| Records |
| Author |
Bertone, G.; Bozorgnia, N.; Kim, J.S.; Liem, S.; McCabe, C.; Otten, S.; Ruiz de Austri, R. |
| Title |
Identifying WIMP dark matter from particle and astroparticle data |
Type |
Journal Article |
| Year |
2018 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
| Volume |
03 |
Issue |
3 |
Pages |
026 - 42pp |
| Keywords |
dark matter detectors; dark matter experiments; dark matter theory |
| Abstract |
One of the most promising strategies to identify the nature of dark matter consists in the search for new particles at accelerators and with so-called direct detection experiments. Working within the framework of simplified models, and making use of machine learning tools to speed up statistical inference, we address the question of what we can learn about dark matter from a detection at the LHC and a forthcoming direct detection experiment. We show that with a combination of accelerator and direct detection data, it is possible to identify newly discovered particles as dark matter, by reconstructing their relic density assuming they are weakly interacting massive particles (WIMPs) thermally produced in the early Universe, and demonstrating that it is consistent with the measured dark matter abundance. An inconsistency between these two quantities would instead point either towards additional physics in the dark sector, or towards a non-standard cosmology, with a thermal history substantially different from that of the standard cosmological model. |
Address  |
[Bertone, Gianfranco; Bozorgnia, Nassim; Liem, Sebastian] Univ Amsterdam, GRAPPA Inst, Inst Theoret Phys Amsterdam, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands, Email: g.bertone@uva.nl; |
| Corporate Author |
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Thesis |
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| Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1475-7516 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000427501000002 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
3522 |
| Permanent link to this record |
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| Author |
Bertone, G.; Cerdeño, D.G.; Fornasa, M.; Ruiz de Austri, R.; Trotta, R. |
| Title |
Identification of dark matter particles with LHC and direct detection data |
Type |
Journal Article |
| Year |
2010 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
| Volume |
82 |
Issue |
5 |
Pages |
055008 - 7pp |
| Keywords |
|
| Abstract |
Dark matter (DM) is currently searched for with a variety of detection strategies. Accelerator searches are particularly promising, but even if weakly interacting massive particles are found at the Large Hadron Collider (LHC), it will be difficult to prove that they constitute the bulk of the DM in the Universe Omega(DM). We show that a significantly better reconstruction of the DM properties can be obtained with a combined analysis of LHC and direct detection data, by making a simple Ansatz on the weakly interacting massive particles local density rho(0)((chi) over bar1), i.e., by assuming that the local density scales with the cosmological relic abundance, (rho(0)((chi) over bar1)/rho(DM)) = (Omega(0)((chi) over bar1)/Omega(DM)). We demonstrate this method in an explicit example in the context of a 24-parameter supersymmetric model, with a neutralino lightest supersymmetric particle in the stau coannihilation region. Our results show that future ton-scale direct detection experiments will allow to break degeneracies in the supersymmetric parameter space and achieve a significantly better reconstruction of the neutralino composition and its relic density than with LHC data alone. |
| Address |
[Bertone, G.] Univ Zurich, Inst Theoret Phys, CH-8057 Zurich, Switzerland |
| Corporate Author |
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Thesis |
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| Publisher |
Amer Physical Soc |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1550-7998 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
|
| Notes |
ISI:000281741400005 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ elepoucu @ |
Serial |
380 |
| Permanent link to this record |
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| Author |
Bertone, G.; Cerdeño, D.G.; Fornasa, M.; Pieri, L.; Ruiz de Austri, R.; Trotta, R. |
| Title |
Complementarity of indirect and accelerator dark matter searches |
Type |
Journal Article |
| Year |
2012 |
Publication |
Physical Review D |
Abbreviated Journal |
Phys. Rev. D |
| Volume |
85 |
Issue |
5 |
Pages |
055014 - 10pp |
| Keywords |
|
| Abstract |
Even if supersymmetric particles are found at the Large Hadron Collider (LHC), it will be difficult to prove that they constitute the bulk of the dark matter (DM) in the Universe using LHC data alone. We study the complementarity of LHC and DM indirect searches, working out explicitly the reconstruction of the DM properties for a specific benchmark model in the coannihilation region of a 24-parameters supersymmetric model. Combining mock high-luminosity LHC data with presentday null searches for gamma rays from dwarf galaxies with the Fermi Large Area Telescope, we show that current Fermi Large Area Telescope limits already have the capability of ruling out a spurious wino-like solution which would survive using LHC data only, thus leading to the correct identification of the cosmological solution. We also demonstrate that upcoming Planck constraints on the reionization history will have a similar constraining power and discuss the impact of a possible detection of gamma rays from DM annihilation in the Draco dwarf galaxy with a Cherenkov-Telescope-Array-like experiment. Our results indicate that indirect searches can be strongly complementary to the LHC in identifying the DM particles, even when astrophysical uncertainties are taken into account. |
| Address |
[Bertone, G.] Univ Amsterdam, GRAPPA Inst, NL-1090 GL Amsterdam, Netherlands |
| Corporate Author |
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Thesis |
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| Publisher |
Amer Physical Soc |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1550-7998 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
|
| Notes |
WOS:000301647300005 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
948 |
| Permanent link to this record |
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| Author |
Begone, G.; Deisenroth, M.P.; Kim, J.S.; Liem, S.; Ruiz de Austri, R.; Welling, M. |
| Title |
Accelerating the BSM interpretation of LHC data with machine learning |
Type |
Journal Article |
| Year |
2019 |
Publication |
Physics of the Dark Universe |
Abbreviated Journal |
Phys. Dark Universe |
| Volume |
24 |
Issue |
|
Pages |
100293 - 5pp |
| Keywords |
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| Abstract |
The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically convergent scans of high-dimensional BSM theories is consequently challenging, and in practice unfeasible for very high-dimensional BSM theories. We present here a new machine learning method that accelerates the interpretation of LHC data, by learning the relationship between BSM theory parameters and data. As a proof-of-concept, we demonstrate that this technique accurately predicts natural SUSY signal events in two signal regions at the High Luminosity LHC, up to four orders of magnitude faster than standard techniques. The new approach makes it possible to rapidly and accurately reconstruct the theory parameters of complex BSM theories, should an excess in the data be discovered at the LHC. |
| Address |
[Begone, Gianfranco; Liem, Sebastian] Univ Amsterdam, GRAPPA, Sci Pk 904, NL-1098 XH Amsterdam, Netherlands, Email: jongsoo.kim@tu-dortmund.de |
| Corporate Author |
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Thesis |
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| Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2212-6864 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000465292500018 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
3994 |
| Permanent link to this record |
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| Author |
Balazs, C. et al; Mamuzic, J.; Ruiz de Austri, R. |
| Title |
A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications |
Type |
Journal Article |
| Year |
2021 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
| Volume |
05 |
Issue |
5 |
Pages |
108 - 46pp |
| Keywords |
Phenomenology of Field Theories in Higher Dimensions; Supersymmetry Phenomenology |
| Abstract |
Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensive to evaluate. We describe a number of global optimisation algorithms that are not yet widely used in particle astrophysics, benchmark them against random sampling and existing techniques, and perform a detailed comparison of their performance on a range of test functions. These include four analytic test functions of varying dimensionality, and a realistic example derived from a recent global fit of weak-scale supersymmetry. Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms. |
| Address |
[Balazs, Csaba] Monash Univ, Sch Phys & Astron, Melbourne, Vic 3800, Australia, Email: bstienen@science.ru.nl; |
| Corporate Author |
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Thesis |
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| Publisher |
Springer |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1029-8479 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000762408900002 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5149 |
| Permanent link to this record |
