Published on 8 May 2024
Synthesizing broadcast channels using shared randomness
This paper studies the problem of synthesizing a two-user broadcast channel using a common message, when the input terminal shares independent randomness with each output terminal. The authors provide inner and lower bounds on the rate tradeoff between communication and shared randomness. These bounds are tight for some special cases like point-to-point channels and channels without inputs studied in prior work.
Published on 8 May 2024
Team of robots track moving people by sharing object observations
A team of mobile robots can more accurately track moving people in their environment by sharing observations of people's locations with each other in real-time. But robots accumulate error in their position estimates, so they must repeatedly estimate the change in coordinate frames between themselves and neighbors. This paper presents a full system for robots to build maps of generic objects seen recently, align the maps to estimate relative positions, and use those to share observations of people for collaborative tracking.
Published on 8 May 2024
Using game techniques to engage software engineering students
This paper investigates applying gamification in software engineering education through a tertiary study, finding it can increase student engagement and motivation. However, improper implementation may negatively impact performance. Key areas for gamification are testing and quality, with competition and cooperation the most used game elements.
Published on 8 May 2024
Universal threshold for primordial black hole formation
This paper mathematically proves that there is a universal threshold for primordial black hole formation, expressed in terms of the volume-averaged compaction function. This threshold is independent of the shape of the initial density perturbation that collapses to form the black hole. The key insight is that at the threshold of black hole formation, the collapsing configuration displays persistent self-similarity near the center, a fundamental property of critical gravitational collapse.
Published on 8 May 2024
Detecting unusual certificates
The authors propose using the Isolation Forest algorithm to detect anomalous X.509 certificates in Certificate Transparency logs. This unsupervised machine learning method builds random trees to isolate outliers. It identifies certificates significantly different from typical ones based on quantitative attributes like subject name length or public key type, without needing to pre-define anomalies. When standards compliance checks are insufficient, it can reveal potential issues needing investigation. The technique seems promising when traine...
Published on 8 May 2024
A more literal title summarizing the main contributions
A succinct and accessible summary of the key points, for a general audience.
Published on 8 May 2024
Machine learning classification of outer solar system objects
This paper presents a supervised machine learning model to classify icy bodies beyond Neptune called trans-Neptunian objects (TNOs) into different dynamical groups. The model was trained on a large and diverse dataset of real and synthetic TNO orbits. It uses custom features from numerical integrations to identify complex resonant dynamics. When tested, the model matched human judgement 98% of the time, offering major improvements in efficiency over manual classification as observations increase exponentially.
Published on 8 May 2024
Linear model with time-varying interactions
This paper introduces a mathematical model with multiple interacting components, where the interaction strengths vary randomly over time. The authors apply an analytical technique called Dynamical Mean Field Theory to find an exact solution for the model's behavior. Key results describe how the system's variability and stability depend on the time-scale of the fluctuating interactions in non-trivial ways. For some parameters, slower interaction fluctuations counterintuitively destabilize the system. The analytical solution also enables mappi...
Published on 8 May 2024
Quantum synchronization through interference blockades
A study showing that undriven spin-1 oscillators can exhibit synchronization to an external drive through quantum interference blockades, which normally suppress phase locking, and this effect also occurs between non-directly coupled spins in a chain.
Published on 8 May 2024
Simplified analysis of randomized quasi-Monte Carlo convergence under boundary growth conditions
This paper analyzes the convergence rates of randomized quasi-Monte Carlo methods for integrands that are unbounded near the boundary. Using spectral analysis with Fourier and Walsh-Fourier transforms, the variance decay rates are shown to closely match the boundary growth condition exponent. Guidance is provided on importance sampling densities that minimize variance.
Published on 8 May 2024
Embryonic oscillators with frequency memory
Experiments reveal vertebrate embryonic oscillators can actively change internal frequency to adapt to external signals over time. This suggests a new 'unclocklike' behavior, inconsistent with standard limit cycle models. Simple models are proposed where a phase oscillator activates a memory variable controlling the oscillator's frequency. Two coupling variations are studied. These models recapitulate intriguing properties seen experimentally like broad entrainment ranges and plateauing entrainment phase with detuning. New phenomena are also...
Published on 8 May 2024
Detecting cracks from limited wave data
This paper proposes methods to detect the location and shape of cracks using limited acoustic wave data from just one wave source. A contrast sampling method initially determines a rough crack location. Then a variant factorization technique recovers the crack's convex hull using one plane wave. Newton's method further refines the shape. Numerical results demonstrate effectively detecting cracks from minimal data.
Published on 8 May 2024
Unified view of symmetry and fusion rules in topological phases
This paper revisits the mathematical structure connecting conformal field theories (CFTs), chiral CFTs, and topological orders. It proposes a new 'bulk semionization' technique to extract a fusion subalgebra from bulk CFT data. This reveals connections between generalized symmetry, fractional supersymmetry, and topological holography, offering a unified framework applicable to topological phases in general dimensions.
Published on 8 May 2024
Encoder-decoder model for interactive free verse generation with controllable high-quality rhyming
The paper proposes a novel fine-tuning approach to generate lyrics and free verse poems with controllable, high-quality rhyming. By prepending the rhyming word to the start of each line, the model makes the critical rhyming decision first while still generating the verse left-to-right. Extensive experiments show this approach produces more readable text and better rhyming compared to prior state-of-the-art methods. A high-quality multilingual dataset is also introduced to demonstrate wide applicability.
Published on 8 May 2024
Protecting privacy in conversational agents
This paper introduces a new threat model where adversarial third parties manipulate context to trick conversational agents into leaking private user data. The authors propose AirGapAgent, an architecture that restricts agent access to only necessary user data for a task. Experiments show AirGapAgent protects up to 97% of user data from context manipulation attacks while maintaining utility.
Published on 8 May 2024
3D perception of vehicle surroundings
This paper surveys recent research on 3D occupancy perception, which seeks to capture detailed 3D structures around vehicles to enable autonomous driving systems to precisely understand complex environments. It highlights that occupancy perception combines inputs from multiple sensors and fuses information across data sources. Key challenges include converting 2D images to 3D representations, integrating multi-camera and multi-frame observations, and training networks. The paper analyzes performance on datasets and discusses future opportuni...
Published on 8 May 2024
Dimension distortion under compactly Holder mappings
This paper introduces compactly Holder mappings between metric spaces, which resemble Sobolev mappings but without requiring a measure. It shows these mappings distort the Minkowski dimension of a set, providing quantitative bounds. Even for Sobolev maps between weighted Euclidean spaces, the result generalizes prior work.
Published on 8 May 2024
Quantized neural network training equivalence
This paper proves that many proposed complex gradient estimators for quantized neural networks are equivalent to simpler estimators like the straight-through estimator. After adjustments to the learning rate and weight initialization, models using complex estimators train almost identically to those using the straight-through estimator.
Published on 8 May 2024
Recovering lost watermarks using image denoising
This paper proposes a robust image watermarking model that introduces a denoising module between the noise layer and decoder in the typical encoder-decoder architecture. The denoising module reduces noise and recovers watermark information lost during attacks, improving robustness. Additionally, a SE module is added to the encoder to fuse watermarking information pixel and channel-wise, enhancing efficiency. Experiments show the model matches or exceeds state-of-the-art methods under high noise levels. Ablations demonstrate the value of each...
Published on 8 May 2024
Stable optical modulators using thin lithium tantalate films
Researchers fabricated lithium tantalate thin-film optical modulators that show much better long-term stability than equivalent lithium niobate devices, without sacrificing optical loss, drive voltage or bandwidth.
Published on 8 May 2024
Unequal vacuum selection probabilities
This paper studies how a field sitting at the top of a potential can roll down to the left or right side with unequal probabilities, if the top of the potential is only C1 continuous. Using Fokker-Planck equations, they show the probability depends on the square root of the 2nd derivative on each side. Numerical simulations verify the theory. This may explain cosmic asymmetries.
Published on 8 May 2024
Numerical validation of kinetic theory for interacting soliton gases
This paper uses the Riemann problem for interacting soliton gases to validate the spectral kinetic theory for the KdV and focusing NLS equations. It develops analytical solutions and numerical methods to model collisions between dense, polychromatic soliton gases composed of distinct monochromatic components. Comparisons are made between theoretical predictions and numerical simulations, providing robust confirmation of the kinetic theory in a broad parameter range.
Published on 8 May 2024
New quantum defects in silicon for telecom emission
This paper computationally screens over 22,000 defects in silicon to discover new quantum emitters formed by group III elements bound to carbon, which are structurally and electronically analogous to the known T center defect. Some have improved optical properties and higher symmetry. The paper suggests these could be promising spin-photon interfaces, and proposes a hydrogen-assisted synthesis route.
Published on 8 May 2024
Radar-based human pose estimation through multi-format feature fusion
This paper introduces ProbRadarM3F, a novel radar-based model for indoor human pose estimation. It fuses traditional heatmap features from radar signals with new positional encoding features guided by generated probability maps. This allows it to capture more of the latent spatial information in radar data. Experiments show ProbRadarM3F outperforms prior state-of-the-art methods on the HuPR dataset for 14 keypoint detection, demonstrating the value of multi-format radar feature fusion.
Published on 8 May 2024
Simplified quantum Fourier transforms
This paper proposes two methods to break down the Fourier transform, a key operation in quantum computing, into sequences of smaller 'component' Fourier transforms. This reduces the computational complexity from quadratic to linearithmic time. One method handles systems with Hilbert space dimension equal to a power of an odd number, and the other handles dimensions that are a product of coprime odd numbers. The latter method is also applied to quickly compute the Wigner and Weyl functions. Overall, this allows large Fourier transforms and ot...
Published on 8 May 2024
Kinematic analysis of endpoint marking in verbs and intensification in adjectives
This paper investigates how signers of Austrian Sign Language use hand motion to convey semantic distinctions in verbs (actions with clear endpoints vs. ongoing actions) and grammatical distinctions in adjectives (intensified vs. non-intensified). Motion capture analysis reveals that telic verbs have higher peak velocity and shorter duration compared to atelic verbs. Intensified adjectives have longer duration compared to non-intensified forms. Individual differences between signers likely reflect personal signing style.
Published on 8 May 2024
Selective classification to enable reliable deep learning deployment
This paper proposes a selective classification framework that allows for distribution shifts between training and deployment. It focuses on developing non-training-based confidence scores to reject likely-incorrect predictions on deep learning models. The key ideas are margin-based scores that are more reliable than existing methods under label/covariance shifts.
Published on 8 May 2024
Analysis of the SQP Method for Acoustic Waveform Inversion
This paper analyzes the Sequential Quadratic Programming (SQP) method for an acoustic full waveform inversion problem in the time domain. The analysis is challenging due to hyperbolicity and second-order bilinear structure leading to loss of regularity in SQP. A novel strategy is proposed using a smooth-in-time condition, tailored self-mapping operator, and two-step estimation with Stampacchia's method to prove R-superlinear convergence of SQP.