<p>Neutrino emission from nuclear reactors provides real-time insights into reactor power and fuel evolution, with potential applications in monitoring and nuclear safeguards. Following reactor shutdown, a low-intensity flux of “residual neutrinos” persists due to the decay of long-lived fission isotopes in the partially burnt fuel remaining within the reactor cores and in spent nuclear fuel stored in nearby cooling pools. The Double Chooz experiment at the Chooz B nuclear power plant in France achieved the first quantitative measurement of this residual flux based on 17.2 days of reactor-off data. In the energy range where the residual signal is most pronounced, the neutrino detector located 400 m from the cores recorded <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><mn>106</mn><mo>±</mo><mn>18</mn></math> neutrino candidate events (<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><mrow><mn>5.9</mn><mi>σ</mi></mrow></math> significance). This measurement is in excellent agreement with the predicted value of <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><mn>88</mn><mo>±</mo><mn>7</mn></math> events derived from detailed reactor simulations modeling the decay activities of fission products and incorporating the best-available models of neutrino spectra.</p>

Brazil

T. Abrahão

Germany

H. Almazan

J.C. dos Anjos

S. Appel

France

J.C. Barriere

I. Bekman

T.J.C. Bezerra

L. Bezrukov

United States

E. Blucher

C. Bourgeois

C. Buck

J. Busenitz

A. Cabrera

Spain

M. Cerrada

E. Chauveau

P. Chimenti

O. Corpace

J.V. Dawson

J.F. Du

Z. Djurcic

A. Etenko

Japan

H. Furuta

I. Gil-Botella

A. Givaudan

H. Gomez

M.C. Goodman

T. Hara

J. Haser

D. Hellwig

A. Hourlier

M. Ishitsuka

J. Jochum

C. Jollet

K. Kale

M. Kaneda

M. Karakac

T. Kawasaki

E. Kemp

D. Kryn

M. Kuze

T. Lachenmaier

C.E. Lane

T. Lasserre

D. Lhuillier

H.P. Lima

M. Lindner

J.M. LoSecco

B. Lubsandorzhiev

J. Maeda

C. Mariani

J. Maricic

J. Martino

T. Matsubara

G. Mention

A. Meregaglia

T. Miletic

R. Milincic

A. Minotti

X. Mougeot

D. Navas-Nicolás

Y. Nikitenko

P. Novella

L. Oberauer

M. Obolensky

A. Onillon

A. Oralbaev

C. Palomares

I.M. Pepe

L. Perisse

G. Pronost

J. Reichenbacher

S. Schönert

S. Schoppmann

L. Scola

R. Sharankova

V. Sibille

V. Sinev

M. Skorokhvatov

P. Soldin

A. Stahl

I. Stancu

M.R. Stock

L.F.F. Stokes

F. Suekane

S. Sukhotin

T. Sumiyoshi

C. Veyssiere

B. Viaud

M. Vivier

S. Wagner

C. Wiebusch

G. Yang

F. Yermia

First Measurement of Neutrino Emissions from Spent Nuclear Fuel by the Double Chooz Experiment

Two machine learning techniques for jet measurements at the LHCb experiment are presented: a regression-based method for jet-energy calibration and a deep neural network algorithm for jet flavour tagging, distinguishing between $\textit{b}$-quark, $\textit{c}$-quark, and light parton jets. These techniques are applied to a search for inclusive $$ H\to b\overline{b} $$ and $$ H\to c\overline{c} $$ decays using a LHCb dataset corresponding to an integrated luminosity of 1.6 fb . The observed (expected) 95% confidence level upper limits correspond to 6.6 (11.1) times the SM cross-section for the $$ H\to b\overline{b} $$ process, and 1003 (1834) times the SM cross-section for the $$ H\to c\overline{c} $$ process.

Netherlands

R. Aaij

United Kingdom

A. Abdelmotteleb

Switzerland

C. Abellan Beteta

F. Abudinén

T. Ackernley

A. Adefisoye

B. Adeva

M. Adinolfi

Sweden

P. Adlarson

C. Agapopoulou

C. Aidala

Z. Ajaltouni

S. Akar

K. Akiba

Poland

M. Akthar

Italy

P. Albicocco

J. Albrecht

Lithuania

R. Aleksiejunas

F. Alessio

P. Alvarez Cartelle

R. Amalric

S. Amato

J. Amey

Y. Amhis

China

L. An

L. Anderlini

M. Andersson

P. Andreola

M. Andreotti

S. Andres Estrada

A. Anelli

D. Ao

C. Arata

F. Archilli

Z. Areg

M. Argenton

Costa Rica

S. Arguedas Cuendis

L. Arnone

A. Artamonov

M. Artuso

E. Aslanides

R. Ataíde Da Silva

M. Atzeni

B. Audurier

J. Authier

D. Bacher

I. Bachiller Perea

S. Bachmann

M. Bachmayer

J. Back

P. Baladron Rodriguez

V. Balagura

A. Balboni

W. Baldini

Z. Baldwin

L. Balzani

H. Bao

J. Baptista de Souza Leite

C. Barbero Pretel

M. Barbetti

I. Barbosa

R. Barlow

M. Barnyakov

S. Barsuk

W. Barter

J. Bartz

S. Bashir

B. Batsukh

P. Battista

A. Bay

A. Beck

M. Becker

F. Bedeschi

I. Bediaga

N. Behling

S. Belin

A. Bellavista

K. Belous

I. Belov

I. Belyaev

E. Ben-Haim

G. Benane

G. Bencivenni

A. Berezhnoy

R. Bernet

S. Bernet Andres

A. Bertolin

C. Betancourt

F. Betti

J. Bex

Machine learning techniques for jet reconstruction at LHCb and application to the search for $$ H\to b\overline{b} $$ and $$ H\to c\overline{c} $$ in $$ \sqrt{s}=13 $$ TeV $\textit{pp}$ collisions