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Science Week - 2019

Canada/Pacific
Auditorium (TRIUMF)

Auditorium

TRIUMF

4004 Wesbrook Mall
Description

SCIENCE WEEK – 2019

Registration Was closed on Thursday for Catering counts

 

TRIUMF's Science Week 2019 will be held from August 19-23.

This year's program features a summer school for IAMI, a workshop to discuss the first science of the ARIEL era with CANREB, a symposium celebrating 20 years of ISAC science, the TRIUMF Users’ Group (TUG) Annual General Meeting, and a data science and quantum computing workshop. Science Week is a wonderful opportunity for the whole TRIUMF community to come together, exchange ideas, and learn about the multidisciplinary program of the lab.

 

Please join us at TRIUMF for a week of activities highlighting our exciting science – past, present, and future!

Should you wish to attend these events the cost to attend for regular participants is $40 for all events, but an a la carte registration is available at a cost of $10 per meeting.

Graduate and Undergraduate Students may attend these same meetings at a cost of $20 for all meetings or an a la carte option of $10 per meeting is also available.

Please go to:

http://mis.triumf.ca/events/event.jsf?confcode=SW2019

Registration for the BBQ on Wednesday, August 21 after the ISAC20 Symposium event is incuded in registration, we require you to sign up for catering numbers.

    • IAMI Summer School: Welcome and IAMI introduction Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Dr Cornelia Hoehr (TRIUMF)
    • IAMI Summer School: Radiochemsitry 101 - Introduction to Nuclear Medicine Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Prof. Caterina Ramogida
    • IAMI Summer School: From target to tracer Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Dr Valery Radchenko (TRIUMF)
    • IAMI Summer School: Radiotherapy - different treatments Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Dr Cornelia Hoehr (TRIUMF)
    • 10:30 AM
      Coffee Break
    • IAMI Summer School: Cyclotron production of Ga-68 and Zr-89 using pressed targets Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Prof. Brigitte Guerin
    • IAMI Summer School: Targeted radionuclide therapy for cancer and infections Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Prof. Kate Dadachova
    • 12:30 PM
      Lunch
    • IAMI Summer School: Hands on Lab Session and Outreach Workshop (Students only) Radiochemistry labs

      Radiochemistry labs

      TRIUMF

      Conveners: Prof. Caterina Ramogida, Dr Valery Radchenko (TRIUMF)
    • IAMI Summer School: Outreach computing session - bring your own laptop Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Prof. Christian Diget
    • 3:30 PM
      Coffee Break
    • IAMI Summer School: Hands on Lab Session and Outreach Workshop (Students only) Radiochemistry labs

      Radiochemistry labs

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Prof. Caterina Ramogida, Dr Valery Radchenko (TRIUMF)
    • IAMI Summer School: Outreach computing session - bring your own laptop Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Prof. Christian Diget
    • 10:20 AM
      Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • 12:30 PM
      Lunch Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • 3:40 PM
      Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • ISAC20 Symposium: Session 1: co-chair Gordon Ball/Rick Baartman Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Gordon Ball (TRIUMF)
      • 1
        Welcome
        Speaker: Dr Jonathan Bagger (TRIUMF)
      • 2
        Introduction
        Speaker: Dr Gordon Ball (TRIUMF)
        group photo
        Slides
        Video
      • 3
        ISAC RIB Production Systems and target development
        Speaker: Dr Pierre Bricault
        Slides
      • 4
        ISAC Source Development
        Speaker: Dr Jens Lassen (TRIUMF)
      • 5
        ISAC Linear Accelerators
        Speaker: Robert Laxdal (TRIUMF)
        Slides
      • 6
        Application of ISAC facility for production of medical radionuclides: past, present and future perspectives
        Speaker: Dr Valery Radchenko (TRIUMF)
        Slides
    • 10:05 AM
      Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • ISAC20 Symposium: Session 2: co-chair Kyle Leach/Alan Shotter Auditorium

      Auditorium

      TRIUMF

      Convener: Gordon Ball (TRIUMF)
      • 7
        Angular correlation measurements at ISAC: using the atomic nucleus to search for BSM physics for 20 yrs
        Speaker: Prof. Dan Melconian
        Slides
      • 8
        Superallowed Fermi Beta Decay: Two decades of fundamental research at ISAC
        Speaker: Prof. Gwen Grinyer (University of Regina)
        Slides
      • 9
        Early Days of beta-NMR at TRIUMF
        Speaker: Prof. Rob Kiefl (TRIUMF and UBC)
        Slides
      • 10
        ISAC’s continuing mission to explore the stars
        Speaker: Prof. Alison Laird (York University)
        Slides
      • 11
        Twenty+ years of ab initio nuclear theory
        Speaker: Dr Petr Navratil (TRIUMF)
        Slides
    • 12:30 PM
      Lunch Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • ISAC20 Symposium: Session 3: co-chair Corina Andreoiu/Andrew MacFarlane Auditorium

      Auditorium

      TRIUMF

      Convener: Gordon Ball
      • 12
        Unmasking nuclear halo features with two decades of ISOL beams at TRIUMF
        Speaker: Prof. Rituparna Kanungo (Saint Mary's University)
        Slides
      • 13
        Nuclear shapes, coexistence and collective behaviors studied at ISAC
        Speaker: Dr Adam Garnsworthy (TRIUMF)
        Slides
      • 14
        Indirect studies of astrophysics around the Coulomb barrier
        Speaker: Dr Barry Davids (TRIUMF)
        Slides
      • 15
        From structural distortions to weak magnetism - exploring the capabilities of beta-NMR
        Speaker: Dr Zaher Salman
        Slides
    • 3:15 PM
      Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • ISAC20 Symposium: Session 4: co-chair Greg Hackman/Dennis Muecher Auditorium

      Auditorium

      TRIUMF

      Convener: Gordon Ball (TRIUMF)
      • 16
        Pushing the limits: Towards the neutron drip line with ISAC
        Speaker: Dr Iris Dillmann (TRIUMF)
        Slides
      • 17
        The Emergence of nuclear-shell-model studies at ISAC
        Speaker: Dr Anna Kwiatkowski (TRIUMF)
        Slides
      • 18
        Francium: Uranium and hydrogen baked into one
        Speaker: Prof. Gerald Gwinner (University of Manitoba)
        Slides
      • 19
        Advances in beta-NMR @ ISAC
        Speaker: Dr Sarah Dunsiger (TRIUMF)
        Slides
      • 20
        Symposium Summary
        Speaker: Prof. Alan Shotter
        Slides
        Video
    • BBQ (time to be confirmed)
      Convener: Prof. Reiner Kruecken (TRIUMF)
    • TUG AGM: Introduction and Welcome Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Caterina Ramogida, Prof. Gwen Grinyer (University of Regina)
      • 21
        Welcome
        Speaker: Dr Jonathan Bagger (TRIUMF)
      • 22
        Introduction
        Speaker: Dr Anna Kwiatkowski (TRIUMF)
        Slides
      • 23
        Physical Sciences Division Report
        Speaker: Prof. Jens Dilling (TRIUMF)
        Slides
      • 24
        Life Sciences Division Report
        Speaker: Dr Cornelia Hoehr (TRIUMF)
      • 25
        Accelerator Division Report
        Speaker: Dr Oliver Kester (TRIUMF)
        Slides
      • 26
        Update to TRIUMF Governance
        Speaker: Dr Jonathan Bagger (TRIUMF)
      • 27
        Update to TRIUMF Org Chart
        Speaker: Anne Louise Aboud (TRIUMF)
    • 10:30 AM
      Coffee Break
    • TUG AGM Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Caterina Ramogida, Prof. Gwen Grinyer (University of Regina)
      • 28
        TRIUMF Users Office
        Speaker: Dr Marcello Pavan (TRIUMF)
        Slides
      • 29
        Beam time planning for 2020
        Speaker: Prof. Reiner Kruecken (TRIUMF)
        Slides
      • 30
        Q&A with TRIUMF Management
    • 12:30 PM
      Lunch
    • TUG AGM Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Caterina Ramogida, Prof. Gwen Grinyer (University of Regina)
      • 31
        New electron gun for the TITAN-EBIT (Student Prize Talk)
        Speaker: Kilian Dietrich (TRIUMF)
      • 32
        TUG Poster Slam!
    • 3:15 PM
      Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • TUG AGM Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Caterina Ramogida, Prof. Gwen Grinyer (University of Regina)
      • 33
        Ab initio predictions of light nuclei
        Speaker: Dr Anna McCoy
      • 34
        Range Verification in Proton Therapy using a Tumor Marker and Gamma Ray Spectroscopy
        Speaker: Prof. Dennis Muecher
      • 35
        Current-Induced Non-Magnetic State in Mott Insulator Ca2RuO4
        Speaker: Prof. Graeme Luke
      • 36
        ALPHA, the Trapped Antihydrogen Experiment: Status and Prospects
        Speaker: Dr Andrea Capra
        Slides
      • 37
        TUG News and Information
        Speaker: Prof. Gwen Grinyer (University of Regina)
        Slides
      • 38
        Student Prize Announcements
    • Data Science and Quantum Computing Workshop: Hands-on Session: Machine Learning Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Dr Wojciech Fedorko (TRIUMF)
      slides
    • 10:30 AM
      Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • Data Science and Quantum Computing Workshop: Hands-on Session: Quantum Computing Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Convener: Dr Olivia Di Matteo (TRIUMF)
      slides
      • 40
        Hands-on Session: Developing Quantum Applications in Q#
        In this workshop, participants will learn to use the Quantum Development Kit and the Q# programming language to develop quantum applications and test them using simulators. The workshop consists of a short lecture and a series of hands-on exercises, covering a wide variety of tasks and concepts. No prior software installation needed to participate, all materials are available online.
        Speaker: Dr Christopher Granade (Microsoft)
    • 12:30 PM
      Lunch
    • Data Science and Quantum Computing Workshop Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Dr Olivia Di Matteo (TRIUMF), Dr Wojciech Fedorko (TRIUMF)
      slides
      • 41
        Deep Learning Applications to Medical Imaging
        Medical imaging has revolutionized medicine. Now medical imaging itself is witnessing a deep learning revolution. Clinically-relevant medical image interpretation tasks (e.g. image segmentation and image classification) have been re-formulated under a deep learning framework with impressive results. These early successes have been attributed to three factors: data, learning algorithms, and fast computation. I will present examples of deep learning applications to medical imaging from our research group highlighting the versatility, opportunities, and challenges in this area (website: www.MedicalImageAnalysis.com).
        Speaker: Dr Ghassan Hamarneh
        Slides
      • 42
        Quantum Variational Autoencoders and their applications
        Generative models are among the most promising approaches toward understanding unlabelled data. They have a wide range of applications in structured prediction, molecular & material design, image analysis, speech synthesis, and computer vision. They pair with supervised learning models to help perform ML tasks when labelling data is expensive or labels are only available in a different domain. Quantum Boltzmann machine is a powerful generative model that can naturally be implemented on a quantum annealing device. However, the development of quantum-classical hybrid (QCH) algorithms is critical to deploy state-of-the-art computational models on current commercially available devices. A Quantum Variational Autoencoder (QVAE) is one such hybrid algorithm that consists of a latent generative process, formalized as a quantum or classical Boltzmann machine (QBM or BM). A quantum annealing processor is used for sampling from the Boltzmann prior distribution. The classical autoencoding structure is realized by a deep neural network, which allows inference to and generating samples from, the latent space. We have successfully employed D-Wave quantum annealers as Boltzmann samplers to train end-to-end QVAE. The hybrid structure of QVAE allows us to deploy current quantum annealing devices in a QCH generative model with latent variables that achieves competitive performance on datasets such as MNIST.
        Speaker: Dr Hossein Sadeghi (D-Wave)
      • 43
        Enhancing quantum simulators with neural networks
        The recent advances in qubit manufacturing and coherent control of synthetic quantum matter are leading to a new generation of intermediate scale quantum hardware, with promising progress towards scalable simulation of quantum matter and materials. In order to enhance the capabilities of this class of quantum devices, some of the more arduous experimental tasks can be off-loaded to classical algorithms running on conventional computers. In this talk, I will present recent efforts in deploying machine learning algorithms on data generated by quantum simulators, and show how neural networks can be trained to detect quantum phase transitions and reconstruct experimental wavefunctions.
        Speaker: Dr Giacomo Torlai (Flatiron Institute)
      • 44
        Quantum Algorithms for Solving Dynamic Programming Problems
        We introduce quantum algorithms for solving finite-horizon and infinite-horizon dynamic programming problems. We visit the query complexity lower bounds for classical randomized algorithms for the same tasks and consequently demonstrate a polynomial separation between the query complexity of our quantum algorithms and best-case query complexity of classical randomized algorithms. Up to polylogarithmic factors, our quantum algorithms provide quadratic advantage in terms of the numbers of states and actions in the dynamic programming problem. Nevertheless, the speed-up achieved is at the expense of appearance of other polynomial factors in the scaling of the algorithm which contribute to the precision of the solution. Our framework pertains to discrete and combinatorial optimization problems solved classically using dynamic programming techniques. As an example, we show how quantum computers can solve the travelling salesperson problem quadratically faster than the Bellman–Held–Karp algorithm does.
        Speaker: Dr Pooya Ronagh (1QBit, IQC, UW)
    • Coffee Break Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
    • Data Science and Quantum Computing Workshop Auditorium

      Auditorium

      TRIUMF

      4004 Wesbrook Mall
      Conveners: Dr Olivia Di Matteo (TRIUMF), Dr Wojciech Fedorko (TRIUMF)
      slides
      • 45
        Projects at TRIUMF
        A foreword on Machine Learning projects started at TRIUMF
        Speaker: Dr Wojciech Fedorko (TRIUMF)
        Slides
      • 46
        Variational AutoEncoders (VAEs) for water Cherenkov detectors
        A Variational AutoEncoder (VAE) is a generative method used to approximate the probability distribution of processes in very high dimensional spaces. We apply VAEs for generative modelling of Water Cherenkov detectors which are used to perform precision measurements on neutrinos. In this talk, I will discuss the steps and challenges in applying VAEs to simulated neutrino events in the proposed Intermediate Water Cherenkov Detector (IWCD). Initial results from the project show promise in the application of VAEs for synthetic data generation and unsupervised learning from labelled and unlabelled datasets.
        Speaker: Mr Abhishek Kajal (TRIUMF/University of Manitoba)
      • 47
        Extrapolating Nuclear Many-Body Calculations with Constrained Gaussian Processes
        The properties of nuclei can be computed from first principles starting from realistic interactions between nucleons. Using suitable basis functions, the many-body wavefunction is found by diagonalizing a Hamiltonian matrix (i.e. solving the Schrödinger equation). Due to limited computational resources only a finite basis size can be used. This is frequently insufficient for complete convergence. The "true value" of a calculated quantity (e.g. ground state energy) is predicted by extrapolating to infinite basis size. The functional form of such an extrapolation is unknown but by the variational principle the signs of the derivatives are known. In this work we use knowledge of monotonicity and convexity to constrain a Gaussian Process (GP) model and predict ground state energies. A GP is a machine learning tool which generates a distribution of viable functions which satisfy known data points. It is easy to compute and automatically produces uncertainties on predictions. However, applying derivative constraints is not simple and requires iteratively tightening the constraints and improving the GP model via Sequential Monte Carlo. This novel method shows promise in providing more meaningful confidence intervals on theoretical predictions than existing methods, allowing a more useful comparison to experiment.
        Speaker: Mr Peter Gysbers
      • 48
        Expressive Structured Representations in Deep Generative Models
        Deep generative models, such as variational autoencoders and generative adversarial networks, are among the most exciting recent developments in machine learning. Variational autoencoders, in particular, have seen a tremendous rise in popularity due to their principled variational framework and powerful neural approximations to previously infeasible inference tasks, including marginal and posterior inference with arbitrary distributions. Their applications comprise a broad range of topics in computer science, such as image and video synthesis, temporal forecasting, and feature learning. In this talk, we first revisit the basic principles of variational autoencoders with a focus on the underlying implicit modeling assumptions. Using these insights, we identify their representational limitations and reinterpret them from the viewpoint of probabilistic graphical models. Finally, we discuss a structure learning approach that overcomes these limitations through an explicit and dynamic encoding of latent dependencies, leading to an efficient and more expressive variant of traditional variational learning. The benefits of this approach will be illustrated with applications in computer vision and computer graphics. _________________________ Short Bio Andreas Lehrmann works at the intersection of machine learning, quantitative finance, and computer vision. His research focuses on the development of expressive neural architectures for structured data and approximate methods for the associated inference tasks. He is also interested in deep generative models exploiting contextual information in non-stationary time-series. Fields of application in finance and vision include volatility and hedging of derivatives, natural language processing, conditional video synthesis, and scene understanding. Before assuming his current role as a machine learning research team lead with Borealis AI, Andreas was a postdoctoral research scientist at Facebook Reality Labs and Disney Research (United States). Prior to that, he was a Microsoft Research Ph.D. scholar at ETH Zurich (Switzerland) and the Max-Planck-Institute for Intelligent Systems (Germany).
        Speaker: Dr Andreas Lehrmann
      • 49
        Solving Technological Challenges with the Fujitsu Digital Annealer
        The Fujitsu Digital Annealer is a new technology that is used to solve large-scale combinatorial optimization problems instantly. The Digital Annealer uses a digital circuit design and can solve problems which are intractable for classical computers. In this workshop, we introduce how the Digital Annealer works for solving combinatorial optimization problems with use cases drawn from scientific fields including health care, pharmaceuticals, and physics. Included is an introduction to expressing technical problems in a quadratic unconstrained binary optimization (QUBO) format for solution using the Digital Annealer.
        Speakers: Mr Jeffrey English (Fujitsu), Mr Tadayoshi Ozaki (Fujitsu)
        Slides