115 citations · 322 across the 12 of their papers we have counts for
12 papers
Apparent ice accumulation rate in East Antarctica: Relation with temperature and thinning pattern
Radhendushka Srivastava, Debasis Sengupta, Prosenjit Ghosh
We present here formal evidence of a strong linkage between temperature and East Antarctic ice accumulation over the past eight hundred kiloyears, after accounting for thinning. Th…
A semi-parametric model for assessing the effect of temperature on ice accumulation rate from Antarctic ice core data
Radhendushka Srivastava, Debasis Sengupta
In this paper, we present a semiparametric model for describing the effect of temperature on Antarctic ice accumulation on a paleoclimatic time scale. The model is motivated by sha…
PC-Droid: Faster diffusion and improved quality for particle cloud generation
Matthew Leigh, Debajyoti Sengupta, John Andrew Raine +2
Building on the success of PC-JeDi we introduce PC-Droid, a substantially improved diffusion model for the generation of jet particle clouds. By leveraging a new diffusion formulat…
The Interplay of Machine Learning--based Resonant Anomaly Detection Methods
Tobias Golling, Gregor Kasieczka, Claudius Krause +6
Machine learning--based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD metho…
CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation
Debajyoti Sengupta, Samuel Klein, John Andrew Raine +1
Model independent techniques for constructing background data templates using generative models have shown great promise for use in searches for new physics processes at the LHC. W…
Yield Strength-Plasticity Trade-Off and Uncertainty Quantification for Machine-learning-based Design of Refractory High-Entropy Alloys
Stephen A. Giles, Hugh Shortt, Peter K. Liaw +1
Development of process-structure-property relationships in materials science is an important and challenging frontier which promises improved materials and reduced time and cost in…
The Mass-ive Issue: Anomaly Detection in Jet Physics
Tobias Golling, Takuya Nobe, Dimitrios Proios +8
In the hunt for new and unobserved phenomena in particle physics, attention has turned in recent years to using advanced machine learning techniques for model independent searches.…
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant +3
In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with tra…
Compton-Thick AGN in the NuSTAR era VIII: A joint NuSTAR-XMM-Newton monitoring of the changing-look Compton-thick AGN NGC 1358
Stefano Marchesi, Xiurui Zhao, Núria Torres-Albà +18
We present the multi-epoch monitoring with NuSTAR and XMM-Newton of NGC 1358, a nearby Seyfert 2 galaxy whose properties made it a promising candidate X-ray changing look AGN, i.e.…
CURTAINs for your Sliding Window: Constructing Unobserved Regions by Transforming Adjacent Intervals
John Andrew Raine, Samuel Klein, Debajyoti Sengupta +1
We propose a new model independent technique for constructing background data templates for use in searches for new physics processes at the LHC. This method, called CURTAINs, uses…
Recoil imaging for directional detection of dark matter, neutrinos, and physics beyond the Standard Model
C. A. J. O'Hare, D. Loomba, K. Altenmüller +164
Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detecto…
Dilepton constraints in the Inert Doublet Model from Run 1 of the LHC
G. Belanger, B. Dumont, A. Goudelis +3
Searches in final states with two leptons plus missing transverse energy, targeting supersymmetric particles or invisible decays of the Higgs boson, were performed during Run 1 of…