Alignment of images from multiple modalities is a very important procedure for many medical and industrial applications. Often times it is not possible to utilize a supervised method due to the lack ...of labeled data for any specific sensor architecture. In this study, a new unsupervised approach is proposed for a sensor-camera system aligned in one axis, that warps the image-like frames onto each other with a second-degree polynomial sampled from the cross-correlation maximizing segment shifts. This methodology will allow the registration process to adjust for focal differences and varying image modalities between the sensors. Thus, novel architectures utilizing seldom-used sensors will more easily adapt to industrial and medical work environments.
Results of a search for new physics in final states with an energetic jet and large missing transverse momentum are reported. The search uses proton-proton collision data corresponding to an ...integrated luminosity of 139 fb−1 at a center-of-mass energy of 13 TeV collected in the period 2015–2018 with the ATLAS detector at the Large Hadron Collider. Compared to previous publications, in addition to an increase of almost a factor of four in the data size, the analysis implements a number of improvements in the signal selection and the background determination leading to enhanced sensitivity. Events are required to have at least one jet with transverse momentum above 150 GeV and no reconstructed leptons (e , μ or τ) or photons. Several signal regions are considered with increasing requirements on the missing transverse momentum starting at 200 GeV. Overall agreement is observed between the number of events in data and the Standard Model predictions. Model-independent 95% confidence-level limits on visible cross sections for new processes are obtained in the range between 736 fb and 0.3 fb. Results are also translated into improved exclusion limits in models with pair-produced weakly interacting dark-matter candidates, large extra spatial dimensions, supersymmetric particles in several compressed scenarios, axionlike particles, and new scalar particles in dark-energy-inspired models. In addition, the data are translated into bounds on the invisible branching ratio of the Higgs boson.
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Noise injection is a fundamental tool for data augmentation, and yet there is no widely accepted procedure to incorporate it with learning frameworks. This study analyzes the effects of adding or ...applying different noise models of varying magnitudes to Convolutional Neural Network (CNN) architectures. Noise models that are distributed with different density functions are given common magnitude levels via Structural Similarity (SSIM) metric in order to create an appropriate ground for comparison. The basic results are conforming with the most of the common notions in machine learning, and also introduce some novel heuristics and recommendations on noise injection. The new approaches will provide better understanding on optimal learning procedures for image classification.
A
bstract
A search for pair production of third-generation scalar leptoquarks decaying into a top quark and a
τ
-lepton is presented. The search is based on a dataset of
pp
collisions at
s
= 13 TeV ...recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb
−
1
. Events are selected if they have one light lepton (electron or muon) and at least one hadronically decaying
τ
-lepton, or at least two light leptons. In addition, two or more jets, at least one of which must be identified as containing
b
-hadrons, are required. Six final states, defined by the multiplicity and flavour of lepton candidates, are considered in the analysis. Each of them is split into multiple event categories to simultaneously search for the signal and constrain several leading backgrounds. The signal-rich event categories require at least one hadronically decaying
τ
-lepton candidate and exploit the presence of energetic final-state objects, which is characteristic of signal events. No significant excess above the Standard Model expectation is observed in any of the considered event categories, and 95% CL upper limits are set on the production cross section as a function of the leptoquark mass, for different assumptions about the branching fractions into
tτ
and
bν
. Scalar leptoquarks decaying exclusively into
tτ
are excluded up to masses of 1
.
43 TeV while, for a branching fraction of 50% into
tτ
, the lower mass limit is 1
.
22 TeV.
A
bstract
Measurements of the production cross-sections of the Standard Model (SM) Higgs boson (
H
) decaying into a pair of
τ
-leptons are presented. The measurements use data collected with the ...ATLAS detector from
pp
collisions produced at the Large Hadron Collider at a centre-of-mass energy of
s
= 13 TeV, corresponding to an integrated luminosity of 139 fb
−
1
. Leptonic (
τ
→
ℓν
ℓ
ν
τ
) and hadronic (
τ
→ hadrons
ν
τ
) decays of the
τ
-lepton are considered. All measurements account for the branching ratio of
H → ττ
and are performed with a requirement
|y
H
| <
2
.
5, where
y
H
is the true Higgs boson rapidity. The cross-section of the
pp → H → ττ
process is measured to be 2
.
94
±
0.21
stat
−
0.32
+
0.37
(syst) pb, in agreement with the SM prediction of 3
.
17
±
0
.
09 pb. Inclusive cross-sections are determined separately for the four dominant production modes: 2
.
65
±
0.41
stat
−
0.67
+
0.91
(syst) pb for gluon-gluon fusion, 0
.
197
±
0.028
stat
−
0.026
+
0.032
(syst) pb for vector-boson fusion, 0
.
115
±
0.058
stat
−
0.040
+
0.042
(syst) pb for vector-boson associated production, and 0
.
033
±
0.031
stat
−
0.017
+
0.022
(syst) pb for top-quark pair associated production. Measurements in exclusive regions of the phase space, using the simplified template cross-section framework, are also performed. All results are in agreement with the SM predictions.
A search for a heavy neutral Higgs boson,
A
, decaying into a
Z
boson and another heavy Higgs boson,
H
, is performed using a data sample corresponding to an integrated luminosity of 139 fb
-
1
from ...proton–proton collisions at
s
=
13
TeV
recorded by the ATLAS detector at the LHC. The search considers the
Z
boson decaying into electrons or muons and the
H
boson into a pair of
b
-quarks or
W
bosons. The mass range considered is 230–800
GeV
for the
A
boson and 130–700
GeV
for the
H
boson. The data are in good agreement with the background predicted by the Standard Model, and therefore 95% confidence-level upper limits for
σ
×
B
(
A
→
Z
H
)
×
B
(
H
→
b
b
or
H
→
W
W
)
are set. The upper limits are in the range 0.0062–0.380 pb for the
H
→
b
b
channel and in the range 0.023–8.9 pb for the
H
→
W
W
channel. An interpretation of the results in the context of two-Higgs-doublet models is also given.
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A search is presented for the production of a single top quark via left-handed flavour-changing neutral-current (FCNC) interactions of a top quark, a gluon and an up or charm quark. Two production ...processes are considered:
u
+
g
→
t
and
c
+
g
→
t
. The analysis is based on proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. The data set corresponds to an integrated luminosity of 139 fb
-
1
. Events with exactly one electron or muon, exactly one
b
-tagged jet and missing transverse momentum are selected, resembling the decay products of a singly produced top quark. Neural networks based on kinematic variables differentiate between events from the two signal processes and events from background processes. The measured data are consistent with the background-only hypothesis, and limits are set on the production cross-sections of the signal processes:
σ
(
u
+
g
→
t
)
×
B
(
t
→
W
b
)
×
B
(
W
→
ℓ
ν
)
<
3.0
pb and
σ
(
c
+
g
→
t
)
×
B
(
t
→
W
b
)
×
B
(
W
→
ℓ
ν
)
<
4.7
pb at the 95% confidence level, with
B
(
W
→
ℓ
ν
)
=
0.325
being the sum of branching ratios of all three leptonic decay modes of the
W
boson. Based on the framework of an effective field theory, the cross-section limits are translated into limits on the strengths of the
tug
and
tcg
couplings occurring in the theory:
|
C
uG
u
t
|
/
Λ
2
<
0.057
TeV
-
2
and
|
C
uG
c
t
|
/
Λ
2
<
0.14
TeV
-
2
. These bounds correspond to limits on the branching ratios of FCNC-induced top-quark decays:
B
(
t
→
u
+
g
)
<
0.61
×
10
-
4
and
B
(
t
→
c
+
g
)
<
3.7
×
10
-
4
.
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This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the ...LHC in proton-proton collisions at sqrts=13 TeV and corresponding to an integrated luminosity of 137 fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bbover ¯. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst) pb.
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Understanding the variations in trading price (volatility), and its response to exogenous information, is a well-researched topic in finance. In this study, we focus on finding stable and accurate ...volatility predictors for a relatively new asset class of cryptocurrencies, in particular Bitcoin, using deep learning representations of public social media data obtained from Twitter. For our experiments, we extracted semantic information and user statistics from over 30 million Bitcoin-related tweets, in conjunction with 15-minute frequency price data over a horizon of 144 days. Using this data, we built several deep learning architectures that utilized different combinations of the gathered information. For each model, we conducted ablation studies to assess the influence of different components and feature sets over the prediction accuracy. We found statistical evidences for the hypotheses that: (i) temporal convolutional networks perform significantly better than both classical autoregressive models and other deep learning-based architectures in the literature, and (ii) tweet author meta-information, even detached from the tweet itself, is a better predictor of volatility than the semantic content and tweet volume statistics. We demonstrate how different information sets gathered from social media can be utilized in different architectures and how they affect the prediction results. As an additional contribution, we make our dataset public for future research.
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