PDF Summary on Searches for long- lived particles

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Summary on Searches for long- lived particles

ATLAS FPN meeting 16 Sept 2022

Mariia Didenko, Paolo Sabatini, Victoria Sánchez, Emma Torró

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E. Torró ATLAS FPN meeting 16 Sept 2022

E. T o rró 1 4 N o v 2 0 1 8

2 s s p p f ¯ f ¯ f f

Analysis Overview ‣ T a rg e t mo d e ls: H id d e n se ct o r w ith a h e a vy n e u tra l b o so n , 𝜙 , d e ca yi n g t o t w o l o n g - live d n e u tra l sca la rs, s, t h a t d e ca y to p a irs o f SM fe rmi o n s. ‣ Se p a ra te t h e se le ct io n i n t w o g ro u p s: ‣ H ig h ma ss sa mp le s: m 𝜙 = 4 0 0 t o 1 0 0 0 G e V ; m S = 5 0 t o 4 0 0 G e V ‣ L o w ma ss sa mp le s: m 𝜙 = 1 2 5 t o 2 0 0 G e V ; m S = 5 t o 5 0 G e V ‣ T ri g g e r: d e d ica te d CalRatio (C a lo ri me te r R a ti o : E H /E EM ) tri g g e rs ‣ H ig h ma ss sa mp le s: d e fa u lt C a lR a ti o t ri g g e r se e d e d b y L 1 _ T AU 6 0 ‣ L o w ma ss sa mp le s: C a lR a ti o t ri g g e r se e d e d b y L 1 T o p o L 1 _ L L P-N O MA T C H ‣ Si g n a tu re : 2 d isp la ce d j e ts in t h e C a lo ri me te r ‣ Ba ckg ro u n d co n tri b u ti o n s ma in ly fro m: ‣ mu lt ije ts: j e ts p ro d u ce d f ro m n e u tra l h a d ro n s ‣ N o n -co lli si o n b a ckg ro u n d s: ‣ b e a m-i n d u ce d b a ckg ro u n d (BI B) ‣ co smi c mu o n s ‣ Al l e st ima te d u si n g d a ta -d ri ve n me th o d s

‣ Se a rch f o r p a irs o f n e u tra l lo n g -l ive d p a rt icl e s d e ca yi n g t o SM fe rmi o n s in t h e C a lo ri me te r

2-CalRatio search

2

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0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

xy [m]

LLP L 0

0.2 0.4 0.6 0.8 1 1.2 1.4

Efficiency ECal start ECal end HCal start HCal end

L1 seed: 60GeV-high-ET

L1 seed: 100GeV-high-ET

v2016 L1 seed: low-ET

v2018 L1 seed: low-ET

ATLAS Simulation

)=(600,150) GeV ,ms

(mΦ

=3.31m cτ

2-CalRatio search

•

Search for pairs of neutral long-lived particles decaying to SM fermions in the Calorimeter

3

E. T o rró 1 4 N o v 2 0 1 8

2 s s p p f ¯ f ¯ f f

Analysis Overview ‣ Ta rg e t mo d e ls: H id d e n se ct o r w ith a h e a vy n e u tra l b o so n , 𝜙 , d e ca yi n g t o t w o l o n g - live d n e u tra l sca la rs, s, t h a t d e ca y to p a irs o f SM fe rmi o n s. ‣ Se p a ra te t h e se le ct io n in t w o g ro u p s: ‣ H ig h ma ss sa mp le s: m

𝜙

= 4 0 0 t o 1 0 0 0 G e V ; m

S

= 5 0 t o 4 0 0 G e V ‣ L o w ma ss sa mp le s: m

𝜙

= 1 2 5 t o 2 0 0 G e V ; m

S

= 5 t o 5 0 G e V ‣ T ri g g e r: d e d ica te d CalRatio (C a lo ri me te r R a tio : E

H

/E

EM

) tri g g e rs ‣ H ig h ma ss sa mp le s: d e fa u lt C a lR a tio t ri g g e r se e d e d b y L 1 _ T AU 6 0 ‣ L o w ma ss sa mp le s: C a lR a tio t ri g g e r se e d e d b y L 1 T o p o L 1 _ L L P-N O MA T C H ‣ Si g n a tu re : 2 d isp la ce d je ts in t h e C a lo ri me te r ‣ Ba ckg ro u n d co n tri b u tio n s ma in ly fro m: ‣ mu lt ije ts: j e ts p ro d u ce d f ro m n e u tra l h a d ro n s ‣ N o n -co lli si o n b a ckg ro u n d s: ‣ b e a m-i n d u ce d b a ckg ro u n d (BI B) ‣ co smi c mu o n s ‣ Al l e st ima te d u si n g d a ta -d ri ve n me th o d s

‣ Se a rch f o r p a irs o f n e u tra l lo n g -l ive d p a rt icl e s d e ca yi n g t o SM fe rmi o n s in t h e C a lo ri me te r

E. Torró 14 Nov 2018

2

s s p

p f

f¯

f¯ f

Analysis Overview

‣

Target models: Hidden sector with a heavy neutral boson, 𝜙, decaying to two long- lived neutral scalars, s, that decay to pairs of SM fermions.

‣

Separate the selection in two groups:

‣

High mass samples: m^𝜙 = 400 to 1000 GeV; mS = 50 to 400 GeV

‣

Low mass samples: m^𝜙 = 125 to 200 GeV; mS = 5 to 50 GeV

‣

Trigger: dedicated CalRatio (Calorimeter Ratio: EH/EEM) triggers

‣

High mass samples: default CalRatio trigger seeded by L1_TAU60

‣

Low mass samples: CalRatio trigger seeded by L1Topo L1_LLP-NOMATCH

‣

Signature: 2 displaced jets in the Calorimeter

‣

Background contributions mainly from:

‣

multijets: jets produced from neutral hadrons

‣

Non-collision backgrounds:

‣

beam-induced background (BIB)

‣

cosmic muons

‣

All estimated using data-driven methods

‣

Search for pairs of neutral long-lived particles decaying to SM fermions in the CalorimeterSignature: 2 displaced jets in the Calorimeter

1 jet

•

Glance entry: https://atlas-glance.cern.ch/atlas/analysis/papers/details.php?id=13726

•

Sent to arXive on 2nd March 2022 arXiv:2203.01009

•

Paper published on 1st June 2022 JHEP 06 (2022) 005

•

Target models: Hidden sector with a heavy neutral boson, 𝜙, decaying to two long-lived neutral scalars, s, that decay to pairs of SM fermions.

•

Dedicated CalRatio triggers, improved in 2018

JHEP 06 (2022) 005

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Displaced jet tagging NN

•

Neural network trained to tag jets as signal, beam-induced-background (BIB), multijets

•

Takes as input tracks, topoclusters, muon segments

•

Some of these input variables have a non-negligible mismodelling

4

JHEP 06 (2022) 005

Adding adversary NN

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0 1 2 3 4 5

min

ΔR

∑

0 0.2 0.4 0.6

BDT THigh-E

−1

10 1 10

Number of events

=1.84m )=(600,150) GeV; cτ

,ms

(mΦ

=13 TeV s

A B

C D

0 1 2 3 4 5

min

ΔR

∑

0 0.2 0.4 0.6

BDT THigh-E

−1

10 1 10

Number of events

main data

ATLAS

=13 TeV, 139 fb-1

s

A B

C D

Results

•

Used ABCD data-driven method for background estimation

•

Multiple validations done

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•

The limits are calculated using the simultaneous ABCD method, where signal contamination in regions B, C and D is taken into account.

High-ET selection

JHEP 06 (2022) 005

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τ [m]

c

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10

−3

10

−2

10

−1

10 1

ss→HB×) SMσ / σ95% CL upper limit on (

2016 CalRatio-only

(2015)-2016 ID+CR+MS

) = (125, 55) GeV , mS

HS (mH

= 1.05 m τgen

c

ATLAS

= 13 TeV, 139 fb-1

s

Obs.

, 2σ 1σ

Exp. ± = 100%

→ ss

BH

= 10%

→ ss

BH

= 1%

→ ss

BH

• Very good improvement wrt 2016 data CalRatio analyses

• Improvements come from:

• 2018 version of LLP-NOMATCH trigger

• Displaced jet NN tagger more sensitive than previous method

• Increase in lumi

•

Second exotic result using pyhf for statistical interpretation!!

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6

2-CalRatio search

JHEP 06 (2022) 005

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E. Torró 2 CalRatio PAM 19 Nov 2021

Material for reinterpretation…

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•

^HEPData

•

Requested by theorist, eﬃciency maps as a function of the main LLP characteristics: LLP mass, decay mode, pT, eta, decay position

0 50 100 150 200 250

−3

10

−2

10

−1

10 1

Region A Efficiency

Simulation

ATLAS

13 TeV

selection Low-ET

Bin Index

LLP1

Bin Index 2LLP

0 50 100 150 200 250

−3

10

−2

10

−1

10 1

Region A Efficiency

Simulation

ATLAS

13 TeV

selection High-ET

Bin Index LLP1

Bin Index 2LLP

JHEP 06 (2022) 005

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Displaced dark-photon jet search

8

• Search for pairs of displaced dark-photon jets

• FRVZ, HAHM models

0 2 4 6 8 10 12

xy [m]

d L True γ 0

0.2 0.4 0.6 0.8 1 1.2 1.4

Efficiency ^{=50 mm}^d^γ^τ)=(125, 0.4) GeV; c

γd

H, m

d (m FRVZ 2γ

=25 mm

γd

)=(125, 0.4) GeV; cτ

γd

H, m

d (m HAHM 2γ

=10 mm

γd

)=(800, 0.4) GeV; cτ

γd

H, m

d (m FRVZ 2γ

Simulation ATLAS

>6 GeV

,2 µ

>20 GeV, pT ,1

µ

|<1, pT

, |η µ µ

d→ γ

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

xy [m]

d L True γ 0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Efficiency ^{=50 mm}^d^γ^τ)=(125, 0.4) GeV; c

γd

H, m

d (m FRVZ 2γ

=10 mm

γd

)=(800, 0.4) GeV; cτ

γd

H, m

d (m FRVZ 2γ

=25 mm

γd

)=(125, 0.4) GeV; cτ

γd

H, m

d (m HAHM 2γ

>30 GeV

|<1, pT

, |η q

-,q

+e

→e γd

CalRatio trigger for caloDPJ

Narrow-scan trigger for muDPJ

• Glance entry: https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/

PAPERS/EXOT-2019-05/

• Sent to arXive on 24th June 2022 arXiv:2206.12181

• Submitted to JHEP

arXiv:2206.12181

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LLP summary plots

9

• Collecting the latest results from all LLP searches using the Hidden sector HSS model or dark- photon models:

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10 10⁻⁴ 10⁻³ 10⁻² 10⁻¹ 1 10 10² 10³

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10

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10

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Searches:

Muon System (2 Vtx Only), 139 fb-1 arXiv:2203.00587

Muon System (1 Vtx + 2 Vtx), 36 fb-1 Phys. Rev. D 99 (2019) 052005

Calorimeter, 139 fb-1 arXiv:2203.01009 Calorimeter, 33 fb-1 Eur. Phys. J. C 79 (2019) 481 Tracker+Muon System, 36 fb-1 Phys. Rev. D 101 (2020) 052013

LLP masses:

50 GeV 150 GeV

275 GeV 400 GeV

475 GeV

(March 2022) Preliminary

ATLAS 13TeV, 33-139fb^-1 = 1000 GeV Hidden Sector, mΦ

results ATLAS

Selected

95% CL observed limits

τ [m]

c

ss) [pb]→ΦB(×σ

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10

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10

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Searches:

Calorimeter, 139 fb-1 arXiv:2203.01009

Tracker+Muon System, 36 fb-1 Phys. Rev. D 101 (2020) 052013 Tracker (LRT), 139 fb-1 JHEP 11 (2021) 229 Tracker (b-tag), 36 fb-1 JHEP 10 (2018) 031 Monojet, 139 fb-1 ATL-PHYS-PUB-2021-020

inv, 7-8-13 TeV combination H→

ATLAS-CONF-2020-052

LLP masses:

5-8 GeV 15-20 GeV 25-35 GeV 40 GeV 45-60 GeV Any

Prompt Stable

ATLAS 13TeV, 36-139fb^-1 = 125 GeV Hidden Sector, mH

results ATLAS

Selected

τ [m]

c

ss)→B(H

mPhi = 125 GeV

mPhi = 1000 GeV

ATL-PHYS-PUB-2022-007

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105 10⁻³ 10⁻² 10⁻¹ 1 10 10² 10

15 20 25 30 35 40 45 50 55

Searches:

Calorimeter, 139 fb-1 arXiv:2203.01009 Calorimeter, 11 fb-1 Eur. Phys. J. C 79 (2019) 481 Tracker+Muon System, 36 fb-1 Phys. Rev. D 101 (2020) 052013 Tracker (LRT), 139 fb-1 JHEP 11 (2021) 229

ATLAS 13TeV, 11-139 fb^-1 Hidden Sector, m_H = 125 GeV ss) = 10%

B(H→

τ [m]

c

LLP mass [GeV]

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10 10⁻¹ 1 10

Dark Photon mass [GeV]

−8

10

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10

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10

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10

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εVector portal coupling

Non-ATLAS searches

JHEP 06 (2018) 004

-1) Displaced (139 fb

ATLAS-CONF-2022-001

-1) Prompt (20.3 fb

JHEP 02 (2016) 062

-1) Monojet (139 fb

ATL-PHYS-PUB-2021-020

FRVZ Model

d+X 2γ H→

= 125 GeV mH

BR=10%

BR=5%

BR=1%

BR=0.5%

BR=0.1%

Vector-Portal-only limits BR=10%

BR=50%

Preliminary

ATLAS s=8-13 TeV, 20.3-139 fb^-1

mPhi = 125 GeV

All ATLAS + non-ATLAS limits

mPhi = 125 GeV

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CalRatio+X search

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Long-lived

CalRatio + Z/W

11

• Signature: Displaced jet in the Calorimeter + prompt SM Z/W decaying leptonically

•

^Benefits:

•

Single displaced object search

•

can use SM lepton triggers, no need to rely on specific triggers

• Targeting several theory models with a common final state:

•

Dark sector model with 𝜙 → Z(ll) Zd with LLP Zd

•

GGM SUSY model with 𝛘 → G Z (ﬀ)

•

ALP + Z/W model

•

^{Z/W HSS}

7

Search for 1 displaced calorimeter jet + Z (ll)

Targeting Dark Sector model: production of

ϕ → ZZ

_d with LLP

Z

_d

Strategy in a nutshell:

• Main backgrounds: Z+jets, dibosons , BIB, QCD

• Analysis just started: playing with with leptons, investigating NN performance on these jets

• Collecting ideas to improve performances of the current NN (optimal for HSS model)

• Worst performances due to lower pT, diﬃcult event features ..investigating!

Previous analysis (36/fb) 

PRL 122 151801

Targeting SUSY model: production of LLP

X

₁⁰

→ Gff ˜

DISPLACED AXION LIKE PARTICLES MODEL

3

Limits on the ALP-gluon couplings vs. ALP mass from collider and accelerator searches

Γ_ag = 2C_G²_˜Ma³/( f_a²π)

g_ag = 4C_G_˜ /f_a

~What we can e

xtend gg

l = e, μ l⁺ l⁻

*

Width of ALP decay to gluons:

Coupling to gluons scaled by ALP’s energy scale :

f

_a

C_W_˜ , C_B_˜

C_G_˜

➤ Many searches assume ALP coupled to photons, but nothing observed so far: assume photophobic ALPs so coupling to photons is suppressed (i.e. , suggested by theorists ); focus on ALP decays to gluons, and the

production channel via a Z boson

➤ The cross-section depends only on ALP’s coupling to the Z boson ( one parameter , since ), and its mass

➤ ALP’s lifetime depends on the coupling to gluons ( ) and the ALP’s mass: can extend existing limits to lower values of

C

_B_˜

= − tan θ

_w

C

_W_˜

C

_W_˜

C

_B_˜

( C

_W_˜

) C

_G_˜

C

_G_˜

•

Glance entry: https://atlas-glance.cern.ch/atlas/

analysis/analyses/details.php?id=6978

Benchmarks

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CalRatio + Z/W: status

12

• We have our own derivations, EXOT15, used by us and MS vertex

• Had to re-define them to include leptons

• Added lepton triggers

• Had to add skimming to reduce size (> 0 trackless jets)

• Added trigger matching for leptons

• Added large-R jets

𝓁 𝓁

•

High boost: Single well

reconstructed displaced akt4 jet

𝓁 𝓁

• Low boost: Two relatively well reconstructed displaced akt4 jets

• Intermediate boost: Single badly reconstructed displaced akt4 jet:

• reco pt << LLP pt —> killed by cleaning

• but good akt10!

𝓁 𝓁

Derivations

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CalRatio + Z/W: status

13

• Had to fix a couple of bugs and re-make the derivations

• Bug in trackless jet definition

• Bug in cleanLLP flag definition

• New derivation cache built yesterday. New production coming soon

Data/MC checks

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CalRatio + Z/W: status

14

• First time this analysis is done in ATLAS!

• Z-channel and W-channel done in parallel

• Trigger strategy defined

• Two selection strategies

• 1. Simple cut-based selection. Use optimisation procedure on s/sqrt(B)

• 2. Event-level BDT

• Background estimation with ABCD

• Implement all analysis in RECAST

Status and plans

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15

• Identified good separation variables in Z-Channel and W-Channel

• Displaced jets variables

• Event variables

Cut-based selection

W+LLP SELECTION: PRESELECTION

5

➤ Started with a basic + jet preselection:

➤ For signal, one of the LLPs must be matched to the jet with the highest low- NN signal score (sig1-L jet) and the LLP must decay within the calorimeters

➤ Will use a cut in low- NN signal score to identify LLPs, as its performance is homogenous among diﬀerent signal samples and has good separation power for low mass signals

W → eν

ΔR < 0.4 E_T

E_T

W+LLP SELECTION: PRESELECTION

7

➤ Other relevant variables for displaced jet identification are jet pT, jet logRatio i.e. log( ), jet width and minimum (jet, tracks)

➤ More plots in link preselection cuts

W → eν

E

_HCAL

/ E

_ECAL

Δ R

Z+LLP SELECTION: DISCRIMINATING VARIABLES

12

W+LLP SELECTION: PRESELECTION

6

➤ For WHSS samples, there is a worse reconstruction, possibly due to the presence of a second LLP, but this is yet to be studied

➤ An interesting variable is : it is lower wrt background for signal due to higher momentum values. Again, this feature is more clearly observed for W+ALPs than for WHSS.

W → eν

W

Δϕ(e, ^MET) W

W-JET VARIABLES

5

➤ Some discrimination power in

distance sig1 jet with lepton and MET

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W+LLP SELECTION: FIRST TEST SELECTION

9

➤ After this process, came up with an initial test selection, with the following cutflow

➤ This selection is not really optimized, the next step is to use a C++ based code to properly optimize the selection based on the interesting variables found with good signal vs background discrimination power

➤ The following step will be to train a BDT or similar to further optimize the selection

Background 1 GeV ALP 40 GeV ALP WHSS 125-16 WHSS 200-50 WHSS 600-150

~6M 7240 9893 17280 5542 3620

Jet selection:

LowEt-NN signal > 0.7 655000 2830 3430 8990 3630 2330

MinDeltaR(tracks) > 0.2 551990 2610 3170 8660 3490 2220

Remove TileGap 526830 2570 3130 8570 3450 2200

LowEt-NN qcd < 0.0025 35650 1180 1400 4240 1980 1390

pT > 60 GeV 3740 880 1280 3170 1600 1260

logRatio > 0.5 1370 750 1040 2510 1190 890

Width < 0.05 870 680 940 2230 900 640

W → enu

Raw entries mc16a Rough estimate of expected events for full Run2

CalRatio + Z/W: status

16

• Preliminary sensitivity with cut-based

Cut-based selection

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17

• BDT tests ongoing

BDT

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18

RECAST

• Implement all analysis in RECAST, quick workflow to obtain expected limits for testing selections.

• All Implemented and working!!

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Latest talks on our results

19

• Bienal Murcia 2022 talk by Mariia: https://www.um.es/fisica/bienal-2022/programa.php

• ICHEP 2022 poster by Victoria (on behalf to ATLAS): https://agenda.infn.it/event/28874/timetable/?view=standard#807-search-for-long-lived-neut

• IDM 2022 talk by Victoria (on behalf to ATLAS): https://indico.cern.ch/event/922783/timetable/?view=standard#154-searches-for-exotic-decays

• ICNFP 2022 talk by Mariia (on behalf to ATLAS): https://indico.cern.ch/event/1133591/timetable/?layout=room#20220830.detailed

• 11th LHC-LLP workshop talk by Victoria: https://indico.cern.ch/event/1128662/timetable/

• ATLAS EXOTICS workshop 2022: talk by Emma and talk by Mariia

• Red LHC 2022: Emma moderating LLP Round table

• TAE 2022: Emma teaching a course in LLPs

• Exotics workshop, Sept 2021

• New and uncovered analyses in UEH — ALPs, ML ABCD

• Dark QCD — re-interpretation of 2CalRatio search for emerging jets signatures

• Dark photons, dark Z, ALPs — CalR + Z plans, generated models, ALPs

• pyhf for statistical combinations in Exotics — 2-CalRatio studies on pyhf vs. Roostats

• 10th LHC LLP workshop, Nov 2021

• Machine learning techniques for LLP searches at the LHC and beyond — 2016 data analysis, ML ABCD

• Pyhf intro — RECASTed 2016 data result PUB NOTE

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Responsibility positions in the team

20

• E. Torró: analysis contact for the 2-CalRatio publication

• E. Torró (and Mason Proﬃt): analysis contact for the CalRatio+X analyses

• E. Torró: EB for the displaced dark-photon jets

• V. Sánchez: analysis contact for the NCB studies for Run-2 paper: https://atlas- glance.cern.ch/atlas/analysis/analyses/details.php?id=5485

• E. Torró: ATLAS representative for the LHC LLP Working Group https://lpcc.web.cern.ch/lhc-

llp-wg

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Backup

21

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•

Neural network trained to tag jets as signal, beam-induced-background (BIB), multijets

•

Takes as input tracks, topoclusters, muon segments

•

Some of these input variables have a non-negligible mismodelling

22

JHEP 06 (2022) 005

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•

Used adversarial NN to reduce the impact of mismodelled inputs on the final eﬃciency

23

Adding adversary NN

JHEP 06 (2022) 005

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−0.4 −0.2 0 0.2 0.4

T BDT Low-E

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

Fraction of events

Main data BIB data

)=(200,50) GeV ,ms

(mΦ

=1.26m cτ

)=(125,55) GeV ,ms

(mΦ

=1.05m cτ

ATLAS

=13 TeV, 139 fb-1

s

Multijets background estimation: ABCD

•

Select two variables to define a Signal Region (A) and three Control Regions (B, C, D)

•

One of the variables is a per-event BDT to separate BIB from QCD from signal

24

BIB-like background

Multijets-like background

JHEP 06 (2022) 005

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•

Final NN has a great discrimination power between signal, BIB and multi jets

25

JHEP 06 (2022) 005

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0 1 2 3 4 5

min

ΔR

∑

0 0.2 0.4 0.6

BDT THigh-E

−1

10 1 10

Number of events

=1.84m )=(600,150) GeV; cτ

,ms

(mΦ

=13 TeV s

A B

C D

0 1 2 3 4 5

min

ΔR

∑

0 0.2 0.4 0.6

BDT THigh-E

−1

10 1 10

Number of events

main data

ATLAS

=13 TeV, 139 fb-1

s

A B

C D

Multijets background estimation: ABCD

•

Select two variables to define a Signal Region (A) and three Control Regions (B, C, D)

•

One of the variables is a per-event BDT to separate BIB from QCD from signal

26

•

The limits are calculated using the simultaneous ABCD method, where signal contamination in regions B, C and D is taken into account.

High-ET selection

0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24

T BDT Low-E

0 50 100 150 200 250 300 350

Number of events

low-ET

VRCD

observed A expected A

ATLAS

=13 TeV, 139 fb-1

s

•

Validation of the method performed in multiple VRs. All with good agreement

JHEP 06 (2022) 005

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10 10⁻¹ 1 10

τ [m]

c

−4

10

−3

10

−2

10

−1

10 1

2016 CalRatio-only

(2015)-2016 ID+CR+MS

) = (125, 55) GeV , mS

HS (mH

= 1.05 m τgen

c

ATLAS

= 13 TeV, 139 fb-1

s

Obs.

, 2σ 1σ

Exp. ± = 100%

→ ss

BH

= 10%

→ ss

BH

= 1%

→ ss

BH

Limits: Comparison to previous results

•

Use lifetime extrapolation to present limits as a function of the lifetime

•

Second exotic result using pyhf for statistical interpretation!!

27

• Very good improvement wrt 2016 data CalRatio analyses

• Improvements come from:

• 2018 version of LLP-NOMATCH trigger

• Displaced jet NN tagger more sensitive than previous method

• Increase in lumi

mPhi = 125 GeV (other mass results in next slide)

0 0.5 1 1.5

2 2.5 3 3.5 4 4.5 5

mH1000_mS275_ltlow

mH1000_mS50

mH125_mS35_ltlowmH125_mS55_ltlow

mH200_mS50 mH400_mS100

mH600_mS150_ltlow

mH600_mS275 mH600_mS50 Expected limit +/- 1σ

Expected limit +/- 2σ Observed limit

asymptotic, all systematics, pyhf asymptotic, all systematics, roostats asymptotic, stat only, pyhf

asymptotic, stat only, roostats toys, all systematics, pyhf toys, all systematics, roostats toys, stat only, pyhf

toys, stat only, roostats

Simulation Internal

ATLAS 13TeV

CalRatio R21

model

ratio to exp. asym. syst.

JHEP 06 (2022) 005

(28)

E. Torró 2 CalRatio PAM 19 Nov 2021

−1

10 1 10

τ [m]

c

−4

10

−3

10

−2

10

−1

10

[pb]B×σ95% CL upper limit on

S) =

Φ, m HS (m

= 0.59 m τgen

c (600, 50) GeV,

= 1.84 m τgen

c (600, 150) GeV,

= 4.29 m τgen

c (600, 275) GeV,

ATLAS

= 13 TeV, 139 fb-1

s

Obs. Exp.

−1

10 1 10

τ [m]

c

−4

10

−3

10

−2

10

−1

10

S) =

Φ, m HS (m

= 0.41 m τgen

c (1000, 50) GeV,

= 2.40 m τgen

c (1000, 275) GeV,

= 6.04 m τgen

c (1000, 475) GeV,

ATLAS

= 13 TeV, 139 fb-1

s

Obs. Exp.

−3

10 10⁻² 10⁻¹ 1 10

τ [m]

c

−4

10

−3

10

−2

10

−1

10 1

S) =

H, m HS (m

= 0.41 m τgen

c (125, 5) GeV,

= 0.58 m τgen

c (125, 16) GeV,

= 1.31 m τgen

c (125, 35) GeV,

= 1.05 m τgen

c (125, 55) GeV,

ATLAS

= 13 TeV, 139 fb-1

s

Obs. Exp.

= 100%

→ ss

BH

= 10%

→ ss

BH

= 1%

→ ss

BH

−2

10 10⁻¹ 1 10

τ [m]

c

−1

10 1 10 102

103

S) =

Φ, m HS (m

= 0.22 m τgen

c (60, 5) GeV,

= 0.66 m τgen

c (60, 16) GeV,

ATLAS

= 13 TeV, 139 fb-1

s

Obs. Exp.

1 10

τ [m]

c

−3

10

−2

10

−1

10

S) =

Φ, m HS (m

= 1.61 m τgen

c (400, 100) GeV,

= 1.25 m τgen

c (200, 50) GeV,

ATLAS

= 13 TeV, 139 fb-1

s

Obs. Exp.

mPhi = 600 GeV

Limits: Summary plots for all masses

28

mPhi = 125 GeV mPhi = 60 GeV

mPhi = 1000 GeV

mPhi = 200, 400 GeV

JHEP 06 (2022) 005

(29)

Displaced dark-photon jet search

29

• CNN and DNN taggers for multijets, BIB and cosmic muons

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 BIB Tagger Score

2

10−

−1

10 1

Entries normalised to unit area

ATLAS

)=(125, 0.4) GeV

γd

H, m FRVZ (m

)=(800, 0.4) GeV

γd

H, m FRVZ (m

)=(125, 0.4) GeV

γd

H, m HAHM (m

Collision BIB dataset

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 QCD Tagger Score

−3

10

−2

10

−1

10 1

)=(125, 0.4) GeV

γd

H, m FRVZ (m

)=(800, 0.4) GeV

γd

H, m FRVZ (m

)=(125, 0.4) GeV

γd

H, m HAHM (m

QCD multi-jet MC

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Cosmic-ray Tagger Score

2

10− 1

10−

1

ATLAS

)=(125, 0.4) GeV

γd

H, m FRVZ (m

)=(800, 0.4) GeV

γd

H, m FRVZ (m

)=(125, 0.4) GeV

γd

H, m HAHM (m

Cosmics (Empty BC)

arXiv:2206.12181