Mr. Mateusz Wasiluk Profile

Mateusz Wasiluk

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 14 October 2020 Paper

Particle identification using machine learning at the HADES experiment

Mateusz Wasiluk

Proceedings Volume 11581, 115810P (2020) https://doi.org/10.1117/12.2580444

KEYWORDS: Particles, Sensors, Machine learning, Data modeling, Ions, Binary data, Monte Carlo methods

Read Abstract +

The recent outburst in the popularity of the computational technology associated with a broad topic of data science results in a high and still growing accessibility of tools allowing one to make use of sophisticated machine learning algorithms without an expert-level knowledge in the field. Due to that, the usage of such mechanisms became widespread in many branches of business and science, where it helps to analyse large and/or complicated data sets in a relatively quick and efficient way, while obtaining highly accurate results. This paper briefly describes the preparation and evaluation of a solution based on these mechanisms and designed for the problem of particle identification in the HADES experiment at the Facility for Antiproton and Ion Research in Europe. The research was conducted with the usage of data coming from 1.23 AGeV Au+Au collisions in the HADES detector simulated using Monte Carlo methods of the GEANT toolkit. The next step will focus on applying the prepared solution to experimental data, but the development is still ongoing.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years