arXiv subjects

Martin Andersson

Publications and source records attributed to Martin Andersson.

At least 19 recordsLinked to original sources

arXiv2026

Leveraging Slowly Time-Varying AP-AP Channels for Interference Mitigation in Dynamic TDD

We address the challenge of cross-link interference in dynamic time-division duplexing (TDD) systems. Specifically, we focus on mitigating the interference caused by access points (APs) operating in downlink to APs operating in uplink. To this end, we exploit that channels between APs typically vary much more slowly over time than channels between users and APs. This observation allows us to jointly estimate the uplink user data and the AP-AP channels using a least-squares formulation over multiple coherence intervals, during which the AP-AP channels stay constant. We derive conditions for unique solvability of this least-squares problem by analyzing the rank of the regression matrix. For cases where a unique solution does not exist, we propose to transform the problem into a uniquely solvable one by sacrificing a subset of the uplink data samples. Numerical results demonstrate that our proposed methods achieve substantial gains over baseline algorithms. Further, we observe that one of our proposed algorithms achieves almost perfect AP-AP interference mitigation when the AP-AP channels vary very slowly over time.

eess.SP↗

arXiv2025

Gauge-Invariant Long-Wavelength TDDFT Without Empty States: From Polarizability to Kubo Conductivity Across Heterogeneous Materials

Electromagnetic response is commonly computed in two languages: length-gauge molecular polarizabilities and velocity-gauge (Kubo) conductivities for periodic solids. We introduce a compact, gauge-invariant bridge that carries the same microscopic inputs-transition dipoles and interaction kernels-from molecules to crystals and heterogeneous media, with explicit SI prefactors and fine-structure scaling via $(\alpha_{\rm fs})$. The long-wavelength limit is handled through a reduced dielectric matrix that retains local-field mixing, interfaces and 2D layers are treated with sheet boundary conditions (rather than na\"ive ultrathin films), and length-velocity equivalence is enforced in practice by including the equal-time (diamagnetic/contact) term alongside the paramagnetic current. Finite temperature is addressed on the Matsubara axis with numerically stable real-axis evaluation (complex polarization propagator), preserving unit consistency end-to-end. The framework enables predictive, unit-faithful observables from radio frequency to ultraviolet-RF/microwave heating and penetration depth, dielectric-logging contrast, interfacial optics of thin films and 2D sheets, and adsorption metrics via imaginary-axis polarizabilities. Numerical checks (gauge overlay and optical $(f)$-sum saturation) validate the implementation. Immediate priorities include compact, temperature- and salinity-aware kernels with quantified uncertainties and \emph{operando} interfacial diagnostics for integration into multiphysics digital twins.

cond-mat.mtrl-sci↗

arXiv2025

Concentration bounds for intrinsic dimension estimation using Gaussian kernels

We prove finite-sample concentration and anti-concentration bounds for dimension estimation using Gaussian kernel sums. Our bounds provide explicit dependence on sample size, bandwidth, and local geometric and distributional parameters, characterizing precisely how regularity conditions influence statistical performance. We also propose a bandwidth selection heuristic using derivative information, supported by numerical experiments.

math.ST↗

arXiv2025

Is Repeater-Assisted Massive MIMO Compatible with Dynamic TDD?

We present a framework for joint amplification and phase shift optimization of the repeater gain in dynamic time-division duplex (TDD) repeater-assisted massive MIMO networks. Repeaters, being active scatterers with amplification and phase shift, enhance the received signal strengths for users. However, they inevitably also amplify undesired noise and interference signals, which become particularly prominent in dynamic TDD systems due to the concurrent downlink (DL) and uplink (UL) transmissions, introducing cross-link interference among access points and users operating in opposite transmit directions. This causes a non-trivial trade-off between amplification of desired and undesired signals. To underpin the conditions under which such a trade-off can improve performance, we first derive DL and UL spectral efficiencies (SEs), and then develop a repeater gain optimization algorithm for SE maximization. Numerically, we show that our proposed algorithm successfully calibrates the repeater gain to amplify the desired signal while limiting the interference.

eess.SP↗

arXiv2025

Non-parametric estimation of non-linear diffusion coefficient in parabolic SPDEs

In this article, we introduce a novel non-parametric predictor, based on conditional expectation, for the unknown diffusion coefficient function $\sigma$ in the stochastic partial differential equation $Lu = \sigma(u)\dot{W}$, where $L$ is a parabolic second order differential operator and $\dot{W}$ is a suitable Gaussian noise. We prove consistency and derive an upper bound for the error in the $L^p$ norm, in terms of discretization and smoothening parameters $h$ and $\varepsilon$. We illustrate the applicability of the approach and the role of the parameters with several interesting numerical examples.

math.ST↗

arXiv2025

On the Effectiveness of Classical Regression Methods for Optimal Switching Problems

Simple regression methods provide robust, near-optimal solutions for optimal switching problems, including high-dimensional ones (up to 50). While the theory requires solving intractable PDE systems, the Longstaff-Schwartz algorithm with classical regression methods achieves excellent switching decisions without extensive hyperparameter tuning. Testing linear models (OLS, Ridge, LASSO), tree-based methods (random forests, gradient boosting), $k$-nearest neighbors, and feedforward neural networks on four benchmark problems, we find that several simple methods maintain stable performance across diverse problem characteristics, outperforming the neural networks we tested against. In our comparison, $k$-NN regression performs consistently well, and with minimal hyperparameter tuning. We establish concentration bounds for this regressor and show that PCA enables $k$-NN to scale to high dimensions.

math.OC↗

arXiv2025

Role of defects in atom probe analysis of sol-gel silica

Silicon dioxide is a suitable material to encapsulate proteins at room temperature so that they can be analysed at the atomic level using laser-assisted atom probe tomography (La-APT). To achieve this goal, in this study we show that UV and deep UV lasers can achieve a high success rate in La-APT of silica in terms of chemical resolution and three-dimensional image volume, with both lasers providing comparable results. Since the La-APT analyses are driven by photon absorption, in order to understand the mechanisms behind the enhanced absorption of UV light, we performed density functional theory calculations to model the electronic and optical properties of amorphous silica matrices generated using a Monte Carlo approach to structural optimisation. In particular, we have investigated the role of various defects introduced during sample preparation, such as substitutional and interstitial carbon, sodium and gallium ions, and hydrogen. Our results show that the presence of defects increases the absorption of silica in the UV and deep-UV range and thus improves the La-APT capabilities of the material. However, due to the low density of free charge carriers resulting from the absorption of laser energy by defects, deviations from the nominal chemical composition and suboptimal chemical resolution may occur, potentially limiting the optimal acquisition of APT mass spectra.

cond-mat.mtrl-sci↗

arXiv2025

GenAI in Entrepreneurship: a systematic review of generative artificial intelligence in entrepreneurship research: current issues and future directions

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are recognized to have significant effects on industry and business dynamics, not least because of their impact on the preconditions for entrepreneurship. There is still a lack of knowledge of GenAI as a theme in entrepreneurship research. This paper presents a systematic literature review aimed at identifying and analyzing the evolving landscape of research on the effects of GenAI on entrepreneurship. We analyze 83 peer-reviewed articles obtained from leading academic databases: Web of Science and Scopus. Using natural language processing and unsupervised machine learning techniques with TF-IDF vectorization, Principal Component Analysis (PCA), and hierarchical clustering, five major thematic clusters are identified: (1) Digital Transformation and Behavioral Models, (2) GenAI-Enhanced Education and Learning Systems, (3) Sustainable Innovation and Strategic AI Impact, (4) Business Models and Market Trends, and (5) Data-Driven Technological Trends in Entrepreneurship. Based on the review, we discuss future research directions, gaps in the current literature, as well as ethical concerns raised in the literature. We highlight the need for more macro-level research on GenAI and LLMs as external enablers for entrepreneurship and for research on effective regulatory frameworks that facilitate business experimentation, innovation, and further technology development.

econ.GN↗

arXiv2024

User-to-User Interference Mitigation in Dynamic TDD MIMO Systems with Multi-Antenna Users

We propose a novel method for user-to-user interference (UUI) mitigation in dynamic time-division duplex multiple-input multiple-output communication systems with multi-antenna users. Specifically, we consider the downlink data transmission in the presence of UUI caused by a user that simultaneously transmits in uplink. Our method introduces an overhead for estimation of the user-to-user channels by transmitting pilots from the uplink user to the downlink users. Each downlink user obtains a channel estimate that is used to design a combining matrix for UUI mitigation. We analytically derive an achievable spectral efficiency for the downlink transmission in the presence of UUI with our mitigation technique. Through numerical simulations, we show that our method can significantly improve the spectral efficiency performance in cases of heavy UUI.

eess.SP↗

arXiv2024

Joint Optimization of Switching Point and Power Control in Dynamic TDD Cell-Free Massive MIMO

We consider a cell-free massive multiple-input multiple-output (CFmMIMO) network operating in dynamic time division duplex (DTDD). The switching point between the uplink (UL) and downlink (DL) data transmission phases can be adapted dynamically to the instantaneous quality-of-service (QoS) requirements in order to improve energy efficiency (EE). To this end, we formulate a problem of optimizing the DTDD switching point jointly with the UL and DL power control coefficients, and the large-scale fading decoding (LSFD) weights for EE maximization. Then, we propose an iterative algorithm to solve the formulated challenging problem using successive convex approximation with an approximate stationary solution. Simulation results show that optimizing switching points remarkably improves EE compared with baseline schemes that adjust switching points heuristically.

eess.SP↗

arXiv2024

Evaporation of cations from non-conductive nano-samples using single-cycle THz pulses: an experimental and theoretical study

This study investigates the emission of cations from silica samples by single-cycle THz pulses, focusing on the influence of pulse polarity. Negative THz pulses were found to efficiently trigger the evaporation of cations from nanoneedles in amorphous silica samples compared to positive pulses. Conversely, this dependence on pulse polarity could not be found in samples with metallic behaviour such as LaB$_6$ and when multi-cycle pulses in different frequency ranges such as ultraviolet (UV) are used. First-principles simulations focus on silica under THz laser irradiation and show critical fields for ion evaporation of hydroxyl groups from Si(OH)$_4$, which serves as a model precursor molecule for the amorphous solid matrix. To explain our experimental results, we propose a simplified theoretical model that determines the role of the polarity of the THz pulse by taking into account the differences in electron mobility between silica and semi-metallic samples. The study explores the nonlinear microscopic mechanisms of atomic evaporation under external static and THz laser fields and clarifies the dynamics of THz-enhanced APT and related applications.

cond-mat.mtrl-sci↗

arXiv2023

Effect of fiber curvature on gas diffusion layer two-phase dynamics of a proton exchange membrane fuel cell

The dynamics of two-phase flow within the cathode of a proton exchange membrane fuel cell, particularly in Gas Diffusion Layers (GDLs) with varying fiber curvatures, remain underexplored. Using a periodic surface model, we stochastically reconstruct three GDL types with different fiber curvatures, incorporating vital parameters derived from a physical GDL. Considering the randomness in reconstruction, the structure generation process is iterated four times for each GDL type, enabling an ensemble average analysis. Pore network models are adopted to reveal disparities in these GDL porous structures. The subsequent two-phase simulations are conducted to explore liquid transport through these GDLs and interfaces to assembled gas channels. Time-varying GDL total, local water saturation, and capillary pressure are investigated. Results show stochastic reconstructions exhibit similar frequency peak ranges in pore and throat diameters, and coordination numbers, but diverge from the physical GDL. Bigger fiber curvature tends to enhance pore network connectivity by increasing smaller pores, leading to heightened water saturation and capillary pressure. Straight-fiber GDLs, compared to curved-fiber GDLs, show greater potential proximity to the physical GDL in terms of overall water saturation and capillary pressure but are also accompanied by increased uncertainty. Despite similar layer porosity, water saturation in the same layer of all samples differs increasingly from the inlet to the outlet. Water breakthrough and detachment near the GDL can induce significant water saturation instability at the GDL and gas channel interface. Detached droplets in gas channels connected with straight-fiber GDLs exhibit larger sizes and slower movement than those in channels assembled with curved-fiber GDLs. These findings can be utilized in future GDL design and optimization.

physics.flu-dyn↗

arXiv2022

Exploring Singularities in point clouds with the graph Laplacian: An explicit approach

We develop theory and methods that use the graph Laplacian to analyze the geometry of the underlying manifold of datasets. Our theory provides theoretical guarantees and explicit bounds on the functional forms of the graph Laplacian when it acts on functions defined close to singularities of the underlying manifold. We use these explicit bounds to develop tests for singularities and propose methods that can be used to estimate geometric properties of singularities in the datasets.

stat.ML↗

arXiv2022

Waveform discrimination by fitting derivative of synchronized ideal normalized curves, dSINC fit

dSINC proposes an alternative algorithm for waveform discrimination of measurement data from multi-layer scintillator sandwich designs. dSINC attempts to solve problems related to noise and peaks-piling sensitivity in the feature extraction step of traditional KNN waveform discrimination, by fitting the derivative of the entire gain section of the waveform against ideal waveforms learned from training data and thereby completely sidestepping the problems of feature extraction.

physics.ins-det↗

arXiv2022

Numerical simulation of two-phase flow in gas diffusion layer and gas channel of proton exchange membrane fuel cells

Liquid water within the cathode Gas Diffusion Layer (GDL) and Gas Channel (GC) of Proton Exchange Membrane Fuel Cells (PEMFCs) is strongly coupled to gas transport properties, thereby affecting the electrochemical conversion rates. In this study, the GDL and GC regions are utilized as the simulation domain, which differs from previous studies that only focused on any one of them. A volume-of-fluid method is adopted to numerically investigate the two-phase flow (gas and liquid) behavior, e.g., water transport pattern evolution, water coverage ratio as well as local and total water saturation. To obtain GDL geometries, an in-house geometry-based method is developed for GDL reconstruction. Furthermore, to study the effect of GDL carbon fiber diameter, the same procedure is used to reconstruct three GDL structures by varying the carbon fiber diameter but keeping the porosity and geometric dimensions constant. The wall wettability is introduced with static contact angles at carbon fiber surfaces and channel walls. The results show that the GDL fiber microstructure has a significant impact on the two-phase flow patterns in the cathode field. Different stages of two-phase flow pattern evolution in both cathode domains are observed. Due to the difference in wettability, the water coverage of the GDL/GC interface is smaller than that of the channel side and top walls. It is also found that the water saturation inside the GDLs stabilizes after the water breakthrough, while local water saturation at the interface keeps irregular oscillations. Last but not the least, a water saturation balance requirement between the GDL and GC is observed. In terms of varying fiber diameter, a larger fiber diameter would result in less water saturation in the GDL but more water in the GC, in addition to faster water movement throughout the total domain.

physics.flu-dyn↗

arXiv2022

Large Eddy Simulations of Turbulent Pipe Flows At Moderate-To-High Reynolds Numbers

Wall-bounded turbulence is relevant for many engineering and natural science applications, yet there are still aspects of its underlying physics that are not fully understood, particularly at high Reynolds numbers. In this study, we investigate fully-developed turbulent pipe flows at moderate-to-high friction velocity Reynolds numbers ($361 \leq Re_{\tau} \leq 2,000$), corresponding to bulk velocity-based Reynolds numbers of $11,700 \leq Re_{b} \leq 82,500$, using wall-modeled Large Eddy Simulations (LES) in OpenFOAM. A grid convergence study is performed for $Re_{\tau} = 361$, followed by an investigation of the accuracy of various subgrid-scale stress models for the same Reynolds number. Results show that the Wall-Adapting Local Eddy (WALE) model performs well compared to experiments and Direct Numerical Simulations (DNS), while One-Equation Eddy-Viscosity Model (OEEVM) and Smagorinsky (SMG) are too dissipative. LES utilizing WALE are then performed for four different Reynolds numbers with gradually refined grids, revealing excellent agreement with DNS data in the outer region. However, a significant deviation from DNS data is observed in the sub-viscous layer region, indicating the need for further mesh refinement in the wall-normal direction to accurately capture the smallest-scale motions' behavior. Additional mesh sensitivity analysis uncovered that, as the $Re_{\tau}$ value rises, it becomes crucial for a grid to adhere to the condition of $\Delta x^{+} \leq 20 - 25$ and $\Delta z^{+} \leq 10$ in order to precisely capture substantial large and small scale fluctuations. Overall, the WALE model enables accurate numerical simulations of high-Reynolds-number, wall-bounded flows at a fraction of the computational cost required for temporal and spatial resolution of the inner layer.

physics.flu-dyn↗

arXiv2022

Non-uniformly hyperbolic endomorphisms

We show the existence of large $\mathcal C^1$ open sets of area preserving endomorphisms of the two-torus which have no dominated splitting and are non-uniformly hyperbolic, meaning that Lebesgue almost every point has a positive and a negative Lyapunov exponent. The integrated Lyapunov exponents vary continuously with the dynamics in the $\mathcal C^1$ topology and can be taken as far away from zero as desired. Explicit real analytic examples are obtained by deforming linear endomorphisms, including expanding ones. The technique works in nearly every homotopy class and the examples are stably ergodic (in fact Bernoulli), provided that the linear map has no eigenvalue of modulus one.

math.DS↗

arXiv2022

Historic behaviour vs. physical measures for irrational flows with multiple stopping points

We study Birkhoff averages along trajectories of smooth reparameterizations of irrational linear flows of the two torus with two stopping points, say $\mathbf p$ and $\mathbf q$, of quadratic order. The limiting behaviour of such averages is independent of the starting point in a set of full Haar-Lebesgue measure and depends in an intricate way on the Diophantine properties of both the slope $α$ of the linear flow as well as the relative position of $\mathbf p$ and $\mathbf q$. In particular, if $α$ is Diophantine, then Birkhoff limits diverge almost everywhere (historic behaviour) and if $α$ is sufficiently Liouville, then there exists some $\mathbf p$ and $\mathbf q$ such that the Birkhoff averages converge almost everywhere (unique physical measure).

math.DS↗