arXiv subjects

Abhishek Roy

Publications and source records attributed to Abhishek Roy.

At least 19 recordsLinked to original sources

arXiv2026

Observing relativistic trajectories of single photons

While the standard interpretation of quantum mechanics does not assign definite trajectories to particles, the Bohmian interpretation does. Only recently has an operational method for reconciling Bohmian mechanics with relativity been proposed. Here, we experimentally reconstruct relativistic Bohmian trajectories of a single photon in a Michelson-Sagnac interferometer, where counter-propagating probability amplitudes interfere head-on at the speed of light. As predicted by the relativistic Bohmian theory, we observe subluminal and superluminal features of the Bohmian trajectories of the photon traversing through the fringes. Our work provides experimental access to relativistic Bohmian mechanics and enables exploration of its unusual and counterintuitive properties.

quant-ph↗

arXiv2026

Photonic Quantum-Accelerated Machine Learning

Machine learning is widely applied in modern society, but has yet to capitalise on the unique benefits offered by quantum resources. Boson sampling -- a quantum-interference based sampling protocol -- is a resource that is classically hard to simulate and can be implemented on current quantum hardware. Here, we present a quantum accelerator for classical machine learning, using boson sampling to provide a high-dimensional quantum fingerprint for reservoir computing. We show robust performance improvements under various conditions: imperfect photon sources down to complete distinguishability; scenarios with severe class imbalances, classifying both handwritten digits and biomedical images; and sparse data, maintaining model accuracy with twenty times less training data. Crucially, we demonstrate the acceleration of our scheme on a photonic quantum processing unit, providing experimental validation that boson-sampling-enhanced learning with Fock states delivers real performance gains on actual quantum hardware.

quant-ph↗

arXiv2026

Dark Photon mediated Inelastic Dark Matter in Cosmology, Astrophysics and Colliders

We explore the phenomenology of Dark Photon iDM (A$^{\prime}$iDM) where the Standard Model (SM) is extended by a dark sector containing an additional $U(1)_D$ gauge symmetry under which all SM particles are neutral, and that couples to the SM hypercharge gauge boson through a kinetic mixing parameter $ε$. The model contains two Majorana states $χ_1$ and $χ_2$ with $δ=M_{χ_2}-M_{χ_1}>0$ and $χ_1$ the dark matter candidate, and a dark photon $A^{\prime}$ with mass $M_{A^{\prime}}$. Our analysis represents an integration of existing ones, where only specific benchmarks of the A$^{\prime}$iDM scenario have been discussed. In particular, we fix the $U(1)_D$ coupling $α_D$ equal to the electromagnetic one $α_{EM}$ and $ε$ to its experimental upper bound, and perform a complete scan of the remaining parameters $(M_{χ_1},δ, M_{A^{\prime}})$, discussing the $χ_1$ relic abundance, its direct and indirect searches, as well as potential signals from astrophysics and accelerators. Our scan shows that $α_D$ = $α_{EM}$ is not disfavored, as some previous analyses, limited to specific benchmarks, may suggest. We also find that when the $χ_1$ relic density matches observation direct and indirect searches are not kinematically accessible. On the other hand we find that the projected luminosity of FASER, a detector searching for Long Lived Particles (LLP) decay at the LHC, can probe or rule out the parameters space of the model for $M_{χ_1}\lesssim$ 7 GeV, 100 MeV $\lesssim δ\lesssim$ 300 MeV and $M_{A^{\prime}}\lesssim$ 25 GeV. This range of parameter could be significantly extended by the FASER 2 upgrade proposed for the High-Luminosity phase at the LHC. The parameter space probed by LLP seaches partially overlaps with that probed by $χ_1$ capture in neutron stars.

hep-ph↗

arXiv2026

Deterring Searches for Child Sexual Abuse Material on Google Search and Promoting Help-Seeking

Google Search deploys a "Onebox" feature at the top of the results page when users conduct searches for Child Sexual Abuse Material. This study evaluates the impact of a strategic shift in this feature, comparing a revised intervention, focused on repercussions and therapeutic resources, to a previous iteration that focused on reporting. Using a difference-in-differences analysis of internal Google Search logs data, we found the new messaging resulted in a 3.8 percentage point reduction as compared to the status quo in subsequent CSAM-related queries within the same Search session. We found an average click through rate of 0.73% on any of the hyperlinked buttons to help-providing resources. Together, this research presents convergent evidence that a subset of individuals can be deterred from ongoing CSAM-seeking and redirected to therapeutic services.

cs.HC↗

arXiv2026

Probing Inelastic Dark Matter via Cosmic-Ray Upscattering in NGC 1068

We study constraints on sub-GeV inelastic dark matter (iDM) from cosmic-ray (CR) cooling in the active galactic nucleus (AGN) NGC 1068. In dense dark matter (DM) spikes surrounding supermassive black holes, high-energy CR protons can efficiently lose energy through scatterings with dark matter particles. We consider a minimal vector-portal iDM framework and consistently include both elastic and deep inelastic scattering (DIS) contributions to the CR energy-loss rate. We find that DIS processes dominate at high momentum transfer and substantially enhance the DM-induced cooling effect. By requiring the resulting cooling timescale to remain compatible with the observed Standard Model cooling in NGC 1068, we derive constraints on the iDM parameter space. Our results demonstrate that AGN cosmic-ray cooling probes previously unexplored regions of sub-GeV iDM parameter space inaccessible to current direct-detection experiments.

hep-ph↗

arXiv2026

Evaluating Language Models for Harmful Manipulation

Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a framework for evaluating harmful AI manipulation via context-specific human-AI interaction studies. We illustrate the utility of this framework by assessing an AI model with 10,101 participants spanning interactions in three AI use domains (public policy, finance, and health) and three locales (US, UK, and India). Overall, we find that that the tested model can produce manipulative behaviours when prompted to do so and, in experimental settings, is able to induce belief and behaviour changes in study participants. We further find that context matters: AI manipulation differs between domains, suggesting that it needs to be evaluated in the high-stakes context(s) in which an AI system is likely to be used. We also identify significant differences across our tested geographies, suggesting that AI manipulation results from one geographic region may not generalise to others. Finally, we find that the frequency of manipulative behaviours (propensity) of an AI model is not consistently predictive of the likelihood of manipulative success (efficacy), underscoring the importance of studying these dimensions separately. To facilitate adoption of our evaluation framework, we detail our testing protocols and make relevant materials publicly available. We conclude by discussing open challenges in evaluating harmful manipulation by AI models.

cs.AI↗

arXiv2026

"It didn't feel right but I needed a job so desperately": Understanding People's Emotions & Help Needs During Financial Scams

Online financial scams represent a long-standing and serious threat for which people seek help. We present a study to understand people's in situ motivations for engaging with scams and the help needs they express before, during, and after encountering a scam. We identify the main emotions scammers exploited (e.g., fear, hope) and characterize how they did so. We examine factors -- such as financial insecurity and legal precarity -- which elevate people's risk of engaging with specific scams and experiencing harm. We indicate when people sought help and describe their help-seeking needs and emotions at different stages of the scam. We discuss how these needs could be met through the design of contextually-specific prevention, diagnostic, mitigation, and recovery interventions.

cs.HC↗

arXiv2026

Scrutinizing Fermionic Dark Matter in Scotogenic Model with Low Reheating Temperature

The scotogenic model provides a minimal and elegant framework that simultaneously explains neutrino masses and accommodates a viable dark matter (DM) candidate. In this work, we investigate the phenomenology of fermionic DM in the scotogenic model, with a particular emphasis on the effects of a non-standard cosmological history characterized by a low reheating temperature. We demonstrate that entropy injection from inflaton decay can significantly dilute the DM abundance, thereby relaxing the annihilation cross section required to reproduce the observed relic density and opening new regions of viable parameter space. We further analyze the complementarity between current and future direct detection experiments and charged lepton flavour violation (cLFV) searches in probing this scenario. Our results show that next-generation direct detection experiments such as DARWIN and XLZD, together with upcoming cLFV searches (in particular the future sensitivity of $μ\rightarrow 3e$ and $μ\rightarrow e$ conversion experiments), will be capable of testing substantial regions of the parameter space, including those associated with low reheating temperatures.

hep-ph↗

arXiv2026

Resurrecting Kaluza-Klein Dark Matter with Low-Temperature Reheating

In Universal Extra Dimension (UED) scenarios, the lightest Kaluza-Klein (KK) particle is naturally stable due to a remnant discrete symmetry, KK parity, arising from extra-dimensional compactification. This stability requires no ad hoc symmetry and renders Kaluza-Klein dark matter a well-motivated candidate, provided it reproduces the observed relic abundance. The minimal UED (mUED) framework being highly predictive is strongly constrained by the combined requirements of relic density and collider searches under standard cosmological assumptions. We revisit the dark matter phenomenology of mUED in the presence of a nonstandard cosmological history featuring a low reheating temperature driven by prolonged inflaton decay. Solving the coupled Boltzmann equations for dark matter, radiation, and inflaton energy densities, we show that entropy injection during reheating can dilute the relic abundance by orders of magnitude, reopening large regions of parameter space previously ruled out. We further demonstrate that the revived parameter space is consistent with current collider, direct-detection, and indirect-detection constraints, while remaining testable by upcoming experiments.

hep-ph↗

arXiv2026

Riemannian Dueling Optimization

Dueling optimization considers optimizing an objective with access to only a comparison oracle of the objective function. It finds important applications in emerging fields such as recommendation systems and robotics. Existing works on dueling optimization mainly focused on unconstrained problems in the Euclidean space. In this work, we study dueling optimization over Riemannian manifolds, which covers important applications that cannot be solved by existing dueling optimization algorithms. In particular, we propose a Riemannian Dueling Normalized Gradient Descent (RDNGD) method and establish its iteration complexity when the objective function is geodesically L-smooth or geodesically (strongly) convex. We also propose a projection-free algorithm, named Riemannian Dueling Frank-Wolfe (RDFW) method, to deal with the situation where projection is prohibited. We establish the iteration and oracle complexities for RDFW. We illustrate the effectiveness of the proposed algorithms through numerical experiments on both synthetic and real applications.

math.OC↗

arXiv2026

Illuminating Scalar Dark Matter Co-Scattering in EFT with Monophoton Signatures

We investigate the co-scattering mechanism for dark matter production in an EFT framework which contains new $Z_2$-odd singlets, namely two fermions $N_{1,2}$ and a real scalar $χ$. The singlet scalar $χ$ is the dark matter candidate. The dimension-5 operators play a vital role to set the observed DM relic density. We focus on a nearly degenerate mass spectrum for the $Z_2$ odd particles to allow for a significant contribution from the co-scattering or co-annihilation mechanisms. We present two benchmark points where either of the two mechanisms primarily set the DM relic abundance. The main constraint on the model at the LHC arise from the ATLAS mono-$γ$ search. We obtain the parameter space allowed by the observed relic density and the mono-$γ$ search after performing a scan over the key parameters, the masses $M_{N_{1,2}}, M_χ$ and couplings $c_3^\prime, y^\prime_{11,22}$. We find the region of parameter space where the relic abundance is set primarily by the co-scattering mechanism while being allowed by the LHC search. We also determine how the model can be further probed at the HL-LHC via the mono-$γ$ signature.

hep-ph↗

arXiv2025

Acceleration via silver step-size on Riemannian manifolds with applications to Wasserstein space

There is extensive literature on accelerating first-order optimization methods in a Euclidean setting. Under which conditions such acceleration is feasible in Riemannian optimization problems is an active area of research. Motivated by the recent success of dynamic stepsize methods in the Euclidean setting, we undertake a study of such algorithms in the Riemannian setting. We provide the new class of algorithms determined by the choice of vector transport that allows the dynamic stepsize acceleration on Riemannian manifolds for the function classes associated with the corresponding vector transport. As a core application, we show our algorithm recovers the standard Wasserstein gradient descent on 2-Wasserstein space, and as a result provides the first provable accelerated gradient method in Wasserstein space. In addition, we validate the numerical strength of the algorithm for standard benchmark tasks on the space of symmetric positive definite matrices.

math.OC↗

arXiv2025

Construction of 2-D Z-Complementary Array Code Sets with Flexible Lengths for Different System Requirements

In this paper, we propose a new and optimal construction of two-dimensional (2-D) Z-complementary array code set (ZCACS) using multivariable extended Boolean functions (EBFs). The proposed 2-D arrays have many applications in modern wireless communications, such as multi-carrier code division multiple access (MC-CDMA), massive multiple input multiple output (mMIMO), etc. The main theoretical problem for sequences and 2-D arrays for application in MC-CDMA lies in the efficient construction of such sequences and arrays, which have low peak-to-mean envelope power ratio (PMEPR) and flexible parameter values. The PMEPR measures the power efficiency of the concerned system and hence has been an important research topic for past several years. The proposed construction produces a better PMEPR upper bound than the existing constructions. We also propose a tighter upper bound for the set size which translates more number of supported users in the communication system. We show that for some special cases, the proposed code set is optimal with respect to that bound. Finally, We derive 2-D Golay complementary array set (GCAS) and Golay complementary set (GCS) from the proposed construction, which has significant application in uniform rectangular array (URA)-based massive multiple-input multiple-output (mMIMO) system to achieve omnidirectional transmission. The simulation result shows the performance benefits of the derived arrays. In essence, we show that the flexibility of the parameters of the proposed 2-D ZCACS makes it a good candidate for practical use cases, both in theory and simulation.

cs.IT↗

arXiv2025

Online Covariance Estimation in Nonsmooth Stochastic Approximation

We consider applying stochastic approximation (SA) methods to solve nonsmooth variational inclusion problems. Existing studies have shown that the averaged iterates of SA methods exhibit asymptotic normality, with an optimal limiting covariance matrix in the local minimax sense of Hájek and Le Cam. However, no methods have been proposed to estimate this covariance matrix in a nonsmooth and potentially non-monotone (nonconvex) setting. In this paper, we study an online batch-means covariance matrix estimator introduced in Zhu et al.(2023). The estimator groups the SA iterates appropriately and computes the sample covariance among batches as an estimate of the limiting covariance. Its construction does not require prior knowledge of the total sample size, and updates can be performed recursively as new data arrives. We establish that, as long as the batch size sequence is properly specified (depending on the stepsize sequence), the estimator achieves a convergence rate of order $O(\sqrt{d}n^{-1/8+\varepsilon})$ for any $\varepsilon>0$, where $d$ and $n$ denote the problem dimensionality and the number of iterations (or samples) used. Although the problem is nonsmooth and potentially non-monotone (nonconvex), our convergence rate matches the best-known rate for covariance estimation methods using only first-order information in smooth and strongly-convex settings. The consistency of this covariance estimator enables asymptotically valid statistical inference, including constructing confidence intervals and performing hypothesis testing.

stat.ML↗

arXiv2025

ShieldUp!: Inoculating Users Against Online Scams Using A Game Based Intervention

Online scams are a growing threat in India, impacting millions and causing substantial financial losses year over year. This white paper presents ShieldUp!, a novel mobile game prototype designed to inoculate users against common online scams by leveraging the principles of psychological inoculation theory. ShieldUp! exposes users to weakened versions of manipulation tactics frequently used by scammers, and teaches them to recognize and pre-emptively refute these techniques. A randomized controlled trial (RCT) with 3,000 participants in India was conducted to evaluate the game's efficacy in helping users better identify scams scenarios. Participants were assigned to one of three groups: the ShieldUp! group (play time: 15 min), a general scam awareness group (watching videos and reading tips for 10-15 min), and a control group (plays "Chrome Dino", an unrelated game, for 10 minutes). Scam discernment ability was measured using a newly developed Scam Discernment Ability Test (SDAT-10) before the intervention, immediately after, and at a 21-day follow-up. Results indicated that participants who played ShieldUp! showed a significant improvement in their ability to identify scams compared to both control groups, and this improvement was maintained at follow-up. Importantly, while both interventions initially led users to to show increased skepticism towards even genuine online offers (NOT Scam scenarios), this effect dissipated after 21 days, suggesting no long-term negative impact on user trust. This study demonstrates the potential of game-based inoculation as a scalable and effective scam prevention strategy, offering valuable insights for product design, policy interventions, and future research, including the need for longitudinal studies and cross-cultural adaptations.

cs.HC↗

arXiv2025

Systematic Construction of Golay Complementary Sets of Arbitrary Lengths and Alphabet Sizes

One of the important applications of Golay complementary sets (GCSs) is the reduction of peak-to-mean envelope power ratio (PMEPR) in orthogonal frequency division multiplexing (OFDM) systems. OFDM has played a major role in modern wireless systems such as long-term-evolution (LTE), 5th generation (5G) wireless standards, etc. This paper searches for systematic constructions of GCSs of arbitrary lengths and alphabet sizes. The proposed constructions are based on extended Boolean functions (EBFs). For the first time, we can generate codes of independent parameter choices.

cs.IT↗

arXiv2024

Revisiting the decoupling limit of the Georgi-Machacek model with a scalar singlet

We study the connection between collider and dark matter phenomenology in the singlet extension of the Georgi-Machacek model. In this framework, the singlet scalar serves as a suitable thermal dark matter (DM) candidate. Our focus lies on the region $v_χ<1$ GeV, where $v_χ$ is the common vacuum expectation value of the neutral components of the scalar triplets of the model. Setting bounds on the model parameters from theoretical, electroweak precision and LHC experimental constraints, we find that the BSM Higgs sector is highly constrained. Allowed values for the masses of the custodial fiveplets, triplets and singlet are restricted to the range $140~ {\rm GeV }< M_{H_5} < 350~ {\rm GeV }$, $150~ {\rm GeV }< M_{H_3} < 270 ~{\rm GeV }$ and $145~ {\rm GeV }< M_{H} < 300~ {\rm GeV }$. The extended scalar sector provides new channels for DM annihilation into BSM scalars that allow to satisfy the observed relic density constraint while being consistent with direct DM detection limits. The allowed region of the parameter space of the model can be explored in the upcoming DM detection experiments, both direct and indirect. In particular, the possible high values of BR$(H^0_5\toγγ)$ can lead to an indirect DM signal within the reach of CTA. The same feature also provides the possibility of exploring the model at the High-Luminosity run of the LHC. In a simple cut-based analysis, we find that a signal of about $4σ$ significance can be achieved in final states with at least two photons for one of our benchmark points.

hep-ph↗

arXiv2024

A Survey of Scam Exposure, Victimization, Types, Vectors, and Reporting in 12 Countries

Scams are a widespread issue with severe consequences for both victims and perpetrators, but existing data collection is fragmented, precluding global and comparative local understanding. The present study addresses this gap through a nationally representative survey (n = 8,369) on scam exposure, victimization, types, vectors, and reporting in 12 countries: Belgium, Egypt, France, Hungary, Indonesia, Mexico, Romania, Slovakia, South Africa, South Korea, Sweden, and the United Kingdom. We analyze 6 survey questions to build a detailed quantitative picture of the scams landscape in each country, and compare across countries to identify global patterns. We find, first, that residents of less affluent countries suffer financial loss from scams more often. Second, we find that the internet plays a key role in scams across the globe, and that GNI per-capita is strongly associated with specific scam types and contact vectors. Third, we find widespread under-reporting, with residents of less affluent countries being less likely to know how to report a scam. Our findings contribute valuable insights for researchers, practitioners, and policymakers in the online fraud and scam prevention space.

cs.CY↗