952 citations · 3.4k across the 79 of their papers we have counts for
82 papers
Meta-learning accelerates detector design optimization
Maxim Borisyak, Nikita Gladin, Andrey Ustyuzhanin
The quality of a detector design is ultimately determined by the quality of the inference it enables, that is, by the accuracy with which the quantities of interest are reconstruct…
Generative design of inorganic materials
Jose Recatala-Gomez, Haiwen Dai, Zhu Ruiming +9
Materials discovery is fundamental to advance next-generation technologies as well as for sustainable and circular economy. Beyond computational screening, generative models are ef…
Friction-Augmented Drifting Models for Resource-Efficient Domain Translation
Arkadii Kazanskii, Tatiana Petrova, Andrey Ustyuzhanin +3
Single-step generators promise high-fidelity synthesis at a fraction of the inference and training cost of ordinary differential equation (ODE)-based flow models, a central concern…
On the Codesign of Scientific Experiments and Industrial Systems
Tommaso Dorigo, Pietro Vischia, Shahzaib Abbas +84
The optimization of large experiments in fundamental science, such as detectors for subnuclear physics at particle colliders, shares with the optimization of complex systems for in…
MiAD: Mirage Atom Diffusion for De Novo Crystal Generation
Andrey Okhotin, Maksim Nakhodnov, Nikita Kazeev +3
In recent years, diffusion-based models have demonstrated exceptional performance in searching for simultaneously stable, unique, and novel (S.U.N.) crystalline materials. However,…
ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation
Ekaterina Trofimova, Zosia Shamina, Maria Selifanova +7
We introduce ML2B, the first benchmark for evaluating cross-lingual task comprehension in end-to-end ML pipeline generation by large language models. Despite growing global AI adop…
Inverse Design of Broadband Antennas for Terahertz Devices Based on 2D Materials
M. Lukianov, A. Maevskiy, N. Kazeev +5
Terahertz (THz) technology, a cornerstone of next-generation high-speed communication and sensing, has long been hindered by impedance mismatch challenges that limit device perform…
Time-local stochastic equation of motion for solid ionic electrolytes
Aleksandr Rodin, Ben Andrew Olsen, Andrey Ustyuzhanin +1
Numerical studies of ionic motion through solid electrolytes commonly involve static nudged-elastic band (NEB) methods or costly \emph{ab initio} molecular dynamics (AIMD). Buildin…
Studies of Hadronic Showers in SND@LHC
LHC Collaboration
The SND@LHC experiment was built for observing neutrinos arising from LHC pp collisions. The detector consists of two sections: a target instrumented with SciFi modules and a hadro…
Multi-property directed generative design of inorganic materials through Wyckoff-augmented transfer learning
Shuya Yamazaki, Wei Nong, Ruiming Zhu +3
Accelerated materials discovery is an urgent demand to drive advancements in fields such as energy conversion, storage, and catalysis. Property-directed generative design has emerg…
Wyckoff Transformer: Generation of Symmetric Crystals
Nikita Kazeev, Wei Nong, Ignat Romanov +4
Crystal symmetry plays a fundamental role in determining its physical, chemical, and electronic properties such as electrical and thermal conductivity, optical and polarization beh…
Observation of collider neutrinos without final state muons with the SND@LHC experiment
LHC Collaboration
We report the observation of neutrino interactions without final state muons at the LHC, with a significance of 6.4. A data set of proton-proton collisions at …
Predicting ionic conductivity in solids from the machine-learned potential energy landscape
Artem Maevskiy, Alexandra Carvalho, Emil Sataev +5
Discovering new superionic materials is essential for advancing solid-state batteries, which offer improved energy density and safety compared to the traditional lithium-ion batter…
Local-time formula for dissipation in solid ionic electrolytes
A. Rodin, B. A. Olsen, A. Ustyuzhanin +2
When ions move through solids, they interact with the solid's constituent atoms and cause them to vibrate around their equilibrium points. This vibration, in turn, modifies the pot…
Linguacodus: A Synergistic Framework for Transformative Code Generation in Machine Learning Pipelines
Ekaterina Trofimova, Emil Sataev, Andrey E. Ustyuzhanin
In the ever-evolving landscape of machine learning, seamless translation of natural language descriptions into executable code remains a formidable challenge. This paper introduces…
Measurement of the muon flux at the SND@LHC experiment
LHC Collaboration
The Scattering and Neutrino Detector at the LHC (\SND) started taking data at the beginning of Run 3 of the LHC. The experiment is designed to perform measurements with neutrinos p…
Observation of collider muon neutrinos with the SND@LHC experiment
LHC Collaboration
We report the direct observation of muon neutrino interactions with the SND@LHC detector at the Large Hadron Collider. A data set of proton-proton collisions at …
Directional Sensitivity of the NEWSdm Experiment to Cosmic Ray Boosted Dark Matter
N. Y. Agafonova, A. Alexandrov, A. M. Anokhina +54
We present a study of a directional search for Dark Matter boosted forward when scattered by cosmic-ray nuclei, using a module of the NEWSdm experiment. The boosted Dark Matter flu…
The Tracking Machine Learning challenge : Throughput phase
Sabrina Amrouche, Laurent Basara, Paolo Calafiura +18
This paper reports on the second "Throughput" phase of the Tracking Machine Learning (TrackML) challenge on the Codalab platform. As in the first "Accuracy" phase, the participants…
Sensitivity of the SHiP experiment to dark photons decaying to a pair of charged particles
SHiP Collaboration, C. Ahdida, A. Akmete +331
Dark photons are hypothetical massive vector particles that could mix with ordinary photons. The simplest theoretical model is fully characterised by only two parameters: the mass…
Deep learning for Directional Dark Matter search
Artem Golovatiuk, Giovanni De Lellis, Andrey Ustyuzhanin
We provide an algorithm for detection of possible dark matter particle interactions recorded within NEWSdm detector. The NEWSdm (Nuclear Emulsions for WIMP Search directional measu…
Study of the and states in decays
LHCb collaboration, R. Aaij, C. Abellán Beteta +956
The decays are studied using a data set corresponding to an integrated luminosity of 9fb collected with the LHCb detector in proton-proton co…
SND@LHC
SHiP Collaboration, C. Ahdida, A. Akmete +341
We propose to build and operate a detector that, for the first time, will measure the process at the LHC and search for feebly interacting particles (FIPs) in an unexplor…
Black-Box Optimization with Local Generative Surrogates
Sergey Shirobokov, Vladislav Belavin, Michael Kagan +2
We propose a novel method for gradient-based optimization of black-box simulators using differentiable local surrogate models. In fields such as physics and engineering, many proce…