Showing 1–50 of 160 results for author: Bhattacharyya, R

Calibration and Performance of Germanium High Voltage Detectors for SuperCDMS SNOLAB

Authors: M. F. Albakry, I. Alkhatib, D. Alonso-González, J. Anczarski, T. Aralis, T. Aramaki, A. Ashtari Esfahani, I. Ataee Langroudy, R. Bhattacharyya, A. J. Biffl, P. L. Brink, M. Buchanan, R. Bunker, B. Cabrera, R. Calkins, R. A. Cameron, P. Camus, C. Cartaro, D. G. Cerdeño, Y. -Y. Chang, M. Chaudhuri, J. -H. Chen, R. Chen, J. Cooley, J. Corbett , et al. (118 additional authors not shown)

Abstract: As SuperCDMS SNOLAB is getting ready to search for low mass dark matter particles, using cryogenic Ge and Si detectors, a set of six of the new SuperCDMS High Voltage (HV) detectors (four Ge and two Si) were tested in the Cryogenic Underground TEst facility (CUTE) at SNOLAB. This provided the first opportunity to gain experience with this new detector type and assess their performance thoroughly u… ▽ More As SuperCDMS SNOLAB is getting ready to search for low mass dark matter particles, using cryogenic Ge and Si detectors, a set of six of the new SuperCDMS High Voltage (HV) detectors (four Ge and two Si) were tested in the Cryogenic Underground TEst facility (CUTE) at SNOLAB. This provided the first opportunity to gain experience with this new detector type and assess their performance thoroughly under low background conditions. Here we describe the SuperCDMS HV detector concept and discuss some of the newly developed analysis methods and approaches. Focusing on the Ge detectors, we investigate the detector performance under voltage bias (up to 90 V), exercise the low energy (keV to sub-keV range) calibration based on the electron capture peaks generated by the decay of $^{71}$Ge, assess the detector resolution, and demonstrate the unexpected (and encouraging) ability of these detectors to also measure high energy interactions in the hundreds of keV range with good resolution (better than 3% at 356 keV). △ Less

Submitted 24 June, 2026; originally announced June 2026.

Comments: 16 pages, 12 figures, submitted to Astroparticle Physics Journal

Frequency-dependent criticality in optical properties of the Drude metals, including plasmas and seawater

Authors: Bikram Keshari Behera, Rhitabrata Bhattacharyya, Shyamal Biswas

Abstract: We have analytically determined attenuation constant, phase constant, and reflectivity of Drude metals over the entire frequency range ($0<ω<\infty$) for an incident electromagnetic (plane) wave, within a single framework of classical electrodynamics, taking into account bound charges and currents in the background. We have compared our result with existing experimental data for the reflectivity o… ▽ More We have analytically determined attenuation constant, phase constant, and reflectivity of Drude metals over the entire frequency range ($0<ω<\infty$) for an incident electromagnetic (plane) wave, within a single framework of classical electrodynamics, taking into account bound charges and currents in the background. We have compared our result with existing experimental data for the reflectivity of plasmas and that of seawater in this regard. Interestingly, for the Drude metal with a high carrier concentration ($ω_pτ\gg1$), we have obtained a simple form of attenuation constant $k_-\simeq+\sqrt{\frac{με}{2}}\sqrt{ω_p^2-ω^2+|ω_p^2-ω^2|}$ for a wide range of high frequencies below and above plasma frequency $ω_{p}$. Such a result gives rise to criticality in conductors' optical properties, such as attenuation constant, group velocity, and complex dielectric constant, \textit{etc} near around $ω_{p}$. We have obtained critical exponents for these quantities. We have also obtained a quantum correction to the optical properties within the Drude-Sommerfeld model with the Thomas-Fermi screening. △ Less

Submitted 8 August, 2026; v1 submitted 27 April, 2026; originally announced May 2026.

Comments: 9 pages, 2 figure

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity

Authors: Riddhiman Bhattacharyya, Sayak Chakrabarty, Imon Banerjee

Abstract: Contextual MDPs are powerful tools with wide applicability in areas from biostatistics to machine learning. However, specializing them to offline datasets has been challenging due to a lack of robust, theoretically backed methods. Our work tackles this problem by introducing a new approach towards adaptive estimation and cost optimization of contextual MDPs. This estimator, to the best of our know… ▽ More Contextual MDPs are powerful tools with wide applicability in areas from biostatistics to machine learning. However, specializing them to offline datasets has been challenging due to a lack of robust, theoretically backed methods. Our work tackles this problem by introducing a new approach towards adaptive estimation and cost optimization of contextual MDPs. This estimator, to the best of our knowledge, is the first of its kind, and is endowed with strong optimality guarantees. We achieve this by overcoming the key technical challenges evolving from the endogenous properties of contextual MDPs; such as non-stationarity, or model irregularity. Our guarantees are established under complete generality by utilizing the relatively recent and powerful statistical technique of $T$-estimation (Baraud, 2011). We first provide a procedure for selecting an estimator given a sample from a contextual MDP and use it to derive oracle risk bounds under two distinct, but nevertheless meaningful, loss functions. We then consider the problem of determining the optimal control with the aid of the aforementioned density estimate and provide finite sample guarantees for the cost function. △ Less

Submitted 5 May, 2026; originally announced May 2026.

Comments: 28 pages, Published in TMLR

Asymptotic behaviour of bigraded components of local cohomology modules

Authors: Rajsekhar Bhattacharyya, Tony J. Puthenpurakal, Sudeshna Roy, Jyoti Singh

Abstract: Let $C$ be a commutative Noetherian ring containing a field $K$ of characteristic zero. Let $R=C[X_1, \ldots, X_n, Y_1, \ldots, Y_m]$ be a polynomial ring over $C$ with $\mathrm{bideg}~ c=(0,0)$ for all $c \in C$, $\mathrm{bideg}~ X_i=(1,0)$ and $\mathrm{bideg}~ Y_j=(0,1)$ for $i=1, \ldots, n$ and $j=1, \ldots, m$. Let $I$ be a bihomogeneous ideal in $R$. In this article, we study asymptotic behav… ▽ More Let $C$ be a commutative Noetherian ring containing a field $K$ of characteristic zero. Let $R=C[X_1, \ldots, X_n, Y_1, \ldots, Y_m]$ be a polynomial ring over $C$ with $\mathrm{bideg}~ c=(0,0)$ for all $c \in C$, $\mathrm{bideg}~ X_i=(1,0)$ and $\mathrm{bideg}~ Y_j=(0,1)$ for $i=1, \ldots, n$ and $j=1, \ldots, m$. Let $I$ be a bihomogeneous ideal in $R$. In this article, we study asymptotic behaviour of bigraded pieces of the local cohomology module $H^i_I(R)$. Moreover, under the extra assumption that $C$ is regular, we investigate the asymptotic stability of invariants associated to its bigraded components. Consequently, we obtain certain properties of components of the bigraded local cohomology module $H^i_I(R)$, where $C=K$ is a field and $I$ is a binomial edge ideal. △ Less

Submitted 22 March, 2026; originally announced March 2026.

MSC Class: Primary 13D45; 14B15; Secondary 13N10; 32C36

Adaptive Prototype-based Interpretable Grading of Prostate Cancer

Authors: Riddhasree Bhattacharyya, Pallabi Dutta, Sushmita Mitra

Abstract: Prostate cancer being one of the frequently diagnosed malignancy in men, the rising demand for biopsies places a severe workload on pathologists. The grading procedure is tedious and subjective, motivating the development of automated systems. Although deep learning has made inroads in terms of performance, its limited interpretability poses challenges for widespread adoption in high-stake applica… ▽ More Prostate cancer being one of the frequently diagnosed malignancy in men, the rising demand for biopsies places a severe workload on pathologists. The grading procedure is tedious and subjective, motivating the development of automated systems. Although deep learning has made inroads in terms of performance, its limited interpretability poses challenges for widespread adoption in high-stake applications like medicine. Existing interpretability techniques for prostate cancer classifiers provide a coarse explanation but do not reveal why the highlighted regions matter. In this scenario, we propose a novel prototype-based weakly-supervised framework for an interpretable grading of prostate cancer from histopathology images. These networks can prove to be more trustworthy since their explicit reasoning procedure mirrors the workflow of a pathologist in comparing suspicious regions with clinically validated examples. The network is initially pre-trained at patch-level to learn robust prototypical features associated with each grade. In order to adapt it to a weakly-supervised setup for prostate cancer grading, the network is fine-tuned with a new prototype-aware loss function. Finally, a new attention-based dynamic pruning mechanism is introduced to handle inter-sample heterogeneity, while selectively emphasizing relevant prototypes for optimal performance. Extensive validation on the benchmark PANDA and SICAP datasets confirms that the framework can serve as a reliable assistive tool for pathologists in their routine diagnostic workflows. △ Less

Submitted 5 March, 2026; originally announced March 2026.

Observations of a Twin Pair of Atypical Solar Flares and a Magnetic-reconnection Scenario

Authors: Satyam Agarwal, Alphonse C. Sterling, Shibu K. Mathew, Ronald L. Moore, Qiang Hu, Ramit Bhattacharyya

Abstract: We present observations and a magnetic-reconnection scenario of a twin pair of "atypical flares" that occurred on 2022 April 22 in a quadrupolar magnetic configuration formed by two active regions. The spatio-temporal evolution of the two flares is examined using images from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO), and from the ground-based Multi-Applica… ▽ More We present observations and a magnetic-reconnection scenario of a twin pair of "atypical flares" that occurred on 2022 April 22 in a quadrupolar magnetic configuration formed by two active regions. The spatio-temporal evolution of the two flares is examined using images from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO), and from the ground-based Multi-Application Solar Telescope (MAST) in Udaipur, India. Characteristic of atypical flares and indicative of slipping reconnection, the ribbons of each flare (1) do not spread apart and (2) grow longer by sequential brightening of new flare kernels. The two atypical flares are homologous and plausibly have homologous triggers. There are four additional pairs of flare ribbons, each from a different flaring event that releases much less energy than the atypical flares. Two of these four pairs are produced by precursors, each possibly triggering one of the two atypical flares. The remaining two pairs accompany a filament activation, occurring twice within the span of the two atypical flares. Using a nonlinear force-free field (NLFFF) extrapolation model, we approximate the coronal magnetic field and find two quasi-separatrix layers (QSLs) that are nearly rooted in the flare ribbons. The observations and the extrapolated field together suggest a scenario in which the nearly simultaneous occurrence of many reconnections between magnetic field lines crossing at small angles (slipping reconnection) within each of the two QSLs produces the observed pair of atypical flares. △ Less

Submitted 2 March, 2026; originally announced March 2026.

Comments: Accepted for publication in ApJ

Optimal enhancement of the Overhauser and Solid Effects within a unified framework

Authors: Sarfraj Fency, Rangeet Bhattacharyya

Abstract: The Overhauser effect (OE) and the Solid effect (SE) are two Dynamic Nuclear Polarization techniques. These two-spin techniques are widely used to create nonequilibrium nuclear spin states having polarization far beyond its equilibrium value. OE is commonly encountered in liquids, and SE is a solid-state technique. Here, we report a single framework based on a recently proposed quantum master equa… ▽ More The Overhauser effect (OE) and the Solid effect (SE) are two Dynamic Nuclear Polarization techniques. These two-spin techniques are widely used to create nonequilibrium nuclear spin states having polarization far beyond its equilibrium value. OE is commonly encountered in liquids, and SE is a solid-state technique. Here, we report a single framework based on a recently proposed quantum master equation, to explain both OE and SE. To this end, we use a fluctuation-regularized quantum master equation that predicts dipolar relaxation and drive-induced dissipation, in addition to the standard environmental dissipation channels. Importantly, this unified approach predicts the existence of optimal microwave drive amplitudes that maximize the OE and SE enhancements. We also report optimal enhancement regime for electron-nuclear coupling for maximal enhancement. △ Less

Submitted 2 February, 2026; originally announced February 2026.

Comments: 12 pages, 4 figures

Investigation of magnetic topology and triggering mechanisms of a C-class flare and active-region blowout jet

Authors: Yogesh Kumar Maurya, Ramit Bhattacharyya, Peter Wyper

Abstract: Coronal jets are collimated plasma eruptions which are ubiquitous in the solar atmosphere. Believed to be triggered by magnetic reconnection, these jets can contribute to various phenomena, including coronal heating and particle acceleration. Coronal jets are a contemporary area of research with their onset mechanism meriting further attention. Importantly, a subclass of jets, the blowout jets, ar… ▽ More Coronal jets are collimated plasma eruptions which are ubiquitous in the solar atmosphere. Believed to be triggered by magnetic reconnection, these jets can contribute to various phenomena, including coronal heating and particle acceleration. Coronal jets are a contemporary area of research with their onset mechanism meriting further attention. Importantly, a subclass of jets, the blowout jets, are particularly interesting because of their broad spire, suggesting substantial three-dimensional (3D) reconnection between open and closed field lines involving 3D null points. Consequently, here we explore the onset of a blowout jet associated with Active Region (AR) SPoCA 29093 detected by Spatial Possibilistic Clustering Algorithm (SPoCA). This AR produced a C1.1-class flare on 10 November 2022 and we investigate it using a data-constrained magnetohydrodynamic simulation initiated with a non force-free-field (NFFF) extrapolation of the photospheric magnetic field. Key elements of the extrapolated field lines are the presence of a 3D null and a magnetic flux rope (MFR) co-located with the jet activity region, the evolution of which is further traced in the simulation. The simulation suggests that magnetic reconnection is responsible for the evolution of the MFR, leading to a near-simultaneous onset of the flare and jet as observed by the AIA/SDO. In particular, the simulation shows spontaneous creation and annihilation of 3D null pairs via magnetic reconnection near the jet region. Such spontaneous null pair generation, in principle, can trigger or contribute to coronal jets; opening up a new avenue for further research. △ Less

Submitted 2 February, 2026; originally announced February 2026.

Comments: The research article is accepted in The ApJ. The same will be published by the journal soon

Safe Langevin Soft Actor Critic

Authors: Mahesh Keswani, Samyak Jain, Raunak P. Bhattacharyya

Abstract: Balancing reward and safety in constrained reinforcement learning remains challenging due to poor generalization from sharp value minima and inadequate handling of heavy-tailed risk distribution. We introduce Safe Langevin Soft Actor-Critic (SL-SAC), a principled algorithm that addresses both issues through parameter-space exploration and distributional risk control. Our approach combines three ke… ▽ More Balancing reward and safety in constrained reinforcement learning remains challenging due to poor generalization from sharp value minima and inadequate handling of heavy-tailed risk distribution. We introduce Safe Langevin Soft Actor-Critic (SL-SAC), a principled algorithm that addresses both issues through parameter-space exploration and distributional risk control. Our approach combines three key mechanisms: (1) Adaptive Stochastic Gradient Langevin Dynamics (aSGLD) for reward critics, promoting ensemble diversity and escape from poor optima; (2) distributional cost estimation via Implicit Quantile Networks (IQN) with Conditional Value-at-Risk (CVaR) optimization for tail-risk mitigation; and (3) a reactive Lagrangian relaxation scheme that adapts constraint enforcement based on the empirical CVaR of episodic costs. We provide theoretical guarantees on CVaR estimation error and demonstrate that CVaR-based Lagrange updates yield stronger constraint violation signals than expected-cost updates. On Safety-Gymnasium benchmarks, SL-SAC achieves the lowest cost in 7 out of 10 tasks while maintaining competitive returns, with cost reductions of 19-63% in velocity tasks compared to state-of-the-art baselines. △ Less

Submitted 31 January, 2026; originally announced February 2026.

Comments: 20 pages, 12 figures

LeanTutor: Towards a Verified AI Mathematical Proof Tutor

Authors: Manooshree Patel, Rayna Bhattacharyya, Thomas Lu, Arnav Mehta, Niels Voss, Narges Norouzi, Gireeja Ranade

Abstract: This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language, they are error prone. Theorem provers such as Lean allow for provable-correctness, but these are hard for students to learn. We present a proof-of-concept system (LeanTutor) by combining the complementary strengths of LL… ▽ More This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language, they are error prone. Theorem provers such as Lean allow for provable-correctness, but these are hard for students to learn. We present a proof-of-concept system (LeanTutor) by combining the complementary strengths of LLMs and theorem provers. LeanTutor is composed of three modules: (i) an autoformalizer/proof-checker, (ii) a next-step generator, and (iii) a natural language feedback generator. To evaluate the system, we introduce PeanoBench, a dataset of 371 Peano Arithmetic proofs in human-written natural language and formal language, derived from the Natural Numbers Game. △ Less

Submitted 3 March, 2026; v1 submitted 24 January, 2026; originally announced January 2026.

Comments: This work was intended as a replacement of arXiv:2506.08321 and any subsequent updates will appear there

Learning Safe Autonomous Driving Policies Using Predictive Safety Representations

Authors: Mahesh Keswani, Raunak Bhattacharyya

Abstract: Safe reinforcement learning (SafeRL) is a prominent paradigm for autonomous driving, where agents are required to optimize performance under strict safety requirements. This dual objective creates a fundamental tension, as overly conservative policies limit driving efficiency while aggressive exploration risks safety violations. The Safety Representations for Safer Policy Learning (SRPL) framework… ▽ More Safe reinforcement learning (SafeRL) is a prominent paradigm for autonomous driving, where agents are required to optimize performance under strict safety requirements. This dual objective creates a fundamental tension, as overly conservative policies limit driving efficiency while aggressive exploration risks safety violations. The Safety Representations for Safer Policy Learning (SRPL) framework addresses this challenge by equipping agents with a predictive model of future constraint violations and has shown promise in controlled environments. This paper investigates whether SRPL extends to real-world autonomous driving scenarios. Systematic experiments on the Waymo Open Motion Dataset (WOMD) and NuPlan demonstrate that SRPL can improve the reward-safety tradeoff, achieving statistically significant improvements in success rate (effect sizes r = 0.65-0.86) and cost reduction (effect sizes r = 0.70-0.83), with p < 0.05 for observed improvements. However, its effectiveness depends on the underlying policy optimizer and the dataset distribution. The results further show that predictive safety representations play a critical role in improving robustness to observation noise. Additionally, in zero-shot cross-dataset evaluation, SRPL-augmented agents demonstrate improved generalization compared to non-SRPL methods. These findings collectively demonstrate the potential of predictive safety representations to strengthen SafeRL for autonomous driving. △ Less

Submitted 23 December, 2025; v1 submitted 19 December, 2025; originally announced December 2025.

Comments: 8 pages, 4 figures

Instance Dependent Testing of Samplers using Interval Conditioning

Authors: Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote, Uddalok Sarkar, Sayantan Sen

Abstract: Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Provably correct testers like Barbarik, Teq, Flash, CubeProbe for testing of different kinds of samplers were proposed only in the last few years. All these testers focus on the worst-case efficiency, and do not support ver… ▽ More Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Provably correct testers like Barbarik, Teq, Flash, CubeProbe for testing of different kinds of samplers were proposed only in the last few years. All these testers focus on the worst-case efficiency, and do not support verification of samplers over infinite domains, a case occurring frequently in Astronomy, Finance, Network Security, etc. In this work, we design the first tester of samplers with instance-dependent efficiency, allowing us to test samplers over natural numbers. Our tests are developed via a novel distance estimation algorithm between an unknown and a known probability distribution using an interval conditioning framework. The core technical contribution is a new connection with probability mass estimation of a continuous distribution. The practical gains are also substantial: our experiments establish up to 1000x speedup over state-of-the-art testers. △ Less

Submitted 6 December, 2025; originally announced December 2025.

Discrete Time Crystals in Noninteracting Dissipative Systems

Authors: Gourab Das, Saptarshi Saha, Rangeet Bhattacharyya

Abstract: Many-body quantum systems, under suitable conditions, exhibit time-translation symmetry breaking and settle in a discrete time crystalline (DTC) phase -- an out-of-equilibrium quantum phase of matter. The defining feature of DTC is a robust subharmonic response. However, the DTC phase is fragile in the presence of environmental dissipation. Here, we propose and exemplify a DTC phase in a nonintera… ▽ More Many-body quantum systems, under suitable conditions, exhibit time-translation symmetry breaking and settle in a discrete time crystalline (DTC) phase -- an out-of-equilibrium quantum phase of matter. The defining feature of DTC is a robust subharmonic response. However, the DTC phase is fragile in the presence of environmental dissipation. Here, we propose and exemplify a DTC phase in a noninteracting system that owes its stability to environmental dissipation. The lifetime of this DTC is independent of initial conditions and the size of the system, though it depends on the frequency of the external driver. We experimentally demonstrate this realization of DTC using Nuclear Magnetic Resonance spectroscopy. △ Less

Submitted 12 November, 2025; originally announced November 2025.

Comments: 16 pages, 5 figures

Search for low-mass electron-recoil dark matter using a single-charge sensitive SuperCDMS-HVeV Detector

Authors: SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. Alonso-González, 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. Cerdeño, Y. -Y. Chang, M. Chaudhuri, J. -H. Chen, R. Chen, N. Chott, J. Cooley , et al. (124 additional authors not shown)

Abstract: We present constraints on low-mass dark matter electron scattering and absorption interactions using a SuperCDMS high-voltage eV-resolution (HVeV) detector. Data were taken underground in the NEXUS facility located at Fermilab with an overburden of 225 meters of water equivalent. The experiment benefits from the minimizing of luminescence from the printed circuit boards in the detector holder used… ▽ More We present constraints on low-mass dark matter electron scattering and absorption interactions using a SuperCDMS high-voltage eV-resolution (HVeV) detector. Data were taken underground in the NEXUS facility located at Fermilab with an overburden of 225 meters of water equivalent. The experiment benefits from the minimizing of luminescence from the printed circuit boards in the detector holder used in all previous HVeV studies. A blind analysis of $6.1\,\mathrm{g\cdot days}$ of exposure produces exclusion limits for dark matter-electron scattering cross sections for masses as low as $1\,\mathrm{MeV}/c^2$, as well as on the photon-dark photon mixing parameter and the coupling constant between axionlike particles and electrons for particles with masses $>1.2\,\mathrm{eV}/c^2$ probed via absorption processes. △ Less

Submitted 15 March, 2026; v1 submitted 3 September, 2025; originally announced September 2025.

Comments: 9 pages, 3 figures and 1 table

Journal ref: Phys. Rev. D 113, 032001 (2026)

Determination of Fluctuation correlation time in solid-state Nuclear Magnetic Resonance

Authors: Saptarshi Saha, Rangeet Bhattacharyya

Abstract: Solid-state NMR provides a wide variety of experimental techniques to detect and analyze a material's chemical and physical environment. Here, we offer a theoretical demonstration of a new approach that could be a promising candidate for characterizing the local environments and shifts. Prethermalization by applying a spin-locking pulse brings a new research paradigm in solid-state NMR and has not… ▽ More Solid-state NMR provides a wide variety of experimental techniques to detect and analyze a material's chemical and physical environment. Here, we offer a theoretical demonstration of a new approach that could be a promising candidate for characterizing the local environments and shifts. Prethermalization by applying a spin-locking pulse brings a new research paradigm in solid-state NMR and has not been hitherto explored for such purposes. We show that a prethermal state can also be effective in this case. A prethermal state is described using its lifetime and the value of transverse magnetization. Using these two variables, we successfully detect the changes in the environmental parameter and chemical and dynamical shifts (such as Lamb shifts). Our results exhibit that the lifetime increases with increasing environmental correlation time. On the other hand, the transverse magnetization decreases with the increase in the strength of the shift parameter. Based on these observations, we propose that the prethermalization dynamics can yield important information on local environment. △ Less

Submitted 31 August, 2025; originally announced September 2025.

Comments: 18 pages, 6 figures

Multi-channel, multi-template event reconstruction for SuperCDMS data using machine learning

Authors: M. F. Albakry, I. Alkhatib, D. Alonso-Gonzalez, J. Anczarski, T. Aralis, T. Aramaki, I. Ataee Langroudy, C. Bathurst, R. Bhattacharyya, A. J. Biff, P. L. Brink, M. Buchanan, R. Bunker, B. Cabrera, R. Calkins, R. A. Cameron, C. Cartaro, D. G. Cerdeno, Y. -Y. Chang, M. Chaudhuri, J. H. Chen, R. Chen, N. Chott, J. Cooley, H. Coombes , et al. (117 additional authors not shown)

Abstract: SuperCDMS SNOLAB uses kilogram-scale germanium and silicon detectors to search for dark matter. Each detector has Transition Edge Sensors (TESs) patterned on the top and bottom faces of a large crystal substrate, with the TESs electrically grouped into six phonon readout channels per face. Noise correlations are expected among a detector's readout channels, in part because the channels and their r… ▽ More SuperCDMS SNOLAB uses kilogram-scale germanium and silicon detectors to search for dark matter. Each detector has Transition Edge Sensors (TESs) patterned on the top and bottom faces of a large crystal substrate, with the TESs electrically grouped into six phonon readout channels per face. Noise correlations are expected among a detector's readout channels, in part because the channels and their readout electronics are located in close proximity to one another. Moreover, owing to the large size of the detectors, energy deposits can produce vastly different phonon propagation patterns depending on their location in the substrate, resulting in a strong position dependence in the readout-channel pulse shapes. Both of these effects can degrade the energy resolution and consequently diminish the dark matter search sensitivity of the experiment if not accounted for properly. We present a new algorithm for pulse reconstruction, mathematically formulated to take into account correlated noise and pulse shape variations. This new algorithm fits N readout channels with a superposition of M pulse templates simultaneously - hence termed the N$\times$M filter. We describe a method to derive the pulse templates using principal component analysis (PCA) and to extract energy and position information using a gradient boosted decision tree (GBDT). We show that these new N$\times$M and GBDT analysis tools can reduce the impact from correlated noise sources while improving the reconstructed energy resolution for simulated mono-energetic events by more than a factor of three and for the 71Ge K-shell electron-capture peak recoils measured in a previous version of SuperCDMS called CDMSlite to $<$ 50 eV from the previously published value of $\sim$100 eV. These results lay the groundwork for position reconstruction in SuperCDMS with the N$\times$M outputs. △ Less

Submitted 27 August, 2025; originally announced August 2025.

Comments: 22 pages, 8 figures

Enhancing Joint Human-AI Inference in Robot Missions: A Confidence-Based Approach

Authors: Duc-An Nguyen, Clara Colombatto, Steve Fleming, Ingmar Posner, Nick Hawes, Raunak Bhattacharyya

Abstract: Joint human-AI inference holds immense potential to improve outcomes in human-supervised robot missions. Current day missions are generally in the AI-assisted setting, where the human operator makes the final inference based on the AI recommendation. However, due to failures in human judgement on when to accept or reject the AI recommendation, complementarity is rarely achieved. We investigate joi… ▽ More Joint human-AI inference holds immense potential to improve outcomes in human-supervised robot missions. Current day missions are generally in the AI-assisted setting, where the human operator makes the final inference based on the AI recommendation. However, due to failures in human judgement on when to accept or reject the AI recommendation, complementarity is rarely achieved. We investigate joint human-AI inference where the inference made with higher confidence is selected. Through a user study with N=100 participants on a representative simulated robot teleoperation task, specifically studying the inference of robots' control delays we show that: a) Joint inference accuracy is higher and its extent is regulated by the confidence calibration of the AI agent, and b) Humans change their inferences based on AI recommendations and the extent and direction of this change is also regulated by the confidence calibration of the AI agent. Interestingly, our results show that pairing poorly-calibrated AI-DSS with humans hurts performance instead of helping the team, reiterating the need for AI-based decision support systems with good metacognitive sensitivity. To the best of our knowledge, our study presents the first application of a maximum-confidence-based heuristic for joint human-AI inference within a simulated robot teleoperation task. △ Less

Submitted 5 August, 2025; originally announced August 2025.

Low-Energy Calibration of SuperCDMS HVeV Cryogenic Silicon Calorimeters Using Compton Steps

Authors: SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. Alonso-Gonźalez, 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. Cerdeño, Y. -Y. Chang, M. Chaudhuri, J. -H. Chen, R. Chen, N. Chott , et al. (126 additional authors not shown)

Abstract: 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 succes… ▽ More 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 SuperCDMS High-Voltage eV-resolution (HVeV) detectors operated with 0 V bias across the crystal. This new calibration at 0 V is compared with the established high-voltage calibration using optical photons. The comparison indicates that the detector response at 0 V is about 30% weaker than expected, highlighting challenges in detector response modeling for low-mass dark matter searches. △ Less

Submitted 9 December, 2025; v1 submitted 4 August, 2025; originally announced August 2025.

Comments: 14 pages + title and references, 13 figures, and 6 table

Journal ref: Phys.Rev.D 112 (2025) 092014

LeanTutor: Towards a Verified AI Mathematical Proof Tutor

Authors: Manooshree Patel, Rayna Bhattacharyya, Thomas Lu, Arnav Mehta, Niels Voss, Narges Norouzi, Gireeja Ranade

Abstract: This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language, they are error prone. Theorem provers such as Lean allow for provable-correctness, but these are hard for students to learn. We present a proof-of-concept system (LeanTutor) by combining the complementary strengths of LL… ▽ More This paper considers the development of an AI-based provably-correct mathematical proof tutor. While Large Language Models (LLMs) allow seamless communication in natural language, they are error prone. Theorem provers such as Lean allow for provable-correctness, but these are hard for students to learn. We present a proof-of-concept system (LeanTutor) by combining the complementary strengths of LLMs and theorem provers. LeanTutor is composed of three modules: (i) an autoformalizer/proof-checker, (ii) a next-step generator, and (iii) a natural language feedback generator. To evaluate the system, we introduce PeanoBench, a dataset of 371 Peano Arithmetic proofs in human-written natural language and formal language, derived from the Natural Numbers Game. △ Less

Submitted 3 March, 2026; v1 submitted 9 June, 2025; originally announced June 2025.

Comments: Comments: Previously this version appeared as arXiv:2601.17473 which was submitted as a new work by accident

On the Magnetic Reconnection and its Properties during a Flare Using a Magnetohydrodynamics Simulation

Authors: Sushree S Nayak, Qiang Hu, Wen He, Sanjay Kumar, Ramit Bhattacharyya

Abstract: We study the magnetic reconnection during a flare by investigating flare ribbon dynamics using observations and data-constrained magnetohydrodynamics (MHD) simulation. In particular, we estimate the reconnection flux and the reconnection flux rates using flare ribbons of an M1.1 flare hosted by the active region 12184 utilizing the technique developed by Qiu et al. (2002, ApJ, 565, 1335). The reco… ▽ More We study the magnetic reconnection during a flare by investigating flare ribbon dynamics using observations and data-constrained magnetohydrodynamics (MHD) simulation. In particular, we estimate the reconnection flux and the reconnection flux rates using flare ribbons of an M1.1 flare hosted by the active region 12184 utilizing the technique developed by Qiu et al. (2002, ApJ, 565, 1335). The reconnection flux and corresponding flux rates are found to be 10^20 Mx and 10^18 Mx/s respectively. To understand the flare onset and the origin of flare ribbons, we perform an MHD simulation initiated by the non-force-free-field extrapolation. Importantly, the extrapolated configuration identifies a three-dimensional (3D) magnetic neutral point and a flux rope in the flaring region, which is crucial to the flaring activity. The reconnection initiates at the null point and, subsequently the flux rope rises and appears to reconnect there, which is favorable for the eruption of the filament. The surrounding field lines also seem to take part in the null point reconnection. In later stage, a current sheet is formed below the null point ensuing a secondary reconnection near an X-type topology, further contributing to the energy release process in the flare. We trace the footpoint evolution of the field lines lying over the flare ribbons and find a significant similarity between the observed flare ribbons and the evolution of footpoints computed from the MHD simulation. We estimated induced electric field during the flare and found it to be $\approx$ .52 V/cm, a slight less value, as per many past literatures. Additional findings are the enhancement of vertical current density near the flaring ribbons, a signature of successive reconnections near the null point. Overall, the present work contributes to the understanding of the ribbon formation in a flaring process and the involved magnetic reconnection. △ Less

Submitted 16 May, 2025; originally announced May 2025.

Comments: Accepted for publication in the Solar Physics journal

Quantum Speed Limit in Driven-dissipative Systems

Authors: Sarfraj Fency, Riddhi Chatterjee, Rangeet Bhattacharyya

Abstract: Every quantum operation that takes a system from one state to another is known to have bounds on operation time, due to Heisenberg uncertainty principle. In open quantum systems (OQS), such bounds have been principally affected by system environment coupling. In the recent past, drives on OQS have shown to give rise to drive-induced dissipation (DID). In this work, we investigate how DID affects t… ▽ More Every quantum operation that takes a system from one state to another is known to have bounds on operation time, due to Heisenberg uncertainty principle. In open quantum systems (OQS), such bounds have been principally affected by system environment coupling. In the recent past, drives on OQS have shown to give rise to drive-induced dissipation (DID). In this work, we investigate how DID affects the quantum speed limits. To this end, we use a recently-reported quantum master equation that takes into account environment fluctuations and provide a closed form estimate of drive-induced dissipation. On such a system, we use Gradient Ascent Pulse Engineering (GRAPE) to find optimal route to move from an initial state to a desired final state. Our key result is that there exists an optimal evolution time that maximizes fidelity. This work enables robust quantum control in open systems, addressing a key challenge in scaling quantum technologies. By improving fidelity and efficiency, our method advances practical quantum computing under realistic dissipative conditions. △ Less

Submitted 10 April, 2025; originally announced April 2025.

Comments: 17 pages, 5 figures

Joint Decision-Making in Robot Teleoperation: When are Two Heads Better Than One?

Authors: Duc-An Nguyen, Raunak Bhattacharyya, Clara Colombatto, Steve Fleming, Ingmar Posner, Nick Hawes

Abstract: Operators working with robots in safety-critical domains have to make decisions under uncertainty, which remains a challenging problem for a single human operator. An open question is whether two human operators can make better decisions jointly, as compared to a single operator alone. While prior work has shown that two heads are better than one, such studies have been mostly limited to static an… ▽ More Operators working with robots in safety-critical domains have to make decisions under uncertainty, which remains a challenging problem for a single human operator. An open question is whether two human operators can make better decisions jointly, as compared to a single operator alone. While prior work has shown that two heads are better than one, such studies have been mostly limited to static and passive tasks. We investigate joint decision-making in a dynamic task involving humans teleoperating robots. We conduct a human-subject experiment with $N=100$ participants where each participant performed a navigation task with two mobiles robots in simulation. We find that joint decision-making through confidence sharing improves dyad performance beyond the better-performing individual (p<0.0001). Further, we find that the extent of this benefit is regulated both by the skill level of each individual, as well as how well-calibrated their confidence estimates are. Finally, we present findings on characterising the human-human dyad's confidence calibration based on the individuals constituting the dyad. Our findings demonstrate for the first time that two heads are better than one, even on a spatiotemporal task which includes active operator control of robots. △ Less

Submitted 28 January, 2025; originally announced March 2025.

Comments: To be published in the 2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

ACM Class: I.2.9

Efficient Self-Supervised Grading of Prostate Cancer Pathology

Authors: Riddhasree Bhattacharyya, Surochita Pal Das, Sushmita Mitra

Abstract: Prostate cancer grading using the ISUP system (International Society of Urological Pathology) for treatment decisions is highly subjective and requires considerable expertise. Despite advances in computer-aided diagnosis systems, few have handled efficient ISUP grading on Whole Slide Images (WSIs) of prostate biopsies based only on slide-level labels. Some of the general challenges include managin… ▽ More Prostate cancer grading using the ISUP system (International Society of Urological Pathology) for treatment decisions is highly subjective and requires considerable expertise. Despite advances in computer-aided diagnosis systems, few have handled efficient ISUP grading on Whole Slide Images (WSIs) of prostate biopsies based only on slide-level labels. Some of the general challenges include managing gigapixel WSIs, obtaining patch-level annotations, and dealing with stain variability across centers. One of the main task-specific challenges faced by deep learning in ISUP grading, is the learning of patch-level features of Gleason patterns (GPs) based only on their slide labels. In this scenario, an efficient framework for ISUP grading is developed. The proposed TSOR is based on a novel Task-specific Self-supervised learning (SSL) model, which is fine-tuned using Ordinal Regression. Since the diversity of training samples plays a crucial role in SSL, a patch-level dataset is created to be relatively balanced w.r.t. the Gleason grades (GGs). This balanced dataset is used for pre-training, so that the model can effectively learn stain-agnostic features of the GP for better generalization. In medical image grading, it is desirable that misclassifications be as close as possible to the actual grade. From this perspective, the model is then fine-tuned for the task of ISUP grading using an ordinal regression-based approach. Experimental results on the most extensive multicenter prostate biopsies dataset (PANDA challenge), as well as the SICAP dataset, demonstrate the effectiveness of this novel framework compared to state-of-the-art methods. △ Less

Submitted 26 January, 2025; originally announced January 2025.

Adaptive Class Learning to Screen Diabetic Disorders in Fundus Images of Eye

Authors: Shramana Dey, Pallabi Dutta, Riddhasree Bhattacharyya, Surochita Pal, Sushmita Mitra, Rajiv Raman

Abstract: The prevalence of ocular illnesses is growing globally, presenting a substantial public health challenge. Early detection and timely intervention are crucial for averting visual impairment and enhancing patient prognosis. This research introduces a new framework called Class Extension with Limited Data (CELD) to train a classifier to categorize retinal fundus images. The classifier is initially tr… ▽ More The prevalence of ocular illnesses is growing globally, presenting a substantial public health challenge. Early detection and timely intervention are crucial for averting visual impairment and enhancing patient prognosis. This research introduces a new framework called Class Extension with Limited Data (CELD) to train a classifier to categorize retinal fundus images. The classifier is initially trained to identify relevant features concerning Healthy and Diabetic Retinopathy (DR) classes and later fine-tuned to adapt to the task of classifying the input images into three classes: Healthy, DR, and Glaucoma. This strategy allows the model to gradually enhance its classification capabilities, which is beneficial in situations where there are only a limited number of labeled datasets available. Perturbation methods are also used to identify the input image characteristics responsible for influencing the models decision-making process. We achieve an overall accuracy of 91% on publicly available datasets. △ Less

Submitted 21 January, 2025; originally announced January 2025.

Comments: Accepted at International Conference on Pattern Recognition (ICPR) 2024

Data-Constrained Magnetohydrodynamics Simulation of a Confined X-class Flare in NOAA Active Region 11166

Authors: Sanjay Kumar, Pawan Kumar, Sadashiv, Sushree S. Nayak, Satyam Agarwal, Avijeet Prasad, Ramit Bhattacharyya, Ramesh Chandra

Abstract: In this paper, we present a magnetohydrodynamics simulation of NOAA active region 11166 to understand the origin of a confined X-class flare that peaked at 23:23 UT on 2011 March 9. The simulation is initiated with a magnetic field extrapolated from the corresponding photospheric magnetogram using a non-force-free-field extrapolation technique. Importantly, the initial magnetic configuration ident… ▽ More In this paper, we present a magnetohydrodynamics simulation of NOAA active region 11166 to understand the origin of a confined X-class flare that peaked at 23:23 UT on 2011 March 9. The simulation is initiated with a magnetic field extrapolated from the corresponding photospheric magnetogram using a non-force-free-field extrapolation technique. Importantly, the initial magnetic configuration identifies three-dimensional (3D) magnetic nulls and quasi-separatrix layers (QSLs), which nearly agree with the bright structures appeared in multi-wavelength observations. The Lorentz force associated with the extrapolated field self-consistently generates the dynamics that leads to the magnetic reconnections at the 3D nulls and the QSLs. These reconnections are found to contribute to the pre-flare activities and, ultimately, lead to the development of the flare ribbons. Notably, the anchored spine of the 3D null and the complete absence of flux rope in the flaring region are congruent with the confined nature of the flare. Furthermore, the simulation also suggests the role of reconnections at the 3D null with an open spine in the onset of a jet away from the flaring site. △ Less

Submitted 19 January, 2025; originally announced January 2025.

Comments: 22 pages, Accepted for Publication in Solar Physics

ReputeStream: Mitigating Free-Riding through Reputation-Based Multi-Layer P2P Live Streaming

Authors: Rashmi Kushwaha, Rahul Bhattacharyya, Yatindra Nath Singh

Abstract: This paper presents a novel algorithm for peer-to-peer (P2P) live streaming that addresses the limitations of single-layer systems through a multi-layered approach. The proposed solution adapts to diverse user capabilities and bandwidth conditions while tackling common P2P challenges such as free-riding, malicious behavior, churn, and flash crowds. By implementing a reputation-based system, the al… ▽ More This paper presents a novel algorithm for peer-to-peer (P2P) live streaming that addresses the limitations of single-layer systems through a multi-layered approach. The proposed solution adapts to diverse user capabilities and bandwidth conditions while tackling common P2P challenges such as free-riding, malicious behavior, churn, and flash crowds. By implementing a reputation-based system, the algorithm promotes fair resource sharing and active participation. The algorithm also incorporates a request-to-join mechanism to effectively manage flash crowds. In addition, a dynamic reputation system improves network efficiency by strategically positioning high-reputation peers closer to video sources or other significant contributors. △ Less

Submitted 28 November, 2024; originally announced November 2024.

Adaptive Invariant Extended Kalman Filter with Noise Covariance Tuning for Attitude Estimation

Authors: Yash Pandey, Rahul Bhattacharyya, Yatindra Nath Singh

Abstract: Attitude estimation is crucial in aerospace engineering, robotics, and virtual reality applications, but faces difficulties due to nonlinear system dynamics and sensor limitations. This paper addresses the challenge of attitude estimation using quaternion-based adaptive right invariant extended Kalman filtering (RI-EKF) that integrates data from inertial and magnetometer sensors. Our approach appl… ▽ More Attitude estimation is crucial in aerospace engineering, robotics, and virtual reality applications, but faces difficulties due to nonlinear system dynamics and sensor limitations. This paper addresses the challenge of attitude estimation using quaternion-based adaptive right invariant extended Kalman filtering (RI-EKF) that integrates data from inertial and magnetometer sensors. Our approach applies the expectation-maximization (EM) algorithm to estimate noise covariance, exploiting RI-EKF symmetry properties. We analyze the adaptive RI-EKF's stability, convergence, and accuracy, validating its performance through simulations and comparison with the left invariant EKF. Monte Carlo simulations validate the effectiveness of our noise covariance estimation technique across various window lengths. △ Less

Submitted 2 October, 2024; originally announced October 2024.

Comments: This work has been submitted to the IEEE for possible publication

Robust Attitude Estimation with Quaternion Left-Invariant EKF and Noise Covariance Tuning

Authors: Yash Pandey, Rahul Bhattacharyya, Yatindra Nath Singh

Abstract: Accurate estimation of noise parameters is critical for optimal filter performance, especially in systems where true noise parameter values are unknown or time-varying. This article presents a quaternion left-invariant extended Kalman filter (LI-EKF) for attitude estimation, integrated with an adaptive noise covariance estimation algorithm. By employing an iterative expectation-maximization (EM) a… ▽ More Accurate estimation of noise parameters is critical for optimal filter performance, especially in systems where true noise parameter values are unknown or time-varying. This article presents a quaternion left-invariant extended Kalman filter (LI-EKF) for attitude estimation, integrated with an adaptive noise covariance estimation algorithm. By employing an iterative expectation-maximization (EM) approach, the filter can effectively estimate both process and measurement noise covariances. Extensive simulations demonstrate the superiority of the proposed method in terms of attitude estimation accuracy and robustness to initial parameter misspecification. The adaptive LI-EKF's ability to adapt to time-varying noise characteristics makes it a promising solution for various applications requiring reliable attitude estimation, such as aerospace, robotics, and autonomous systems. △ Less

Submitted 17 September, 2024; originally announced September 2024.

Comments: This work has been submitted to the IEEE for possible publication

Reputation-Driven Peer-to-Peer Live Streaming Architecture for Preventing Free-Riding

Authors: Rashmi Kushwaha, Rahul Bhattacharyya, Yatindra Nath Singh

Abstract: We present a peer-to-peer (P2P) live-streaming architecture designed to address challenges such as free-riding, malicious peers, churn, and network instability through the integration of a reputation system. The proposed algorithm incentivizes active peer participation while discouraging opportunistic behaviors, with a reputation mechanism that rewards altruistic peers and penalizes free riders an… ▽ More We present a peer-to-peer (P2P) live-streaming architecture designed to address challenges such as free-riding, malicious peers, churn, and network instability through the integration of a reputation system. The proposed algorithm incentivizes active peer participation while discouraging opportunistic behaviors, with a reputation mechanism that rewards altruistic peers and penalizes free riders and malicious actors. To manage peer dynamics, the algorithm continuously updates the strategies and adjusts to changing neighbors. It also implements a request-to-join mechanism for flash crowd scenarios, allowing the source node to delegate requests to child nodes, forming an interconnected tree structure that efficiently handles high demand and maintains system stability. The decentralized reputation mechanism promotes long-term sustainability in the P2P live streaming system. △ Less

Submitted 14 September, 2024; originally announced September 2024.

Comments: 6 Pages, 6 Figure

Exploring the magnetic and thermal evolution of a coronal jet

Authors: Sushree S Nayak, Samrat Sen, Arpit Kumar Shrivastav, R. Bhattacharyya, P. S. Athiray

Abstract: Coronal jets are the captivating eruptions which are often found in the solar atmosphere, and primarily formed due to magnetic reconnection. Despite their short-lived nature and lower energy compared to many other eruptive events, e.g. flares and coronal mass ejections, they play an important role in heating the corona and accelerating charged particles. However, their generation in the ambience o… ▽ More Coronal jets are the captivating eruptions which are often found in the solar atmosphere, and primarily formed due to magnetic reconnection. Despite their short-lived nature and lower energy compared to many other eruptive events, e.g. flares and coronal mass ejections, they play an important role in heating the corona and accelerating charged particles. However, their generation in the ambience of non-standard flare regime is not fully understood, and warrant a deeper investigation, in terms of their onset, growth, eruption processes, and thermodynamic evolution. Toward this goal, this paper reports the results of a data-constrained three-dimensional (3D) magnetohydrodynamics (MHD) simulation of an eruptive jet; initialized with a Non-Force-Free-Field (NFFF) extrapolation and carried out in the spirit of Implicit Large Eddy Simulation (ILES). The simulation focuses on the magnetic and dynamical properties of the jet during its onset, and eruption phases, that occurred on February 5, 2015 in an active region NOAA AR12280, associated with a seemingly three-ribbon structure. In order to correlate its thermal evolution with computed energetics, the simulation results are compared with differential emission measurement (DEM) analysis in the vicinity of the jet. Importantly, this combined approach provides an insight to the onset of reconnection in transients in terms of emission and the corresponding electric current profiles from MHD evolutions. The presented study captures the intricate topological dynamics, finds a close correspondence between the magnetic and thermal evolution in and around the jet location. Overall, it enriches the understanding of the thermal evolution due to MHD processes, which is one of the broader aspects to reveal the coronal heating problem. △ Less

Submitted 5 September, 2024; originally announced September 2024.

Comments: 26 pages, 16 figures, accepted for publication in the Astrophysical Journal. Animations associated with Figure 1, Figure 7, and Figure 8 are available upon reasonable request from the corresponding authors

A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers

Authors: Daniel Omeiza, Raunak Bhattacharyya, Marina Jirotka, Nick Hawes, Lars Kunze

Abstract: Transparency in automated systems could be afforded through the provision of intelligible explanations. While transparency is desirable, might it lead to catastrophic outcomes (such as anxiety), that could outweigh its benefits? It's quite unclear how the specificity of explanations (level of transparency) influences recipients, especially in autonomous driving (AD). In this work, we examined the… ▽ More Transparency in automated systems could be afforded through the provision of intelligible explanations. While transparency is desirable, might it lead to catastrophic outcomes (such as anxiety), that could outweigh its benefits? It's quite unclear how the specificity of explanations (level of transparency) influences recipients, especially in autonomous driving (AD). In this work, we examined the effects of transparency mediated through varying levels of explanation specificity in AD. We first extended a data-driven explainer model by adding a rule-based option for explanation generation in AD, and then conducted a within-subject lab study with 39 participants in an immersive driving simulator to study the effect of the resulting explanations. Specifically, our investigation focused on: (1) how different types of explanations (specific vs. abstract) affect passengers' perceived safety, anxiety, and willingness to take control of the vehicle when the vehicle perception system makes erroneous predictions; and (2) the relationship between passengers' behavioural cues and their feelings during the autonomous drives. Our findings showed that passengers felt safer with specific explanations when the vehicle's perception system had minimal errors, while abstract explanations that hid perception errors led to lower feelings of safety. Anxiety levels increased when specific explanations revealed perception system errors (high transparency). We found no significant link between passengers' visual patterns and their anxiety levels. Our study suggests that passengers prefer clear and specific explanations (high transparency) when they originate from autonomous vehicles (AVs) with optimal perceptual accuracy. △ Less

Submitted 16 August, 2024; originally announced August 2024.

Comments: Submitted to Transportation Research Part F: Traffic Psychology and Behaviour. arXiv admin note: text overlap with arXiv:2307.00633

Light Dark Matter Constraints from SuperCDMS HVeV Detectors Operated Underground with an Anticoincidence Event Selection

Authors: SuperCDMS Collaboration, M. F. Albakry, I. Alkhatib, D. Alonso-González, D. W. P. Amaral, J. Anczarski, T. Aralis, T. Aramaki, I. J. Arnquist, I. Ataee Langroudy, E. Azadbakht, 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. Cerdeño, Y. -Y. Chang, M. Chaudhuri, J. -H. Chen , et al. (117 additional authors not shown)

Abstract: This article presents constraints on dark-matter-electron interactions obtained from the first underground data-taking campaign with multiple SuperCDMS HVeV detectors operated in the same housing. An exposure of 7.63 g-days is used to set upper limits on the dark-matter-electron scattering cross section for dark matter masses between 0.5 and 1000 MeV/$c^2$, as well as upper limits on dark photon k… ▽ More This article presents constraints on dark-matter-electron interactions obtained from the first underground data-taking campaign with multiple SuperCDMS HVeV detectors operated in the same housing. An exposure of 7.63 g-days is used to set upper limits on the dark-matter-electron scattering cross section for dark matter masses between 0.5 and 1000 MeV/$c^2$, as well as upper limits on dark photon kinetic mixing and axion-like particle axioelectric coupling for masses between 1.2 and 23.3 eV/$c^2$. Compared to an earlier HVeV search, sensitivity was improved as a result of an increased overburden of 225 meters of water equivalent, an anticoincidence event selection, and better pile-up rejection. In the case of dark-matter-electron scattering via a heavy mediator, an improvement by up to a factor of 25 in cross-section sensitivity was achieved. △ Less

Submitted 5 September, 2024; v1 submitted 10 July, 2024; originally announced July 2024.

Comments: 7 pages + title and references, 4 figures, and 1 table

Journal ref: Phys. Rev. D, 111 012006 (2025)

Emergence of superradiance in dissipative dipolar-coupled spin systems

Authors: Saptarshi Saha, Yeshma Ibrahim, Rangeet Bhattacharyya

Abstract: In the superradiance phenomenon, a collection of non-interacting atoms exhibits collective dissipation due to interaction with a common radiation field, resulting in a non-monotonic decay profile. This work shows that dissipative dipolar-coupled systems exhibit an identical collective dissipation aided by the nonsecular part of the dipolar coupling. We consider a simplified dipolar network where t… ▽ More In the superradiance phenomenon, a collection of non-interacting atoms exhibits collective dissipation due to interaction with a common radiation field, resulting in a non-monotonic decay profile. This work shows that dissipative dipolar-coupled systems exhibit an identical collective dissipation aided by the nonsecular part of the dipolar coupling. We consider a simplified dipolar network where the dipolar interaction between the spin-pairs is assumed to be identical. Hence the dynamics remain confined in the block diagonal Hilbert spaces. For a suitable choice of the initial condition, the resulting dynamics require dealing with a smaller subspace which helps extend the analysis to a larger spin network. To include the nonsecular dipolar relaxation, we use a fluctuation-regulated quantum master equation. We note that a successful observation of superradiance in this system requires a weak system-bath coupling. Moreover, we find that for an ensemble of N spins, the maximum intensity of the radiation exhibits a nearly quadratic scaling (N^2), and the dipolar relaxation time follows an inverse square proportionality (1/N^2); these two observations help characterize the emergence of superradiance. Our results agree well with the standard results of pure spin superradiance observed experimentally in various systems. △ Less

Submitted 13 June, 2024; originally announced June 2024.

Comments: 22 pages, 10 figures

Exploring the generation and annihilation of three dimensional nulls through MHD simulations in initially chaotic magnetic field devoid of nulls

Authors: Yogesh Kumar Maurya, Ramit Bhattacharyya, David I. Pontin, Sanjay Kumar

Abstract: Three-dimensional (3D) magnetic nulls are abundant in the solar atmosphere, as been firmly established through contemporary observations. They are established to be important magnetic structures in, for example, jets and circular ribbon flares. While simulations and extrapolations support this, the mechanisms behind 3D null generation remain an open question. Recent magnetohydrodynamics (MHD) simu… ▽ More Three-dimensional (3D) magnetic nulls are abundant in the solar atmosphere, as been firmly established through contemporary observations. They are established to be important magnetic structures in, for example, jets and circular ribbon flares. While simulations and extrapolations support this, the mechanisms behind 3D null generation remain an open question. Recent magnetohydrodynamics (MHD) simulations propose that magnetic reconnection is responsible for both generating and annihilating 3D nulls, a novel concept. However, these simulations began with initial magnetic fields already supporting pre-existing nulls, raising the question of whether magnetic reconnection can create nulls in fields initially devoid of them. Previously, this question was briefly explored in a simulation with an initial chaotic magnetic field. However, the study failed to precisely identify locations, topological degrees, and natures (spiral or radial) of nulls, and it approximated magnetic reconnection without fully tracking field line in time. In this paper these findings are revisited in light of recent advancements and tools used to locate and trace nulls, along with the tracing of field lines, through which the concept of generation/annihilation of 3D nulls from chaotic fields is established in a precise manner. △ Less

Submitted 10 June, 2024; originally announced June 2024.

Generation and annihilation of three dimensional magnetic nulls in extrapolated solar coronal magnetic field: Data-based Implicit Large Eddy Simulation

Authors: Yogesh Kumar Maurya, Ramit Bhattacharyya, David I. Pontin

Abstract: Three-dimensional magnetic nulls are the points where magnetic field vanishes and are preferential sites for magnetic reconnection: a process which converts magnetic energy into heat and accelerates charged particles along with a rearrangement of magnetic field lines. In the solar corona, the reconnections manifest as coronal transients including solar flares, coronal mass ejections and coronal je… ▽ More Three-dimensional magnetic nulls are the points where magnetic field vanishes and are preferential sites for magnetic reconnection: a process which converts magnetic energy into heat and accelerates charged particles along with a rearrangement of magnetic field lines. In the solar corona, the reconnections manifest as coronal transients including solar flares, coronal mass ejections and coronal jets. The nulls are generally found to be collocated with complex active regions on the solar photosphere. Extrapolation of magnetic field from corresponding photospheric magnetogram indicate an abundance of these nulls in solar atmosphere. Nevertheless, their generation is still not well understood. Recently, Maurya et al. (2023) have demonstrated magnetic reconnection to be a cause for generation and annihilation of magnetic nulls through magnetohydrodynamics simulation, where the initial magnetic field is idealized to have a single radial null. This article further extends the study in a more realistic scenario where the initial magnetic field is constructed by extrapolating photospheric magnetogram data and hence, incorporates field line complexities inherent to a complex active region. For the purpose, the active region NOAA 11977 hosting a C6.6 class flare is selected. The simulation is initiated using non-force-free extrapolated magnetic field from the photospheric vector magnetogram at around 02:48:00 UT on 17 February 2014, 16 minutes before the flare peak. The generation, annihilation and dynamics of nulls are explored by a complimentary usage of trilinear null detection technique and tracing of magnetic field line dynamics. It is found that the nulls can spontaneously generate/annihilate in pairs while preserving the topological degree and can have observational implications like footpoint brightenings. Magnetic reconnection is found to be the cause of such generation and annihilation. △ Less

Submitted 18 April, 2024; originally announced April 2024.

CC-VPSTO: Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation for Online Robot Motion Planning under Uncertainty

Authors: Lara Brudermüller, Guillaume Berger, Julius Jankowski, Raunak Bhattacharyya, Raphaël Jungers, Nick Hawes

Abstract: Reliable robot autonomy hinges on decision-making systems that account for uncertainty without imposing overly conservative restrictions on the robot's action space. We introduce Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation (CC-VPSTO), a real-time capable framework for generating task-efficient robot trajectories that satisfy constraints with high probability by formulatin… ▽ More Reliable robot autonomy hinges on decision-making systems that account for uncertainty without imposing overly conservative restrictions on the robot's action space. We introduce Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation (CC-VPSTO), a real-time capable framework for generating task-efficient robot trajectories that satisfy constraints with high probability by formulating stochastic control as a chance-constrained optimisation problem. Since such problems are generally intractable, we propose a deterministic surrogate formulation based on Monte Carlo sampling, solved efficiently with gradient-free optimisation. To address bias in naïve sampling approaches, we quantify approximation error and introduce padding strategies to improve reliability. We focus on three challenges: (i) sample-efficient constraint approximation, (ii) conditions for surrogate solution validity, and (iii) online optimisation. Integrated into a receding-horizon MPC framework, CC-VPSTO enables reactive, task-efficient control under uncertainty, balancing constraint satisfaction and performance in a principled manner. The strengths of our approach lie in its generality, i.e. no assumptions on the underlying uncertainty distribution, system dynamics, cost function, or the form of inequality constraints; and its applicability to online robot motion planning. We demonstrate the validity and efficiency of our approach in both simulation and on a Franka Emika robot. △ Less

Submitted 6 April, 2026; v1 submitted 2 February, 2024; originally announced February 2024.

Comments: 23 pages, 12 figures, submitted to International Journal of Robotics Research

Study of Reconnection Dynamics and Plasma Relaxation in MHD simulation of a Solar Flare

Authors: Satyam Agarwal, Ramit Bhattacharyya, Shangbin Yang

Abstract: Self-organization in continuous systems is associated with dissipative processes. In particular, for magnetized plasmas, it is known as magnetic relaxation, where the magnetic energy is converted into heat and kinetic energy of flow through the process of magnetic reconnection. An example of such a system is the solar corona, where reconnection manifests as solar transients like flares and jets. C… ▽ More Self-organization in continuous systems is associated with dissipative processes. In particular, for magnetized plasmas, it is known as magnetic relaxation, where the magnetic energy is converted into heat and kinetic energy of flow through the process of magnetic reconnection. An example of such a system is the solar corona, where reconnection manifests as solar transients like flares and jets. Consequently, toward investigation of plasma relaxation in solar transients, we utilize a novel approach of data-constrained MHD simulation for an observed solar flare. The selected active region NOAA 12253 hosts a GOES M1.3 class flare. The investigation of extrapolated coronal magnetic field in conjunction with the spatiotemporal evolution of the flare reveals a hyperbolic flux tube (HFT), overlying the observed brightenings. MHD simulation is carried out with the EULAG-MHD numerical model to explore the corresponding reconnection dynamics. The overall simulation shows signatures of relaxation. For a detailed analysis, we consider three distinct sub-volumes. We analyze the magnetic field line dynamics along with time evolution of physically relevant quantities like magnetic energy, current density, twist, and gradients in magnetic field. In the terminal state, none of the sub-volumes are seen to reach a force-free state, thus remaining in non-equilibrium, suggesting the possibility of further relaxation. We conclude that the extent of relaxation depends on the efficacy and duration of reconnection, and hence, on the energetics and time span of the flare. △ Less

Submitted 21 January, 2024; originally announced January 2024.

Prethermalization in an open quantum system coupled to a spatially correlated Bosonic bath

Authors: Saptarshi Saha, Rangeet Bhattacharyya

Abstract: A nearly-integrable isolated quantum many-body system reaches a quasi-stationary prethermal state before a late thermalization. Here, we revisit a particular example in the settings of an open quantum system. We consider a collection of non-interacting atoms coupled to a spatially correlated bosonic bath characterized by a bath correlation length. Our result implies that the integrability of the s… ▽ More A nearly-integrable isolated quantum many-body system reaches a quasi-stationary prethermal state before a late thermalization. Here, we revisit a particular example in the settings of an open quantum system. We consider a collection of non-interacting atoms coupled to a spatially correlated bosonic bath characterized by a bath correlation length. Our result implies that the integrability of the system depends on such a correlation length. If this length is much larger than the distance between the atoms, such a system behaves as a nearly integrable open quantum system. We study the properties of the emerging prethermal state for this case, i.e., the state's lifetime, the extensive numbers of existing quasi-conserved quantities, the emergence of the generalized Gibbs state, and the scaling of von Neumann entropy, etc. We find that for the prethermal state, the maximum growth of entropy is logarithmic with the number of atoms, whereas such growth is linear for the final steady state, which is the Gibbs state in this case. Finally, we discuss how such prethermal states can have significant applications in quantum entanglement storage devices. △ Less

Submitted 6 January, 2024; originally announced January 2024.

Testing Self-Reducible Samplers

Authors: Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote, Uddalok Sarkar, Sayantan Sen

Abstract: Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to find. Recently, in a series of works, testers like $\mathsf{Barbarik}$, $\mathsf{Teq}$, $\mathsf{Flash}$ for testing of some particular kinds of samplers, like CNF-samplers and Horn-samplers, were obtained. But their techn… ▽ More Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to find. Recently, in a series of works, testers like $\mathsf{Barbarik}$, $\mathsf{Teq}$, $\mathsf{Flash}$ for testing of some particular kinds of samplers, like CNF-samplers and Horn-samplers, were obtained. But their techniques have a significant limitation because one can not expect to use their methods to test for other samplers, such as perfect matching samplers or samplers for sampling linear extensions in posets. In this paper, we present a new testing algorithm that works for such samplers and can estimate the distance of a new sampler from a known sampler (say, uniform sampler). Testing the identity of distributions is the heart of testing the correctness of samplers. This paper's main technical contribution is developing a new distance estimation algorithm for distributions over high-dimensional cubes using the recently proposed sub-cube conditioning sampling model. Given subcube conditioning access to an unknown distribution $P$, and a known distribution $Q$ defined over $\{0,1\}^n$, our algorithm $\mathsf{CubeProbeEst}$ estimates the variation distance between $P$ and $Q$ within additive error $ζ$ using $O\left({n^2}/{ζ^4}\right)$ subcube conditional samples from $P$. Following the testing-via-learning paradigm, we also get a tester which distinguishes between the cases when $P$ and $Q$ are $\varepsilon$-close or $η$-far in variation distance with probability at least $0.99$ using $O({n^2}/{(η-\varepsilon)^4})$ subcube conditional samples. The estimation algorithm in the sub-cube conditioning sampling model helps us to design the first tester for self-reducible samplers. △ Less

Submitted 18 December, 2023; originally announced December 2023.

Comments: To be published in the 38th AAAI Conference on Artificial Intelligence (AAAI-24); Abstract shortened to meet with arxiv criteria

On local cohomology modules over ramified regular local rings

Authors: Rajsekhar Bhattacharyya

Abstract: In this paper, we show examples of local cohomology modules over ramified regular local ring, having finite set of associated primes. In doing so we consider our ramified regular local ring as Eisenstein extension of an unramified regular local ring sitting inside it and we use the Mayer-Vietoris spectral sequence to show the finiteness of the set of associated primes. In ramified regular local ri… ▽ More In this paper, we show examples of local cohomology modules over ramified regular local ring, having finite set of associated primes. In doing so we consider our ramified regular local ring as Eisenstein extension of an unramified regular local ring sitting inside it and we use the Mayer-Vietoris spectral sequence to show the finiteness of the set of associated primes. In ramified regular local ring for extended ideal (from the unramified one) set of associative primes of a local cohomology module is always finite. Using this result, for non extended ideal, we show example of local cohomology module which has finite set of associative primes and where associative primes also contains prime number $p$. △ Less

Submitted 8 April, 2024; v1 submitted 11 December, 2023; originally announced December 2023.

Comments: 5 pages, reference added

MSC Class: 13D45

RF-Enhanced Road Infrastructure for Intelligent Transportation

Authors: Dajiang Suo, Heyi Li, Rahul Bhattacharyya, Zijin Wang, Shengxuan Ding, Ou Zheng, Daniel Valderas, Joan Melià-Seguí, Mohamed Abdel-Aty, Sanjay E. Sarma

Abstract: The EPC GEN 2 communication protocol for Ultra-high frequency Radio Frequency Identification (RFID) has offered a promising avenue for advancing the intelligence of transportation infrastructure. With the capability of linking vehicles to RFID readers to crowdsource information from RFID tags on road infrastructures, the RF-enhanced road infrastructure (REI) can potentially transform data acquisit… ▽ More The EPC GEN 2 communication protocol for Ultra-high frequency Radio Frequency Identification (RFID) has offered a promising avenue for advancing the intelligence of transportation infrastructure. With the capability of linking vehicles to RFID readers to crowdsource information from RFID tags on road infrastructures, the RF-enhanced road infrastructure (REI) can potentially transform data acquisition for urban transportation. Despite its potential, the broader adoption of RFID technologies in building intelligent roads has been limited by a deficiency in understanding how the GEN 2 protocol impacts system performance under different transportation settings. This paper fills this knowledge gap by presenting the system architecture and detailing the design challenges associated with REI. Comprehensive real-world experiments are conducted to assess REI's effectiveness across various urban contexts. The results yield crucial insights into the optimal design of on-vehicle RFID readers and on-road RFID tags, considering the constraints imposed by vehicle dynamics, road geometries, and tag placements. With the optimized designs of encoding schemes for reader-tag communication and on-vehicle antennas, REI is able to fulfill the requirements of traffic sign inventory management and environmental monitoring while falling short of catering to the demand for high-speed navigation. In particular, the Miller 2 encoding scheme strikes the best balance between reading performance (e.g., throughput) and noise tolerance for the multipath effect. Additionally, we show that the on-vehicle antenna should be oriented to maximize the available time for reading on-road tags, although it may reduce the received power by the tags in the forward link. △ Less

Submitted 1 November, 2023; originally announced November 2023.

Onset and evolution of solar flares: Application of 2D and 3D models of magnetic reconnection

Authors: Bhuwan Joshi, Prabir K. Mitra, Astrid M. Veronig, R. Bhattacharyya

Abstract: The contemporary multi-wavelength observations have revealed various important features during solar flares which, on one hand, support the two-dimensional (2D) "standard flare model" while, on other hand, also urge for the exploration of three-dimensional (3D) magnetic field topologies involved in flares. Traditionally, the formation of parallel ribbons on both side of the polarity inversion line… ▽ More The contemporary multi-wavelength observations have revealed various important features during solar flares which, on one hand, support the two-dimensional (2D) "standard flare model" while, on other hand, also urge for the exploration of three-dimensional (3D) magnetic field topologies involved in flares. Traditionally, the formation of parallel ribbons on both side of the polarity inversion line (PIL) and associated overlying loop arcades have been recognized as the most prominent features of eruptive flares which has formed the basis for the development of the standard model providing a 2D description of the flare-associated phenomena. The actual flare, however, occurs in a more complicated 3D magnetic structure. Thus, despite the general applicability, the standard model has limited or no scope in explaining some of the features which exclusively requires a 3D description. In this context, the observations of "circular ribbon flares" stand out where one of the ribbons presents an almost fully closed quasi-circular or quasi-ellipsoidal shape, evidencing the involvement of a typical fan-spine magnetic configuration. In this article, we discuss observational features vis à vis theoretical understanding of solar flares in view of 2D and 3D models of magnetic reconnection. We highlight a few complex cases of circular ribbon flares exhibiting parallel ribbons, a coronal jet, and/or an erupting magnetic flux rope. Exploring various 3D topologies also enables us to probe similarities between the circumstances that govern the onset of jets, confined flares and CME-producing eruptive flares. △ Less

Submitted 30 September, 2023; originally announced October 2023.

Comments: 21 pages, 5 figures, invited review in the 3rd BINA workshop, to be published in the Bulletin of the Liège Royal Society of Sciences

Formation of an observed eruptive flux rope above the torus instability threshold through tether-cutting magnetic reconnection

Authors: Avijeet Prasad, Sanjay Kumar, Alphonse C. Sterling, Ronald L. Moore, Guillaume Aulanier, R. Bhattacharyya, Qiang Hu

Abstract: Erupting magnetic flux ropes (MFRs) play a crucial role in producing solar flares. However, the formation of erupting MFRs in complex coronal magnetic configurations and their subsequent evolution in the flaring events are not fully understood. We performed an MHD simulation of active region NOAA 12241 to understand the formation of a rising MFR during the onset of an M6.9 flare on 2014 December 1… ▽ More Erupting magnetic flux ropes (MFRs) play a crucial role in producing solar flares. However, the formation of erupting MFRs in complex coronal magnetic configurations and their subsequent evolution in the flaring events are not fully understood. We performed an MHD simulation of active region NOAA 12241 to understand the formation of a rising MFR during the onset of an M6.9 flare on 2014 December 18, around 21:41 UT. The MHD simulation was initialised with an extrapolated non-force-free magnetic field generated from the photospheric vector magnetogram of the active region taken a few minutes before the flare. The initial magnetic field topology displays a pre-existing sheared arcade enveloping the polarity inversion line. The simulated dynamics exhibit the movement of the oppositely directed legs of the sheared arcade field lines towards each other due to the converging Lorentz force, resulting in the onset of tether-cutting magnetic reconnection that produces an underlying flare arcade and flare ribbons. Concurrently, an MFR above the flare arcade develops inside the sheared arcade and shows a rising motion. The MFR is found to be formed in a torus-unstable region, thereby explaining its eruptive nature. Interestingly, the location and rise of the rope are in good agreement with the corresponding observations seen in EUV channels. Furthermore, the foot points of the simulation's flare arcade match well with the location of the observed parallel ribbons of the flare. The presented simulation supports the development of the MFR by the tether-cutting magnetic reconnection inside the sheared coronal arcade during flare onset. The MFR is then found to extend along the polarity inversion line (PIL) through slip-running reconnection. The MFR's eruptive nature is ascribed both to its formation in the torus-unstable region and also to the runaway tether-cutting reconnection. △ Less

Submitted 13 July, 2023; originally announced July 2023.

Comments: 12 pages, 8 figures, accepted for publication in Astronomy & Astrophysics

Journal ref: A&A 677, A43 (2023)

Magnetohydrodynamics simulation of magnetic flux rope formation in a quadrupolar magnetic field configuration

Authors: Sanjay Kumar, Avijeet Prasad, Sushree S. Nayak, Satyam Agarwal, R. Bhattacharyya

Abstract: Magnetic flux ropes (MFRs) play an important role in high-energetic events like solar flares and coronal mass ejections in the solar atmosphere. Importantly, solar observations suggest an association of some flaring events with quadrupolar magnetic configurations. However, the formation and subsequent evolution of MFRs in such magnetic configurations still need to be fully understood. In this pape… ▽ More Magnetic flux ropes (MFRs) play an important role in high-energetic events like solar flares and coronal mass ejections in the solar atmosphere. Importantly, solar observations suggest an association of some flaring events with quadrupolar magnetic configurations. However, the formation and subsequent evolution of MFRs in such magnetic configurations still need to be fully understood. In this paper, we present idealized magnetohydrodynamics (MHD) simulations of MFR formation in a quadrupolar magnetic configuration. A suitable initial magnetic field having a quadrupolar configuration is constructed by modifying a three-dimensional (3D) linear force-free magnetic field. The initial magnetic field contains neutral lines, which consist of X-type null points. The simulated dynamics initially demonstrate the oppositely directed magnetic field lines located across the polarity inversion lines (PILs) moving towards each other, resulting in magnetic reconnections. Due to these reconnections, four highly twisted MFRs form over the PILs. With time, the foot points of the MFRs move towards the X-type neutral lines and reconnect, generating complex magnetic structures around the neutral lines, thus making the MFR topology more complex in the quadrupolar configuration than those formed in bipolar loop systems. Further evolution reveals the non-uniform rise of the MFRs. Importantly, the simulations indicate that the pre-existing X-type null points in magnetic configurations can be crucial to the evolution of the MFRs and may lead to the observed brightenings during the onset of some flaring events in the quadrupolar configurations. △ Less

Submitted 12 July, 2023; originally announced July 2023.

Comments: 18 pages, 9 figures

Journal ref: Plasma Phys. Control. Fusion 2023 65 085008

Effects of Explanation Specificity on Passengers in Autonomous Driving

Authors: Daniel Omeiza, Raunak Bhattacharyya, Nick Hawes, Marina Jirotka, Lars Kunze

Abstract: The nature of explanations provided by an explainable AI algorithm has been a topic of interest in the explainable AI and human-computer interaction community. In this paper, we investigate the effects of natural language explanations' specificity on passengers in autonomous driving. We extended an existing data-driven tree-based explainer algorithm by adding a rule-based option for explanation ge… ▽ More The nature of explanations provided by an explainable AI algorithm has been a topic of interest in the explainable AI and human-computer interaction community. In this paper, we investigate the effects of natural language explanations' specificity on passengers in autonomous driving. We extended an existing data-driven tree-based explainer algorithm by adding a rule-based option for explanation generation. We generated auditory natural language explanations with different levels of specificity (abstract and specific) and tested these explanations in a within-subject user study (N=39) using an immersive physical driving simulation setup. Our results showed that both abstract and specific explanations had similar positive effects on passengers' perceived safety and the feeling of anxiety. However, the specific explanations influenced the desire of passengers to takeover driving control from the autonomous vehicle (AV), while the abstract explanations did not. We conclude that natural language auditory explanations are useful for passengers in autonomous driving, and their specificity levels could influence how much in-vehicle participants would wish to be in control of the driving activity. △ Less

Submitted 2 July, 2023; originally announced July 2023.

Emergence and stability of discrete time-crystalline phases in open quantum systems

Authors: Saptarshi Saha, Rangeet Bhattacharyya

Abstract: Here we provide a theoretical framework to analyze discrete time-crystalline phases (DTC) in open quantum many-body systems. As a particular realization, we choose a quantum many-body system that exhibits cascaded prethermalization . The analysis uses a fluctuation-regulated quantum master equation. The master equation captures the dissipative effects of the drive and dipolar coupling on the dynam… ▽ More Here we provide a theoretical framework to analyze discrete time-crystalline phases (DTC) in open quantum many-body systems. As a particular realization, we choose a quantum many-body system that exhibits cascaded prethermalization . The analysis uses a fluctuation-regulated quantum master equation. The master equation captures the dissipative effects of the drive and dipolar coupling on the dynamics regularized by the thermal fluctuations. We find that the dissipators from the drive and the dipolar interactions lend stability to the dynamics and are directly responsible for the robustness. Specifically, we find that longer fluctuation correlation time enhances the stability of DTC. Our results are in good agreement with the experiments. Finally, we show and quantify how the DTC performance degrades with temperature. △ Less

Submitted 31 August, 2023; v1 submitted 26 June, 2023; originally announced June 2023.

Comments: 13 pages, 6 figures

Anomalous Aharonov-Bohm Interference in the Presence of Edge Reconstruction

Authors: Sourav Biswas, Hemanta Kumar Kundu, Rajarshi Bhattacharyya, Vladimir Umansky, Moty Heiblum

Abstract: Interferometry is a vital tool for studying fundamental features in the quantum Hall effect (QHE). For instance, Aharonov-Bohm (AB) interference in a quantum Hall interferometer can probe the wave-particle duality of electrons and quasiparticles. Here, we report an unusual AB interference in a quantum Hall Fabry-Pérot interferometer (FPI), whose Coulomb interactions were suppressed with a grounded… ▽ More Interferometry is a vital tool for studying fundamental features in the quantum Hall effect (QHE). For instance, Aharonov-Bohm (AB) interference in a quantum Hall interferometer can probe the wave-particle duality of electrons and quasiparticles. Here, we report an unusual AB interference in a quantum Hall Fabry-Pérot interferometer (FPI), whose Coulomb interactions were suppressed with a grounded drain in the interior bulk of the FPI. In a descending filling factor from $ν=3$ to $ν\approx5/3$, the magnetic field periodicity, which corresponded to a single 'flux quantum,' agreed accurately with the enclosed area of the FPI. However, in the filling range, $ν\approx5/3$ to $ν=1$, the field periodicity increased markedly, apriori suggesting a drastic shrinkage of the AB area. Moreover, the modulation gate voltage periodicity decreased abruptly at this range. We attribute these unexpected observations to a ubiquitous edge reconstruction, leading to dynamical area changing with the field and a modified modulation gate-edge capacitance. These results are reproducible and support future interference experiments with a QHE-FPI. △ Less

Submitted 5 June, 2023; originally announced June 2023.

Comments: 23 pages, 12 figures, Supplementary Information

Journal ref: Physical Review Letters 132, 076301 (2024)

Hall effect on the magnetic reconnections during the evolution of a three-dimensional magnetic flux rope

Authors: Kamlesh Bora, Satyam Agarwal, Sanjay Kumar, Ramit Bhattacharyya

Abstract: We present a novel Hall magnetohydrodynamics (HMHD) numerical simulation of a three-dimensional (3D) magnetic flux rope (MFR) -- generated by magnetic reconnections from an initial 3D bipolar sheared field. Magnetic reconnections during the HMHD evolution are compared with the MHD. In both simulations, the MFRs generate as a consequence of the magnetic reconnection at null points which has not bee… ▽ More We present a novel Hall magnetohydrodynamics (HMHD) numerical simulation of a three-dimensional (3D) magnetic flux rope (MFR) -- generated by magnetic reconnections from an initial 3D bipolar sheared field. Magnetic reconnections during the HMHD evolution are compared with the MHD. In both simulations, the MFRs generate as a consequence of the magnetic reconnection at null points which has not been realized in contemporary simulations. Interestingly, the evolution is faster and more intricate in the HMHD simulation. Repetitive development of the twisted magnetic field lines (MFL) in the vicinity of 3D nulls (reconnection site) is unique to the HMHD evolution of the MFR. The dynamical evolution of magnetic field lines around the reconnection site being affected by the Hall forcing, correspondingly affects the large-scale structures. △ Less

Submitted 19 May, 2023; originally announced May 2023.

Comments: Accepted for publication in Physica Scripta

MilliKelvin microwave impedance microscopy in a dry dilution refrigerator

Authors: Leonard Weihao Cao, Chen Wu, Rajarshi Bhattacharyya, Ruolun Zhang, Monica T. Allen

Abstract: Microwave impedance microscopy (MIM) is a near-field imaging technique that has been used to visualize the local conductivity of materials with nanoscale resolution across the GHz regime. In recent years, MIM has shown great promise for the investigation of topological states of matter, correlated electronic states and emergent phenomena in quantum materials. To explore these low-energy phenomena,… ▽ More Microwave impedance microscopy (MIM) is a near-field imaging technique that has been used to visualize the local conductivity of materials with nanoscale resolution across the GHz regime. In recent years, MIM has shown great promise for the investigation of topological states of matter, correlated electronic states and emergent phenomena in quantum materials. To explore these low-energy phenomena, many of which are only detectable in the milliKelvin regime, we have developed a novel low-temperature MIM incorporated into a dilution refrigerator. This setup which consists of a tuning-fork-based atomic force microscope with microwave reflectometry capabilities, is capable of reaching temperatures down to 70 mK during imaging and magnetic fields up to 9 T. To test the performance of this microscope, we demonstrate microwave imaging of the conductivity contrast between graphite and silicon dioxide at cryogenic temperatures and discuss the resolution and noise observed in these results. We extend this methodology to visualize edge conduction in Dirac semimetal cadmium arsenide in the quantum Hall regime △ Less

Submitted 29 September, 2023; v1 submitted 5 May, 2023; originally announced May 2023.

Comments: This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Review of Scientific Instruments and may be found at doi.org/10.1063/5.0159548

Journal ref: Volume 94, Issue 9, Year 2023

First measurement of the nuclear-recoil ionization yield in silicon at 100 eV

Authors: M. F. Albakry, I. Alkhatib, D. Alonso, D. W. P. Amaral, P. An, T. Aralis, T. Aramaki, I. J. Arnquist, I. Ataee Langroudy, E. Azadbakht, S. Banik, P. S. Barbeau, C. Bathurst, R. Bhattacharyya, P. L. Brink, R. Bunker, B. Cabrera, R. Calkins, R. A. Cameron, C. Cartaro, D. G. Cerdeño, Y. -Y. Chang, M. Chaudhuri, R. Chen, N. Chott , et al. (115 additional authors not shown)

Abstract: We measured the nuclear--recoil ionization yield in silicon with a cryogenic phonon-sensitive gram-scale detector. Neutrons from a mono-energetic beam scatter off of the silicon nuclei at angles corresponding to energy depositions from 4\,keV down to 100\,eV, the lowest energy probed so far. The results show no sign of an ionization production threshold above 100\,eV. These results call for furthe… ▽ More We measured the nuclear--recoil ionization yield in silicon with a cryogenic phonon-sensitive gram-scale detector. Neutrons from a mono-energetic beam scatter off of the silicon nuclei at angles corresponding to energy depositions from 4\,keV down to 100\,eV, the lowest energy probed so far. The results show no sign of an ionization production threshold above 100\,eV. These results call for further investigation of the ionization yield theory and a comprehensive determination of the detector response function at energies below the keV scale. △ Less

Submitted 3 March, 2023; originally announced March 2023.

Journal ref: Physical Review Letters 131.9 (2023): 091801