Event Classification in Liquid Scintillator Using PMT Hit Patterns

Name: Event Classification in Liquid Scintillator Using PMT Hit Patterns
Brand: Springer Nature
SKU: 9783030316150
Availability: InStock

Best Price (Coupon Required):
Buy Event Classification in Liquid Scintillator Using PMT Hit Patterns for $76.50 at @ Link.springer.com when you apply the 10% OFF coupon at checkout.
Click “Get Coupon & Buy” to copy the code and unlock the deal.

Set a price drop alert to never miss an offer.

1 Offer Price Range: $84.99 - $84.99

BEST PRICE

Single Product Purchase

$76.50

@ Link.springer.com with extra coupon

Price Comparison

Seller	Contact Seller	List Price	On Sale	Shipping	Best Promo	Final Price	Volume Discount	Financing	Availability	Seller's Page
BEST PRICE 1 Product Purchase @ Link.springer.com		$84.99	$84.99		10% OFF This deals requires coupon	$76.50		See Site	In stock	Visit Store

Product Details

Brand

Springer Nature

Manufacturer

N/A

Part Number

GTIN

9783030316150

Condition

New

Product Description

The search for neutrinoless double beta decay is one of the highest priority areas in particle physics today; it could provide insights to the nature of neutrino masses (currently not explained by the Standard Model) as well as how the universe survived its early stages. One promising experimental approach involves the use of large volumes of isotope-loaded liquid scintillator, but new techniques for background identification and suppression must be developed in order to reach the required sensitivity levels and clearly distinguish the signal. The results from this thesis constitute a significant advance in this area, laying the groundwork for several highly effective and novel approaches based on a detailed evaluation of state-of-the-art detector characteristics. This well written thesis includes a particularly clear and comprehensive description of the theoretical motivations as well as impressively demonstrating the effective use of diverse statistical techniques. The professionally constructed signal extraction framework contains clever algorithmic solutions to efficient error propagation in multi-dimensional space. In general, the techniques developed in this work will have a notable impact on the field.

Available Colors

N/A

Available Sizes

N/A