Tootfinder

Chemical transformation of CO in evolving protoplanetary discs across stellar masses: a route to C-rich inner regions
Andrew D. Sellek, Ewine F. van Dishoeck
https://arxiv.org/abs/2507.11631

Chemical transformation of CO in evolving protoplanetary discs across stellar masses: a route to C-rich inner regions
Protoplanetary discs around Very Low Mass Stars (VLMS) show hydrocarbon-rich MIR spectra indicative of C/O>1 in their inner discs, in contrast to discs around higher-mass hosts which mostly show O-bearing species. One scenario proposed to elevate C/O in VLMS inner discs is the advection of O-depleted gas from the outer disc. However, if CO gas remains abundant, C/O can be at most ~1. We test if chemical transformation of CO into other species allows this transport scenario to produce C/O signif…

Arbitrary high-fidelity binomial codes from multiphoton spin-boson interactions
Pradip Laha, Peter van Loock
https://arxiv.org/abs/2507.08585 https://

Arbitrary high-fidelity binomial codes from multiphoton spin-boson interactions
Encoding a qubit in the continuous degrees of freedom of a quantum system, such as bosonic modes, is a powerful alternative to modern quantum error correction (QEC). Among the most prominent bosonic QEC codes, binomial codes provide protection against loss and dephasing errors by encoding logical states in superpositions of Fock states with binomially weighted coefficients. While much attention has been given to their error-correcting capabilities and integration into fault-tolerant architectur…

FastTrack: a fast method to evaluate mass transport in solid leveraging universal machine learning interatomic potential
Hanwen Kang, Tenglong Lu, Zhanbin Qi, Jiandong Guo, Sheng Meng, Miao Liu
https://arxiv.org/abs/2508.10505

FastTrack: a fast method to evaluate mass transport in solid leveraging universal machine learning interatomic potential
We introduce a rapid, accurate framework for computing atomic migration barriers in crystals by combining universal machine learning force fields (MLFFs) with 3D potential energy surface sampling and interpolation. Our method suppresses periodic self interactions via supercell expansion, builds a continuous PES from MLFF energies on a spatial grid, and extracts minimum energy pathways without predefined NEB images. Across twelve benchmark electrode and electrolyte materials including LiCoO2, Li…

Freeze-in production of scalaron dark matter in $f(R)$ gravity
Basabendu Barman, Ashmita Das, Rakesh Kumar SivaKumar, Rudra Pratap Udgata
https://arxiv.org/abs/2506.06436

Freeze-in production of scalaron dark matter in $f(R)$ gravity
We demonstrate that the scalaron, a scalar degree of freedom, emerging from the $f(R)$ theory of gravity, can account for the observed dark matter (DM) abundance if its mass is around the MeV scale, to ensure its cosmological stability. Focusing on two well-known $f(R)$ gravity models, we systematically show that if scalaron production proceeds via the freeze-in mechanism, the right relic abundance is satisfied over a very narrow window of reheating temperature $10^{14}\lesssim T_{\rm rh}\lesss…

DMER-Ranker: Learning to Rank Emotion Descriptions in the Absence of Ground Truth
Zheng Lian, Licai Sun, Haoyu Chen, Zebang Cheng, Fan Zhang, Ziyu Jia, Ziyang Ma, Fei Ma, Xiaojiang Peng, Jianhua Tao
https://arxiv.org/abs/2507.04278

DMER-Ranker: Learning to Rank Emotion Descriptions in the Absence of Ground Truth
Descriptive Multimodal Emotion Recognition (DMER) is a newly proposed task that aims to describe a person's emotional state using free-form natural language. Unlike traditional discriminative methods that rely on predefined emotion taxonomies, DMER provides greater flexibility in emotional expression, enabling fine-grained and interpretable emotion representations. However, this free-form prediction paradigm introduces significant challenges in evaluation. Existing methods either depend on grou…

Numerical approximation of a PDE-constrained Optimization problem that appears in Data-Driven Computational Mechanics
Pedro B. Bazon, Cristian G. Gebhardt, Gustavo C. Buscaglia, Roberto F. Ausas
https://arxiv.org/abs/2506.10894

Numerical approximation of a PDE-constrained Optimization problem that appears in Data-Driven Computational Mechanics
We investigate an optimization problem that arises when working within the paradigm of Data-Driven Computational Mechanics. In the context of the diffusion-reaction problem, such an optimization problem seeks for the continuous primal fields (gradient and flux) that are closest to some predefined discrete fields taken from a material data set. The optimization is performed over primal fields that satisfy the physical conservation law and the geometrical compatibility. We consider a reaction ter…

Single Block On
Paritosh Ranjan, Surajit Majumder, Prodip Roy
https://arxiv.org/abs/2507.06236 https://arxiv.org/pdf/2507.06236

Single Block On
In the digital age, individuals increasingly maintain active presences across multiple platforms ranging from social media and messaging applications to professional and communication tools. However, the current model for managing user level privacy and abuse is siloed, requiring users to block undesirable contacts independently on each platform. This paper introduces Single Block On (SBO) a unified and interoperable system enabling users to block an individual once and have that block propagat…

Understanding the Error Sensitivity of Privacy-Aware Computing
Mat\'ias Mazzanti (University of Buenos Aires), Esteban Mocskos (University of Buenos Aires), Augusto Vega (IBM T. J. Watson Research Center), Pradip Bose (IBM T. J. Watson Research Center)
https://arxiv.org/abs/2506.07957

Understanding the Error Sensitivity of Privacy-Aware Computing
Homomorphic Encryption (HE) enables secure computation on encrypted data without decryption, allowing a great opportunity for privacy-preserving computation. In particular, domains such as healthcare, finance, and government, where data privacy and security are of utmost importance, can benefit from HE by enabling third-party computation and services on sensitive data. In other words, HE constitutes the "Holy Grail" of cryptography: data remains encrypted all the time, being protected while in …

Evidence For Turbulent Concentration In Particle-Laden Midplane Layers of Planet-Forming Disks
Orkan M. Umurhan, Debanjan Sengupta, Paul R. Estrada
https://arxiv.org/abs/2508.05858

Evidence For Turbulent Concentration In Particle-Laden Midplane Layers of Planet-Forming Disks
In this study we investigate the axisymmetric, weakly turbulent state of settled particle layers in a localized model of a protoplanetary disk. We focus on conditions in which the large-scale axisymmetric filaments typically associated with the streaming instability (SI) either cannot form or have not yet developed. Under these circumstances, we observe small-scale particle clumping consistent with turbulent concentration (TC), in which short particle filaments collect along regions of high gas…

Grand Design Spiral Arms in the Compact, Embedded Protoplanetary Disk of Haro 6-13
Jane Huang, Masataka Aizawa, Jaehan Bae, Sean M. Andrews, Myriam Benisty, Edwin A. Bergin, Stefano Facchini, Christian Ginski, Michael K\"uffmeier
https://arxiv.org/abs/2506.06433

Grand Design Spiral Arms in the Compact, Embedded Protoplanetary Disk of Haro 6-13
Millimeter continuum spiral arms have so far only been detected in a handful of protoplanetary disks, and thus we have a limited understanding of the circumstances in which they can form. In particular, substructures in small disks ($R\lessapprox 50$ au) have not been well-characterized in comparison with large disks. We present ALMA 1.3 mm continuum observations of the disk around the T Tauri star Haro 6-13 at a resolution of $\sim0.04''$ ($\sim5$ au). A pair of low-contrast spiral arms are de…