistical mixtures classes, common physics. Crucially, neither individual nor class proportions required, yet...
The axion is a promising dark matter candidate, which was originally proposed to solve the strong-CP problem in particle physics. To date, available parameter space for and axionlike relatively unexplored, particularly at masses m_{a}≲1 μeV. ABRACADABRA new experimental program search over broad range of masses, 10^{-12}≲m_{a}≲10^{-6} eV. ABRACADABRA-10 cm small-scale prototype future detector that could be sensitive QCD axion. In this Letter, we present first results from 1 month axions...
This report of the BOOST2012 workshop presents results four working groups that studied key aspects jet substructure. We discuss potential first-principle QCD calculations to yield a precise description substructure jets and study accuracy state-of-the-art Monte Carlo tools. Limitations experiments' ability resolve are evaluated, with focus on impact additional (pile-up) proton collisions performance in future LHC operating scenarios. A final section summarizes lessons learnt from analyses...
A bstract We introduce the energy flow polynomials: a complete set of jet substructure observables which form discrete linear basis for all infrared- and collinear-safe observables. Energy polynomials are multiparticle correlators with specific angular structures that direct consequence infrared collinear safety. establish powerful graph-theoretic representation allows us to design efficient algorithms their computation. Many common exact combinations polynomials, we demonstrate spanning...
First-principle simulations are at the heart of high-energy physics research program. They link vast data output multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range applications modern machine learning to event generation simulation-based inference, including conceptional developments driven by specific requirements particle physics. New ideas tools developed interface will improve speed precision forward simulations, handle...
Jets of hadrons produced at high-energy colliders provide experimental access to the dynamics asymptotically free quarks and gluons their confinement into hadrons. In this Letter, we show that high energies Large Hadron Collider (LHC), together with exceptional resolution its detectors, allow multipoint correlation functions energy flow operators be directly measured within jets for first time. Using Open Data from CMS experiment, reformulating jet substructure in terms these correlators...
With the vast data-collecting capabilities of current and future high-energy collider experiments, there is an increasing demand for computationally efficient simulations. Generative machine learning models enable fast event generation, yet so far these approaches are largely constrained to fixed data structures rigid detector geometries. In this paper, we introduce EPiC-GAN - equivariant point cloud generative adversarial network which can produce clouds variable multiplicity. This flexible...
Motivated by the galactic positron excess seen PAMELA and ATIC/PPB-BETS, we propose that dark matter is a TeV-scale particle annihilates into pseudoscalar ``axion.'' The absence of an antiproton or gamma ray constrain axion mass branching ratios. In simplest realization, associated with Peccei-Quinn symmetry, in which case it has around 360--800 MeV decays muons. We present simple predictive supersymmetric model implementing this scenario, where both Higgsino obtain masses from same source...
Traditional calculations in perturbative quantum chromodynamics (pQCD) are based on an order-by-order expansion the strong coupling ${\ensuremath{\alpha}}_{s}$. Observables that calculable this way known as ``safe.'' Recently, a class of unsafe observables was discovered do not have valid ${\ensuremath{\alpha}}_{s}$ but nevertheless pQCD using all-orders resummation. These called ``Sudakov safe'' since singularities at each order regulated by Sudakov form factor. In paper, we give concrete...
Dark sectors, consisting of new, light, weakly-coupled particles that do not interact with the known strong, weak, or electromagnetic forces, are a particularly compelling possibility for new physics. Nature may contain numerous dark each their own beautiful structure, distinct particles, and forces. This review summarizes physics motivation sectors exciting opportunities experimental exploration. It is summary Intensity Frontier subgroup "New, Light, Weakly-coupled Particles" Community...
We propose an inclusive search for dark photons A^{'} at the LHCb experiment based on both prompt and displaced dimuon resonances. Because couplings of photon are inherited from via kinetic mixing, A^{'}→μ^{+}μ^{-} rate can be directly inferred off-shell γ^{*}→μ^{+}μ^{-} rate, making this a fully data-driven search. For run 3 LHC, we estimate that will have sensitivity to large regions unexplored dark-photon parameter space, especially in 210-520 MeV 10-40 GeV mass ranges. This leverages...