ACAT 2021

Session

Plenary

Plenary

Nov 29, 2021, 3:20 PM

Auditorium (Virtual and IBS Science Culture Center, Daejeon, South Korea)

Conveners

Plenary

• Gudrun Heinrich (KIT)
• Soonwook Hwang
• Patricia Mendez Lorenzo (CERN)

Plenary

• Andrey Pikelner (BLTP JINR)
• John J. Oh (NIMS (South Korea))
• Maria Girone (CERN)

Plenary

• Jerome LAURET (Brookhaven National Laboratory)
• Sunny Seo
• Doris Yangsoo Kim (Soongsil University)

Plenary: Plenary

• Sunny Seo
• Doris Yangsoo Kim (Soongsil University)
• Jerome LAURET (Brookhaven National Laboratory)

Plenary

• Jennifer Ngadiuba (FNAL)
• Pushpalatha Bhat (Fermi National Accelerator Lab. (US))
• Sung Woo YOUN (Institute for Basic Science)

Plenary

• Andrey Arbuzov (Joint Institute for Nuclear Research (RU))
• Monique Werlen
• Monique Werlen (EPFL - Ecole Polytechnique Federale Lausanne (CH))
• Doris Yangsoo Kim (Soongsil University)

Plenary

• Marilena Bandieramonte (University of Pittsburgh (US))
• Doris Yangsoo Kim (Soongsil University)
• Daniel Maitre

783. How WHO helps to fight the COVID pandemic with data (contribution ID 783)

Julia Fitzner

11/29/21, 3:20 PM

The World Health Organization has been and is monitoring the development of the pandemic through the regular collection of disease and laboratory data from all member states. Data is collected on the number of cases and death, the age distribution, infections in health care workers, but also on what public health measures are taken and where how many people are vaccinated. This data allows...

795. Machine Learning for LHC Theory (contribution ID 795)

Anja Butter

11/29/21, 3:50 PM

Over the next years, measurements at the LHC and the HL-LHC will provide us with a wealth of data. The best hope of answering fundamental questions like the nature of dark matter, is to adopt big data techniques in simulations and analyses to extract all relevant information.

On the theory side, LHC physics crucially relies on our ability to simulate events efficiently from first...

790. Verifying Mathematical Proofs with Computers (contribution ID 790)

Kevin Buzzard (Imperial College London)

11/29/21, 4:20 PM

792. Modern multiloop calculations: Search for new algorithms and fast computer algebra systems (contribution ID 792)

Roman N. Lee

11/30/21, 3:00 PM

Multiloop calculations are vital for obtaining high-precision predictions in Standard Model. In particular, such predictions are important for the possibility to discover New Physics which is expected to reveal itself in tiny deviations. The methods of multiloop calculations are rapidly evolving for already a few decades. New algorithms as well as their specific software implementations appear...

787. Autonomous Driving, the missing piece (contribution ID 787)

Alberto Broggi

11/30/21, 3:30 PM

Autonomous driving is an extremely hot topic, and the whole automotive industry is now working hard to transition from research to products. Deep learning and the progress of silicon technology are the main enabling factors that boosted the industry interest and are currently pushing the automotive sector towards futuristic self-driving cars. Computer vision is one of the most important...

788. High-performance Analysis, Today and Tomorrow (contribution ID 788)

Josh Bendavid (CERN)

11/30/21, 4:00 PM

The unprecedented volume of data and Monte Carlo simulations at the HL-LHC will pose increasing challenges for data analysis both in terms of computing resource requirements as well as "time to insight". I will discuss the evolution and current state of analysis data formats, software, infrastructure and workflows at the LHC, and the directions being taken towards fast, efficient, and...

796. Biomimetic neural network inspired by human hearing (contribution ID 796)

Kang-Hun Ahn

12/1/21, 3:00 PM

Human hearing has a very amazing ability that even advanced technology cannot imitate. The difference in energy between the smallest and loudest audible sounds is about a trillion times. The frequency resolution is also excellent, so the ear can distinguish a frequency difference of about 4 Hz. What is more surprising is that it can be heard even where there is a louder noise than the sound of...

786. Racing for what? Acceleration and Competition in the Academic Sciences (contribution ID 786)

Ruth Mueller

12/1/21, 3:30 PM

In this talk, I will discuss the impacts of what has been termed a growing culture of speed and hypercompetition in the academic sciences. Drawing on qualitative social sciences research in the life sciences, I will discuss how acceleration and hypercompetition impact epistemic diversity in science, i.e. the range of research topics researchers consider they can address, as well as human...

794. Understanding Machine Learning via Exactly Solvable Statistical Physics Models (contribution ID 794)

Lenka Zdeborova

12/1/21, 4:30 PM

The affinity between statistical physics and machine learning has a long history, I will describe the main lines of this long-lasting friendship in the context of current theoretical challenges and open questions about deep learning. Theoretical physics often proceeds in terms of solvable synthetic models, I will describe the related line of work on solvable models of simple feed-forward...

791. Quantum Computing: where is it going and what is it good for? (contribution ID 791)

Joseph Lykken

12/2/21, 9:00 AM

The technology of quantum computers and related systems is advancing rapidly, and powerful programmable quantum processors are already being made available by various companies. Long before we reach the promised land of fully fault tolerant large scale quantum computers, it is possible that unambiguous “quantum advantage” will be demonstrated for certain kinds of problems, including problems...

782. Quantum Computing for Data Science (contribution ID 782)

Barry Sanders

12/2/21, 9:30 AM

Invited plenary

I provide a perspective on the development of quantum computing for data science, including a dive into state-of-the-art for both hardware and algorithms and the potential for quantum machine learning.

785. Generators and the (Accelerated) Future (contribution ID 785)

Joshua Isaacson

12/2/21, 10:00 AM

With the upcoming High Luminosity LHC coming online in the near future, event generators will need to generate a similar number of events. Currently, the current estimated cost to generate these events exceeds the computing budget of the LHC experiments. To address these issues, the event generators need to improve their speed. Many different approaches are being taken to achieve this goal. I...

784. Outlook on software framework in nuclear physics (contribution ID 784)

Adrien MATTA (IN2P3/CNRS, LPC Caen)

12/3/21, 3:20 PM

Over the past decades nuclear physics experiment has seen a drastic increase in complexity. With the arrival of second generation radioactive ions beams facilities all over the world, the run for exploring more and more exotic nuclei is raging. The low intensity of RI-beams require more complex setup, covering larger solid angle, and detecting a wider variety of charged and neutral particles....

789. Unsupervised Machine Learning for New Physics Searches (contribution ID 789)

Michael Spannowsky (University of Durham (GB))

12/3/21, 4:50 PM

In the absence of new physics signals and in the presence of a plethora of new physics scenarios that could hide in the copiously produced LHC collision events, unbiased event reconstruction and classification methods have become a major research focus of the high-energy physics community. Unsupervised machine learning methods, often used as anomaly-detection methods, are trained on Standard...