Accelerating the BSM interpretation of LHC data with machine learning

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

Cycle-based Cluster Variational Method for Direct and Inverse Inference

We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We end up with a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. The inverse problem of finding the couplings of a Markov random field from empirical covariances can be addressed region wise. It turns out that this can be done efficiently in particular in the Ising context, where fixed point equations can be derived along with a one-parameter log likelihood function to minimize. Numerical experiments confirm the effectiveness of these considerations both for the direct and inverse MRF inference.Comment: 47 pages, 16 figure

The Cluster Variation Method for Efficient Linkage Analysis on Extended Pedigrees

BACKGROUND: Computing exact multipoint LOD scores for extended pedigrees rapidly becomes infeasible as the number of markers and untyped individuals increase. When markers are excluded from the computation, significant power may be lost. Therefore accurate approximate methods which take into account all markers are desirable. METHODS: We present a novel method for efficient estimation of LOD scores on extended pedigrees. Our approach is based on the Cluster Variation Method, which deterministically estimates likelihoods by performing exact computations on tractable subsets of variables (clusters) of a Bayesian network. First a distribution over inheritances on the marker loci is approximated with the Cluster Variation Method. Then this distribution is used to estimate the LOD score for each location of the trait locus. RESULTS: First we demonstrate that significant power may be lost if markers are ignored in the multi-point analysis. On a set of pedigrees where exact computation is possible we compare the estimates of the LOD scores obtained with our method to the exact LOD scores. Secondly, we compare our method to a state of the art MCMC sampler. When both methods are given equal computation time, our method is more efficient. Finally, we show that CVM scales to large problem instances. CONCLUSION: We conclude that the Cluster Variation Method is as accurate as MCMC and generally is more efficient. Our method is a promising alternative to approaches based on MCMC sampling

Quantum Gravity in 2+1 Dimensions: The Case of a Closed Universe

In three spacetime dimensions, general relativity drastically simplifies, becoming a ``topological'' theory with no propagating local degrees of freedom. Nevertheless, many of the difficult conceptual problems of quantizing gravity are still present. In this review, I summarize the rather large body of work that has gone towards quantizing (2+1)-dimensional vacuum gravity in the setting of a spatially closed universe.Comment: 61 pages, draft of review for Living Reviews; comments, criticisms, additions, missing references welcome; v2: minor changes, added reference

Culture Adaptation Alters Transcriptional Hierarchies among Single Human Embryonic Stem Cells Reflecting Altered Patterns of Differentiation

We have used single cell transcriptome analysis to re-examine the substates of early passage, karyotypically Normal, and late passage, karyotypically Abnormal (‘Culture Adapted’) human embryonic stem cells characterized by differential expression of the cell surface marker antigen, SSEA3. The results confirmed that culture adaptation is associated with alterations to the dynamics of the SSEA3(+) and SSEA3(-) substates of these cells, with SSEA3(-) Adapted cells remaining within the stem cell compartment whereas the SSEA3(-) Normal cells appear to have differentiated. However, the single cell data reveal that these substates are characterized by further heterogeneity that changes on culture adaptation. Notably the Adapted population includes cells with a transcriptome substate suggestive of a shift to a more naïve-like phenotype in contrast to the cells of the Normal population. Further, a subset of the Normal SSEA3(+) cells expresses genes typical of endoderm differentiation, despite also expressing the undifferentiated stem cell genes, POU5F1 (OCT4) and NANOG, whereas such apparently lineage-primed cells are absent from the Adapted population. These results suggest that the selective growth advantage gained by genetically variant, culture adapted human embryonic stem cells may derive in part from a changed substate structure that influences their propensity for differentiation

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

The calcium channel β2 (CACNB2) subunit repertoire in teleosts

© 2008 Ebert et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Superparamagnetic colloids in viscous fluids

The influence of a magnetic field on the aggregation process of superparamagnetic colloids has been well known on short time for a few decades. However, the influence of important parameters, such as viscosity of the liquid, has received only little attention. Moreover, the equilibrium state reached after a long time is still challenging on some aspects. Indeed, recent experimental measurements show deviations from pure analytical models in extreme conditions. Furthermore, current simulations would require several years of computing time to reach equilibrium state under those conditions. In the present paper, we show how viscosity influences the characteristic time of the aggregation process, with experimental measurements in agreement with previous theories on transient behaviour. Afterwards, we performed numerical simulations on equivalent systems with lower viscosities. Below a critical value of viscosity, a transition to a new aggregation regime is observed and analysed. We noticed this result can be used to reduce the numerical simulation time from several orders of magnitude, without modifying the intrinsic physical behaviour of the particles. However, it also implies that, for high magnetic fields, granular gases could have a very different behaviour from colloidal liquids

Diacylglycerol regulates acute hypoxic pulmonary vasoconstriction via TRPC6

Background: Hypoxic pulmonary vasoconstriction (HPV) is an essential mechanism of the lung that matches blood perfusion to alveolar ventilation to optimize gas exchange. Recently we have demonstrated that acute but not sustained HPV is critically dependent on the classical transient receptor potential 6 (TRPC6) channel. However, the mechanism of TRPC6 activation during acute HPV remains elusive. We hypothesize that a diacylglycerol (DAG)-dependent activation of TRPC6 regulates acute HPV. Methods: We investigated the effect of the DAG analog 1-oleoyl-2-acetyl-sn-glycerol (OAG) on normoxic vascular tone in isolated perfused and ventilated mouse lungs from TRPC6-deficient and wild-type mice. Moreover, the effects of OAG, the DAG kinase inhibitor R59949 and the phospholipase C inhibitor U73122 on the strength of HPV were investigated compared to those on non-hypoxia-induced vasoconstriction elicited by the thromboxane mimeticum U46619. Results: OAG increased normoxic vascular tone in lungs from wild-type mice, but not in lungs from TRPC6-deficient mice. Under conditions of repetitive hypoxic ventilation, OAG as well as R59949 dose-dependently attenuated the strength of acute HPV whereas U46619-induced vasoconstrictions were not reduced. Like OAG, R59949 mimicked HPV, since it induced a dose-dependent vasoconstriction during normoxic ventilation. In contrast, U73122, a blocker of DAG synthesis, inhibited acute HPV whereas U73343, the inactive form of U73122, had no effect on HPV. Conclusion: These findings support the conclusion that the TRPC6-dependency of acute HPV is induced via DAG