Tootfinder

Precision premium transformation -- a high-precision astrometric solution based on the precision premium curve
Z. J. Zheng, Q. Y. Peng, F. R. Lin, D. Li, Y. Zheng
https://arxiv.org/abs/2403.05883

Precision premium transformation -- a high-precision astrometric solution based on the precision premium curve
Context. In Gaia era, atmospheric turbulence, which causes stochastic wander of a star image, is a fundamental limitation to the astrometric accuracy of ground-based optical imaging. However, the positional bias caused by turbulence (called turbulence error here) can be effectively reduced by measuring a target relative to another reference (a star or a fast-moving target) which locates in the range of only several tens of arcsec, since they suffer from similar turbulence errors. This phenomeno…

Kyiv: Russia uses new guided bombs in Myrnohrad attack: https://benborges.xyz/2024/03/10/kyiv-russia-uses.html

HDA-LVIO: A High-Precision LiDAR-Visual-Inertial Odometry in Urban Environments with Hybrid Data Association
Jian Shi, Wei Wang, Mingyang Qi, Xin Li, Ye Yan
https://arxiv.org/abs/2403.06590

HDA-LVIO: A High-Precision LiDAR-Visual-Inertial Odometry in Urban Environments with Hybrid Data Association
To enhance localization accuracy in urban environments, an innovative LiDAR-Visual-Inertial odometry, named HDA-LVIO, is proposed by employing hybrid data association. The proposed HDA_LVIO system can be divided into two subsystems: the LiDAR-Inertial subsystem (LIS) and the Visual-Inertial subsystem (VIS). In the LIS, the LiDAR pointcloud is utilized to calculate the Iterative Closest Point (ICP) error, serving as the measurement value of Error State Iterated Kalman Filter (ESIKF) to construct…

The Impact of Quantization on the Robustness of Transformer-based Text Classifiers
Seyed Parsa Neshaei, Yasaman Boreshban, Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel
https://arxiv.org/abs/2403.05365

The Impact of Quantization on the Robustness of Transformer-based Text Classifiers
Transformer-based models have made remarkable advancements in various NLP areas. Nevertheless, these models often exhibit vulnerabilities when confronted with adversarial attacks. In this paper, we explore the effect of quantization on the robustness of Transformer-based models. Quantization usually involves mapping a high-precision real number to a lower-precision value, aiming at reducing the size of the model at hand. To the best of our knowledge, this work is the first application of quanti…

This https://arxiv.org/abs/2404.05392 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

T-DEED: Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in Sports Videos
In this paper, we introduce T-DEED, a Temporal-Discriminability Enhancer Encoder-Decoder for Precise Event Spotting in sports videos. T-DEED addresses multiple challenges in the task, including the need for discriminability among frame representations, high output temporal resolution to maintain prediction precision, and the necessity to capture information at different temporal scales to handle events with varying dynamics. It tackles these challenges through its specifically designed architec…

LATTE: Low-Precision Approximate Attention with Head-wise Trainable Threshold for Efficient Transformer
Jiing-Ping Wang (Andy), Ming-Guang Lin (Andy), An-Yeu (Andy), Wu
https://arxiv.org/abs/2404.07519

LATTE: Low-Precision Approximate Attention with Head-wise Trainable Threshold for Efficient Transformer
With the rise of Transformer models in NLP and CV domain, Multi-Head Attention has been proven to be a game-changer. However, its expensive computation poses challenges to the model throughput and efficiency, especially for the long sequence tasks. Exploiting the sparsity in attention has been proven to be an effective way to reduce computation. Nevertheless, prior works do not consider the various distributions among different heads and lack a systematic method to determine the threshold. To a…

This https://arxiv.org/abs/2307.07371 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Two-Way Quantum Time Transfer: A Method for Daytime Space-Earth Links
High-precision remote clock synchronization is crucial for many classical and quantum network applications. Evaluating options for space-Earth links, we find that traditional solutions may not produce the desired synchronization for low Earth orbits and unnecessarily complicate quantum-networking architectures. Demonstrating an alternative, we use commercial off-the-shelf quantum-photon sources and detection equipment to synchronize two remote clocks across our freespace testbed utilizing a met…

This https://arxiv.org/abs/2307.11153 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Exploring the impact of high-precision top-quark pair production data on the structure of the proton at the LHC
The impact of recent LHC top-quark pair production single differential cross section measurements at 13 TeV collision energy on the structure of the proton is explored. In particular, the impact of these high-precision data on the gluon and other parton distribution functions (PDFs) of the proton at intermediate and large partonic momentum fraction $x$ is analyzed. This study extends the CT18 global analysis framework to include these new data. The interplay between top-quark pair and inclusive…

This https://arxiv.org/abs/2307.12609 has been replaced.
link: https://scholar.google.com/scholar?q=a

AndroLibZoo: A Reliable Dataset of Libraries Based on Software Dependency Analysis
Android app developers extensively employ code reuse, integrating many third-party libraries into their apps. While such integration is practical for developers, it can be challenging for static analyzers to achieve scalability and precision when libraries account for a large part of the code. As a direct consequence, it is common practice in the literature to consider developer code only during static analysis --with the assumption that the sought issues are in developer code rather than the l…

A method for accelerating low precision operations by sparse matrix multiplication
Hongyaoxing Gu
https://arxiv.org/abs/2403.06924 https://

A method for accelerating low precision operations by sparse matrix multiplication
In recent years, the fervent demand for computational power across various domains has prompted hardware manufacturers to introduce specialized computing hardware aimed at enhancing computational capabilities. Particularly, the utilization of tensor hardware supporting low precision has gained increasing prominence in scientific research. However, the use of low-precision tensor hardware for computational acceleration often introduces errors, posing a fundamental challenge of simultaneously ach…

A Copula Graphical Model for Multi-Attribute Data using Optimal Transport
Qi Zhang, Bing Li, Lingzhou Xue
https://arxiv.org/abs/2404.06735 https://<…

A Copula Graphical Model for Multi-Attribute Data using Optimal Transport
Motivated by modern data forms such as images and multi-view data, the multi-attribute graphical model aims to explore the conditional independence structure among vectors. Under the Gaussian assumption, the conditional independence between vectors is characterized by blockwise zeros in the precision matrix. To relax the restrictive Gaussian assumption, in this paper, we introduce a novel semiparametric multi-attribute graphical model based on a new copula named Cyclically Monotone Copula. This…

This https://arxiv.org/abs/2211.05907 has been replaced.
link: https://scholar.google.com/scholar?q=a

Microscopics of de Sitter Entropy from Precision Holography
We calculate quantum corrections to the entropy of four-dimensional de Sitter space induced by higher-derivative terms in the gravitational action and by one-loop effects. Employing the intertwinement in semiclassical gravity of Euclidean de Sitter and anti-de Sitter saddles, we embed effective de Sitter gravity theories in M-theory and express the entropy in terms of the regularized Euclidean anti-de Sitter action on an auxiliary $\mathrm{EAdS}_4 \times S^7/\mathbb{Z}_k$ background. We conject…

Precision Air Flow Control via EHD Actuator: A Co-simulation and Control Design Case Study
Afshin Shaygani, Kazimierz Adamiak, Mehrdad R. Kermani
https://arxiv.org/abs/2402.06588 …

Precision Air Flow Control via EHD Actuator: A Co-simulation and Control Design Case Study
A Dielectric Barrier Discharge (DBD) plasma actuator for controlling airflow is proposed. It consists of diverging and converging nozzles, two concentric cylinders and an actuator mounted in-between the two cylinders. The actuator employs electrohydrodynamic (EHD) body force to induce an air jet within the air gap between the two cylinders, effectively creating a suction area while passing through the diverging nozzle, due to the Coanda effect. While merging with the air stream inside the inner…

This https://arxiv.org/abs/2209.04783 has been replaced.
link: https://scholar.google.com/scholar?q=a

Operational verification of the existence of a spacetime manifold
We argue that there exists an operational way to establish the objective reality of the notions of space and time. Specifically, we propose a theory-independent protocol for a gedanken-experiment, whose outcome is a signal establishing the observability of the spacetime manifold, without a priori assuming its existence. The experimental signal contains the information about the dimension and the topology of spacetime (with the currently achievable precision), and establishes its manifold struct…

This https://arxiv.org/abs/2403.04982 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

A 28.6 mJ/iter Stable Diffusion Processor for Text-to-Image Generation with Patch Similarity-based Sparsity Augmentation and Text-based Mixed-Precision
This paper presents an energy-efficient stable diffusion processor for text-to-image generation. While stable diffusion attained attention for high-quality image synthesis results, its inherent characteristics hinder its deployment on mobile platforms. The proposed processor achieves high throughput and energy efficiency with three key features as solutions: 1) Patch similarity-based sparsity augmentation (PSSA) to reduce external memory access (EMA) energy of self-attention score by 60.3 %, le…

HDA-LVIO: A High-Precision LiDAR-Visual-Inertial Odometry in Urban Environments with Hybrid Data Association
Jian Shi, Wei Wang, Mingyang Qi, Xin Li, Ye Yan
https://arxiv.org/abs/2403.06590

HDA-LVIO: A High-Precision LiDAR-Visual-Inertial Odometry in Urban Environments with Hybrid Data Association
To enhance localization accuracy in urban environments, an innovative LiDAR-Visual-Inertial odometry, named HDA-LVIO, is proposed by employing hybrid data association. The proposed HDA_LVIO system can be divided into two subsystems: the LiDAR-Inertial subsystem (LIS) and the Visual-Inertial subsystem (VIS). In the LIS, the LiDAR pointcloud is utilized to calculate the Iterative Closest Point (ICP) error, serving as the measurement value of Error State Iterated Kalman Filter (ESIKF) to construct…

The Impact of Quantization on the Robustness of Transformer-based Text Classifiers
Seyed Parsa Neshaei, Yasaman Boreshban, Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel
https://arxiv.org/abs/2403.05365

The Impact of Quantization on the Robustness of Transformer-based Text Classifiers
Transformer-based models have made remarkable advancements in various NLP areas. Nevertheless, these models often exhibit vulnerabilities when confronted with adversarial attacks. In this paper, we explore the effect of quantization on the robustness of Transformer-based models. Quantization usually involves mapping a high-precision real number to a lower-precision value, aiming at reducing the size of the model at hand. To the best of our knowledge, this work is the first application of quanti…

Electroweak, QCD and flavour physics studies with ATLAS data from Run 2 of the LHC
ATLAS Collaboration
https://arxiv.org/abs/2404.06829 https://

Electroweak, QCD and flavour physics studies with ATLAS data from Run 2 of the LHC
A summary of precision measurements sensitive to electroweak, QCD and quark-flavour effects performed by the ATLAS Collaboration at the Large Hadron Collider is reported. The measurements are predominantly performed on proton-proton ($pp$) collision data recorded at a centre-of-mass energy of 13 TeV taken from 2015 to 2018, with an integrated luminosity of up to 140 fb$^{-1}$, with some results based on $pp$ and Pb+Pb data recorded at lower nucleon centre-of-mass energies. The results cover a w…

Wall Street investors push Norfolk Southern to copy CSX's scheme that boosted profits at expense of workers & customers with "precision scheduled railroading." Claim that they can avoid hurting customers by phasing it in over 3 years. https://www.nytimes.com/2024/…

Norfolk Southern Faces Activist Investor Challenge
A year after a derailment in Ohio raised questions about rail safety, an investment firm is seeking to install new management in an effort to increase profits.

This https://arxiv.org/abs/2401.15242 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Direct high-precision measurement of the mass difference of $^{77}$As-$^{77}$Se related to neutrino mass determination
The first direct determination of the ground-state-to-ground-state ${β^{-}}$-decay $Q$-value of $^{77}$As to $^{77}$Se was performed by measuring their atomic mass difference utilizing the double Penning trap mass spectrometer, JYFLTRAP. The resulting $Q$-value is 684.463(70) keV, representing a remarkable 24-fold improvement in precision compared to the value reported in the most recent Atomic Mass Evaluation (AME2020). With the significant reduction of the uncertainty of the ground-state-to-…

A new way to evaluate G-Wishart normalising constants via Fourier analysis
Ching Wong, Giusi Moffa, Jack Kuipers
https://arxiv.org/abs/2404.06803 https://<…

A new way to evaluate G-Wishart normalising constants via Fourier analysis
The G-Wishart distribution is an essential component for the Bayesian analysis of Gaussian graphical models as the conjugate prior for the precision matrix. Evaluating the marginal likelihood of such models usually requires computing high-dimensional integrals to determine the G-Wishart normalising constant. Closed-form results are known for decomposable or chordal graphs, while an explicit representation as a formal series expansion has been derived recently for general graphs. The nested infi…

Exploring Physiological Responses in Virtual Reality-based Interventions for Autism Spectrum Disorder: A Data-Driven Investigation
Gianpaolo Alvari, Ersilia Vallefuoco, Melanie Cristofolini, Elio Salvadori, Marco Dianti, Alessia Moltani, Davide Dal Castello, Paola Venuti, Cesare Furlanello
https://arxiv.org/abs/2404.07159…

Exploring Physiological Responses in Virtual Reality-based Interventions for Autism Spectrum Disorder: A Data-Driven Investigation
Virtual Reality (VR) has emerged as a promising tool for enhancing social skills and emotional well-being in individuals with Autism Spectrum Disorder (ASD). Through a technical exploration, this study employs a multiplayer serious gaming environment within VR, engaging 34 individuals diagnosed with ASD and employing high-precision biosensors for a comprehensive view of the participants' arousal and responses during the VR sessions. Participants were subjected to a series of 3 virtual scenarios…

Sustainable and Precision Agriculture with the Internet of Everything (IoE)
Adil Z Babar, \"Ozg\"ur B. Akan
https://arxiv.org/abs/2404.06341 http…

Sustainable and Precision Agriculture with the Internet of Everything (IoE)
The accelerated pace of global population growth underscores the crucial role of the agricultural sector in mitigating food scarcity, as well as in supporting livelihoods through employment opportunities and bolstering national economies. This sector faces several critical challenges, including resource depletion, socioeconomic issues, gaps in technology and innovation, and the impact of climate change. The introduction of mechanization has significantly transformed agriculture by enhancing sus…

Spectrogram-Based Detection of Auto-Tuned Vocals in Music Recordings
Mahyar Gohari, Paolo Bestagini, Sergio Benini, Nicola Adami
https://arxiv.org/abs/2403.05380

Spectrogram-Based Detection of Auto-Tuned Vocals in Music Recordings
In the domain of music production and audio processing, the implementation of automatic pitch correction of the singing voice, also known as Auto-Tune, has significantly transformed the landscape of vocal performance. While auto-tuning technology has offered musicians the ability to tune their vocal pitches and achieve a desired level of precision, its use has also sparked debates regarding its impact on authenticity and artistic integrity. As a result, detecting and analyzing Auto-Tuned vocals…

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys
Nathan Johnson, Aashwin Ananda Mishra, Apurva Mehta
https://arxiv.org/abs/2403.06329

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys
The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a beginner but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting comp…

This https://arxiv.org/abs/2311.16472 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Combining critical and quantum metrology
Critical metrology relies on the precise preparation of a system in its ground state near a quantum phase transition point where quantum correlations get very strong. Typically this increases the quantum Fisher information with respect to changes in system parameters and thus improves the optimally possible measurement precision limited by the Cramér-Rao bound. Hence critical metrology involves encoding information about the unknown parameter in changes of the system's ground state. Conversely…

The R2D2 deep neural network series paradigm for fast precision imaging in radio astronomy
Amir Aghabiglou, Chung San Chu, Arwa Dabbech, Yves Wiaux
https://arxiv.org/abs/2403.05452

The R2D2 deep neural network series paradigm for fast precision imaging in radio astronomy
Radio-interferometric (RI) imaging entails solving high-resolution high-dynamic range inverse problems from large data volumes. Recent image reconstruction techniques grounded in optimization theory have demonstrated remarkable capability for imaging precision, well beyond CLEAN's capability. These range from advanced proximal algorithms propelled by handcrafted regularization operators, such as the SARA family, to hybrid plug-and-play (PnP) algorithms propelled by learned regularization denois…

This https://arxiv.org/abs/2401.10326 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

The Smallness of Matter Effects in Long-Baseline Muon Neutrino Disappearance
Current long-baseline accelerator experiments, NOvA and T2K, are making excellent measurements of neutrino oscillations and the next generation of experiments, DUNE and HK, will make measurements at the $\mathcal O(1\%)$ level of precision. These measurements are a combination of the appearance channel which is more challenging experimentally but depends on many oscillation parameters, and the disappearance channel which is somewhat easier and allows for precision measurements of the atmospheri…

Bootstrap percolation is local
Ivailo Hartarsky, Augusto Teixeira
https://arxiv.org/abs/2404.07903 https://arxiv.org/pdf/2404.07903…

Bootstrap percolation is local
Metastability thresholds lie at the heart of bootstrap percolation theory. Yet proving precise lower bounds is notoriously hard. We show that for two of the most classical models, two-neighbour and Froböse, upper bounds are sharp to essentially arbitrary precision, by linking them to their local counterparts. In Froböse bootstrap percolation, iteratively, any vertex of the square lattice that is the only healthy vertex of a $1\times1$ square becomes infected and infections never heal. We pr…

Inverse solving the Schr\"odinger equation for precision alignment of a microcavity
Charlie Mattschas, Marius Puplauskis, Chris Toebes, Violetta Sharoglazova, Jan Klaers
https://arxiv.org/abs/2404.07760

Inverse solving the Schrödinger equation for precision alignment of a microcavity
In paraxial approximation, the electromagnetic eigenmodes inside an optical microresonator can be derived from a Schrödinger-type eigenvalue problem. In this framework, tilting the cavity mirrors effectively introduces a linear potential to the system. In our work, we apply solution strategies for inverse problems to precisely determine and control the relative orientation of two mirrors forming an optical microcavity. Our approach employs the inversion of the Schrödinger equation to reconstr…

This https://arxiv.org/abs/2309.13774 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Combinatorial summation of Feynman diagrams: Equation of state of the 2D SU(N) Hubbard model
Feynman's diagrammatic series is a common language for a formally exact theoretical description of systems of infinitely-many interacting quantum particles, as well as a foundation for precision computational techniques. Here we introduce a universal framework for efficient summation of connected or skeleton Feynman diagrams for generic quantum many-body systems. It is based on an explicit combinatorial construction of the sum of the integrands by dynamic programming, at a computational cost th…

Attempting to Prove the Riemann Hypothesis through the Reflection Formula
Farid Kenas
https://arxiv.org/abs/2403.05347 https://arxiv.…

Attempting to Prove the Riemann Hypothesis through the Reflection Formula
The Riemann Hypothesis, originally proposed by the eminent mathematician Bernard Riemann in 1859, remains one of the most profound challenges in number theory. It posits that all non-trivial zeros of the Riemann zeta function ζ(s) are concentrated precisely along the critical line where the real part equals 1/2. In this paper, our aim is to present an attempt to prove this conjecture. Our approach relies on the use of the reflection formula. By applying this tool with precision and insight, we…

Controllable seismic velocity synthesis using generative diffusion models
Fu Wang, Xinquan Huang, Tariq Alkhalifah
https://arxiv.org/abs/2402.06277 https:/…

Controllable seismic velocity synthesis using generative diffusion models
Accurate seismic velocity estimations are vital to understanding Earth's subsurface structures, assessing natural resources, and evaluating seismic hazards. Machine learning-based inversion algorithms have shown promising performance in regional (i.e., for exploration) and global velocity estimation, while their effectiveness hinges on access to large and diverse training datasets whose distributions generally cover the target solutions. Additionally, enhancing the precision and reliability of …

IsoPredict: Dynamic Predictive Analysis for Detecting Unserializable Behaviors in Weakly Isolated Data Store Applications
Chujun Geng, Spyros Blanas, Michael D. Bond, Yang Wang
https://arxiv.org/abs/2404.04621

IsoPredict: Dynamic Predictive Analysis for Detecting Unserializable Behaviors in Weakly Isolated Data Store Applications
This paper presents the first dynamic predictive analysis for data store applications under weak isolation levels, called Isopredict. Given an observed serializable execution of a data store application, Isopredict generates and solves SMT constraints to find an unserializable execution that is a feasible execution of the application. Isopredict introduces novel techniques that handle divergent application behavior; solve mutually recursive sets of constraints; and balance coverage, precision, …

Towards a realistic noise modelling of quantum sensors for future satellite gravity missions
Jo\~ao Encarna\c{c}\~ao, Christian Siemes, Ilias Daras, Olivier Carraz, Aaron Strangfeld, Philipp Zingerle, Roland Pail
https://arxiv.org/abs/2404.07835

Towards a realistic noise modelling of quantum sensors for future satellite gravity missions
Cold Atom Interferometry accelerometers and gradiometers have emerged as promising candidates for future gravimetric satellite missions due to their potential for detecting gravitational forces and gradients with high precision and accuracy. Mapping the Earth's gravity field from space offers valuable insights into climate change, hydro- and biosphere evolution, and seismic activity prediction. Current satellite gravimetry missions have demonstrated the utility of gravity data in understanding …

Efficient and Provably Convergent Computation of Information Bottleneck: A Semi-Relaxed Approach
Lingyi Chen, Shitong Wu, Jiachuan Ye, Huihui Wu, Wenyi Zhang, Hao Wu
https://arxiv.org/abs/2404.04862

Efficient and Provably Convergent Computation of Information Bottleneck: A Semi-Relaxed Approach
Information Bottleneck (IB) is a technique to extract information about one target random variable through another relevant random variable. This technique has garnered significant interest due to its broad applications in information theory and deep learning. Hence, there is a strong motivation to develop efficient numerical methods with high precision and theoretical convergence guarantees. In this paper, we propose a semi-relaxed IB model, where the Markov chain and transition probability co…

This https://arxiv.org/abs/2309.07215 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

A New Probe of the High-z BAO scale: BAO tomography With CMB $\times$ LIM-Nulling Convergence
Standard rulers such as the baryon acoustic oscillation (BAO) scale serve as workhorses for precision tests of cosmology, enabling distance measurements that probe the geometry and expansion history of our Universe. Aside from BAO measurements from the cosmic microwave background (CMB), most standard ruler techniques operate at relatively low redshifts and depend on biased tracers of the matter density field. In a companion paper, we explored the scientific reach of nulling estimators, where CM…

A 28.6 mJ/iter Stable Diffusion Processor for Text-to-Image Generation with Patch Similarity-based Sparsity Augmentation and Text-based Mixed-Precision
Jiwon Choi, Wooyoung Jo, Seongyon Hong, Beomseok Kwon, Wonhoon Park, Hoi-Jun Yoo
https://arxiv.org/abs/2403.04982

A 28.6 mJ/iter Stable Diffusion Processor for Text-to-Image Generation with Patch Similarity-based Sparsity Augmentation and Text-based Mixed-Precision
This paper presents an energy-efficient stable diffusion processor for text-to-image generation. While stable diffusion attained attention for high-quality image synthesis results, its inherent characteristics hinder its deployment on mobile platforms. The proposed processor achieves high throughput and energy efficiency with three key features as solutions: 1) Patch similarity-based sparsity augmentation (PSSA) to reduce external memory access (EMA) energy of self-attention score by 60.3 %, le…

Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning
K Naveen Kumar, C Krishna Mohan, Aravind Machiry
https://arxiv.org/abs/2404.04139

Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning
Federated Learning (FL) is a collaborative learning paradigm enabling participants to collectively train a shared machine learning model while preserving the privacy of their sensitive data. Nevertheless, the inherent decentralized and data-opaque characteristics of FL render its susceptibility to data poisoning attacks. These attacks introduce malformed or malicious inputs during local model training, subsequently influencing the global model and resulting in erroneous predictions. Current FL …

This https://arxiv.org/abs/2402.05734 has been replaced.
link: https://scholar.google.com/scholar?q=a

First operation of a multi-channel Q-Pix prototype: measuring transverse electron diffusion in a gas time projection chamber
We report measurements of the transverse diffusion of electrons in P-10 gas (90% Ar, 10% CH4) in a laboratory-scale time projection chamber (TPC) utilizing a novel pixelated signal capture and digitization technique known as Q-Pix. The Q-Pix method incorporates a precision switched integrating transimpedance amplifier whose output is compared to a threshold voltage. Upon reaching the threshold, a comparator sends a 'reset' signal, initiating a discharge of the integrating capacitor. The time di…

This https://arxiv.org/abs/2401.00499 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Generating High-Precision Force Fields for Molecular Dynamics Simulations to Study Chemical Reaction Mechanisms using Molecular Configuration Transformer
Theoretical studies on chemical reaction mechanisms have been crucial in organic chemistry. Traditionally, calculating the manually constructed molecular conformations of transition states for chemical reactions using quantum chemical calculations is the most commonly used method. However, this way is heavily dependent on individual experience and chemical intuition. In our previous study, we proposed a research paradigm that uses enhanced sampling in molecular dynamics simulations to study che…

This https://arxiv.org/abs/2403.09998 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

FBPT: A Fully Binary Point Transformer
This paper presents a novel Fully Binary Point Cloud Transformer (FBPT) model which has the potential to be widely applied and expanded in the fields of robotics and mobile devices. By compressing the weights and activations of a 32-bit full-precision network to 1-bit binary values, the proposed binary point cloud Transformer network significantly reduces the storage footprint and computational resource requirements of neural network models for point cloud processing tasks, compared to full-pre…

Parameter estimation for quantum jump unraveling
Marco Radaelli, Joseph A. Smiga, Gabriel T. Landi, Felix C. Binder
https://arxiv.org/abs/2402.06556 https:…

Parameter estimation for quantum jump unraveling
We consider the estimation of parameters encoded in the measurement record of a continuously monitored quantum system in the jump unraveling. This unraveling picture corresponds to a single-shot scenario, where information is continuously gathered. Here, it is generally difficult to assess the precision of the estimation procedure via the Fisher Information due to intricate temporal correlations and memory effects. In this paper we provide a full set of solutions to this problem. First, for mul…

Numerical model of Phobos' motion incorporating the effects of free rotation
Yongzhang Yang, Jianguo Yan, Nianchuan Jian, Koji Matsumoto, Jean-Pierre Barriot
https://arxiv.org/abs/2405.05519

Numerical model of Phobos' motion incorporating the effects of free rotation
High-precision ephemerides are not only useful in supporting space missions, but also in investigating the physical nature of celestial bodies. This paper reports an update to the orbit and rotation model of the Martian moon Phobos. In contrast to earlier numerical models, this paper details a dynamical model that fully considers the rotation of Phobos. Here, Phobos' rotation is first described by Euler's rotational equations and integrated simultaneously with the orbital motion equations. We d…

Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip
Chang Sun, Thea K. {\AA}rrestad, Vladimir Loncar, Jennifer Ngadiuba, Maria Spiropulu
https://arxiv.org/abs/2405.00645

Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip
Model size and inference speed at deployment time, are major challenges in many deep learning applications. A promising strategy to overcome these challenges is quantization. However, a straightforward uniform quantization to very low precision can result in significant accuracy loss. Mixed-precision quantization, based on the idea that certain parts of the network can accommodate lower precision without compromising performance compared to other parts, offers a potential solution. In this work…

AI has the potential to ease the US meat industry's labor vulnerability by letting robots perform some of the high precision tasks required to butcher meat (Bloomberg)
https://www.bloomberg.com/news/articles/2024-…

AI Is Helping Automate One of the World’s Most Gruesome Jobs
Advances in computer vision and machine learning allow robots to perform some of the high precision tasks required to butcher beef and chicken.

Multi Digit Ising Mapping for Low Precision Ising Solvers
Abhishek Kumar Singh, Kyle Jamieson
https://arxiv.org/abs/2404.05631 https://

Multi Digit Ising Mapping for Low Precision Ising Solvers
The last couple of years have seen an ever-increasing interest in using different Ising solvers, like Quantum annealers, Coherent Ising machines, and Oscillator-based Ising machines, for solving tough computational problems in various domains. Although the simulations predict massive performance improvements for several tough computational problems, the real implementations of the Ising solvers tend to have limited precision, which can cause significant performance deterioration. This paper pre…

This https://arxiv.org/abs/2212.06166 has been replaced.
link: https://scholar.google.com/scholar?q=a

Rapid determination of LISA sensitivity to extreme mass ratio inspirals with machine learning
Gravitational wave observations of the inspiral of stellar-mass compact objects into massive black holes (MBHs), extreme mass ratio inspirals (EMRIs), enable precision measurements of parameters such as the MBH mass and spin. The Laser Interferometer Space Antenna is expected to detect sufficient EMRIs to probe the underlying source population, testing theories of the formation and evolution of MBHs and their environments. Population studies are subject to selection effects that vary across the…

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys
Nathan Johnson, Aashwin Ananda Mishra, Apurva Mehta
https://arxiv.org/abs/2403.06329

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys
The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a beginner but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting comp…

This https://arxiv.org/abs/2310.14153 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Spin asymmetry and dipole moments in $τ$-pair production with ultraperipheral heavy ion collisions
The anomalous magnetic (MDM) and electric (EDM) dipole moments of the $τ$ lepton serve as crucial indicators of new physics beyond the Standard Model. Leveraging azimuthal angular asymmetry as a novel tool in ultraperipheral collisions (UPCs), we attain unparalleled precision in the study of these key properties. Driven by the highly linear polarization of coherent photons, this method uniquely enables both the MDM and EDM to contribute to the $\cos2ϕ$ angular distribution in similar magnitud…

Multicolor photometry of LEO mega-constellations Starlink and OneWeb
Hui Zhi, Xiaojun Jiang, Jianfeng Wang
https://arxiv.org/abs/2403.05150 https://…

Multicolor photometry of LEO mega-constellations Starlink and OneWeb
The development of low earth orbit (LEO) mega-constellation fundamentally threatens ground-based optical astronomical observations. To study the photometric properties of the LEO mega-constellations, we used the Xinglong 50 cm telescope to conduct a large-sample, high-precision, and multicolor target-tracking photometry of two typical LEO Mega-constellations: Starlink and OneWeb. Over a three-month observation period starting on 2022 January 1st, we collected 1,447 light curves of 404 satellite…

This https://arxiv.org/abs/2312.06903 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nuc…

Precise Mass Measurements of $A=133$ Isobars with the Canadian Penning Trap: Resolving the $Q_{β^-}$ anomaly at $^{133}$Te
We report precision mass measurements of $^{133}$Sb, $^{133g,m}$Te, and $^{133g,m}$I, produced at CARIBU at Argonne National Laboratory's ATLAS facility and measured using the Canadian Penning Trap mass spectrometer. These masses clarify an anomaly in the $^{133}$Te $β$-decay. The masses reported in the 2020 Atomic Mass Evaluation (M. Wang et al., 2021) produce $Q_{β^-}(^{133}$Te)=2920(6) keV; however, the highest-lying $^{133}$I level populated in this decay is observed at $E_i=2935.83(15)$ …

Contouring Error Bounded Control for Biaxial Switched Linear Systems
Meng Yuan, Ye Wang, Chris Manzie, Zhezhuang Xu, Tianyou Chai
https://arxiv.org/abs/2404.05404

Contouring Error Bounded Control for Biaxial Switched Linear Systems
Biaxial motion control systems are used extensively in manufacturing and printing industries. To improve throughput and reduce machine cost, lightweight materials are being proposed in structural components but may result in higher flexibility in the machine links. This flexibility is often position dependent and compromises precision of the end effector of the machine. To address the need for improved contouring accuracy in industrial machines with position-dependent structural flexibility, th…

Reconstructing rotation curves with artificial neural networks
Gabriela Garcia-Arroyo, Isidro G\'omez-Vargas, J. Alberto V\'azquez
https://arxiv.org/abs/2404.05833

Reconstructing rotation curves with artificial neural networks
Galactic rotation curves have been served as indispensable tools for determining the distribution of mass within galaxies. Despite several advances in precision observations, some discrepancies still persist between the inferred matter distribution from luminosity and observed rotation velocities, often attributed to the presence of dark matter. Traditional parametric models, while insightful, struggle with the complexity of galaxies with prominent bulges or non-circular motions, but in contras…

Fundamental limits of metrology at thermal equilibrium
Paolo Abiuso, Pavel Sekatski, John Calsamiglia, Mart\'i Perarnau-Llobet
https://arxiv.org/abs/2402.06582

Fundamental limits of metrology at thermal equilibrium
We consider the estimation of an unknown parameter $θ$ through a quantum probe at thermal equilibrium. The probe is assumed to be in a Gibbs state according to its Hamiltonian $H_θ$, which is divided in a parameter-encoding term $H^P_θ$ and an additional, parameter-independent, control $H^C$. Given a fixed encoding, we find the maximal Quantum Fisher Information attainable via arbitrary $H^C$, which provides a fundamental bound on the measurement precision. Our bounds show that: (i) assuming…

A 28.6 mJ/iter Stable Diffusion Processor for Text-to-Image Generation with Patch Similarity-based Sparsity Augmentation and Text-based Mixed-Precision
Jiwon Choi, Wooyoung Jo, Seongyon Hong, Beomseok Kwon, Wonhoon Park, Hoi-Jun Yoo
https://arxiv.org/abs/2403.04982

A 28.6 mJ/iter Stable Diffusion Processor for Text-to-Image Generation with Patch Similarity-based Sparsity Augmentation and Text-based Mixed-Precision
This paper presents an energy-efficient stable diffusion processor for text-to-image generation. While stable diffusion attained attention for high-quality image synthesis results, its inherent characteristics hinder its deployment on mobile platforms. The proposed processor achieves high throughput and energy efficiency with three key features as solutions: 1) Patch similarity-based sparsity augmentation (PSSA) to reduce external memory access (EMA) energy of self-attention score by 60.3 %, le…

The TESS SPOC FFI Target Sample Explored with Gaia
Lauren Doyle, David J. Armstrong, Daniel Bayliss, Toby Rodel, Vedad Kunovac
https://arxiv.org/abs/2403.02407

The TESS SPOC FFI Target Sample Explored with Gaia
The TESS mission has provided the community with high-precision times series photometry for $\sim$2.8 million stars across the entire sky via the Full Frame Image (FFI) light curves produced by the TESS Science Processing Operations Centre (SPOC). This set of light curves is an extremely valuable resource for the discovery of transiting exoplanets and other stellar science. However, due to the sample selection, this set of light curves does not constitute a magnitude limited sample. In order to…

This https://arxiv.org/abs/2402.05734 has been replaced.
link: https://scholar.google.com/scholar?q=a

First operation of a multi-channel Q-Pix prototype: measuring transverse electron diffusion in a gas time projection chamber
We report measurements of the transverse diffusion of electrons in P-10 gas (90% Ar, 10% CH4) in a laboratory-scale time projection chamber (TPC) utilizing a novel pixelated signal capture and digitization technique known as Q-Pix. The Q-Pix method incorporates a precision switched integrating transimpedance amplifier whose output is compared to a threshold voltage. Upon reaching the threshold, a comparator sends a 'reset' signal, initiating a discharge of the integrating capacitor. The time di…

Interesting use of #OSINT in wartime.
https://www.bellingcat.com/news/2024/04/02/strike-that-killed-world-central-kitchen-workers-bears-hallmarks-of-israeli-precision-strike/

Precision Spectroscopy and Nuclear Structure Parameters in 7Li ion
Hua Guan, Xiao-Qiu Qi, Peng-Peng Zhou, Wei Sun, Shao-Long Chen, Xu-Rui Chang, Yao Huang, Pei-Pei Zhang, Zong-Chao Yan, G. W. F. Drake, Ai-Xi Chen, Zhen-Xiang Zhong, Ting-Yun Shi, Ke-Lin Gao
https://arxiv.org/abs/2403.06384…

Sample size planning for estimating the global win probability with assurance and precision
Di Shu, Guangyong Zou
https://arxiv.org/abs/2404.04415 https://…

Sample size planning for estimating the global win probability with assurance and precision
Most clinical trials conducted in drug development contain multiple endpoints in order to collectively assess the intended effects of the drug on various disease characteristics. Focusing on the estimation of the global win probability, defined as the average win probability (WinP) across endpoints that a treated participant would have a better outcome than a control participant, we propose a closed-form sample size formula incorporating pre-specified precision and assurance, with precision den…

Horizon-penetrating form of parametrized metrics for static and stationary black holes
Yixuan Ma, Luciano Rezzolla
https://arxiv.org/abs/2404.06509 https:/…

Horizon-penetrating form of parametrized metrics for static and stationary black holes
The Rezzolla-Zhidenko (RZ) and Konoplya-Rezzolla-Zhidenko (KRZ) frameworks provide an efficient approach to characterize agnostically spherically symmetric or stationary black-hole spacetimes in arbitrary metric theories. In their original construction, these metrics were defined only in the spacetime region outside of the event horizon, where they can reproduce any black-hole metric with with percent precision and a few parameters only. At the same time, numerical simulations of accreting blac…

US to provide Ukraine with JDAM-ER bombs to counter Russian electronic warfare systems: https://benborges.xyz/2024/05/04/us-to-provide.html

Semi-Autonomous Laparoscopic Robot Docking with Learned Hand-Eye Information Fusion
Huanyu Tian, Martin Huber, Christopher E. Mower, Zhe Han, Changsheng Li, Xingguang Duan, Christos Bergeles
https://arxiv.org/abs/2405.05817

Semi-Autonomous Laparoscopic Robot Docking with Learned Hand-Eye Information Fusion
In this study, we introduce a novel shared-control system for key-hole docking operations, combining a commercial camera with occlusion-robust pose estimation and a hand-eye information fusion technique. This system is used to enhance docking precision and force-compliance safety. To train a hand-eye information fusion network model, we generated a self-supervised dataset using this docking system. After training, our pose estimation method showed improved accuracy compared to traditional metho…

Solution for Authenticity Identification of Typical Target Remote Sensing Images
Yipeng Lin, Xinger Li, Yang Yang
https://arxiv.org/abs/2405.02362 https://…

Solution for Authenticity Identification of Typical Target Remote Sensing Images
In this paper, we propose a basic RGB single-mode model based on weakly supervised training under pseudo labels, which performs high-precision authenticity identification under multi-scene typical target remote sensing images. Due to the imprecision of Mask generation, we divide the task into two sub-tasks: generating pseudo-mask and fine-tuning model based on generated Masks. In generating pseudo masks, we use MM-Fusion as the base model to generate masks for large objects such as planes and s…

Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference
Akshat Ramachandran, Zishen Wan, Geonhwa Jeong, John Gustafson, Tushar Krishna
https://arxiv.org/abs/2403.05465

Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference
Traditional Deep Neural Network (DNN) quantization methods using integer, fixed-point, or floating-point data types struggle to capture diverse DNN parameter distributions at low precision, and often require large silicon overhead and intensive quantization-aware training. In this study, we introduce Logarithmic Posits (LP), an adaptive, hardware-friendly data type inspired by posits that dynamically adapts to DNN weight/activation distributions by parameterizing LP bit fields. We also develop …

Redshift drift in a universe with structure III: Numerical relativity
Sofie Marie Koksbang, Asta Heinesen, Hayley J. Macpherson
https://arxiv.org/abs/2404.06242

Redshift drift in a universe with structure III: Numerical relativity
Measurements of the cosmic redshift drift - the change in redshift of a source over time - will enable independent detection of cosmological expansion thanks to the immense precision soon reached by new facilities such as the Square Kilometer Array Observatory and the Extremely Large Telescope. We conduct the first ever redshift drift computation in fully relativistic cosmological simulations, with the simulations performed with the Einstein Toolkit. We compute the redshift drift over the full …

Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip
Chang Sun, Thea K. {\AA}rrestad, Vladimir Loncar, Jennifer Ngadiuba, Maria Spiropulu
https://arxiv.org/abs/2405.00645

Gradient-based Automatic Per-Weight Mixed Precision Quantization for Neural Networks On-Chip
Model size and inference speed at deployment time, are major challenges in many deep learning applications. A promising strategy to overcome these challenges is quantization. However, a straightforward uniform quantization to very low precision can result in significant accuracy loss. Mixed-precision quantization, based on the idea that certain parts of the network can accommodate lower precision without compromising performance compared to other parts, offers a potential solution. In this work…

Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference
Akshat Ramachandran, Zishen Wan, Geonhwa Jeong, John Gustafson, Tushar Krishna
https://arxiv.org/abs/2403.05465

Algorithm-Hardware Co-Design of Distribution-Aware Logarithmic-Posit Encodings for Efficient DNN Inference
Traditional Deep Neural Network (DNN) quantization methods using integer, fixed-point, or floating-point data types struggle to capture diverse DNN parameter distributions at low precision, and often require large silicon overhead and intensive quantization-aware training. In this study, we introduce Logarithmic Posits (LP), an adaptive, hardware-friendly data type inspired by posits that dynamically adapts to DNN weight/activation distributions by parameterizing LP bit fields. We also develop …

This https://arxiv.org/abs/2311.12014 has been replaced.
initial toot: https://mastoxiv.page/@ar…

MMC Array to Study X-ray Transitions in Muonic Atoms
The QUARTET collaboration aims to significantly improve the precision of the absolute nuclear charge radii of light nuclei from Li to Ne by using an array of metallic magnetic calorimeters to perform high-precision X-ray spectroscopy of low-lying states in muonic atoms. A proof-of-principle measurement with lithium, beryllium and boron is planned for fall 2023 at the Paul Scherrer Institute. We discuss the performance achieved with the maXs-30 detector module to be used. To place the detector c…

Observation uncertainty effects on the precision of interior planetary parameters
Mykhaylo Plotnykov, Diana Valencia
https://arxiv.org/abs/2405.03860 https…

Observation uncertainty effects on the precision of interior planetary parameters
Determining compositions of low-mass exoplanets is essential in understanding their origins. The certainty by which masses and radius are measured affects our ability to discern planets that are rocky or volatile rich. In this study, we aim to determine sound observational strategies to avoid diminishing returns. We quantify how uncertainties in mass, radius and model assumptions propagate into errors in inferred compositions of rocky and water planets. For a target error in a planet's iron-mas…

Probabilistic Examination of Least Squares Error in Low-bitwidth Cholesky Decomposition
Alexander Osinsky, Roman Bychkov, Mikhail Trefilov, Vladimir Lyashev, Andrey Ivanov
https://arxiv.org/abs/2404.05082

Probabilistic Examination of Least Squares Error in Low-bitwidth Cholesky Decomposition
In this paper, we propose a new approach to justify a round-off error impact on the accuracy of the linear least squares (LS) solution using Cholesky decomposition. This decomposition is widely employed to inverse a matrix in the linear detector of the Multi-User multi-antenna receiver. The proposed stochastic bound is much closer to actual errors than other numerical bounds. It was tested with a half-precision format and validated in realistic scenarios. Experimental results demonstrate our ap…

NeuRSS: Enhancing AUV Localization and Bathymetric Mapping with Neural Rendering for Sidescan SLAM
Yiping Xie, Jun Zhang, Nils Bore, John Folkesson
https://arxiv.org/abs/2405.05807

NeuRSS: Enhancing AUV Localization and Bathymetric Mapping with Neural Rendering for Sidescan SLAM
Implicit neural representations and neural render- ing have gained increasing attention for bathymetry estimation from sidescan sonar (SSS). These methods incorporate multiple observations of the same place from SSS data to constrain the elevation estimate, converging to a globally-consistent bathymetric model. However, the quality and precision of the bathymetric estimate are limited by the positioning accuracy of the autonomous underwater vehicle (AUV) equipped with the sonar. The global posi…

A robust test of general relativity at the galactic scales by combining strong lensing systems and gravitational wave standard sirens
Tonghua Liu, Marek Biesiada, Shuxun Tian, Kai Liao
https://arxiv.org/abs/2404.05907

A robust test of general relativity at the galactic scales by combining strong lensing systems and gravitational wave standard sirens
The measurement of the parametrized post-Newtonian parameter $γ_{\rm{PPN}}$ is a robust test of general relativity (GR). In some modified theories of gravity, $γ_{\rm{PPN}}$ may evolve with the redshift and deviate from one at high redshifts. This means that precise constraints on $γ_{\rm{PPN}}$ acquired in the solar system experiments could not be sufficient to test such theories and it is necessary to constrain $γ_{\rm{PPN}}$with high precision at high redshifts. However, in many approach…

Determining the upper bound of code distance of quantum stabilizer codes through Monte Carlo method based on fully decoupled belief propagation
Zhipeng Liang, Zicheng Wang, Zhengzhong Yi, Yulin Wu, Chen Qiu, Xuan Wang
https://arxiv.org/abs/2402.06481

Determining the upper bound of code distance of quantum stabilizer codes through Monte Carlo method based on fully decoupled belief propagation
Code distance is an important parameter for quantum stabilizer codes (QSCs). Directly precisely computing it is an NP-complete problem. However, the upper bound of code distance can be computed by some efficient methods. In this paper, employing the idea of Monte Carlo method, we propose the algorithm of determining the upper bound of code distance of QSCs based on fully decoupled belief propagation. Our algorithm shows high precision - the upper bound of code distance determined by the algorit…

Evaluation and Optimization of Positional Accuracy for Maritime Positioning Systems
Atilla Alpay Nalcaci, Fidan Mehmeti, Wolfgang Kellerer, Florian Schiegg
https://arxiv.org/abs/2404.04593

Evaluation and Optimization of Positional Accuracy for Maritime Positioning Systems
Navigation and trajectorial estimation of maritime vessels are contingent upon the context of positional accuracy. Even the smallest deviations in the estimation of a given vessel may result in detrimental consequences in terms of economic and ecologic quotients. To ensure an agile and precise environment for maritime vessel positional estimation, preexisting marine radar technologies can be utilized in a way that ensures a higher level of precision compared to GNSS-based identification and pos…

Precision Spectroscopy and Nuclear Structure Parameters in 7Li ion
Hua Guan, Xiao-Qiu Qi, Peng-Peng Zhou, Wei Sun, Shao-Long Chen, Xu-Rui Chang, Yao Huang, Pei-Pei Zhang, Zong-Chao Yan, G. W. F. Drake, Ai-Xi Chen, Zhen-Xiang Zhong, Ting-Yun Shi, Ke-Lin Gao
https://arxiv.org/abs/2403.06384…

Redshift drift in a universe with structure III: Numerical relativity
Sofie Marie Koksbang, Asta Heinesen, Hayley J. Macpherson
https://arxiv.org/abs/2404.06242

Redshift drift in a universe with structure III: Numerical relativity
Measurements of the cosmic redshift drift - the change in redshift of a source over time - will enable independent detection of cosmological expansion thanks to the immense precision soon reached by new facilities such as the Square Kilometer Array Observatory and the Extremely Large Telescope. We conduct the first ever redshift drift computation in fully relativistic cosmological simulations, with the simulations performed with the Einstein Toolkit. We compute the redshift drift over the full …

Quasielastic Lepton-Nucleus Scattering and the Correlated Fermi Gas Model
Bhubanjyoti Bhattacharya, Sam Carey, Erez O. Cohen, Gil Paz
https://arxiv.org/abs/2405.05342

Quasielastic Lepton-Nucleus Scattering and the Correlated Fermi Gas Model
The neutrino research program in the coming decades will require improved precision. A major source of uncertainty is the interaction of neutrinos with nuclei that serve as targets for such experiments. Broadly speaking, this interaction often depends, e.g., for charge-current quasi-elastic scattering, on the combination of ``nucleon physics", expressed by form factors, and ``nuclear physics", expressed by a nuclear model. It is important to get a good handle on both. We present a fully analyti…

FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation
Chris Rockwell, Nilesh Kulkarni, Linyi Jin, Jeong Joon Park, Justin Johnson, David F. Fouhey
https://arxiv.org/abs/2403.03221

FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation
Estimating relative camera poses between images has been a central problem in computer vision. Methods that find correspondences and solve for the fundamental matrix offer high precision in most cases. Conversely, methods predicting pose directly using neural networks are more robust to limited overlap and can infer absolute translation scale, but at the expense of reduced precision. We show how to combine the best of both methods; our approach yields results that are both precise and robust, w…

A Precision Drone Landing System using Visual and IR Fiducial Markers and a Multi-Payload Camera
Joshua Springer, Gylfi {\TH}\'or Gu{\dh}mundsson, Marcel Kyas
https://arxiv.org/abs/2403.03806

A Precision Drone Landing System using Visual and IR Fiducial Markers and a Multi-Payload Camera
We propose a method for autonomous precision drone landing with fiducial markers and a gimbal-mounted, multi-payload camera with wide-angle, zoom, and IR sensors. The method has minimal data requirements; it depends primarily on the direction from the drone to the landing pad, enabling it to switch dynamically between the camera's different sensors and zoom factors, and minimizing auxiliary sensor requirements. It eliminates the need for data such as altitude above ground level, straight-line d…

This https://arxiv.org/abs/2310.06985 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

PlatoSim: An end-to-end PLATO camera simulator for modelling high-precision space-based photometry
PLAnetary Transits and Oscillations of stars (PLATO) is the ESA M3 space mission dedicated to detect and characterise transiting exoplanets including information from the asteroseismic properties of their stellar hosts. The uninterrupted and high-precision photometry provided by space-borne instruments such as PLATO require long preparatory phases. An exhaustive list of tests are paramount to design a mission that meets the performance requirements, and as such, simulations are an indispensable…

This https://arxiv.org/abs/2311.04670 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Curvature-bias corrections using a pseudomass method
Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additio…

This https://arxiv.org/abs/2311.14114 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

SySMOL: Co-designing Algorithms and Hardware for Neural Networks with Heterogeneous Precisions
Recent quantization techniques have enabled heterogeneous precisions at very fine granularity, e.g., each parameter/activation can take on a different precision, resulting in compact neural networks without sacrificing accuracy. However, there is a lack of efficient architectural support for such networks, which require additional hardware to decode the precision settings for individual variables, align the variables, and provide fine-grained mixed-precision compute capabilities. The complexity…

This https://arxiv.org/abs/2311.17175 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Kicking it Off(-shell) with Direct Diffusion
Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We show how a generative diffusion network learns off-shell kinematics given the much simpler on-shell process. It generates off-shell configurations fast and precisely, while reproducing even challenging on-shell features.

Design of Stickbug: a Six-Armed Precision Pollination Robot
Trevor Smith, Madhav Rijal, Christopher Tatsch, R. Michael Butts, Jared Beard, R. Tyler Cook, Andy Chu, Jason Gross, Yu Gu
https://arxiv.org/abs/2404.03489

Design of Stickbug: a Six-Armed Precision Pollination Robot
This work presents the design of Stickbug, a six-armed, multi-agent, precision pollination robot that combines the accuracy of single-agent systems with swarm parallelization in greenhouses. Precision pollination robots have often been proposed to offset the effects of a decreasing population of natural pollinators, but they frequently lack the required parallelization and scalability. Stickbug achieves this by allowing each arm and drive base to act as an individual agent, significantly reduci…

This https://arxiv.org/abs/2307.15841 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Pulse optimization for high-precision motional-mode characterization in trapped-ion quantum computers
High-fidelity operation of quantum computers requires precise knowledge of the physical system through characterization. For motion-mediated entanglement generation in trapped ions, it is crucial to have precise knowledge of the motional-mode parameters such as the mode frequencies and the Lamb-Dicke parameters. Unfortunately, the state-of-the-art mode-characterization schemes do not easily render the mode parameters in a sufficiently scalable and accurate fashion, due to the unwanted excitatio…

This https://arxiv.org/abs/2404.18605 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Uncertainties from metrology in the integrated luminosity measurement with the updated design of the very forward region of a detector at CEPC
At an $e^{+}e^{-}$ collider machine-detector interface includes, among others, a calorimeter dedicated for precision measurement of the integrated luminosity at a per mill level or better. Usually, such a device is placed at the outgoing beams, to keep the spatial symmetries of the head-on collisions at accelerators with a non-zero crossing angle. At CEPC it is currently proposed that the luminometer is placed on the z-axis. We review a feasibility of precision measurement of the integrated lum…

Design of Stickbug: a Six-Armed Precision Pollination Robot
Trevor Smith, Madhav Rijal, Christopher Tatsch, R. Michael Butts, Jared Beard, R. Tyler Cook, Andy Chu, Jason Gross, Yu Gu
https://arxiv.org/abs/2404.03489

Design of Stickbug: a Six-Armed Precision Pollination Robot
This work presents the design of Stickbug, a six-armed, multi-agent, precision pollination robot that combines the accuracy of single-agent systems with swarm parallelization in greenhouses. Precision pollination robots have often been proposed to offset the effects of a decreasing population of natural pollinators, but they frequently lack the required parallelization and scalability. Stickbug achieves this by allowing each arm and drive base to act as an individual agent, significantly reduci…

This https://arxiv.org/abs/2311.17175 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Kicking it Off(-shell) with Direct Diffusion
Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We show how a generative diffusion network learns off-shell kinematics given the much simpler on-shell process. It generates off-shell configurations fast and precisely, while reproducing even challenging on-shell features.

This https://arxiv.org/abs/2401.12428 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators
In recent years, various computing-in-memory (CIM) processors have been presented, showing superior performance over traditional architectures. To unleash the potential of various CIM architectures, such as device precision, crossbar size, and crossbar number, it is necessary to develop compilation tools that are fully aware of the CIM architectural details and implementation diversity. However, due to the lack of architectural support in current popular open-source compiling stacks, existing C…

This https://arxiv.org/abs/2312.13369 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

JLab spectral functions of argon in NuWro and their implications for MicroBooNE
The Short-Baseline Neutrino program in Fermilab aims to resolve the nature of the low-energy excess events observed in LSND and MiniBooNE, and analyze with unprecedented precision neutrino interactions with argon. These studies require reliable estimate of neutrino cross sections, in particular for charged current quasielastic scattering (CCQE). Here, we report updates of the NuWro Monte Carlo generator that, most notably, bring the state-of-the-art spectral functions to model the ground state …

This https://arxiv.org/abs/2403.19643 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Almost All Quantum Channels Are Diagonalizable
We prove the statement "The collection of all elements of $\mathcal S$ which have only simple eigenvalues is dense in $\mathcal S$" for different sets $\mathcal S$, including: all quantum channels, the unital channels, the positive trace-preserving maps, all Lindbladians (GKSL-generators), and all time-dependent Markovian channels. Therefore any element from each of these sets can always be approximated by diagonalizable elements of the same set to arbitrary precision.

This https://arxiv.org/abs/2312.13369 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

JLab spectral functions of argon in NuWro and their implications for MicroBooNE
The Short-Baseline Neutrino program in Fermilab aims to resolve the nature of the low-energy excess events observed in LSND and MiniBooNE, and analyze with unprecedented precision neutrino interactions with argon. These studies require reliable estimate of neutrino cross sections, in particular for charged current quasielastic scattering (CCQE). Here, we report updates of the NuWro Monte Carlo generator that, most notably, bring the state-of-the-art spectral functions to model the ground state …

Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder
Clemens C. Christoph, Amirhossein Kazemipour, Michel R. Vogt, Yu Zhang, Robert K. Katzschmann
https://arxiv.org/abs/2404.04079

Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder
The human shoulder, with its glenohumeral joint, tendons, ligaments, and muscles, allows for the execution of complex tasks with precision and efficiency. However, current robotic shoulder designs lack the compliance and compactness inherent in their biological counterparts. A major limitation of these designs is their reliance on external sensors like rotary encoders, which restrict mechanical joint design and introduce bulk to the system. To address this constraint, we present a bio-inspired …

This https://arxiv.org/abs/2402.19079 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Experimental investigation of a multi-photon Heisenberg-limited interferometric scheme: the effect of imperfections
Interferometric phase estimation is an essential tool for precise measurements of quantities such as displacement, velocity and material properties. The lower bound on measurement uncertainty achievable with classical resources is set by the shot-noise limit (SNL) that scales asymptotically as $1/\sqrt{N}$, where $N$ is the number of resources used. The experiment of [S. Daryanoosh et al., Nat. Commun. ${\bf 9}$, 4606 (2018)] showed how to achieve the ultimate precision limit, the exact Heisenb…

Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder
Clemens C. Christoph, Amirhossein Kazemipour, Michel R. Vogt, Yu Zhang, Robert K. Katzschmann
https://arxiv.org/abs/2404.04079

Self-Sensing Feedback Control of an Electrohydraulic Robotic Shoulder
The human shoulder, with its glenohumeral joint, tendons, ligaments, and muscles, allows for the execution of complex tasks with precision and efficiency. However, current robotic shoulder designs lack the compliance and compactness inherent in their biological counterparts. A major limitation of these designs is their reliance on external sensors like rotary encoders, which restrict mechanical joint design and introduce bulk to the system. To address this constraint, we present a bio-inspired …

Complete NLO QCD Corrections to $ZZ$ Production in Gluon Fusion
Bakul Agarwal, Stephen Jones, Matthias Kerner, Andreas von Manteuffel
https://arxiv.org/abs/2404.05684

Complete NLO QCD Corrections to $ZZ$ Production in Gluon Fusion
We calculate the complete NLO QCD corrections to loop-induced $gg \rightarrow ZZ$ production including full top-quark mass effects. The two-loop virtual corrections are obtained by combining analytic results for the massless, Higgs-mediated, and one-loop factorizable contributions with numerically computed amplitudes containing the top-quark mass. We show that the choice of subtraction scheme for the virtual contribution impacts the precision with which the virtual contribution must be evaluate…