Tootfinder

Tailored Quantum Device Calibration with Statistical Model Checking
Filip Mazurek, Marissa D'Onofrio, Andrew Van Horn, Jiyong Yu, Kavyashree Ranawat, Jungsang Kim, Kenneth R. Brown
https://arxiv.org/abs/2507.12323

Tailored Quantum Device Calibration with Statistical Model Checking
Quantum devices require precisely calibrated analog signals, a process that is complex and time-consuming. Many calibration strategies exist, and all require careful analysis and tuning to optimize system availability. To enable rigorous statistical evaluation of quantum calibration procedures, we leverage statistical model checking (SMC), a technique used in fields that require statistical guarantees. SMC allows for probabilistic evaluation of properties of interest, such as a certain paramete…

Capturing System Drift with Time Series Calibration for Global 21-cm Cosmology Experiments
Christian J. Kirkham, Dominic J. Anstey, Eloy de Lera Acedo
https://arxiv.org/abs/2509.13010

Capturing System Drift with Time Series Calibration for Global 21-cm Cosmology Experiments
To achieve the sensitivity required to detect signals from neutral hydrogen from the Cosmic Dawn and Epoch of Reionisation it is critical to have a well-calibrated instrument which has a stable calibration over the course of the observation. Previous calibration methods do not explicitly use the time information available and make assumptions on the impedance matching of the reference sources. Here we present a new calibration method based on noise wave parameters which fits a calibration solut…

TERF Inc.
https://web.archive.org/web/20190727183834/http://terf.com/

Cohomological Calibration and Curvature Constraints on Product Manifolds: A Topological Lower Bound
Alexander Pigazzini, Magdalena Toda
https://arxiv.org/abs/2509.11834 https://…

Cohomological Calibration and Curvature Constraints on Product Manifolds: A Topological Lower Bound
We establish a quantitative relationship between mixed cohomology classes and the geometric complexity of cohomologically calibrated metric connections with totally skew torsion on product manifolds. Extending the results of Pigazzini--Toda (2025), we show that the dimension of the off-diagonal curvature subspace of a connection $\nabla^C$ is bounded below by the sum of tensor ranks of the mixed Künneth components of its calibration class. The bound depends only on the mixed class $[ω]_{\math…

Sentiment Feedback in Equity Markets: Asymmetries, Retail Heterogeneity, and Structural Calibration
Lucas Marques Sneller
https://arxiv.org/abs/2509.11970 https://

Sentiment Feedback in Equity Markets: Asymmetries, Retail Heterogeneity, and Structural Calibration
We study how sentiment shocks propagate through equity returns and investor clientele using four independent proxies with sign-aligned kappa-rho parameters. A structural calibration links a one standard deviation innovation in sentiment to a pricing impact of 1.06 basis points with persistence parameter rho = 0.940, yielding a half-life of 11.2 months. The impulse response peaks around the 12-month horizon, indicating slow-moving amplification. Cross-sectionally, a simple D10-D1 portfolio earns…

Absolute Calibration of Cluster Mira Variables to Provide a New Anchor for the Hubble Constant Determination
Anupam Bhardwaj, Noriyuki Matsunaga, Caroline D. Huang, Adam G. Riess, Marina Rejkuba
https://arxiv.org/abs/2507.10658

Absolute Calibration of Cluster Mira Variables to Provide a New Anchor for the Hubble Constant Determination
Mira variables in globular clusters can provide an accurate and precise absolute calibration of their period-luminosity relations (PLRs) to independently anchor the cosmic distance scale and determine the Hubble constant. We present homogeneous near-infrared ($JHK_s$) time-series photometric observations of a sample of 55 candidate long-period variables in 18 globular clusters covering a wide metallicity range ($-1.7 < \textrm{[Fe/H]} < -0.1$ dex). The Gaia proper motions, long-period variabili…

Conformal prediction without knowledge of labeled calibration data
Jonas Flechsig, Maximilian Pilz
https://arxiv.org/abs/2509.10321 https://arxiv.org/pdf/2…

Conformal prediction without knowledge of labeled calibration data
We extend the method of conformal prediction beyond the case relying on labeled calibration data. Replacing the calibration scores by suitable estimates, we identify conformity sets $C$ for classification and regression models that rely on unlabeled calibration data. Given a classification model with accuracy $1-β$, we prove that the conformity sets guarantee a coverage of $P(Y \in C) \geq 1-α-β$ for an arbitrary parameter $α\in (0,1)$. The same coverage guarantee also holds for regression …

Joint Bayesian calibration and map-making for intensity mapping experiments
Zheng Zhang, Philip Bull, Mario G. Santos, Ainulnabilah Nasirudin
https://arxiv.org/abs/2509.10992 ht…

Joint Bayesian calibration and map-making for intensity mapping experiments
Line intensity maps have high dynamic range, and demand careful spectral and spatial calibration. We present a Bayesian framework for joint calibration and map-making using Gibbs sampling, which provides access to the full joint posterior of calibration and sky map parameters. Our data model incorporates instrumental noise based on the radiometer equation, capturing the coupling between noise level and system temperature without assuming a fixed noise amplitude. To enable unbiased and fast esti…

Revisiting Cosmic Distance Duality with Megamasers and DESI DR2: Model Independent Constraints on Early-Late Calibration
Brijesh Kanodia, Ujjwal Upadhyay, Yashi Tiwari
https://arxiv.org/abs/2507.11518

Revisiting Cosmic Distance Duality with Megamasers and DESI DR2: Model Independent Constraints on Early-Late Calibration
The Cosmic Distance Duality Relation (CDDR) connects the angular diameter distance ($d_A$) and the luminosity distance ($d_L$) at a given redshift. This fundamental relation holds in any metric theory of gravity, provided that photon number is conserved and light propagates along null geodesics. A deviation from this relation could indicate new physics beyond the standard cosmological model. In this work, we test the validity of the CDDR at very low redshifts ($z < 0.04$) by combining $d_A$ fro…

Joint Optimization-based Targetless Extrinsic Calibration for Multiple LiDARs and GNSS-Aided INS of Ground Vehicles
Junhui Wang, Yan Qiao, Chao Gao, Naiqi Wu
https://arxiv.org/abs/2507.08349

Joint Optimization-based Targetless Extrinsic Calibration for Multiple LiDARs and GNSS-Aided INS of Ground Vehicles
Accurate extrinsic calibration between multiple LiDAR sensors and a GNSS-aided inertial navigation system (GINS) is essential for achieving reliable sensor fusion in intelligent mining environments. Such calibration enables vehicle-road collaboration by aligning perception data from vehicle-mounted sensors to a unified global reference frame. However, existing methods often depend on artificial targets, overlapping fields of view, or precise trajectory estimation, which are assumptions that may…

On the universal calibration of Pareto-type linear combination tests
Parijat Chakraborty, F. Richard Guo, Kerby Shedden, Stilian Stoev
https://arxiv.org/abs/2509.12066 https://

On the universal calibration of Pareto-type linear combination tests
It is often of interest to test a global null hypothesis using multiple, possibly dependent, $p$-values by combining their strengths while controlling the Type I error. Recently, several heavy-tailed combinations tests, such as the harmonic mean test and the Cauchy combination test, have been proposed: they map $p$-values into heavy-tailed random variables before combining them in some fashion into a single test statistic. The resulting tests, which are calibrated under the assumption of indepe…

Material Loss Model Calibration for Tantalum Superconducting Resonators
Guy Moshel, Sergei Masis, Moshe Schechter, Shay Hacohen-Gourgy
https://arxiv.org/abs/2507.12141

Material Loss Model Calibration for Tantalum Superconducting Resonators
Material research is a key frontier in advancing superconducting qubit and circuit performance. In this work, we develop a simple and broadly applicable framework for accurately characterizing two-level system (TLS) loss using internal quality factor measurements of superconducting transmission line resonators over a range of temperatures and readout powers. We applied this method to a series of $α$-Ta resonators that span a wide frequency range, thus providing a methodology for probing the lo…

DiTReducio: A Training-Free Acceleration for DiT-Based TTS via Progressive Calibration
Yanru Huo, Ziyue Jiang, Zuoli Tang, Qingyang Hong, Zhou Zhao
https://arxiv.org/abs/2509.09748

DiTReducio: A Training-Free Acceleration for DiT-Based TTS via Progressive Calibration
While Diffusion Transformers (DiT) have advanced non-autoregressive (NAR) speech synthesis, their high computational demands remain an limitation. Existing DiT-based text-to-speech (TTS) model acceleration approaches mainly focus on reducing sampling steps through distillation techniques, yet they remain constrained by training costs. We introduce DiTReducio, a training-free acceleration framework that compresses computations in DiT-based TTS models via progressive calibration. We propose two c…

And this is why ngscopeclient development is a pain sometimes...
https://github.com/ngscopeclient/scopehal/issues/975#issuecomment-3071989479

Rigol MSO5000 BIN file import issues · Issue #975 · ngscopeclient/scopehal
I've generated a .bin waveform recording using a Rigol MSO5074 containing a 20ms span of the scope's calibration signal on channel 1 and an open input on channel 2, with 1k memory depth at 50kSa/s....

Toward Low-Latency, High-Fidelity Calibration of the LIGO Detectors with Enhanced Monitoring Tools
M. Wade, J. Betzwieser, D. Bhattacharjee, L. Dartez, E. Goetz, J. Kissel, L. Sun, A. Viets, M. Carney, E. Makelele, L. Wade
https://arxiv.org/abs/2508.08423

Toward Low-Latency, High-Fidelity Calibration of the LIGO Detectors with Enhanced Monitoring Tools
Accurate and reliable calibration of the Advanced LIGO detectors has enabled a plethora of gravitational-wave discoveries over the past decade, starting with the ground-breaking discovery, GW150914. Over the past ten years, the calibrated strain data from Advanced LIGO detectors has become available at a lower latency and with more reliability. In this paper, we discuss the relevant history of Advanced LIGO calibration and introduce new tools that have been developed to enable faster and more r…

Rapid Adaptation of SpO2 Estimation to Wearable Devices via Transfer Learning on Low-Sampling-Rate PPG
Zequan Liang, Ruoyu Zhang, Wei Shao, krishna Karthik, Ehsan Kourkchi, Setareh Rafatirad, Houman Homayoun
https://arxiv.org/abs/2509.12515

Rapid Adaptation of SpO2 Estimation to Wearable Devices via Transfer Learning on Low-Sampling-Rate PPG
Blood oxygen saturation (SpO2) is a vital marker for healthcare monitoring. Traditional SpO2 estimation methods often rely on complex clinical calibration, making them unsuitable for low-power, wearable applications. In this paper, we propose a transfer learning-based framework for the rapid adaptation of SpO2 estimation to energy-efficient wearable devices using low-sampling-rate (25Hz) dual-channel photoplethysmography (PPG). We first pretrain a bidirectional Long Short-Term Memory (BiLSTM) m…

A novel pointing technique for the enhancement of Tropospheric Delay Calibration System performances
David Bernacchia, Riccardo Lasagni Manghi, Marco Zannoni, Paolo Tortora, Jose Villalvilla, Javier De Vicente, Paolo Cappuccio, Luciano Iess
https://arxiv.org/abs/2509.13199

A novel pointing technique for the enhancement of Tropospheric Delay Calibration System performances
The beam-crossing is a novel technique aimed at reducing residual tropospheric Doppler noise for microwave radiometer calibrations. In this work, we report the findings of the first test of this technique using ESA's Tropospheric Delay Calibration System (TDCS) at the complex in Malargue. The data consists in 14 tracking passes of the BepiColombo spacecraft collected between October 2023 and March 2024 during two separate test campaigns. We analyzed the performance of the beam-crossing techniqu…

EqualMotion: Accessible Motion Capture for the Creative Industries
Clarice Hilton, Kat Hawkins, Phill Tew, Freddie Collins, Seb Madgwick, Dominic Potts, Tom Mitchell
https://arxiv.org/abs/2507.08744

EqualMotion: Accessible Motion Capture for the Creative Industries
Motion capture technologies are increasingly used in creative and performance contexts but often exclude disabled practitioners due to normative assumptions in body modeling, calibration, and avatar representation. EqualMotion introduces a body-agnostic, wearable motion capture system designed through a disability-centred co-design approach. By enabling personalised calibration, integrating mobility aids, and adopting an inclusive visual language, EqualMotion supports diverse body types and mov…

Replaced article(s) found for physics.ins-det. https://arxiv.org/list/physics.ins-det/new
[1/1]:
- The Calibr-A-Ton: a novel method for calorimeter energy calibration
Vernazza, Motta, Rabour, Ghosh, Becheva, Frau, Le Clerc, Magniette, Sauvan, Davignon

Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
Juraj Gavura, Michal Vavrecka, Igor Farkas, Connor Gade
https://arxiv.org/abs/2507.08572

Robotic Calibration Based on Haptic Feedback Improves Sim-to-Real Transfer
When inverse kinematics (IK) is adopted to control robotic arms in manipulation tasks, there is often a discrepancy between the end effector (EE) position of the robot model in the simulator and the physical EE in reality. In most robotic scenarios with sim-to-real transfer, we have information about joint positions in both simulation and reality, but the EE position is only available in simulation. We developed a novel method to overcome this difficulty based on haptic feedback calibration, us…

Uncertainty Awareness and Trust in Explainable AI- On Trust Calibration using Local and Global Explanations
Carina Newen, Daniel Bodemer, Sonja Glantz, Emmanuel M\"uller, Magdalena Wischnewski, Lenka Schnaubert
https://arxiv.org/abs/2509.08989

Uncertainty Awareness and Trust in Explainable AI- On Trust Calibration using Local and Global Explanations
Explainable AI has become a common term in the literature, scrutinized by computer scientists and statisticians and highlighted by psychological or philosophical researchers. One major effort many researchers tackle is constructing general guidelines for XAI schemes, which we derived from our study. While some areas of XAI are well studied, we focus on uncertainty explanations and consider global explanations, which are often left out. We chose an algorithm that covers various concepts simultan…

Receiver Noise Calibration in CV-QKD accounting for Noise Dynamics
Guillaume Ricard, Yves Jaou\"en, Romain All\'eaume
https://arxiv.org/abs/2509.07549 https://

Receiver Noise Calibration in CV-QKD accounting for Noise Dynamics
Continuous-Variable Quantum Key Distribution (CV-QKD) relies on accurate noise calibration at the receiver to ensure the security of quantum communication. Traditional calibration methods often oversimplify noise characteristics, neglecting the impact of local oscillator (LO) noise and the critical role of noise spectral properties, which can lead to imprecise Shot Noise Calibration (SNC). Our contributions are threefold: 1) we propose an operational framework for calibration, relying on the no…

Signal Fidelity Index-Aware Calibration for Dementia Predictions Across Heterogeneous Real-World Data
Jingya Cheng, Jiazi Tian, Federica Spoto, Alaleh Azhir, Daniel Mork, Hossein Estiri
https://arxiv.org/abs/2509.08679

Signal Fidelity Index-Aware Calibration for Dementia Predictions Across Heterogeneous Real-World Data
\textbf{Background:} Machine learning models trained on electronic health records (EHRs) often degrade across healthcare systems due to distributional shift. A fundamental but underexplored factor is diagnostic signal decay: variability in diagnostic quality and consistency across institutions, which affects the reliability of codes used for training and prediction. \textbf{Objective:} To develop a Signal Fidelity Index (SFI) quantifying diagnostic data quality at the patient level in dementi…

HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models
Xin Tong, Zhi Lin, Jingya Wang, Bo Jin
https://arxiv.org/abs/2509.06596 ht…

HAVE: Head-Adaptive Gating and ValuE Calibration for Hallucination Mitigation in Large Language Models
Large Language Models (LLMs) often produce hallucinations in retrieval-augmented or long-context generation, even when relevant evidence is present. This stems from two issues: head importance is treated as input-agnostic, and raw attention weights poorly reflect each token's true contribution. We present HAVE (Head-Adaptive Gating and ValuE Calibration), a parameter-free decoding framework that directly addresses both challenges. HAVE introduces head-adaptive gating, which performs instance-le…

Analytic estimation of parameters of stochastic volatility diffusion models with exponential-affine characteristic function for currency option pricing
Miko{\l}aj {\L}ab\k{e}dzki
https://arxiv.org/abs/2507.11868

Analytic estimation of parameters of stochastic volatility diffusion models with exponential-affine characteristic function for currency option pricing
This dissertation develops and justifies a novel method for deriving approximate formulas to estimate two parameters in stochastic volatility diffusion models with exponentially-affine characteristic functions and single- or two-factor variance. These formulas aim to improve the accuracy of option pricing and enhance the calibration process by providing reliable initial values for local minimization algorithms. The parameters relate to the volatility of the stochastic factor in instantaneous va…

Generalized Zero-Shot Learning for Point Cloud Segmentation with Evidence-Based Dynamic Calibration
Hyeonseok Kim, Byeongkeun Kang, Yeejin Lee
https://arxiv.org/abs/2509.08280 h…

Generalized Zero-Shot Learning for Point Cloud Segmentation with Evidence-Based Dynamic Calibration
Generalized zero-shot semantic segmentation of 3D point clouds aims to classify each point into both seen and unseen classes. A significant challenge with these models is their tendency to make biased predictions, often favoring the classes encountered during training. This problem is more pronounced in 3D applications, where the scale of the training data is typically smaller than in image-based tasks. To address this problem, we propose a novel method called E3DPC-GZSL, which reduces overconf…

DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation
Xinyu Gao, Xiangtao Meng, Yingkai Dong, Zheng Li, Shanqing Guo
https://arxiv.org/abs/2509.06026

DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation
While Retrieval-Augmented Generation (RAG) effectively reduces hallucinations by integrating external knowledge bases, it introduces vulnerabilities to membership inference attacks (MIAs), particularly in systems handling sensitive data. Existing MIAs targeting RAG's external databases often rely on model responses but ignore the interference of non-member-retrieved documents on RAG outputs, limiting their effectiveness. To address this, we propose DCMI, a differential calibration MIA that miti…

Delving into the depths of NGC 3783 with XRISM II. Cross-calibration of X-ray instruments used in the large, multi-mission observational campaign
XRISM collaboration
https://arxiv.org/abs/2509.08649

Delving into the depths of NGC 3783 with XRISM II. Cross-calibration of X-ray instruments used in the large, multi-mission observational campaign
Accurate X-ray spectroscopic measurements are fundamental for deriving basic physical parameters of the most abundant baryon components in the Universe. The plethora of X-ray observatories currently operational enables a panchromatic view of the high-energy emission of celestial sources. However, uncertainties in the energy-dependent calibration of the instrument transfer functions (e.g. the effective area, energy redistribution, or gain) can limit - and historically, did limit - the accuracy o…

Data-driven optimization of sparse sensor placement in thermal hydraulic experiments
Xicheng Wang, Yun. Feng, Dmitry Grishchenko, Pavel Kudinov, Ruifeng Tian, Sichao Tan
https://arxiv.org/abs/2509.10055

Data-driven optimization of sparse sensor placement in thermal hydraulic experiments
Thermal-Hydraulic (TH) experiments provide valuable insight into the physics of heat and mass transfer and qualified data for code development, calibration and validation. However, measurements are typically collected from sparsely distributed sensors, offering limited coverage over the domain of interest and phenomena of interest. Determination of the spatial configuration of these sensors is crucial and challenging during the pre-test design stage. This paper develops a data-driven framework …

A star-by-star correspondence between X-ray activity and rotation in the young open cluster NGC 2516 with eROSITA
Dario J. Fritzewski, Sydney A. Barnes, Samet Ok, Georg Lamer, Axel Schwope
https://arxiv.org/abs/2509.09996

A star-by-star correspondence between X-ray activity and rotation in the young open cluster NGC 2516 with eROSITA
The coronal soft X-ray emission of cool stars, especially when taken in combination with their measured rotation periods, offers insights into their levels of magnetic activity and related transitions. We study the X-ray properties of low-mass members of the open cluster NGC 2516 to explicate their detailed dependencies on mass and rotation. We analysed the pointed SRG/eROSITA satellite observations of NGC 2516 obtained during the calibration and performance verification phase of the mission. W…

Multi-Stage Location Optimization Through Power Delay Profile Alignment Using Site-Specific Wireless Ray Tracing
Mingjun Ying, Peijie Ma, Dipankar Shakya, Theodore S. Rappaport
https://arxiv.org/abs/2509.11923

Multi-Stage Location Optimization Through Power Delay Profile Alignment Using Site-Specific Wireless Ray Tracing
Ray tracing (RT) simulations require accurate transmitter (TX) and receiver (RX) location information from real-world measurements to accurately characterize wireless propagation behavior in an environment. Such wireless propagation measurements typically employ GPS-based logging for TX/RX locations, which can produce meter-level errors that lead to unreliable RT calibration and validation. These location misalignments cause inaccurate interactions between RT-generated multipath components (MPC…

L2Calib: $SE(3)$-Manifold Reinforcement Learning for Robust Extrinsic Calibration with Degenerate Motion Resilience
Baorun Li, Chengrui Zhu, Siyi Du, Bingran Chen, Jie Ren, Wenfei Wang, Yong Liu, Jiajun Lv
https://arxiv.org/abs/2508.06330

L2Calib: $SE(3)$-Manifold Reinforcement Learning for Robust Extrinsic Calibration with Degenerate Motion Resilience
Extrinsic calibration is essential for multi-sensor fusion, existing methods rely on structured targets or fully-excited data, limiting real-world applicability. Online calibration further suffers from weak excitation, leading to unreliable estimates. To address these limitations, we propose a reinforcement learning (RL)-based extrinsic calibration framework that formulates extrinsic calibration as a decision-making problem, directly optimizes $SE(3)$ extrinsics to enhance odometry accuracy. Ou…

VCO-CARE: VCO-based Calibration-free Analog Readout for Electrodermal activity sensing
Leidy Mabel Alvero-Gonzalez, Matias Miguez, Eric Gutierrez, Juan Sapriza, Susana Pat\'on, David Atienza, Jos\'e Miranda
https://arxiv.org/abs/2509.06698

VCO-CARE: VCO-based Calibration-free Analog Readout for Electrodermal activity sensing
Continuous monitoring of electrodermal activity (EDA) through wearable devices has attracted much attention in recent times. However, the persistent challenge demands analog front-end (AFE) systems with high sensitivity, low power consumption, and minimal calibration requirements to ensure practical usability in wearable technologies. In response to this challenge, this research introduces VCO-CARE, a Voltage-Controlled Oscillator-based Analog Readout tailored for continuous EDA sensing. The re…

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk
Ilia Azizi, Juraj Bodik, Jakob Heiss, Bin Yu
https://arxiv.org/abs/2507.08150 https://

CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk
Accurate uncertainty quantification is critical for reliable predictive modeling, especially in regression tasks. Existing methods typically address either aleatoric uncertainty from measurement noise or epistemic uncertainty from limited data, but not necessarily both in a balanced way. We propose CLEAR, a calibration method with two distinct parameters, $γ_1$ and $γ_2$, to combine the two uncertainty components for improved conditional coverage. CLEAR is compatible with any pair of aleatori…

Joint calibration of the volatility surface and variance term structure
Jiwook Yoo
https://arxiv.org/abs/2509.08096 https://arxiv.org/pdf/2509.08096…

Joint calibration of the volatility surface and variance term structure
This article proposes a calibration framework for complex option pricing models that jointly fits market option prices and the term structure of variance. Calibrated models under the conventional objective function, the sum of squared errors in Black-Scholes implied volatilities, can produce model-implied variance term structures with large errors relative to those observed in the market and implied by option prices. I show that this can occur even when the model-implied volatility surface clos…

NuAncestor: an artificial satellite-borne star for accurate frequency calibration of ground-based EPRV spectrographs
F. Pepe, M. Bugatti, A. Baur, J. Berney, E. Bozzo, C. Broeg, B. Crazzolara, A. Deep, F. Droz, J. Figuereido, H. Haile, L. Jolissaint, S. Lecomte, J. Moerschell, Ch. Mordasini, E. Obrzud, C. Praplan, M. Sarajlic, B. Soja, M. Van den Broeck

NuAncestor: an artificial satellite-borne star for accurate frequency calibration of ground-based EPRV spectrographs
The accuracy of state-of-the-art Extreme Precision Radial Velocity (EPRV) spectrographs depends on the access to extremely precise and stable wavelength calibration sources. There are several available calibration sources (e.g., emission lamps, laser frequency combs, reference cavities) that can be used to calibrate an astronomical spectrograph. However, the calibration as it is currently performed is always 'local'. In the proposed talk we will present the NuAncestor concept that proposes an a…

Introducing a Markov Chain-Based Time Calibration Procedure for Multi-Channel Particle Detectors: Application to the SuperFGD and ToF Detectors of the T2K Experiment
S. Abe, H. Alarakia-Charles, I. Alekseev, C. Alt, T. Arai, T. Arihara, S. Arimoto, A. M. Artikov, Y. Awataguchi, N. Babu, V. Baranov, G. Barr, D. Barrow, L. Bartoszek, L. Bernardi, L. Berns, S. Bhattacharjee, A. V. Boikov, A. Blanchet, A. Blondel, A. Bonnemaison, S. Bordoni, M. H. Bui, T. H. Bui, F. Cadoux, S. Cap, A. Cauc…

Introducing a Markov Chain-Based Time Calibration Procedure for Multi-Channel Particle Detectors: Application to the SuperFGD and ToF Detectors of the T2K Experiment
Inter-channel mis-synchronisation can be a limiting factor to the time resolution of high performance timing detectors with multiple readout channels and independent electronics units. In these systems, time calibration methods employed must be able to efficiently correct for minimal mis-synchronisation between channels and achieve the best detector performance. We present an iterative time calibration method based on Markov Chains, suitable for detector systems with multiple readout channels. …

Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification
Xing Shen, Justin Szeto, Mingyang Li, Hengguan Huang, Tal Arbel
https://arxiv.org/abs/2506.23298

Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification
Multimodal large language models (MLLMs) have enormous potential to perform few-shot in-context learning in the context of medical image analysis. However, safe deployment of these models into real-world clinical practice requires an in-depth analysis of the accuracies of their predictions, and their associated calibration errors, particularly across different demographic subgroups. In this work, we present the first investigation into the calibration biases and demographic unfairness of MLLMs'…

Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
Andrea Forster, Simone Kopeinik, Denic Helic, Stefan Thalmann, Dominik Kowald
https://arxiv.org/abs/2507.03503

Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
Point-of-interest (POI) recommender systems help users discover relevant locations, but their effectiveness is often compromised by popularity bias, which disadvantages less popular, yet potentially meaningful places. This paper addresses this challenge by evaluating the effectiveness of context-aware models and calibrated popularity techniques as strategies for mitigating popularity bias. Using four real-world POI datasets (Brightkite, Foursquare, Gowalla, and Yelp), we analyze the individual …

Benchmarking Optimization Algorithms for Automated Calibration of Quantum Devices
Kevin Pack, Shai Machnes, Frank K. Wilhelm
https://arxiv.org/abs/2509.08555 https://

Benchmarking Optimization Algorithms for Automated Calibration of Quantum Devices
We present the results of a comprehensive study of optimization algorithms for the calibration of quantum devices. As part of our ongoing efforts to automate bring-up, tune-up, and system identification procedures, we investigate a broad range of optimizers within a simulated environment designed to closely mimic the challenges of real-world experimental conditions. Our benchmark includes widely used algorithms such as Nelder-Mead and the state-of-the-art Covariance Matrix Adaptation Evolution …

Impact of Hole-ice Calibration on High Energy Event Reconstruction with the IceCube Upgrade
Kaustav Dutta (for the IceCube Collaboration), Tianlu Yuan (for the IceCube Collaboration), Steve Sclafani (for the IceCube Collaboration), Sarah Mancina (for the IceCube Collaboration)
https://arxiv.org/abs/2507.07062

Impact of Hole-ice Calibration on High Energy Event Reconstruction with the IceCube Upgrade
The IceCube Upgrade, currently under construction at the geographic South Pole, is the next development stage of the IceCube detector. It will consist of seven new columns of novel optical sensors and advanced calibration devices densely deployed at the centre of the existing array. The sensors are frozen into the ice in boreholes created by hot water drilling. The refreezing forms hole ice around modules with optical properties that differ from the surrounding glacial ice. A key objective of t…

Calib3R: A 3D Foundation Model for Multi-Camera to Robot Calibration and 3D Metric-Scaled Scene Reconstruction
Davide Allegro, Matteo Terreran, Stefano Ghidoni
https://arxiv.org/abs/2509.08813

Calib3R: A 3D Foundation Model for Multi-Camera to Robot Calibration and 3D Metric-Scaled Scene Reconstruction
Robots often rely on RGB images for tasks like manipulation and navigation. However, reliable interaction typically requires a 3D scene representation that is metric-scaled and aligned with the robot reference frame. This depends on accurate camera-to-robot calibration and dense 3D reconstruction, tasks usually treated separately, despite both relying on geometric correspondences from RGB data. Traditional calibration needs patterns, while RGB-based reconstruction yields geometry with an unknow…

Thinking with Nothinking Calibration: A New In-Context Learning Paradigm in Reasoning Large Language Models
Haotian Wu, Bo Xu, Yao Shu, Menglin Yang, Chengwei Qin
https://arxiv.org/abs/2508.03363

Thinking with Nothinking Calibration: A New In-Context Learning Paradigm in Reasoning Large Language Models
Reasoning large language models (RLLMs) have recently demonstrated remarkable capabilities through structured and multi-step reasoning. While prior research has primarily focused on improving their training and inference strategies, their potential for in-context learning (ICL) remains largely underexplored. To fill this gap, we propose Thinking with Nothinking Calibration (JointThinking), a new ICL paradigm that leverages the structured difference between two reasoning modes, i.e., Thinking an…

A Pareto-Based Sensitivity Analysis and Multiobjective Calibration Approach for Integrating Streamflow and Evaporation Data
Patricio Yeste, Lieke A. Melsen, Matilde Garc\'ia-Valdecasas Ojeda, Sonia R. G\'amiz-Fortis, Yolanda Castro-D\'iez, Mar\'ia Jes\'us Esteban-Parra
https://arxiv.org/abs/2506.23797

A Pareto-Based Sensitivity Analysis and Multiobjective Calibration Approach for Integrating Streamflow and Evaporation Data
Evaporation is gaining increasing attention as a calibration and evaluation variable in hydrologic studies that seek to improve the physical realism of hydrologic models and go beyond the long-established streamflow-only calibration. However, this trend is not yet reflected in sensitivity analyses aimed at determining the relevant parameters to calibrate, where streamflow has traditionally played a leading role. On the basis of a Pareto optimization approach, we propose a framework to integrate…

Distributed MIMO With Over-the-Air Phase Calibration Integrated Into the TDD Flow
Khac-Hoang Ngo, Erik G. Larsson
https://arxiv.org/abs/2509.03722 https://…

Distributed MIMO With Over-the-Air Phase Calibration Integrated Into the TDD Flow
Reciprocity-based, joint coherent downlink beamforming from multiple access points (APs) in distributed multiple-input multiple-output (MIMO) with independent local oscillators (LOs) requires the APs to be periodically phase-calibrated (a.k.a. phase-synchronized or phase-aligned). Such phase alignment can be accomplished by bidirectional over-the-air measurements between the APs. In this paper, we show how such over-the-air measurements can be integrated into the time-division duplexing (TDD) f…

Variation-matching sensitivity-based virtual fields for hyperelastic material model calibration
Denislav P. Nikolov, Zhiren Zhu, Jonathan B. Estrada
https://arxiv.org/abs/2509.03363

Variation-matching sensitivity-based virtual fields for hyperelastic material model calibration
Accurate identification of nonlinear material parameters from three-dimensional full-field deformation data remains a challenge in experimental mechanics. The virtual fields method (VFM) provides a powerful, computationally efficient approach for material model calibration, however, its success depends critically on the choice of virtual fields and the informativeness of available kinematic data. In this work, we advance the state-of-the-art discrete formulation of the sensitivity-based virtual…

In-orbit Spectral Calibration Prospects for the COSI Space Telescope
Aravind B. Valluvan, Steven E. Boggs, Savitri Gallego, Jarred Roberts, Gabriel Brewster, Sophia Haight, Carolyn Kierans, Sean Pike, Albert Y. Shih, John A. Tomsick, Andreas Zogaluer
https://arxiv.org/abs/2508.10172

In-orbit Spectral Calibration Prospects for the COSI Space Telescope
The Compton Spectrometer and Imager is an upcoming NASA space telescope in the MeV range. COSI's primary science goals include precisely mapping nuclear line and positron annihilation emission in the Milky Way galaxy through Compton imaging. This relies on our ability to maintain COSI's spectral performance over its mission lifetime. Changes to the detectors' gain characteristics over time will result in a non-linear stretching of the entire energy range. Moreover, observations from past MeV te…

Metallicity of Active Galactic Nuclei from ultraviolet and optical emission lines-II. Revisiting the $C43$ metallicity calibration and its implications
O. L. Dors, C. B. Oliveira, M. V. Cardaci, G. F. H\"agele, Mark Armah, R. A. Riffel, L. Ramos Vieira, G. C. Almeida, I. N. Morais, P. C. Santos
https://arxiv.org/abs/2508.05397

Metallicity of Active Galactic Nuclei from ultraviolet and optical emission lines-II. Revisiting the $C43$ metallicity calibration and its implications
In this study, a new semi-empirical calibration is proposed between ultraviolet emission lines (\ion{C}{iii}]$\lambda1909$, \ion{C}{iv}$\lambda1549$, \ion{He}{ii}]$\lambda1640$) of type~2 AGNs and their metallicity ($Z$). This calibration is derived by comparing a large sample of 106 objects (data taken from the literature) located over a wide range of redshifts ($0 \: \lesssim \: z \: \lesssim \: 4.0$) with predictions from photoionization models that adopt a recent C/O-O/H relation derived vi…

Calibration-sample free distortion correction of electron diffraction patterns using deep learning
Matthew R. C. Fitzpatrick, Arthur M. Blackburn, Cristina Cordoba
https://arxiv.org/abs/2509.01075

Calibration-sample free distortion correction of electron diffraction patterns using deep learning
The accuracy of the information that can be extracted from electron diffraction patterns is often limited by the presence of optical distortions. Existing distortion characterization techniques typically require knowledge of the reciprocal lattice of either the sample of interest or a separate calibration sample, the latter of which would need to be swapped in, thus adding time and inconvenience to an experiment. To overcome this limitation, we develop a deep learning (DL) framework for measuri…

Tailoring deep learning for real-time brain-computer interfaces: From offline models to calibration-free online decoding
Martin Wimpff, Jan Zerfowski, Bin Yang
https://arxiv.org/abs/2507.06779

Tailoring deep learning for real-time brain-computer interfaces: From offline models to calibration-free online decoding
Despite the growing success of deep learning (DL) in offline brain-computer interfaces (BCIs), its adoption in real-time applications remains limited due to three primary challenges. First, most DL solutions are designed for offline decoding, making the transition to online decoding unclear. Second, the use of sliding windows in online decoding substantially increases computational complexity. Third, DL models typically require large amounts of training data, which are often scarce in BCI appli…

Crazy scientific instrument idea with probably limited practical use: inverse spectrometer.
Broadband light source (halogen lamp etc), collimating lens, slit, prism, then transmissive LCD to provide selective attenuation at each spectral bin and some kind of focusing optics to combine the resulting light back into a single beam.
Do a bit of calibration for system losses and the light source spectrim and you end up with a device where you can load in a spectrum of an arbitrary lig…

The distribution of calibrated likelihood functions on the probability-likelihood Aitchison simplex
Paul-Gauthier No\'e, Andreas Nautsch, Driss Matrouf, Pierre-Michel Bousquet, Jean-Fran\c{c}ois Bonastre
https://arxiv.org/abs/2509.03365

The distribution of calibrated likelihood functions on the probability-likelihood Aitchison simplex
While calibration of probabilistic predictions has been widely studied, this paper rather addresses calibration of likelihood functions. This has been discussed, especially in biometrics, in cases with only two exhaustive and mutually exclusive hypotheses (classes) where likelihood functions can be written as log-likelihood-ratios (LLRs). After defining calibration for LLRs and its connection with the concept of weight-of-evidence, we present the idempotence property and its associated constrai…

Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim Lens Sample
G. Giannini, A. Alarcon, W. d'Assignies, G. M. Bernstein, M. A. Troxel, C. Chang, B. Yin, A. Amon, J. Myles, N. Weaverdyck, A. Porredon, D. Anbajagane, S. Avila, K. Bechtol, M. R. Becker, J. Blazek, M. Crocce, D. Gruen, M. Rodriguez-Monroy, C. S\'anchez, D. Sanchez Cid, I. Sevilla-Noarbe, M. Aguena, S. Allam, O. Alves, F. Andrade-Oliveira, D. Bacon, S. Bocquet, D. Brooks, R. Camilleri, A. Carner…

Dark Energy Survey Year 6 Results: Redshift Calibration of the MagLim++ Lens Sample
In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3x2pt cosmology analysis. The 3x2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection (Balrog) catalog. Key impr…

Preparation and measurement of an $\rm ^{37}$Ar source for liquid xenon detector calibration
Xu-Nan Guo, Chang Cai, Fei Gao, Yang Lei, Kai-Hang Li, Chun-Lei Su, Ze-Peng Wu, Xiang Xiao, Ling-Feng Xie, Yi-Fei Zhao, Xiao-Peng Zhou
https://arxiv.org/abs/2509.04829

Preparation and measurement of an $\rm ^{37}$Ar source for liquid xenon detector calibration
We present the preparation and measurement of the radioactive isotope $\rm ^{37}Ar$, which was produced using thermal neutrons from a reactor, as a calibration source for liquid xenon time projection chambers. $\rm ^{37}Ar$ is a low-energy calibration source with a half-life of 35.01 days, making it suitable for calibration in the low-energy region of liquid xenon dark-matter experiments. Radioactive isotope $\rm ^{37}Ar$ was produced by irradiating $\rm ^{36}Ar$ with thermal neutrons. It was s…

Mapping Diffuse Radio Sources Using TUNA: A Transformer-Based Deep Learning Approach
Nicoletta Sanvitale, Claudio Gheller, Franco Vazza, Annalisa Bonafede, Virginia Cuciti, Emanuele De Rubeis, Federica Govoni, Matteo Murgia, Valentina Vacca
https://arxiv.org/abs/2507.11320

Mapping Diffuse Radio Sources Using TUNA: A Transformer-Based Deep Learning Approach
Vision Transformers are used via a customized TransUNet architecture, which is a hybrid model combining Transformers into a U-Net backbone, to achieve precise, automated, and fast segmentation of radio astronomy data affected by calibration and imaging artifacts, addressing the identification of faint, diffuse radio sources. Trained on mock radio observations from numerical simulations, the network is applied to the LOFAR Two-meter Sky Survey data. It is then evaluated on key use cases, specifi…

Resolution-Corrected White Dwarf Gravitational Redshifts Validate SDSS-V Wavelength Calibration and Enable Accurate Mass-Radius Tests
Stefan M. Arseneau, J. J. Hermes, Nadia L. Zakamska, Kareem El-Badry, Nicole R. Crumpler, Vedant Chandra, Gautham Adamane Pallathadka, Carles Badenes, Boris T. Gaensicke, Nicola Gentile Fusillo
https://arxiv…

Resolution-Corrected White Dwarf Gravitational Redshifts Validate SDSS-V Wavelength Calibration and Enable Accurate Mass-Radius Tests
Leveraging the large sample size of low-resolution spectroscopic surveys to constrain white dwarf stellar structure requires an accurate understanding of the shapes of hydrogen absorption lines, which are pressure broadened by the Stark effect. Using data from both the Sloan Digital Sky Survey and the Type Ia Supernova Progenitor Survey, we show that substantial biases (5-15 km/s) exist in radial velocity measurements made from observations at low spectral resolution relative to similar measure…

Self-supervised Learning Of Visual Pose Estimation Without Pose Labels By Classifying LED States
Nicholas Carlotti, Mirko Nava, Alessandro Giusti
https://arxiv.org/abs/2509.10405

Self-supervised Learning Of Visual Pose Estimation Without Pose Labels By Classifying LED States
We introduce a model for monocular RGB relative pose estimation of a ground robot that trains from scratch without pose labels nor prior knowledge about the robot's shape or appearance. At training time, we assume: (i) a robot fitted with multiple LEDs, whose states are independent and known at each frame; (ii) knowledge of the approximate viewing direction of each LED; and (iii) availability of a calibration image with a known target distance, to address the ambiguity of monocular depth estima…

CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference
Luben M. C. Cabezas, Vagner S. Santos, Thiago R. Ramos, Pedro L. C. Rodrigues, Rafael Izbicki
https://arxiv.org/abs/2508.17077

CP4SBI: Local Conformal Calibration of Credible Sets in Simulation-Based Inference
Current experimental scientists have been increasingly relying on simulation-based inference (SBI) to invert complex non-linear models with intractable likelihoods. However, posterior approximations obtained with SBI are often miscalibrated, causing credible regions to undercover true parameters. We develop $\texttt{CP4SBI}$, a model-agnostic conformal calibration framework that constructs credible sets with local Bayesian coverage. Our two proposed variants, namely local calibration via regres…

Hybrid Quantum-Classical Scheduling with Problem-Aware Calibration on a Quantum Annealer
Krzysztof Giergiel, Y. Sam Yang, Anthony B. Murphy
https://arxiv.org/abs/2509.04808 http…

Hybrid Quantum-Classical Scheduling with Problem-Aware Calibration on a Quantum Annealer
We evaluate the application of quantum annealing (QA) to a real-world combinatorial optimisation problem-room scheduling for sports camps at the Australian Institute of Sport-using both classical and quantum approaches. Due to current hardware limitations, the full problem cannot be embedded on existing QA platforms, motivating a hybrid method combining classical heuristics with quantum subroutines. We develop an improved formulation and a novel problem-aware calibration scheme, leveraging mult…

Global sky background images for JWST/NIRISS Wide-Field Slitless Spectroscopy
Ga\"el Noirot
https://arxiv.org/abs/2507.10650 https://

Global sky background images for JWST/NIRISS Wide-Field Slitless Spectroscopy
We present updated empirical background images for JWST/NIRISS Wide-Field Slitless Spectroscopy (WFSS) for both orthogonal grisms (GR150C, GR150R) crossed with all NIRISS WFSS wide-band filters (F090W, F115W, F150W, F200W). The background images are created using carefully vetted science and calibration exposures and improve the quality of previous background reference files. We present our methodology to create the background images and assess their quality using background subtracted science …

Empirical Calibration of Na I D and Other Absorption Lines as Tracers of High-Redshift Neutral Outflows
Lorenzo Moretti, Sirio Belli, Gwen C. Rudie, Andrew B. Newman, Minjung Park, Amir H. Khoram, Nima Chartab, Darko Donevski
https://arxiv.org/abs/2507.07160

Empirical Calibration of Na I D and Other Absorption Lines as Tracers of High-Redshift Neutral Outflows
Recent JWST observations of massive galaxies at z > 2 have detected blueshifted absorption in Na I D and other resonant absorption lines, indicative of strong gas outflows in the neutral phase. However, the measured mass outflow rates are highly uncertain because JWST observations can only probe the column density of trace elements such as sodium, while most of the gas is in the form of hydrogen. The conversion between the column density of sodium and that of hydrogen is based on observations o…

Impact of Detector Calibration Accuracy on Black Hole Spectroscopy
Mallika R. Sinha, Ling Sun, Sizheng Ma
https://arxiv.org/abs/2506.15979 https://

Impact of Detector Calibration Accuracy on Black Hole Spectroscopy
Systematic errors in detector calibration can bias signal analyses and potentially lead to incorrect interpretations suggesting violations of general relativity. In this study, we investigate how calibration systematics affect black hole (BH) spectroscopy, a technique that uses the quasinormal modes (QNMs) emitted during the ringdown phase of gravitational waves (GWs) to study remnant BHs formed in compact binary coalescences. We simulate a series of physically motivated, tunable calibration er…

CVIRO: A Consistent and Tightly-Coupled Visual-Inertial-Ranging Odometry on Lie Groups
Yizhi Zhou, Ziwei Kang, Jiawei Xia, Xuan Wang
https://arxiv.org/abs/2508.10867 https://

CVIRO: A Consistent and Tightly-Coupled Visual-Inertial-Ranging Odometry on Lie Groups
Ultra Wideband (UWB) is widely used to mitigate drift in visual-inertial odometry (VIO) systems. Consistency is crucial for ensuring the estimation accuracy of a UWBaided VIO system. An inconsistent estimator can degrade localization performance, where the inconsistency primarily arises from two main factors: (1) the estimator fails to preserve the correct system observability, and (2) UWB anchor positions are assumed to be known, leading to improper neglect of calibration uncertainty. In this …

Failure Prediction Is a Better Performance Proxy for Early-Exit Networks Than Calibration
Piotr Kubaty, Filip Szatkowski, Metod Jazbec, Bartosz W\'ojcik
https://arxiv.org/abs/2508.21495

Failure Prediction Is a Better Performance Proxy for Early-Exit Networks Than Calibration
Early-exit models speed up inference by attaching internal classifiers to intermediate layers of the model and allowing computation to stop once a prediction satisfies an exit criterion. Most early-exit methods rely on confidence-based exit strategies, which motivated some works to calibrate intermediate classifiers to improve the performance of the entire model. In this paper, we show that calibration measures can be misleading indicators of the performance of multi-exit models: a well-calibra…

GrACE: A Generative Approach to Better Confidence Elicitation in Large Language Models
Zhaohan Zhang, Ziquan Liu, Ioannis Patras
https://arxiv.org/abs/2509.09438 https://…

GrACE: A Generative Approach to Better Confidence Elicitation in Large Language Models
Assessing the reliability of Large Language Models (LLMs) by confidence elicitation is a prominent approach to AI safety in high-stakes applications, such as healthcare and finance. Existing methods either require expensive computational overhead or suffer from poor calibration, making them impractical and unreliable for real-world deployment. In this work, we propose GrACE, a Generative Approach to Confidence Elicitation that enables scalable and reliable confidence elicitation for LLMs. GrACE…

Calibration of Quantum Devices via Robust Statistical Methods
Alexandra Ram\^oa, Raffaele Santagati, Nathan Wiebe
https://arxiv.org/abs/2507.06941 https://…

Calibration of Quantum Devices via Robust Statistical Methods
Bayesian inference is a widely used technique for real-time characterization of quantum systems. It excels in experimental characterization in the low data regime, and when the measurements have degrees of freedom. A decisive factor for its performance is the numerical representation of the Bayesian probability distributions. In this work, we explore advanced statistical methods for this purpose, and numerically analyze their performance against the state-of-the-art in quantum parameter learnin…

Automatic Phase Calibration for High-resolution mmWave Sensing via Ambient Radio Anchors
Ruixu Geng, Yadong Li, Dongheng Zhang, Pengcheng Huang, Binquan Wang, Binbin Zhang, Zhi Lu, Yang Hu, Yan Chen
https://arxiv.org/abs/2506.23472

Automatic Phase Calibration for High-resolution mmWave Sensing via Ambient Radio Anchors
Millimeter-wave (mmWave) radar systems with large array have pushed radar sensing into a new era, thanks to their high angular resolution. However, our long-term experiments indicate that array elements exhibit phase drift over time and require periodic phase calibration to maintain high-resolution, creating an obstacle for practical high-resolution mmWave sensing. Unfortunately, existing calibration methods are inadequate for periodic recalibration, either because they rely on artificial refer…

Does Calibration Affect Human Actions?
Meir Nizri, Amos Azaria, Chirag Gupta, Noam Hazon
https://arxiv.org/abs/2508.18317 https://arxiv.org/pdf/2508.18317

Does Calibration Affect Human Actions?
Calibration has been proposed as a way to enhance the reliability and adoption of machine learning classifiers. We study a particular aspect of this proposal: how does calibrating a classification model affect the decisions made by non-expert humans consuming the model's predictions? We perform a Human-Computer-Interaction (HCI) experiment to ascertain the effect of calibration on (i) trust in the model, and (ii) the correlation between decisions and predictions. We also propose further correct…

Deep-Field Analytical Calibration
Andy Park, Xiangchong Li, Rachel Mandelbaum, Matthew Becker
https://arxiv.org/abs/2509.05152 https://arxiv.org/pdf/2509.0…

Deep-Field Analytical Calibration
The next generation of imaging surveys, including the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Euclid, and the Nancy Grace Roman Space Telescope, will place unprecedented constraints on cosmology using weak gravitational lensing. To fully exploit their statistical power, shear measurement methods must achieve sub-percent accuracy while mitigating systematic biases from noise, the point-spread function (PSF), blending, and shear-dependent detection. The analytical calibr…

The Ultimate I-band Calibration of the TRGB Standard Candle
A. Udalski, D. M. Skowron, J. Skowron, M. K. Szyma\'nski, I. Soszy\'nski, P. Pietrukowicz, P. Mr\'oz, R. Poleski, S. Koz{\l}owski, K. Ulaczyk, K. Rybicki, P. Iwanek, M. Gromadzki, M. Wrona, M. Ratajczak, M. J. Mr\'oz
https://arxiv.org/abs/2506.20766

The Ultimate I-band Calibration of the TRGB Standard Candle
We present the ultimate I-band calibration of the tip of the red giant branch (TRGB) standard candle. Our calibration is based on photometry from the outer parts of the Large Magellanic Cloud, 2.75

To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks
Rashika Raina, Nidhi Simmons, David E. Simmons, Michel Daoud Yacoub, Trung Q. Duong
https://arxiv.org/abs/2507.17494

To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks
In next-generation communications and networks, machine learning (ML) models are expected to deliver not only accurate predictions but also well-calibrated confidence scores that reflect the true likelihood of correct decisions. This paper studies the calibration performance of an ML-based outage predictor within a single-user, multi-resource allocation framework. We first establish key theoretical properties of this system's outage probability (OP) under perfect calibration. Importantly, we sh…

Replaced article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[2/3]:
- Towards a Digital Twin of Noisy Quantum Computers: Calibration-Driven Emulation of Transmon Qubits
uller, et al.

Low-Energy Calibration of SuperCDMS HVeV Cryogenic Silicon Calorimeters Using Compton Steps
SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. Alonso-Gon\'zalez, D. W. P. Amaral, J. Anczarski, T. Aralis, T. Aramaki, I. Ataee Langroudy, C. Bathurst, R. Bhattacharyya, A. J. Biffl, P. L. Brink, M. Buchanan, R. Bunker, B. Cabrera, R. Calkins, R. A. Cameron, C. Cartaro, D. G. Cerde\~no, Y. -Y. Chang, M. Chaudhuri, J. -H. Chen, R. Chen, N. Chott, J. Cooley, H. Coombes, P. Cushman, R…

Low-Energy Calibration of SuperCDMS HVeV Cryogenic Silicon Calorimeters Using Compton Steps
Cryogenic calorimeters for low-mass dark matter searches have achieved sub-eV energy resolutions, driving advances in both low-energy calibration techniques and our understanding of detector physics. The energy deposition spectrum of gamma rays scattering off target materials exhibits step-like features, known as Compton steps, near the binding energies of atomic electrons. We demonstrate a successful use of Compton steps for sub-keV calibration of cryogenic silicon calorimeters, utilizing four…

Calibration and Performance Validation of the SST-1M Telescopes Using Crab Nebula Observations
Thomas Tavernier, Jakub Jury\v{s}ek, Vladimir Novotny
https://arxiv.org/abs/2508.08861

Calibration and Performance Validation of the SST-1M Telescopes Using Crab Nebula Observations
SST-1M is a prototype single mirror Small Sized Cherenkov Telescope designed for very high energy (VHE) gamma-ray astronomy. With a 4 meter primary mirror and a 5.6 meter focal length, it provides a wide 9 degree optical field of view, optimized for detecting VHE gamma-rays from 1 TeV to several hundred TeV. Its focal plane is equipped with DigiCam, a fully digital trigger and readout camera made of 1296 silicon photomultiplier (SiPM) pixels. The use of SiPM sensors enables observation under hi…

A Contextual Bandits Approach for Personalization of Hand Gesture Recognition
Duke Lin, Michael Paskett, Ying Yang
https://arxiv.org/abs/2509.08915 https://

A Contextual Bandits Approach for Personalization of Hand Gesture Recognition
In human-computer interaction applications like hand gesture recognition, supervised learning models are often trained on a large population of users to achieve high task accuracy. However, due to individual variability in sensor signals and user behavior, static models may not provide optimal performance for all users. Personalizing pretrained models via calibration--collecting labeled data from each user--can improve performance but introduces user friction and struggles with limited data. To…

Site-Specific Location Calibration and Validation of Ray-Tracing Simulator NYURay at Upper Mid-Band Frequencies
Mingjun Ying, Dipankar Shakya, Peijie Ma, Guanyue Qian, Theodore S. Rappaport
https://arxiv.org/abs/2507.22027

Site-Specific Location Calibration and Validation of Ray-Tracing Simulator NYURay at Upper Mid-Band Frequencies
Ray-tracing (RT) simulators are essential for wireless digital twins, enabling accurate site-specific radio channel prediction for next-generation wireless systems. Yet, RT simulation accuracy is often limited by insufficient measurement data and a lack of systematic validation. This paper presents site-specific location calibration and validation of NYURay, NYU's in-house ray tracer, at upper mid-band frequencies (6.75 GHz and 16.95 GHz). We propose a location calibration algorithm that correc…

Credence Calibration Game? Calibrating Large Language Models through Structured Play
Ke Fang, Tianyi Zhao, Lu Cheng
https://arxiv.org/abs/2508.14390 https://

Credence Calibration Game? Calibrating Large Language Models through Structured Play
As Large Language Models (LLMs) are increasingly deployed in decision-critical domains, it becomes essential to ensure that their confidence estimates faithfully correspond to their actual correctness. Existing calibration methods have primarily focused on post-hoc adjustments or auxiliary model training; however, many of these approaches necessitate additional supervision or parameter updates. In this work, we propose a novel prompt-based calibration framework inspired by the Credence Calibrat…

eKalibr-Inertial: Continuous-Time Spatiotemporal Calibration for Event-Based Visual-Inertial Systems
Shuolong Chen, Xingxing Li, Liu Yuan
https://arxiv.org/abs/2509.05923 https:…

eKalibr-Inertial: Continuous-Time Spatiotemporal Calibration for Event-Based Visual-Inertial Systems
The bioinspired event camera, distinguished by its exceptional temporal resolution, high dynamic range, and low power consumption, has been extensively studied in recent years for motion estimation, robotic perception, and object detection. In ego-motion estimation, the visual-inertial setup is commonly adopted due to complementary characteristics between sensors (e.g., scale perception and low drift). For optimal event-based visual-inertial fusion, accurate spatiotemporal (extrinsic and tempor…

Anchoring Stellar Age Indicators: A Cross-Calibration of [C/N] and Gyrochronology Ages via the Age-Velocity-Dispersion Relation
Yuxi Lu, Marc H. Pinsonneault, Yuan-Sen Ting, Phil R. Van-Lane, John D Roberts, Jamie Tayar, Alexander Stone-Martinez
https://arxiv.org/abs/2506.24010

Anchoring Stellar Age Indicators: A Cross-Calibration of [C/N] and Gyrochronology Ages via the Age-Velocity-Dispersion Relation
Determining stellar ages is challenging, as it depends on other stellar parameters in a non-linear way and often relies on stellar evolution models to infer the underlying relation between these parameters and age. This complexity increases when comparing different age-dating methods, as they rely on distinct indicators and are often applicable to non-overlapping regions of the color-magnitude diagram. Moreover, many empirical calibration methods rely on pre-determined ages, often from open clu…

Quantification of The Age Dependence of Mid-Infrared Star Formation Rate Indicators
Daniela Calzetti (Univ. of Massachusetts, MA, USA), Robert C. Kennicutt (Texas A and M, TX, USA, Univ. of Arizona, AZ, USA), Angela Adamo (Univ. of Stockholm, Sweden), Karin Sandstrom (Univ. of California San Diego, CA, USA), Daniel A. Dale (Univ. of Wyoming, WY, USA), Bruce Elmegreen (Katonah, NY, USA), John S. Gallagher (Univ. of Wisconsin-Madison, WI, USA, Macalester Univ., MN, USA), Benjamin Gregg (…

Quantification of The Age Dependence of Mid-Infrared Star Formation Rate Indicators
We combine James Webb Space Telescope images of the nearby galaxy NGC 5194 in the hydrogen recombination line Pa-alpha (lambda=1.8756 micron) from the Cycle 1 program JWST-FEAST with 21 micron dust continuum images from the Cycle 2 Treasury program JWGT to quantify the difference in the calibration of mid-infrared star formation rates (SFR) between HII regions and galaxies. We use the archival HST H-alpha image to correct the Pa-alpha emission for the effects of dust attenuation. Our data confi…

Hyper Suprime-Cam Y3 results: photo-$z$ bias calibration with lensing shear ratios and cosmological constraints from cosmic shea
Divya Rana, Surhud More, Hironao Miyatake, Sunao Sugiyama, Tianqing Zhang, Masato Shirasaki
https://arxiv.org/abs/2508.21681

Hyper Suprime-Cam Y3 results: photo-$z$ bias calibration with lensing shear ratios and cosmological constraints from cosmic shea
We present an independent calibration of the photometric redshift (photo-$z$) distributions for source galaxies in the HSC-Y3 weak lensing survey using small-scale galaxy-galaxy lensing. By measuring the tangential shear around spectroscopic lens galaxies from GAMA, SDSS, and DESI, divided into fifteen narrow redshift bins, we compute shear ratios that are sensitive to the mean redshift of source galaxies. Using a blinded analysis, we derive constraints on the photo-$z$ bias parameters in sourc…

Robust Radar SLAM for Vehicle Parking Applications
Luis Diener, Jens Kalkkuhl, Markus Enzweiler
https://arxiv.org/abs/2509.07683 https://arxiv.org/pdf/2509…

Robust Radar SLAM for Vehicle Parking Applications
We address ego-motion estimation for automated parking, where centimeter-level accuracy is crucial due to tight spaces and nearby obstacles. Traditional methods using inertial-measurement units and wheel encoders require calibration, making them costly and time-consuming. To overcome this, we propose a radar-based simultaneous localization and mapping (SLAM) approach that leverages the robustness of radar to adverse weather and support for online calibration. Our robocentric formulation fuses f…

Feedback-Controlled Beam Pattern Measurement Method Using a Power-Variable Calibration Source for Cosmic Microwave Background Telescopes
Haruaki Hirose, Masaya Hasegawa, Daisuke Kaneko, Taketo Nagasaki, Ryota Takaku, Tijmen de Haan, Satoru Takakura, Takuro Fujino
https://arxiv.org/abs/2509.09386

Feedback-Controlled Beam Pattern Measurement Method Using a Power-Variable Calibration Source for Cosmic Microwave Background Telescopes
We demonstrate a novel beam pattern measurement method for the side lobe characterization of cosmic microwave background telescopes. The method employs a power-variable artificial microwave source under feedback control from the detector under test on the telescope. It enables us to extend the dynamic range of the beam pattern measurement without introducing nonlinearity effects from the detector. We conducted a laboratory-based proof-of-concept experiment, measuring the H-plane beam pattern of…

Electromagnetic energy calibration of the SoLid detector with horizontal muons
SoLid collaboration
https://arxiv.org/abs/2507.05180 https://

Electromagnetic energy calibration of the SoLid detector with horizontal muons
SoLid is a neutrino experiment at very-short baseline searching for active-to-sterile oscillations of reactor antineutrinos. The detection principle is based on the pairing of two types of solid scintillators: polyvinyl toluene and $^6$Li:ZnS(Ag), which is a new technology used in this field of Physics. In addition to good neutron-gamma discrimination, this setup allows the detector to be highly segmented; the basic detection unit is a 5 cm cube. High segmentation provides numerous advantages i…

EUCLID: Photometric redshift calibration with self-organising maps
W. Roster, A. H. Wright, H. Hildebrandt, R. Reischke, O. Ilbert, W. d'Assignies D., M. Manera, M. Bolzonella, D. C. Masters, S. Paltani, W. G. Hartley, Y. Kang, H. Hoekstra, B. Altieri, A. Amara, S. Andreon, N. Auricchio, C. Baccigalupi, M. Baldi, A. Balestra, S. Bardelli, P. Battaglia, R. Bender, A. Biviano, E. Branchini, M. Brescia, S. Camera, G. Ca\~nas-Herrera, V. Capobianco, C. Carbone, V. F. Cardone, J. Carret…

EUCLID: Photometric redshift calibration with self-organising maps
The Euclid survey aims to trace the evolution of cosmic structures up to redshift $z$ $\sim$ 3 and beyond. Its success depends critically on obtaining highly accurate mean redshifts for ensembles of galaxies $n(z)$ in all tomographic bins, essential for deriving robust cosmological constraints. However, photometric redshifts (photo-$z$s) suffer from systematic biases arising from various sources of uncertainty. To address these challenges, we utilised self-organising maps (SOMs) with mock sampl…

A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration
Emmett Wise, Pushyami Kaveti, Qilong Chen, Wenhao Wang, Hanumant Singh, Jonathan Kelly, David M. Rosen, Matthew Giamou
https://arxiv.org/abs/2507.23045

A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration
Automatic extrinsic sensor calibration is a fundamental problem for multi-sensor platforms. Reliable and general-purpose solutions should be computationally efficient, require few assumptions about the structure of the sensing environment, and demand little effort from human operators. Since the engineering effort required to obtain accurate calibration parameters increases with the number of sensors deployed, robotics researchers have pursued methods requiring few assumptions about the sensing…

Replaced article(s) found for quant-ph. https://arxiv.org/list/quant-ph/new
[2/4]:
- Heisenberg-limited calibration of entangling gates with robust phase estimation
Kenneth Rudinger, J. P. Marceaux, Akel Hashim, David I. Santiago, Irfan Siddiqi, Kevin C. Young

Low Cost Bayesian Experimental Design for Quantum Frequency Estimation with Decoherence
Alexandra Ram\^oa, Lu\'is Paulo Santos, Akihito Soeda
https://arxiv.org/abs/2508.07120

Low Cost Bayesian Experimental Design for Quantum Frequency Estimation with Decoherence
A two-level quantum system evolving under a time-independent Hamiltonian produces oscillatory measurement probabilities. The estimation of the associated frequency is a cornerstone problem in quantum metrology, sensing, calibration and control. In this work, we tackle this task by introducing WES: a Window Expansion Strategy for low cost adaptive Bayesian experimental design. WES employs empirical cost-reduction techniques to keep the optimization overhead low, curb scaling problems, and enable…

Automated Spectroscopic Wavelength Calibration using Dynamic Time Warping
James R. A. Davenport, Francisca Chabour Barra, K. Azalee Bostroem, Sarah Tuttle, Josue Torres, Jessica Birky, Anastasios Tzanidakis, Kal Kadlec, Yuankun Wang, Suzanne L. Hawley, Trevor Z. Dorn-Wallenstein, William Ketzeback, Julene Elias, Abdullah Korra, Anna Panova, Kathryn Devine, Kevin R. Covey

Automated Spectroscopic Wavelength Calibration using Dynamic Time Warping
Here we present an automated method for obtaining wavelength calibrations for one-dimensional spectra, using Dynamic Time Warping (DTW). DTW is a flexible and well-understood algorithm for pattern matching, which has not been widely used in astronomy data analysis. Employing a calibrated template spectrum as a reference, DTW can recover non-linear and even discontinuous dispersion solutions without an initial guess. The algorithm is robust against differing spectral resolution between the templ…

Improvement on LiDAR-Camera Calibration Using Square Targets
Zhongyuan Li, Honggang Gou, Ping Li, Jiaotong Guo, Mao Ye
https://arxiv.org/abs/2506.18294 htt…

Improvement on LiDAR-Camera Calibration Using Square Targets
Precise sensor calibration is critical for autonomous vehicles as a prerequisite for perception algorithms to function properly. Rotation error of one degree can translate to position error of meters in target object detection at large distance, leading to improper reaction of the system or even safety related issues. Many methods for multi-sensor calibration have been proposed. However, there are very few work that comprehensively consider the challenges of the calibration procedure when appli…

Qubit Health Analytics and Clustering for HPC-Integrated Quantum Processors
Xiaolong Deng, Laura Schulz, Martin Schulz
https://arxiv.org/abs/2508.21231 https://

Qubit Health Analytics and Clustering for HPC-Integrated Quantum Processors
Quantum computing in supercomputing centers requires robust tools to analyze calibration datasets, predict hardware performance, and optimize operational workflows. This paper presents a data-driven framework for processing calibration metrics. Our model is based on a real calibration quality metrics dataset from our in-house 20-qubit NISQ device and for more than 250 days. We apply detailed data analysis to uncover temporal patterns and cross-metric correlations. Using unsupervised clustering,…

The LED calibration systems for the mDOM and D-Egg sensor modules of the IceCube Upgrade
R. Abbasi, et al.
https://arxiv.org/abs/2508.03822 https://arxiv.o…

The LED calibration systems for the mDOM and D-Egg sensor modules of the IceCube Upgrade
The IceCube Neutrino Observatory, instrumenting about 1 km$^3$ of deep, glacial ice at the geographic South Pole, is due to be enhanced with the IceCube Upgrade. The IceCube Upgrade, to be deployed during the 2025/26 Antarctic summer season, will consist of seven new strings of photosensors, densely embedded near the bottom center of the existing array. Aside from a world-leading sensitivity to neutrino oscillations, a primary goal is the improvement of the calibration of the optical properties…

A Computationally Aware Multi Objective Framework for Camera LiDAR Calibration
Venkat Karramreddy, Rangarajan Ramanujam
https://arxiv.org/abs/2506.20636 ht…

A Computationally Aware Multi Objective Framework for Camera LiDAR Calibration
Accurate extrinsic calibration between LiDAR and camera sensors is important for reliable perception in autonomous systems. In this paper, we present a novel multi-objective optimization framework that jointly minimizes the geometric alignment error and computational cost associated with camera-LiDAR calibration. We optimize two objectives: (1) error between projected LiDAR points and ground-truth image edges, and (2) a composite metric for computational cost reflecting runtime and resource usa…

Human-Exoskeleton Kinematic Calibration to Improve Hand Tracking for Dexterous Teleoperation
Haiyun Zhang, Stefano Dalla Gasperina, Saad N. Yousaf, Toshimitsu Tsuboi, Tetsuya Narita, Ashish D. Deshpande
https://arxiv.org/abs/2507.23592

Human-Exoskeleton Kinematic Calibration to Improve Hand Tracking for Dexterous Teleoperation
Hand exoskeletons are critical tools for dexterous teleoperation and immersive manipulation interfaces, but achieving accurate hand tracking remains a challenge due to user-specific anatomical variability and donning inconsistencies. These issues lead to kinematic misalignments that degrade tracking performance and limit applicability in precision tasks. We propose a subject-specific calibration framework for exoskeleton-based hand tracking that uses redundant joint sensing and a residual-weigh…

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[2/3]:
- UniCalib: Targetless LiDAR-Camera Calibration via Probabilistic Flow on Unified Depth Representat...
Shu Han, Xubo Zhu, Ji Wu, Ximeng Cai, Wen Yang, Huai Yu, Gui-Song Xia

CONCERTO: forward modeling of interferograms for calibration
A. Lundgren, A. Beelen, G. Lagache, F. -X. Desert, A. Fasano, J. Macias-Perez, A. Monfardini, P. Ade, M. Aravena, E. Barria, A. Benoit, M. Bethermin, J. Bounmy, O. Bourrion, G. Bres, C. De Breuck, M. Calvo, A. Catalano, C. Dubois, C. A Duran, T. Fenouillet, J. Garcia, G. Garde, J. Goupy, C. Hoarau, W. Hu, J. -C. Lambert, F. Levy-Bertrand, J. Marpaud, R. Parra, G. Pisano, N. Ponthieu, L. Prieur, D. Quinatoa, S. Roni, S. Roudie…

CONCERTO: forward modeling of interferograms for calibration
The CarbON [CII] line in post-rEionisation and ReionisaTiOn epoch (CONCERTO) instrument is a low-resolution mapping Fourier-transform spectrometer, based on lumped-element kinetic inductance detector (LEKID) technology, operating at 130- 310 GHz. It was installed on the 12-meter APEX telescope in Chile in April 2021 and operated until December 2022. CONCERTO's main science goal is to constrain the [CII] line fluctuations at high redshift. To reach that goal CONCERTO observed 1.4 deg2 in the COS…

Odometry Calibration and Pose Estimation of a 4WIS4WID Mobile Wall Climbing Robot
Branimir \'Caran, Vladimir Mili\'c, Marko \v{S}vaco, Bojan Jerbi\'c
https://arxiv.org/abs/2509.04016

Odometry Calibration and Pose Estimation of a 4WIS4WID Mobile Wall Climbing Robot
This paper presents the design of a pose estimator for a four wheel independent steer four wheel independent drive (4WIS4WID) wall climbing mobile robot, based on the fusion of multimodal measurements, including wheel odometry, visual odometry, and an inertial measurement unit (IMU) data using Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). The pose estimator is a critical component of wall climbing mobile robots, as their operational environment involves carrying precise measur…

Use of solid fused silica etalon with broadband metallic coatings for calibration of high-resolution optical spectrograph
Supriyo Ghosh (University of Hertfordshire, UK), William Martin (University of Hertfordshire, UK), Kajal Kunverji (University of Hertfordshire, UK), Hugh R. A. Jones (University of Hertfordshire, UK)
https://arxiv.org/a…

Use of solid fused silica etalon with broadband metallic coatings for calibration of high-resolution optical spectrograph
Wavelength calibration is a key factor for high-resolution spectroscopic measurements for precision radial velocities. Hollow-cathode lamps (e.g., ThAr), absorption cells (e.g., iodine cell), dielectric coated Fabry-Pérot etalons and laser frequency combs have been implemented over the years for precise wavelength calibration and wavelength drift measurements. However, due to their various impediments as wavelength calibrators, investigations of alternative methods remain of prime interest. In…

Data-driven Kinematic Modeling in Soft Robots: System Identification and Uncertainty Quantification
Zhanhong Jiang, Dylan Shah, Hsin-Jung Yang, Soumik Sarkar
https://arxiv.org/abs/2507.07370

Data-driven Kinematic Modeling in Soft Robots: System Identification and Uncertainty Quantification
Precise kinematic modeling is critical in calibration and controller design for soft robots, yet remains a challenging issue due to their highly nonlinear and complex behaviors. To tackle the issue, numerous data-driven machine learning approaches have been proposed for modeling nonlinear dynamics. However, these models suffer from prediction uncertainty that can negatively affect modeling accuracy, and uncertainty quantification for kinematic modeling in soft robots is underexplored. In this w…