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We propose a new class of high-rate spatially coupled LDPC (SC-LDPC) codes based on the convolutional selforthogonal codes (CSOCs) first introduced by Massey. The SCLDPC codes are constructed by treating the irregular graph corresponding to the parity-check matrix of a systematic rate R=(n-1) / n CSOC as a convolutional protograph. The protograph can then be lifted using permutation matrices to ge
As a prominent category of side-channel attacks (SCAs), plaintext-checking (PC) oracle-based SCAs offer the advantages of generality and operational simplicity on a targeted device. At TCHES 2023, Rajendran et al. and Tanaka et al. independently proposed the multiple-valued (MV) PC oracle, significantly reducing the required number of queries (a.k.a., traces) in the PC oracle. However, in practice
We introduce Thalassa, a framework designed to convert nonlinear systems of partial differential equations (PDEs) with a time-like component into tensor programs that solve these equations. These programs can run on GPUs as well as machine learning (ML) acceleration hardware, enabling scientific computing fields such as computational fluid dynamics, astrophysics, mechanics and biology to utilize a
The introduction of electric heavy trucks will lead to new charging power requirements on the power grid. This study examines how much charging power is required for the public fast charging of a fully electrified long-haul truck fleet. Probabilistic truck charging profiles are created using agent-based simulations, based on fully representative long-haul goods transport data from the study area.
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercial platforms. However, to broaden the adoption of the technology in the real world, we require robust navigation stacks relying only on low-cost sensors such as depth cameras. This paper presents a first step towards a ro
Digital control systems introduce unavoidable computational latencies. For some controllers this time delay inhibits practical use, even though they in theory could provide more efficient control. For example, solving an optimization problem each sampling period when using model predictive control. By sampling faster than the computation time and executing independent controllers on distributed ha
In this work, we study the problem of estimating the in-ear sound field using microphone measurements at nearby positions. Typically, the sound field is first interpolated to the position of the head under free-field assumptions, followed by filtering through pre-measured head-related transfer functions (HRTFs). While properties of free-field interpolation methods have been well studied with respe
Motivated by the well established idea that collective wisdom is greater than that of an individual, we propose a novel learning dynamics as a sort of companion to the Abelson model of opinion dynamics. Agents are assumed to make independent guesses about the true state of the world after which they engage in opinion exchange leading to consensus. We investigate the problem of finding the optimal
This study investigates the incentives and barriers influencing AI ethics adoption in unregulated environments, drawing on semi‐structured interviews with AI professionals in Bangladesh. Our findings reveal that external pressures, such as international client requirements, drive companies to implement ethical measures, yielding both economic benefits and enhanced reputation. Conversely, tight dea
Post-compression of (sub)-picosecond laser pulses down to sub-100 fs durations has become a standard approach for high-peak-power sources at a high average power [1]. Here, we propose a new post-compression geometry suited for extreme temporal compression of energetic narrowband lasers, such as diode or electrically pumped four-level systems which can deliver kW-average powers [2], but typically e
Intense ultrashort-pulsed laser systems based on Ti:sapphire chirped pulse amplifiers (CPA) operating at 800 nm have been a workhorse of ultrafast science for several decades. More recently, driven by the progress in laser technology, sources with central wavelengths further in the infrared have emerged as powerful tools, in particular to generate soft X-ray (SXR) radiation via high-harmonic gener
Sparse tensor computations suffer from irregular memory access patterns that degrade cache performance. While software prefetching can mitigate this, existing compiler approaches lack the semantic insight needed for effective optimization. We present ASaP, an automatic software prefetching framework integrated within MLIR’s sparse tensor dialect. By leveraging semantic information-tensor formats a
A multi-variable adaptive controller is derived as the explicit solution to a minimax dynamic game. The minimizing player selects the control action as a function of past state measurements and inputs. The maximizing player selects disturbances and model parameters for the underlying linear time-invariant dynamics. This leads to a Bellman equation that can be solved explicitly for the case with un
Coherent extreme ultraviolet (XUV) radiation can be generated in a tabletop configuration via high-order harmonic generation (HHG) in gases. While HHG is inherently inefficient, increasing the conversion efficiency (CE) is crucial for many applications, such as coincidence spectroscopy [1] and coherent imaging [2], which require high XUV throughput. Previous calculations suggest that one way to im
Three different semiconductor nanowires are combined into a single optoelectronic artificial neuron. Our device provides a path towards low power computations with significantly reduced circuit footprint, thus addressing critical limitations in neuromorphic photonics. The false-coloured scanning electron micrograph shown in Figure 1a depicts the fabricated nanowire neuron. Two pin-doped InP nanowi
Photonics-based approaches to neuromorphic hardware offer advantages in speed and connectivity but often suffer from large device footprints.[1] Here, we present an ultra-compact artificial neuron built from semiconductor nanowires. A scanning electron micrograph of the nanowire device is presented in Figure 1a. Inside the dashed box, we show the neuron built from three III-V nanowires - two InP p
Methanol can be produced renewably and used in compression ignition (CI) engines as a replacement for fossil diesel. However, methanol is a low cetane fuel, creating challenges in achieving stable operation, particularly at low load. One potential solution is through surface ignition via a glow plug. In this work, experiments were conducted on a methanol-fueled 2.1 L single cylinder engine instrum
This paper provides a practical guide on how to effectively use the MARRYS helmet for recording and analyzing jaw movements in speech research. Rather than introducing the device itself, which has been described in detail in Gudmundsson et al. (2024), this guide focuses on the setup, data collection, and analysis workflows essential for successful experimental work. Applications include language l
Robotic systems often face execution failures due to unexpected obstacles, sensor errors, or environmental changes. Traditional failure recovery methods rely on predefined strategies or human intervention, making them less adaptable. This paper presents a unified failure recovery framework that combines Vision-Language Models (VLMs), a reactive planner, and Behavior Trees (BTs) to enable real-time
