Tootfinder

Rounding error analysis of randomized CholeskyQR2 for sparse matrices
Haoran Guan, Yuwei Fan
https://arxiv.org/abs/2506.04208 https://

Rounding error analysis of randomized CholeskyQR2 for sparse matrices
This work focuses on rounding error analysis of randomized CholeskyQR2 (RCholeskyQR2) for sparse matrices. We form RCholeskyQR2 with CholeskyQR2 and matrix sketching in order to accelerate CholeskyQR2 and improve its applicability by compressing the input matrix $X \in \mathbb{R}^{m\times n}$. In many real-world applications, the input matrix $X$ is always sparse. In this work, we follow the model of sparse matrices proposed in \cite{CSparse} and provide an improved rounding error analysis of R…

Updating my CloudNativePG Clusters to postgresql:17.5 broke wal archiving to my Ceph S3 Object Store. Here's a new blog post describing the fix:
https://www.beyondwatts.com/posts/debugging-barman-xamzcontents…

beyondwatts | Debugging Barman XAmzContentSHA256Mismatch error after upgrading to postgresql:17.5
In an effort to keep my home cluster up to date, I upgraded CloudNativePG to v1.26 and the associated database clusters to cloudnative-pg/postgresql:17.5. All seemed ok with the upgrade until a couple of days later when the cluster primary instance PVCs started to run out of space. wal archiving had stopped working with the error message:

This https://arxiv.org/abs/2502.14627 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

ATRI: Mitigating Multilingual Audio Text Retrieval Inconsistencies by Reducing Data Distribution Errors
Multilingual audio-text retrieval (ML-ATR) is a challenging task that aims to retrieve audio clips or multilingual texts from databases. However, existing ML-ATR schemes suffer from inconsistencies for instance similarity matching across languages. We theoretically analyze the inconsistency in terms of both multilingual modal alignment direction error and weight error, and propose the theoretical weight error upper bound for quantifying the inconsistency. Based on the analysis of the weight err…

A former employee says fewer than 10,000 people use Ola Krutrim's LLM chatbot, which supports 10 Indian languages, and that over 60% of them are random testers (Swathi Moorthy/The Economic Times)
https://

Krutrim finds few takers for its LLMs and cloud products
Ola founder Aggarwal first announced Krutrim in December 2023, launching an LLM that could support 10 Indian languages, starting with Krutrim chatbot in February 2024, and cloud offering shortly after. Two founders told ET recently that repeated sign-in attempts were blocked by a persistent “logged out of session” error, making sign-up via mobile or Gmail difficult.

This https://arxiv.org/abs/2502.11475 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Focused-DPO: Enhancing Code Generation Through Focused Preference Optimization on Error-Prone Points
Code generation models have shown significant potential for automating programming tasks. However, the challenge of generating accurate and reliable code persists due to the highly complex and long-reasoning nature of the task. Even state-of-the-art models often fail in code generation due to small errors, which can drastically affect the overall functionality of code. Our study identifies that current models tend to produce errors concentrated at specific error-prone points, which significantl…

Spending hours manually updating your Excel dashboards and reports? Copying, pasting, reformatting... 😩 It's tedious, time-consuming, and leaves room for error. What if your key visuals updated automatically when the source data changes?
Excel has a powerful, often overlooked feature perfect for this: the Camera Tool! 📸
It lets you create dynamic, linked visuals from different sheets onto one central summary page. 👉

This https://arxiv.org/abs/2109.10887 has been replaced.
link: https://scholar.google.com/scholar?q=a

Asymptotic error in the eigenfunction expansion for the Green's function of a Sturm-Liouville problem
We study the asymptotic error arising when approximating the Green's function of a Sturm-Liouville problem through a truncation of its eigenfunction expansion, both for the Green's function of a regular Sturm-Liouville problem and for the Green's function associated with the Hermite polynomials, the associated Laguerre polynomials, and the Jacobi polynomials, respectively. We prove that the asymptotic error obtained on the diagonal can be expressed in terms of the coefficients of the related se…

This https://arxiv.org/abs/2502.06381 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Revisiting Optimal Allocations for Binary Responses: Insights from Considering Type-I Error Rate Control
This work revisits optimal response-adaptive designs from a type-I error rate perspective, highlighting when and how much these allocations exacerbate type-I error rate inflation - an issue previously undocumented. We explore a range of approaches from the literature that can be applied to reduce type-I error rate inflation. However, we found that all of these approaches fail to give a robust solution to the problem. To address this, we derive two optimal allocation proportions, incorporating t…

This https://arxiv.org/abs/2408.04576 has been replaced.
initial toot: https://mastoxiv.page/@…

Time-cost-error trade-off relation in thermodynamics: The third law and beyond
Elucidating fundamental limitations inherent in physical systems is a central subject in physics. For important thermodynamic operations such as information erasure, cooling, and copying, resources like time and energetic cost must be expended to achieve the desired outcome within a predetermined error margin. In the context of cooling, the unattainability principle of the third law of thermodynamics asserts that infinite ``resources'' are needed to reach absolute zero. However, the precise ide…

This https://arxiv.org/abs/2505.14927 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Error-Free Demodulation of Pixelated Interferograms: Updated review and circumstantial evidence of plagiarism by 4D Technology Corporation
This paper examines the historical development that led to error-free phase demodulation of pixelated spatial-carrier interferograms between 2004 and 2010. It also evaluates evidence suggesting that 4D Technology Corporation (4DTC), in their SPIE 7790 publication [18], may have adopted key concepts from a manuscript submitted by Servin and collaborators, which at that time was still under peer review [17]. We analyze 4DTC algorithms based on 2x2 and 3x3 spatial convolution phase shifting method…

This https://arxiv.org/abs/2504.03393 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Effects of Interpolation Error and Bias on the Random Mesh Finite Element Method for Inverse Problems
Bayesian inverse problems are an important application for probabilistic solvers of partial differential equations: when fully resolving numerical error is computationally infeasible, probabilistic solvers can be used to consistently model the error and propagate it to the posterior. In this work, the performance of the random mesh finite element method (RM-FEM) is investigated in a Bayesian inverse setting. We show how interpolation error negatively affects the RM-FEM posterior, and how these …

This https://arxiv.org/abs/2505.06459 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles
Physics-Informed Neural Networks (PINNs) have been widely used to obtain solutions to various physical phenomena modeled as Differential Equations. As PINNs are not naturally equipped with mechanisms for Uncertainty Quantification, some work has been done to quantify the different uncertainties that arise when dealing with PINNs. In this paper, we use a two-step procedure to train Bayesian Neural Networks that provide uncertainties over the solutions to differential equation systems provided by…

This https://arxiv.org/abs/2412.11934 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Stepwise Reasoning Error Disruption Attack of LLMs
Large language models (LLMs) have made remarkable strides in complex reasoning tasks, but their safety and robustness in reasoning processes remain underexplored. Existing attacks on LLM reasoning are constrained by specific settings or lack of imperceptibility, limiting their feasibility and generalizability. To address these challenges, we propose the Stepwise rEasoning Error Disruption (SEED) attack, which subtly injects errors into prior reasoning steps to mislead the model into producing i…

Transient Error Analysis of the LMS and RLS Algorithm for Graph Signal Estimation
Haiquan Zhao, Chengjin Li
https://arxiv.org/abs/2506.00403 https://

Transient Error Analysis of the LMS and RLS Algorithm for Graph Signal Estimation
Recently, the proposal of the least mean square (LMS) and recursive least squares (RLS) algorithm for graph signal processing (GSP) provides excellent solutions for processing signals defined on irregular structures such as sensor networks. The existing work has completed the steady state error analysis of the GSP LMS algorithm and GSP RLS algorithm in Gaussian noise scenarios, and a range of values for the step size of the GSP LMS algorithm has also been given. Meanwhile, the transient error a…

This https://arxiv.org/abs/2408.08294 has been replaced.
link: https://scholar.google.com/scholar?q=a

eGAD! double descent is explained by Generalized Aliasing Decomposition
A central problem in data science is to use potentially noisy samples of an unknown function to predict values for unseen inputs. In classical statistics, predictive error is understood as a trade-off between the bias and the variance that balances model simplicity with its ability to fit complex functions. However, over-parameterized models exhibit counterintuitive behaviors, such as "double descent" in which models of increasing complexity exhibit decreasing generalization error. Others may e…

A priori error estimates for the $\theta$-method for the flow of nonsmooth velocity fields
Gennaro Ciampa, Tommaso Cortopassi, Gianluca Crippa, Raffaele D'Ambrosio, Stefano Spirito
https://arxiv.org/abs/2506.02747

A priori error estimates for the $θ$-method for the flow of nonsmooth velocity fields
Velocity fields with low regularity (below the Lipschitz threshold) naturally arise in many models from mathematical physics, such as the inhomogeneous incompressible Navier-Stokes equations, and play a fundamental role in the analysis of nonlinear PDEs. The DiPerna-Lions theory ensures existence and uniqueness of the flow associated with a divergence-free velocity field with Sobolev regularity. In this paper, we establish a priori error estimates showing a logarithmic rate of convergence of nu…

An Open-source Capping Machine Suitable for Confined Spaces
Francisco Munguia-Galeano, Louis Longley, Satheeshkumar Veeramani, Zhengxue Zhou, Rob Clowes, Hatem Fakhruldeen, Andrew I. Cooper
https://arxiv.org/abs/2506.03743

An Open-source Capping Machine Suitable for Confined Spaces
In the context of self-driving laboratories (SDLs), ensuring automated and error-free capping is crucial, as it is a ubiquitous step in sample preparation. Automated capping in SDLs can occur in both large and small workspaces (e.g., inside a fume hood). However, most commercial capping machines are designed primarily for large spaces and are often too bulky for confined environments. Moreover, many commercial products are closed-source, which can make their integration into fully autonomous wo…

This https://arxiv.org/abs/2407.10640 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Error Bounds for the Network Scale-Up Method
Epidemiologists and social scientists have used the Network Scale-Up Method (NSUM) for over thirty years to estimate the size of a hidden sub-population within a social network. This method involves querying a subset of network nodes about the number of their neighbours belonging to the hidden sub-population. In general, NSUM assumes that the social network topology and the hidden sub-population distribution are well-behaved; hence, the NSUM estimate is close to the actual value. However, bound…

This https://arxiv.org/abs/2505.22221 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Tight qubit uncertainty relations studied through weak values in neutron interferometry
In its original formulation, Heisenberg's uncertainty principle describes a trade-off relation between the error of a quantum measurement and the thereby induced disturbance on the measured object. However, this relation is not valid in general. An alternative universally valid relation was derived by Ozawa in 2003, defining error and disturbance in a general concept, experimentally accessible via a tomographic method. Later, it was shown by Hall that these errors correspond to the statistical …

This https://arxiv.org/abs/2503.04091 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Generalization in Federated Learning: A Conditional Mutual Information Framework
Federated learning (FL) is a widely adopted privacy-preserving distributed learning framework, yet its generalization performance remains less explored compared to centralized learning. In FL, the generalization error consists of two components: the out-of-sample gap, which measures the gap between the empirical and true risk for participating clients, and the participation gap, which quantifies the risk difference between participating and non-participating clients. In this work, we apply an i…

Fired HHS employees allege terminations were based on 'error-ridden' personnel records (Politico)
https://www.politico.com/news/2025/06/03/hhs-rif-lawsuit-doge-00382453
http://www.memeorandum.com/250603/p100#a250603p100

This https://arxiv.org/abs/2009.14324 has been replaced.
link: https://scholar.google.com/scholar?q=a

Characterizing Jacobians via the KP equation and via flexes and degenerate trisecants to the Kummer variety: an algebro-geometric approach
This paper is withdrawn since we found a flaw in the proof of Theorem 4, asserting that the base locus of the complete linear system of an ample line bundle on a complex abelian variety is reduced. The error is in page 7, line $ -14$, where we claim that the divisor "mathcal E" on the variety $X$ is linearly equivalent to zero. This is untrue. For instance, it would imply that, for a non-torsion point $x$ on an abelian surface $A$, letting $E_x$, $E_{-x}$, and $E_0$ the exceptional curves in th…

Generalized Hardy's identity for the astroid-type p-circle lattice point problem
Masaya Kitajima
https://arxiv.org/abs/2506.03331 https://

Generalized Hardy's identity for the astroid-type p-circle lattice point problem
Let $r$ be a positive real number and $p$ satisfy $(2/p)\in\mathbb{N}$. Then, we consider the lattice point problem of the closed curves astroid-type $p$-circle $\{x\in\mathbb{R}^{2}|\ |x_{1}|^{p}+|x_{2}|^{p}=r^{p}\}$ which generalize the circle. In investigating the asymptotic behavior of the error term in the area approximation of the circle, G.H. Hardy conjectured an infimum for the evaluation in 1917. One of the grounds for this conjecture is the Hardy's identity, w…

Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
Yiheng Lin, Christopher Yeh, Zaiwei Chen, Adam Wierman
https://arxiv.org/abs/2506.04497

Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
We study the value of stochastic predictions in online optimal control with random disturbances. Prior work provides performance guarantees based on prediction error but ignores the stochastic dependence between predictions and disturbances. We introduce a general framework modeling their joint distribution and define "prediction power" as the control cost improvement from the optimal use of predictions compared to ignoring the predictions. In the time-varying Linear Quadratic Regulator (LQR) s…

Proposal for phased deprecation of a flag F in open-source projects:
Phase 1 - Using F emits a warning.
Phase 2 - Using F is a fatal error unless you add the flag `enable-deprecated-flag-F-and-send-telemetry-to-devs`
Phase 3 - Using `enable-deprecated...` emits a warning.
Phase 4 - Using `enable-deprecated...` is a fatal error unless you add the flag `we-really-need-deprecated-flag-F-and-have-paid-for-1-year-support-here-is-the-receipt`

This https://arxiv.org/abs/2501.09976 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNE_…

Dendritic Localized Learning: Toward Biologically Plausible Algorithm
Backpropagation is the foundational algorithm for training neural networks and a key driver of deep learning's success. However, its biological plausibility has been challenged due to three primary limitations: weight symmetry, reliance on global error signals, and the dual-phase nature of training, as highlighted by the existing literature. Although various alternative learning approaches have been proposed to address these issues, most either fail to satisfy all three criteria simultaneously …

Cowboys’ $31M in space earmarked, but massive commitments leave new deals little margin https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/05/30/cowboys-expensive-commitments-margin-error/8390824100…

I’ve never seen this memory issue on #MacOS before. I had left Safari with Mela’s share sheet/importer app snippet open overnight and came back to a nearly unresponsive computer. I assume one of these has a memory leak. I was able to reboot via the shell using SSH from another device.

Polish presidential election too close to call as campaigning enters final hours
Polls show difference between
pro-European Rafał Trzaskowski
and nationalist Karol Nawrocki within the margin of error
https://www.t…

Don't you love when you're trying to pwn something and stumble across a different bug than the one you were trying to find?
Some years ago I was trying to XSS a webapp and was confronted with a SQL error.
Turns out it *was* XSS-able, but you had to SQL-escape your javascript first.

This https://arxiv.org/abs/2209.09443 has been replaced.
link: https://scholar.google.com/scholar?q=a

Cryogenic in-memory computing using magnetic topological insulators
Machine learning algorithms have been proven effective for essential quantum computation tasks such as quantum error correction and quantum control. Efficient hardware implementation of these algorithms at cryogenic temperatures is essential. Here, we utilize magnetic topological insulators as memristors (termed magnetic topological memristors) and introduce a cryogenic in-memory computing scheme based on the coexistence of the chiral edge state and the topological surface state. The memristive…

Nonsmooth data error estimates for exponential Runge--Kutta methods and applications to split exponential integrators
Qiumei Huang, Alexander Ostermann, Gangfan Zhong
https://arxiv.org/abs/2506.02778

Nonsmooth data error estimates for exponential Runge--Kutta methods and applications to split exponential integrators
We derive error bounds for exponential Runge-Kutta discretizations of parabolic equations with nonsmooth initial data. Our analysis is carried out in a framework of abstract semilinear evolution equations with operators having non-dense domain. In particular, we investigate nonsmooth data error estimates for the Allen-Cahn and the Burgers' equation. As an application, we apply these nonsmooth data error estimates to split exponential integrators and derive a convergence result in terms of the d…

This https://arxiv.org/abs/2506.01056 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

MCP-Zero: Proactive Toolchain Construction for LLM Agents from Scratch
Function-calling has enabled large language models (LLMs) to act as tool-using agents, but injecting thousands of tool schemas into the prompt is costly and error-prone. We introduce MCP-Zero, a proactive agent framework that lets the LLM itself decide when and which external tools to retrieve, thereby assembling a task-specific toolchain from scratch. The framework is built upon three components: (1) Proactive Tool Request, where the model emits a structured $\left<\operatorname{tool\_assistan…

This https://arxiv.org/abs/2408.06211 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Causal Effect Identification and Inference with Endogenous Exposures and a Light-tailed Error
Endogeneity poses significant challenges in causal inference across various research domains. This paper proposes a novel approach to identify and estimate causal effects in the presence of endogeneity. We consider a structural equation with endogenous exposures and an additive error term. Assuming the light-tailedness of the error term, we show that the causal effect can be identified by contrasting extreme conditional quantiles of the outcome given the exposures. Unlike many existing results,…

Heliostat Optical Error Inspection with Polarimetric Imaging Drone
Mo Tian, Kolappan Chidambaranathan, Md Zubair Ebne Rafique, Neel Desai, Jing Bai, Randy Brost, Daniel Small, David Novick, Julius Yellowhair, Yu Yao
https://arxiv.org/abs/2506.02333

Heliostat Optical Error Inspection with Polarimetric Imaging Drone
On a Concentrated Solar Power (CSP) field, optical errors have significant impacts on the collection efficiency of heliostats. Fast, cost-effective, labor-efficient, and non-intrusive autonomous field inspection remains a challenge. Approaches using imaging drone, i.e., Unmanned Aerial Vehicle (UAV) system integrated with high resolution visible imaging sensors, have been developed to address these challenges; however, these approaches are often limited by insufficient imaging contrast. Here we…

Verification of the Timing System for the X-ray Imaging and Spectroscopy Mission in the GPS Unsynchronized Mode
Megumi Shidatsu, Yukikatsu Terada, Takashi Kominato, So Kato, Ryohei Sato, Minami Sakama, Takumi Shioiri, Yugo Motogami, Yuuki Niida, Chulsoo Kang, Toshihiro Takagi, Taichi Nakamoto, Chikara Natsukari, Makoto S. Tashiro, Kenichi Toda, Hironori Maejima, Shin Watanabe, Ryo Iizuka, Rie Sato, Chris Baluta, Katsuhiro Hayashi, Tessei Yoshida, Shoji Ogawa, Yoshiaki Kanemaru, Kotaro Fukushima, Akio Hoshino, Hiromitsu Takahashi, Masayoshi Nobukawa, Tsunefumi Mizuno, Kazuhiro Nakazawa, Shinichiro Uno, Ken Ebisawa, Satoshi Eguchi, Satoru Katsuda, Aya Kubota, Naomi Ota, Atsushi Tanimoto, Yuichi Terashima, Yohko Tsuboi, Yuusuke Uchida, Hideki Uchiyama, Shigeo Yamauchi, Tomokage Yoneyama, Satoshi Yamada, Nagomi Uchida, Matt Holland, Michael Loewenstein, Tahir Yaqoob, Eric D. Miller, Robert S. Hill, Efrain C. Perez-Solis, Morgan D. Waddy, Mark Mekosh, Joseph B. Fox, Isabella S. Brewer, Emily Aldoretta, Koji Mukai, Kenji Hamaguchi, Francois Mernier, Anna Ogorzalek, Katja Pottschmidt, Mihoko Yukita
#toXiv_bot_toot

Dhvani: A Weakly-supervised Phonemic Error Detection and Personalized Feedback System for Hindi
Arnav Rustagi, Satvik Bajpai, Nimrat Kaur, Siddharth Siddharth
https://arxiv.org/abs/2506.02166

Dhvani: A Weakly-supervised Phonemic Error Detection and Personalized Feedback System for Hindi
Computer-Assisted Pronunciation Training (CAPT) has been extensively studied for English. However, there remains a critical gap in its application to Indian languages with a base of 1.5 billion speakers. Pronunciation tools tailored to Indian languages are strikingly lacking despite the fact that millions learn them every year. With over 600 million speakers and being the fourth most-spoken language worldwide, improving Hindi pronunciation is a vital first step toward addressing this gap. This …

During work (no technical hanky panky)

This https://arxiv.org/abs/2506.03074 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

GL-LowPopArt: A Nearly Instance-Wise Minimax Estimator for Generalized Low-Rank Trace Regression
We present `GL-LowPopArt`, a novel Catoni-style estimator for generalized low-rank trace regression. Building on `LowPopArt` (Jang et al., 2024), it employs a two-stage approach: nuclear norm regularization followed by matrix Catoni estimation. We establish state-of-the-art estimation error bounds, surpassing existing guarantees (Fan et al., 2019; Kang et al., 2022), and reveal a novel experimental design objective, $\mathrm{GL}(π)$. The key technical challenge is controlling bias from the non…

This https://arxiv.org/abs/2503.20197 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Enhancing the Robustness of LLM-Generated Code: Empirical Study and Framework
Ensuring the robustness of code generated by large language models (LLMs) is crucial for real-world reliability. However, existing evaluations predominantly focus on correctness, often neglecting key robustness concerns such as missing input validation and insufficient error handling. In this paper, we present the first empirical study on the robustness of LLM-generated code. We introduce novel robustness metrics and analyze four state-of-the-art code LLMs, revealing that, on average, 43.1% of …

Projective error models: Stabilizer codes, Clifford codes, and weak stabilizer codes
Jonas Eidesen
https://arxiv.org/abs/2506.01843 https://

Projective error models: Stabilizer codes, Clifford codes, and weak stabilizer codes
We introduce more general notions of Clifford codes and stabilizer codes, the latter we call weak stabilizer codes. This is all formulated in the language of projective representation theory of finite groups and we give a novel description of the detectable errors for a Clifford code. We also give examples of infinite families of non-stabilizer Clifford codes as well as examples of non-Clifford weak stabilizer codes. The latter of these types of examples is a class of codes that have not been s…

This https://arxiv.org/abs/2505.20212 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Tools for Characterizing the Numerical Error of Stellar Oscillation Codes
Stellar oscillation codes are software instruments that evaluate the normal-mode frequencies of an input stellar model. While inter-code comparisons are often used to confirm the correctness of calculations, they are not suitable for characterizing the numerical error of an individual code. To address this issue, we introduce a set of tools -- 'error measures' -- that facilitate this characterization. We explore the behavior of these error measures as calculation parameters, such as the number …

On the construction of a gradient method of quadratic optimization, optimal from the point of view of minimizing the distance to the exact solution
N. V. Pletnev
https://arxiv.org/abs/2506.04866

On the construction of a gradient method of quadratic optimization, optimal from the point of view of minimizing the distance to the exact solution
Problems of quadratic optimization in Hilbert space often arise when solving ill-posed problems for differential equations. In this case, the target value of the functional is known. In addition, the structure of the functional allows calculating the gradient by solving well-posed problems, which allows applying first-order methods. This article is devoted to the construction of the $m$-moment minimum error method -- an effective method that minimizes the distance to the exact solution. The con…

The Error in a Smooth Weighted Prime Number Formula and Zero-free Regions for the Riemann Zeta Function
Songlin Han
https://arxiv.org/abs/2505.23795 https:…

The Error in a Smooth Weighted Prime Number Formula and Zero-free Regions for the Riemann Zeta Function
We study the error bound for a smooth weighted prime number theorem, and its implication to the zero-free region for the Riemann zeta function using the method of Pintz. We also give an application to the average number of smooth weighted Goldbach representations and generalize the result to the case of smooth weighted average k-Goldbach representations.

Spectral Efficiency Maximization for mmWave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints
Jitendra Singh, Anand Mehrotra, Suraj Srivastava, Aditya K. Jagannatham, Lajos Hanzo
https://arxiv.org/abs/2506.04683

Spectral Efficiency Maximization for mmWave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints
A hybrid transmit precoder (TPC) and receive combiner (RC) pair is conceived for millimeter wave (mmWave) multiple input multiple output (MIMO) integrated sensing and communication (ISAC) systems. The proposed design considers a practical mean squared error (MSE) constraint between the desired and the achieved beampatterns constructed for identifying radar targets (RTs). To achieve optimal performance, we formulate an optimization problem relying on sum spectral efficiency (SE) maximization of …

This https://arxiv.org/abs/2502.10527 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Algorithms and Hardness for Estimating Statistical Similarity
We introduce and study the computational problem of determining statistical similarity between probability distributions. For distributions $P$ and $Q$ over a finite sample space, their statistical similarity is defined as $S_{\mathrm{stat}}(P, Q) := \sum_x \min(P(x), Q(x))$. Despite its fundamental nature as a measure of similarity between distributions, capturing essential concepts such as Bayes error in prediction and hypothesis testing, this computational problem has not been previously exp…

{purrr} has some lesser known functions that make handling of failing function calls easier: safely, quietly, possibly: #rstats…

Wrap a function to capture errors — safely
Creates a modified version of .f that always succeeds. It returns a list with components result and error. If the function succeeds, result contains the returned value and error is NULL. If an error occurred, error is an error object and result is either NULL or otherwise.

The Bayesian Finite Element Method in Inverse Problems: a Critical Comparison between Probabilistic Models for Discretization Error
Anne Poot, Iuri Rocha, Pierre Kerfriden, Frans van der Meeer
https://arxiv.org/abs/2506.02815

The Bayesian Finite Element Method in Inverse Problems: a Critical Comparison between Probabilistic Models for Discretization Error
When using the finite element method (FEM) in inverse problems, its discretization error can produce parameter estimates that are inaccurate and overconfident. The Bayesian finite element method (BFEM) provides a probabilistic model for the epistemic uncertainty due to discretization error. In this work, we apply BFEM to various inverse problems, and compare its performance to the random mesh finite element method (RM-FEM) and the statistical finite element method (statFEM), which serve as a fr…

Offline Map Matching Based on Localization Error Distribution Modeling
Ruilin Xu, Yuchen Song, Kaijie Li, Xitong Gao, Kejiang Ye, Fan Zhang, Juanjuan Zhao
https://arxiv.org/abs/2505.23123

Offline Map Matching Based on Localization Error Distribution Modeling
Offline map matching involves aligning historical trajectories of mobile objects, which may have positional errors, with digital maps. This is essential for applications in intelligent transportation systems (ITS), such as route analysis and traffic pattern mining. Existing methods have two main limitations: (i) they assume a uniform Localization Error Distribution (LED) across urban areas, neglecting environmental factors that lead to suboptimal path search ranges, and (ii) they struggle to ef…

Re-experiment Smart: a Novel Method to Enhance Data-driven Prediction of Mechanical Properties of Epoxy Polymers
Wanshan Cui, Yejin Jeong, Inwook Song, Gyuri Kim, Minsang Kwon, Donghun Lee
https://arxiv.org/abs/2506.01994

Re-experiment Smart: a Novel Method to Enhance Data-driven Prediction of Mechanical Properties of Epoxy Polymers
Accurate prediction of polymer material properties through data-driven approaches greatly accelerates novel material development by reducing redundant experiments and trial-and-error processes. However, inevitable outliers in empirical measurements can severely skew machine learning results, leading to erroneous prediction models and suboptimal material designs. To address this limitation, we propose a novel approach to enhance dataset quality efficiently by integrating multi-algorithm outlier …

This https://arxiv.org/abs/2504.05424 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Speculative Automated Refactoring of Imperative Deep Learning Programs to Graph Execution
Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code -- supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approach…

All tools create a path of least resistance. When it comes to AI chatbots, that path is to trust the AI's outputs.
Unfortunately, all LLMs hallucinate. And as users get used to relying on the machine, their ability and willingness to spot these errors deteriorates.
Blaming the user for this is irresponsible. The problem is caused by the way these tools are designed - so it's up to us, as designers, to fix it.

@…
The forScore website’s been down all day. Attempting to connect to
https://forscore.co or anything in it produces
"
Error establishing a database conn…

This https://arxiv.org/abs/2505.10930 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models
Auto-regressive partial differential equation (PDE) foundation models have shown great potential in handling time-dependent data. However, these models suffer from the shortcut problem deeply rooted in auto-regressive prediction, causing error accumulation. The challenge becomes particularly evident for out-of-distribution data, as the pretraining performance may approach random model initialization for downstream tasks with long-term dynamics. To deal with this problem, we propose physics-info…

This https://arxiv.org/abs/2501.09015 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Family-wise Error Rate Control with E-values
The closure principle is a standard tool for achieving strong family-wise error rate (FWER) control in multiple testing problems. We develop an e-value-based closed testing framework that inherits nice properties of e-values, which are common in settings of sequential hypothesis testing or universal inference for irregular parametric models. We prove that e-value-based closed testing strongly controls the post-hoc FWER in the static setting, and has stronger anytime-valid and always-valid FWER-…

#Wordle 1,443 6/6*
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⬜🟩🟩⬜🟩 13% of 8 (3)
⬜🟩🟩⬜🟩 <1% of 2,846 (3)
⬜🟩🟩🟩🟩 13% of 2,851 (2)
⬜🟩🟩🟩🟩 34% of 769 (1)
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WordleBot
Skill 75/99
Luck 50/99
Well that was close. I don't think there were any other words to try...oops I see, user error on 3rd guess, and then yes my last guess was the only word left.

Practical Short-Length Coding Schemes for Binary Distributed Hypothesis Testing
Ismaila Salihou Adamou, Elsa Dupraz, Reza Asvadi, Tad Matsumoto
https://arxiv.org/abs/2506.01747

Practical Short-Length Coding Schemes for Binary Distributed Hypothesis Testing
This paper addresses the design of practical shortlength coding schemes for Distributed Hypothesis Testing (DHT). While most prior work on DHT has focused on informationtheoretic analyses, deriving bounds on Type-II error exponents via achievability schemes based on quantization and quantizebinning, the practical implementation of DHT coding schemes has remained largely unexplored. Moreover, existing practical coding solutions for quantization and quantize-binning approaches were developed for …

On Hermite type sampling Kantorovich operators in the settings of mixed norm Spaces
Puja Sonawane, A. Sathish Kumar
https://arxiv.org/abs/2506.02468 https:…

On Hermite type sampling Kantorovich operators in the settings of mixed norm Spaces
In this paper, we analyze the convergence behavior of Hermite-type sampling Kantorovich operators in the context of mixed norm spaces. We prove certain direct approximation theorems, including the uniform convergence theorem, the Voronovskaja-type asymptotic formula, and an estimate of error in the approximation in terms of the modulus of continuity in mixed norm settings. Next, we estimate the rate of convergence of these sampling Kantorovich operators in terms of the modulus of continuity. In…

This https://arxiv.org/abs/2505.23240 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Joint estimation of smooth graph signals from partial linear measurements
Given an undirected and connected graph $G$ on $T$ vertices, suppose each vertex $t$ has a latent signal $x_t \in \mathbb{R}^n$ associated to it. Given partial linear measurements of the signals, for a potentially small subset of the vertices, our goal is to estimate $x_t$'s. Assuming that the signals are smooth w.r.t $G$, in the sense that the quadratic variation of the signals over the graph is small, we obtain non-asymptotic bounds on the mean squared error for jointly recovering $x_t$'s, fo…

A gradient-enhanced approach for stable finite element approximations of reaction-convection-diffusion problems
Soheil Firooz, B. Daya Reddy, Paul Steinmann
https://arxiv.org/abs/2506.01873

A gradient-enhanced approach for stable finite element approximations of reaction-convection-diffusion problems
We develop a micromorphic-based approach for finite element stabilization of reaction-convection-diffusion equations, by gradient enhancement of the field of interest via introducing an auxiliary variable. The well-posedness of the coupled-field approach is established, together with an error estimate. Through a set of 1D and 2D numerical examples the high accuracy and enhanced stability of the approach in approximating solutions associated with complex problems is demonstrated, for situations …

Bi-Level optimization for parameter estimation of differential equations using interpolation
Siddharth Prabhu, Srinivas Rangarajan, Mayuresh Kothare
https://arxiv.org/abs/2506.00720

Bi-Level optimization for parameter estimation of differential equations using interpolation
Inverse problem or parameter estimation of ordinary differential equations is a process of obtaining the best parameters using experimental measurements of the states. Single (Multiple)-shooting is a type of sequential optimization method that minimizes the error in the measured and numerically integrated states. However, this requires computing sensitivities i.e. the derivatives of states with respect to the parameters over the numerical integrator, which can get computationally expensive. To …

Geometric Visual Servo Via Optimal Transport
Ethan Canzini, Simon Pope, Ashutosh Tiwari
https://arxiv.org/abs/2506.02768 https://arxi…

Geometric Visual Servo Via Optimal Transport
When developing control laws for robotic systems, the principle factor when examining their performance is choosing inputs that allow smooth tracking to a reference input. In the context of robotic manipulation, this involves translating an object or end-effector from an initial pose to a target pose. Robotic manipulation control laws frequently use vision systems as an error generator to track features and produce control inputs. However, current control algorithms don't take into account the …

Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
Qiming Zhu, Jialun Cao, Xuanang Chen, Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun, Shing-Chi Cheung
https://arxiv.org/abs/2506.03535

Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
Current research on large language models (LLMs) with retrieval-augmented code generation (RACG) mainly focuses on single-language settings, leaving cross-lingual effectiveness and security unexplored. Multi-lingual RACG systems are valuable for migrating code-bases across programming languages (PLs), yet face risks from error (e.g. adversarial data corruption) propagation in cross-lingual transfer. We construct a dataset spanning 13 PLs with nearly 14k instances to explore utility and robustne…

This https://arxiv.org/abs/2009.14324 has been replaced.
link: https://scholar.google.com/scholar?q=a

Characterizing Jacobians via the KP equation and via flexes and degenerate trisecants to the Kummer variety: an algebro-geometric approach
This paper is withdrawn since we found a flaw in the proof of Theorem 4, asserting that the base locus of the complete linear system of an ample line bundle on a complex abelian variety is reduced. The error is in page 7, line $ -14$, where we claim that the divisor "mathcal E" on the variety $X$ is linearly equivalent to zero. This is untrue. For instance, it would imply that, for a non-torsion point $x$ on an abelian surface $A$, letting $E_x$, $E_{-x}$, and $E_0$ the exceptional curves in th…

Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Qiang Chen, Tianyang Han, Jin Li, Ye Luo, Yuxiao Wu, Xiaowei Zhang, Tuo Zhou
https://arxiv.org/abs/2506.00856

Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
Can AI effectively perform complex econometric analysis traditionally requiring human expertise? This paper evaluates an agentic AI's capability to master econometrics, focusing on empirical analysis performance. We develop an ``Econometrics AI Agent'' built on the open-source MetaGPT framework. This agent exhibits outstanding performance in: (1) planning econometric tasks strategically, (2) generating and executing code, (3) employing error-based reflection for improved robustness, and (4) all…

This https://arxiv.org/abs/2404.11444 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Fidelity decay and error accumulation in random quantum circuits
We present a comprehensive analysis of fidelity decay and error accumulation in faulty quantum circuit models. Our work devises an analytical bound for the average fidelity between desired and faulty output states, accounting for errors that may arise during the implementation of two-qubit gates and multi-qubit permutations. It is shown that fidelity decays exponentially with both circuit depth and the number of qubits raised to an architecture-dependent power, and determine the decay rates as …

Functionality Assessment Framework for Autonomous Driving Systems using Subjective Networks
Stefan Orf, Sven Ochs, Valentin Marotta, Oliver Conder, Marc Ren\'e Zofka, J. Marius Z\"ollner
https://arxiv.org/abs/2506.02922

Functionality Assessment Framework for Autonomous Driving Systems using Subjective Networks
In complex autonomous driving (AD) software systems, the functioning of each system part is crucial for safe operation. By measuring the current functionality or operability of individual components an isolated glimpse into the system is given. Literature provides several of these detached assessments, often in the form of safety or performance measures. But dependencies, redundancies, error propagation and conflicting functionality statements do not allow for easy combination of these measures…

This https://arxiv.org/abs/2502.09493 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Quantitative estimates for high-contrast random media
This paper studies quantitative homogenization of elliptic equations with random, uniformly elliptic coefficients that vanish in a union of random holes. Assuming an upper bound on the size of the holes and a separation condition between them, we derive optimal bounds for the regularity radius $r_*$ and suboptimal growth estimates for the corrector. These results are key ingredients for error analysis in stochastic homogenization and serve as crucial input for recent developments in the double-…

This https://arxiv.org/abs/2501.19277 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

On Pareto Optimality for the Multinomial Logistic Bandit
We provide a new online learning algorithm for tackling the Multinomial Logit Bandit (MNL-Bandit) problem. Despite the challenges posed by the combinatorial nature of the MNL model, we develop a novel Upper Confidence Bound (UCB)-based method that achieves Pareto optimality by balancing regret minimization and estimation error of the assortment revenues and the MNL parameters. We develop theoretical guarantees characterizing the tradeoff between regret and estimation error for the MNL-Bandit pr…

Sharp error bounds for approximate eigenvalues and singular values from subspace methods
Irina-Beatrice Haas, Yuji Nakatsukasa
https://arxiv.org/abs/2506.01207

Sharp error bounds for approximate eigenvalues and singular values from subspace methods
Subspace methods are commonly used for finding approximate eigenvalues and singular values of large-scale matrices. Once a subspace is found, the Rayleigh-Ritz method (for symmetric eigenvalue problems) and Petrov-Galerkin projection (for singular values) are the de facto method for extraction of eigenvalues and singular values. In this work we derive quadratic error bounds for approximate eigenvalues obtained via the Rayleigh-Ritz process. Our bounds take advantage of the fact that extremal ei…

Meta-heuristic design of a light-weight homologous backup structure of the primary reflector for the Large Submillimeter Telescope
Chihiro Imamura, Yoichi Tamura, Hiroaki Kawamura, Toshiaki Kimura, Akio Taniguchi, Mikio Kurita
#toXiv_bot_toot

Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty
Niklas Baumgarten, David Schneiderhan
https://arxiv.org/abs/2506.02647 https:/…

Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty
We present a multilevel stochastic gradient descent method for the optimal control of systems governed by partial differential equations under uncertain input data. The gradient descent method used to find the optimal control leverages a parallel multilevel Monte Carlo method as stochastic gradient estimator. As a result, we achieve precise control over the stochastic gradient's bias, introduced by numerical approximation, and its sampling error, arising from the use of incomplete gradients, wh…

Fine-Tuning ASR for Stuttered Speech: Personalized vs. Generalized Approaches
Dena Mujtaba, Nihar Mahapatra
https://arxiv.org/abs/2506.00853 https://

Fine-Tuning ASR for Stuttered Speech: Personalized vs. Generalized Approaches
Stuttering -- characterized by involuntary disfluencies such as blocks, prolongations, and repetitions -- is often misinterpreted by automatic speech recognition (ASR) systems, resulting in elevated word error rates and making voice-driven technologies inaccessible to people who stutter. The variability of disfluencies across speakers and contexts further complicates ASR training, compounded by limited annotated stuttered speech data. In this paper, we investigate fine-tuning ASRs for stuttered…

Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings
Anirudh Nair, Adi Banerjee, Laurent Mombaerts, Matthew Hagen, Tarik Borogovac
https://arxiv.org/abs/2506.00178

Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings
Prompt engineering represents a critical bottleneck to harness the full potential of Large Language Models (LLMs) for solving complex tasks, as it requires specialized expertise, significant trial-and-error, and manual intervention. This challenge is particularly pronounced for tasks involving subjective quality assessment, where defining explicit optimization objectives becomes fundamentally problematic. Existing automated prompt optimization methods falter in these scenarios, as they typicall…

This https://arxiv.org/abs/2505.00427 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

A new approximate Eastin-Knill theorem
Transversal encoded gatesets are highly desirable for fault tolerant quantum computing. However, a quantum error correcting code which exactly corrects for local erasure noise and supports a universal set of transversal gates is ruled out by the Eastin-Knill theorem. Here we provide a new approximate Eastin-Knill theorem for the single-shot regime when we allow for some probability of error in the decoding. In particular, we show that a quantum error correcting code can support a universal set …

IAE Optimized PID Tuning with Phase Margin and Crossover Frequency Constraints
Senol Gulgonul
https://arxiv.org/abs/2506.00923 https://

IAE Optimized PID Tuning with Phase Margin and Crossover Frequency Constraints
This paper presents PMwc-Tune, a novel PID tuning method that uniquely combines frequency-domain robustness constraints with time-domain performance optimization through constrained nonlinear programming. The key contribution is a unified formulation that simultaneously enforces phase margin and crossover frequency requirements (via nonlinear equality constraints) while minimizing the Integral Absolute Error (IAE) of the closed-loop response. The algorithm employs Sequential Quadratic Programmi…

This https://arxiv.org/abs/2501.03742 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Computing accurate eigenvalues using a mixed-precision Jacobi algorithm
We provide a rounding error analysis of a mixed-precision preconditioned Jacobi algorithm, which uses low precision to compute the preconditioner, applies it at high precision (amounting to two matrix-matrix multiplications) and solves the eigenproblem using the Jacobi algorithm at working precision. Our analysis yields meaningfully smaller relative forward error bounds for the computed eigenvalues compared with those of the Jacobi algorithm. We further prove that, after preconditioning, if the…

This https://arxiv.org/abs/2403.11436 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Deep Holes of Twisted Reed-Solomon Codes
The deep holes of a linear code are the vectors that achieve the maximum error distance (covering radius) to the code. {Determining the covering radius and deep holes of linear codes is a fundamental problem in coding theory. In this paper, we investigate the problem of deep holes of twisted Reed-Solomon codes.} The covering radius and a standard class of deep holes of twisted Reed-Solomon codes ${\rm TRS}_k(\mathcal{A}, θ)$ are obtained for a general evaluation set $\mathcal{A} \subseteq \mat…

Power Enhancement of Permutation-Augmented Partial-Correlation Tests via Fixed-Row Permutations
Tianyi Wang, Guanghui Wang, Zhaojun Wang, Changliang Zou
https://arxiv.org/abs/2506.02906

Power Enhancement of Permutation-Augmented Partial-Correlation Tests via Fixed-Row Permutations
Permutation-based partial-correlation tests guarantee finite-sample Type I error control under any fixed design and exchangeable noise, yet their power can collapse when the permutation-augmented design aligns too closely with the covariate of interest. We remedy this by fixing a design-driven subset of rows and permuting only the remainder. The fixed rows are chosen by a greedy algorithm that maximizes a lower bound on power. This strategy reduces covariate-permutation collinearity while prese…

OntoRAG: Enhancing Question-Answering through Automated Ontology Derivation from Unstructured Knowledge Bases
Yash Tiwari, Owais Ahmad Lone, Mayukha Pal
https://arxiv.org/abs/2506.00664

OntoRAG: Enhancing Question-Answering through Automated Ontology Derivation from Unstructured Knowledge Bases
Ontologies are pivotal for structuring knowledge bases to enhance question answering (QA) systems powered by Large Language Models (LLMs). However, traditional ontology creation relies on manual efforts by domain experts, a process that is time intensive, error prone, and impractical for large, dynamic knowledge domains. This paper introduces OntoRAG, an automated pipeline designed to derive ontologies from unstructured knowledge bases, with a focus on electrical relay documents. OntoRAG integr…

This https://arxiv.org/abs/2301.07476 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Negative Moment Bounds for Sample Autocovariance Matrices of Stationary Processes Driven by Conditional Heteroscedastic Errors and Their Applications
We establish a negative moment bound for the sample autocovariance matrix of a stationary process driven by conditional heteroscedastic errors. This moment bound enables us to asymptotically express the mean squared prediction error (MSPE) of the least squares predictor as the sum of three terms related to model complexity, model misspecification, and conditional heteroscedasticity. A direct application of this expression is the development of a model selection criterion that can asymptotically…

Attention-Aided MMSE for OFDM Channel Estimation: Learning Linear Filters with Attention
TaeJun Ha, Chaehyun Jung, Hyeonuk Kim, Jeongwoo Park, Jeonghun Park
https://arxiv.org/abs/2506.00452

Attention-Aided MMSE for OFDM Channel Estimation: Learning Linear Filters with Attention
In orthogonal frequency division multiplexing (OFDM), accurate channel estimation is crucial. Classical signal processing based approaches, such as minimum mean-squared error (MMSE) estimation, often require second-order statistics that are difficult to obtain in practice. Recent deep neural networks based methods have been introduced to address this; yet they often suffer from high complexity. This paper proposes an Attention-aided MMSE (A-MMSE), a novel model-based DNN framework that learns t…

This https://arxiv.org/abs/2207.01061 has been replaced.
link: https://scholar.google.com/scholar?q=a

Computing Vanishing Ideals for Toric Codes
Motivated by applications to the theory of error-correcting codes, we give methods for computing a generating set for the ideal generated by $β$-graded polynomials vanishing on certain subsets of a simplicial complete toric variety $X$ over a finite field $\mathbb{F}_q$, where $β$ is a $d\times r$ matrix whose columns generate a subsemigroup $\mathbb{N}β$ of $\mathbb{N}^d$. We also give a method for computing the vanishing ideal of the set of $\mathbb{F}_q$-rational points of $X$. When $β=[…

$\text{TREX}^2$: Dual-Reconstruction Framework for Teleoperated-Robot with EXtended Reality
Ziliang Zhang, Cong Liu, Hyoseung Kim
https://arxiv.org/abs/2506.01135

$\text{TREX}^2$: Dual-Reconstruction Framework for Teleoperated-Robot with EXtended Reality
Robot teleoperation with extended reality (XR teleoperation) enables intuitive interaction by allowing remote robots to mimic user motions with real-time 3D feedback. However, existing systems face significant motion-to-motion (M2M) latency--the delay between the user's latest motion and the corresponding robot feedback--leading to high teleoperation error and mission completion time. This issue stems from the system's exclusive reliance on network communication, making it highly vulnerable to …

This https://arxiv.org/abs/2407.18929 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Disturbance-based Discretization, Differentiable IDS Channel, and an IDS-Correcting Code for DNA Storage
Insertion, deletion, and substitution (IDS) error-correcting codes have garnered increased attention with recent advancements in DNA storage technology. However, a universal method for designing tailored IDS-correcting codes across varying channel settings remains underexplored. We present an autoencoder-based approach, THEA-code, aimed at efficiently generating IDS-correcting codes for complex IDS channels. In the work, a disturbance-based discretization is proposed to discretize the features …

This https://arxiv.org/abs/2412.16761 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Non-asymptotic Error Analysis of Subspace Identification for Deterministic Systems
The subspace identification method (SIM) has been extensively employed in the identification of discrete-time multiple-input multiple-output (MIMO) linear time-invariant (LTI) systems. This paper focuses on the analysis of perturbation errors for the system matrices in state-space models and the corresponding system poles, under two unified SIMs, based on a single finite-length input/output sample trajectory. Specifically, we derive non-asymptotic upper bounds on these errors, providing a unifi…

Incorporating Correlated Nugget Effects in Multivariate Spatial Models: An Application to Argo Ocean Data
Damilya Saduakhas, David Bolin, Xiaotian Jin, Alexandre B. Simas, Jonas Wallin
https://arxiv.org/abs/2506.03042

Incorporating Correlated Nugget Effects in Multivariate Spatial Models: An Application to Argo Ocean Data
Accurate analysis of global oceanographic data, such as temperature and salinity profiles from the Argo program, requires geostatistical models capable of capturing complex spatial dependencies. This study introduces Gaussian and non-Gaussian hierarchical multivariate Matérn-SPDE models with correlated nugget effects to account for small-scale variability and measurement error correlations. Using simulations and Argo data, we demonstrate that incorporating correlated nugget effects significant…

This https://arxiv.org/abs/2502.14391 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Passive leakage removal unit based on a disordered transmon array
Leakage out from the qubit subspace compromises standard quantum error correction protocols and is a challenge for practical quantum computing. We propose a passive leakage removal unit based on an array of coupled disordered transmons and last-site reset by feedback-measurement or dissipation. The transmons have parametric disorder both in frequency and anharmonicity such that the qubit subspace is protected by localization through energy level mismatch while the energy levels for leakage exci…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Chen Xiong, Pin-Yu Chen, Tsung-Yi Ho
https://arxiv.org/abs/2506.00781 ht…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Recent advances in Large Language Models (LLMs) have spurred transformative applications in various domains, ranging from open-source to proprietary LLMs. However, jailbreak attacks, which aim to break safety alignment and user compliance by tricking the target LLMs into answering harmful and risky responses, are becoming an urgent concern. The practice of red-teaming for LLMs is to proactively explore potential risks and error-prone instances before the release of frontier AI technology. This …

This https://arxiv.org/abs/2503.17228 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Mean value of cubic $L$-funcitons with fixed genus
We investigate the mean value of the first moment of primitive cubic $L$-functions over $\mathbb{F}_q(T)$ in the non-Kummer setting. Specifically, we study the sum \begin{equation*} \sum_{\substack{χ primitive\ cubic\\ genus(χ)=g}}L_q(\frac{1}{2}, χ), \end{equation*} where $L_q(s,χ)$ denotes the $L$-function associated with primitive cubic character $χ$. Using double Dirichlet series, we derive an error term of size $q^{(\frac{7}{8}+\varepsilon)g}$.

The Impact of Uniform Circular Array on Near-field ISAC
Na Xue, Xidong Mu, Yue Chen, Yuanwei Liu
https://arxiv.org/abs/2506.00211 https://

The Impact of Uniform Circular Array on Near-field ISAC
A novel uniform circular array (UCA) based near-field (NF) integrated sensing and communication (ISAC) framework is proposed, where the Cylindrical coordinate is invoked to evaluate the joint positioning performance. The joint squared position error bound (SPEB) of the sensing target (ST) is derived for the coplanar and non-coplanar cases. For the coplanar case, where the ST is located in the coplanar region of the UCA, the approximate Cram{é}r-Rao bound (CRB) expressions for the separate angl…

Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
Florian F\"urrutter, Zohim Chandani, Ikko Hamamura, Hans J. Briegel, Gorka Mu\~noz-Gil
https://arxiv.org/abs/2506.01666

Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
Efficiently compiling quantum operations remains a major bottleneck in scaling quantum computing. Today's state-of-the-art methods achieve low compilation error by combining search algorithms with gradient-based parameter optimization, but they incur long runtimes and require multiple calls to quantum hardware or expensive classical simulations, making their scaling prohibitive. Recently, machine-learning models have emerged as an alternative, though they are currently restricted to discrete ga…

STARS-assisted Near-field ISAC: Sensor Deployment and Beamforming Design
Na Xue, Xidong Mu, Yue Chen, Yuanwei Liu
https://arxiv.org/abs/2506.00192 https://…

STARS-assisted Near-field ISAC: Sensor Deployment and Beamforming Design
A simultaneously transmitting and reflecting surface (STARS) assisted near-field (NF) integrated sensing and communication (ISAC) framework is proposed, where the radio sensors are installed on the STARS to directly conduct the distance-domain sensing by exploiting the characteristic spherical wavefront. A new squared position error bound (SPEB) expression is derived to reveal the dependence on beamforming (BF) design and sensor deployment. To balance the trade-off between the SPEB and the sens…

This https://arxiv.org/abs/2503.14418 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Distributed RISE-based Control for Exponential Heterogeneous Multi-Agent Target Tracking of Second-Order Nonlinear Systems
A distributed implementation of a Robust Integral of the Sign of the Error (RISE) controller is developed for multi-agent target tracking problems with exponential convergence guarantees. Previous RISE-based approaches for multi-agent systems required 2-hop communication, limiting practical applicability. New insights from a Lyapunov-based design-analysis approach are used to eliminate the need for multi-hop communication required in previous literature, while yielding exponential target tracki…

This https://arxiv.org/abs/2504.21845 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

On the Efficacy of the Peeling Decoder for the Quantum Expander Code
The problem of recovering from qubit erasures has recently gained attention as erasures occur in many physical systems such as photonic systems, trapped ions, superconducting qubits and circuit quantum electrodynamics. While several linear-time decoders for error correction are known, their error-correcting capability is limited to half the minimum distance of the code, whereas erasure correction allows one to go beyond this limit. As in the classical case, stopping sets pose a major challenge …

Greedy recursion parameter selection for the One-Way Navier-Stokes (OWNS) equations
Michael K. Sleeman, Tim Colonius
https://arxiv.org/abs/2506.02320 https…

Greedy recursion parameter selection for the One-Way Navier-Stokes (OWNS) equations
The One-Way Navier-Stokes (OWNS) equations use recursive filtering to construct efficient, well-posed one-way approximations to linear hyperbolic systems. The recursion parameters are critical to the accuracy and stability of the method, and have previously been chosen based on heuristic estimates of key eigenvalues (or their branches), which converges slowly and requires trial-and-error tuning for new systems. We review the projection and recursive OWNS formulations (OWNS-P and OWNS-R) for inh…

An adaptive delaminating Levin method in two dimensions
Shukui Chen, Kirill Serkh, James Bremer, Murdock Aubry
https://arxiv.org/abs/2506.02424 https://

An adaptive delaminating Levin method in two dimensions
We present an adaptive delaminating Levin method for evaluating bivariate oscillatory integrals over rectangular domains. Whereas previous analyses of Levin methods impose non-resonance conditions that exclude stationary and resonance points, we rigorously establish the existence of a slowly-varying, approximate solution to the Levin PDE across all frequency regimes, even when the non-resonance condition is violated. This allows us to derive error estimates for the numerical solution of the Lev…

This https://arxiv.org/abs/2407.02722 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Pulse Design of Baseband Flux Control for Adiabatic Controlled-Phase Gates in Superconducting Circuits
Despite progress towards achieving low error rates with superconducting qubits, error-prone two-qubit gates remain a bottleneck for realizing large-scale quantum computers. Therefore, a systematic framework to design high-fidelity gates becomes imperative. One type of two-qubit gate in superconducting qubits is the controlled-phase (CPHASE) gate, which utilizes a conditional interaction between higher energy levels of the qubits controlled by a baseband flux pulse on one of the qubits or a tuna…

Rates of convergence of finite element approximations of second-order mean field games with nondifferentiable Hamiltonians
Yohance A. P. Osborne, Iain Smears
https://arxiv.org/abs/2506.03039

Rates of convergence of finite element approximations of second-order mean field games with nondifferentiable Hamiltonians
We prove a rate of convergence for finite element approximations of stationary, second-order mean field games with nondifferentiable Hamiltonians posed in general bounded polytopal Lipschitz domains with strongly monotone running costs. In particular, we obtain a rate of convergence in the $H^1$-norm for the value function approximations and in the $L^2$-norm for the approximations of the density. We also establish a rate of convergence for the error between the exact solution of the MFG system…

A Positivity-Preserving Finite Element Framework for Accurate Dose Computation in Proton Therapy
Ben S. Ashby, Abdalaziz Hamdan, Tristan Pryer
https://arxiv.org/abs/2506.01105

A Positivity-Preserving Finite Element Framework for Accurate Dose Computation in Proton Therapy
We present a stabilised finite element method for modelling proton transport in tissue, incorporating both inelastic energy loss and elastic angular scattering. A key innovation is a positivity-preserving formulation that guarantees non-negative fluence and dose, even on coarse meshes. This enables reliable computation of clinically relevant quantities for treatment planning. We derive a priori error estimates demonstrating optimal convergence rates and validate the method through numerical ben…