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Category: computing – Page 7

A Hall ‘rectenna’ can detect signals over a 100 GHz frequency range

Many current wireless communication, imaging and sensing technologies rely on components that convert oscillating electric and magnetic fields (i.e., electromagnetic waves) into electrical signals. Some of the most used components are so-called p-n diodes, semiconducting devices that combine two types of materials with distinct electrical properties.

In conventional diode designs, the conversion of electromagnetic waves into electrical signals relies on the nonlinear transport of electrons. This means that the electric current in the devices does not change proportionally with the voltage applied, which allows them to rectify signals (i.e., convert alternating current into direct current) and combine signals with different frequencies.

A key limitation of traditional diodes is that thermal effects introduce noise, causing electrons to move randomly and making weak signals harder to detect. Moreover, electrons typically take a finite time to travel across the device, also known as the transit time, which limits the performance of the diodes at very high frequencies.

Superconducting quantum processor performs well with significantly less wiring

Quantum computers, computing systems that process information using quantum mechanical effects, could outperform classical computers on some computational tasks. These computers rely on qubits, the basic units of quantum information, which can exist in multiple states (0, 1 or both simultaneously), due to quantum effects known as superposition and entanglement.

Many of the quantum computers developed in recent years are based on conventional superconductors, materials that exhibit an electrical resistance of zero at extremely low temperatures. To operate reliably and exhibit superconductivity, circuits based on these materials need to be cooled down to millikelvin temperatures.

In quantum computers, each qubit typically requires its own control line. This means that engineers need to introduce several wires that carry electrical pulses (i.e., signal lines), and the number of necessary wires increases with the number of qubits. As quantum computers grow larger, this can be problematic, as processors become harder to build and reliably operate.

Quantum computers could have a fundamental limit after all

The performance of quantum computers could cap out after around 1,000 qubits, according to a new analysis published in the Proceedings of the National Academy of Sciences. Through new calculations, Tim Palmer at the University of Oxford has reconsidered the mathematical foundations underlying the quantum principles behind the technology, concluding that restrictions on the information-carrying capacity of large quantum systems could make their computing power far more limited than many researchers predict.

For some time, quantum physicists have been growing increasingly excited—and concerned—about the seemingly limitless potential of quantum computers. In a classical computer, information content generally grows linearly as the number of bits increases. But in a quantum computer, each extra qubit doubles the number of quantum states the system can occupy.

Since these states can encode multiple possibilities at the same time, the overall system appears to become exponentially more powerful with each added qubit—at least according to our current understanding of quantum mechanics.

Superconducting chip generates tunable terahertz waves for compact imaging

A tiny crystal chip which uses terahertz radiation to see clearly through a wide range of materials could find applications in health care, biological research, and security screening. Researchers from Scotland and Japan have developed a lightweight superconducting chip, which they say could unlock the full potential of terahertz imaging technologies and lead to the development of more powerful and portable devices.

The team’s paper, titled “Terahertz Imaging System with On-Chip Superconducting Josephson Plasma Emitters for Nondestructive Testing,” is published in IEEE Transactions on Applied Superconductivity.

Terahertz radiation lies between the microwave and infrared frequencies of the electromagnetic spectrum. It passes easily and harmlessly through a wide range of materials, and can be used to identify the characteristic “fingerprint” of molecules and biological materials as it does so, allowing them to be detected and analyzed.

LeWorldModel: Stable End-to-End Joint-Embedding

Joint Embedding Predictive Architectures (JEPAs) offer a compelling framework for learning world models in compact latent spaces, yet existing methods remain fragile, relying on complex multi-term losses, exponential moving averages, pre-trained encoders, or auxiliary supervision to avoid representation collapse. In this work, we introduce LeWorldModel (LeWM), the first JEPA that trains stably end-to-end from raw pixels using only two loss terms: a next-embedding prediction loss and a regularizer enforcing Gaussian-distributed latent embeddings. This reduces tunable loss hyperparameters from six to one compared to the only existing end-to-end alternative. With ~15M parameters trainable on a single GPU in a few hours, LeWM plans up to 48× faster than foundation-model-based world models while remaining competitive across diverse 2D and 3D control tasks. Beyond control, we show that LeWM’s latent space encodes meaningful physical structure through probing of physical quantities. Surprise evaluation confirms that the model reliably detects physically implausible events.

TL;DR: LeWM is a JEPA-based world model that avoids representation collapse using a simple Gaussian regularizer (SIGReg), trains end-to-end from pixels with only two loss terms, and achieves competitive control performance at a fraction of the compute cost.

Catch-bond engineering “turbocharge” T cells to attack prostate cancer

T cells are a powerful weapon in the fight against cancer, forming the basis of treatments such as CAR-T cell therapy and checkpoint inhibitors. This research centers on another type of immunotherapy approach called T cell receptor (TCR) therapy, which engineers T cells to recognize specific proteins on cancer cells, allowing for highly targeted attacks.

Many of these proteins, however, are “self-antigens,” or molecules normally found in the body. To prevent these T cells from attacking healthy tissue, the immune system naturally eliminates the strongest cancer-fighting T cells during development. This leaves behind weaker T cell receptors that may struggle to recognize and destroy tumors, particularly those that have learned to evade immune defenses.

To overcome this challenge, researchers focused on fine-tuning naturally occurring T cell receptors to strengthen their ability to recognize a common prostate cancer protein called prostatic acid phosphatase (PAP), which is commonly expressed on prostate tissue and prostate tumors. The team identified a naturally weak TCR, known as TCR156, that could detect PAP but was not strong enough to effectively kill cancer cells.

Using a novel technique called catch bond engineering, a concept developed by the Lab, the researchers “turbocharged” the T cells. In the body, T cells form brief, mechanical bonds with their targets, known as catch bonds, which help them sense and respond to threats. By altering just one or two amino acids in the T cell receptor, the scientists were able to strengthen these bonds while preserving the T cells’ natural ability to recognize their specific target.

Multiple engineered versions of TCR156 were created and tested. Two candidates proved to be the most effective. These engineered T cells were analyzed for their ability to recognize tumors, release cancer-killing molecules, proliferate, and resist exhaustion. Advanced imaging, single-cell RNA sequencing, and structural analyses were used to confirm that the modifications improved T cell function while maintaining precision and avoiding off-target effects.

Structural and computer modeling studies showed that the catch bond mutations did not change the overall TCR shape but primed it to form a new interaction with PAP when the T cell engaged the tumor, explaining how the engineered T cells could remain highly specific while dramatically boosting their cancer-killing ability.

The researchers found that a single amino acid change created a catch bond hotspot that significantly enhanced T cell function. This change did not directly contact the cancer protein until the T cell engaged dynamically, demonstrating that a tiny modification can have a major effect. Most importantly, the modifications did not make the cells attack healthy tissue.

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A new entanglement-enhanced quantum sensing scheme

Over the past decades, quantum scientists have introduced various technologies that operate leveraging quantum mechanical effects, including quantum sensors, computers and memory devices. Most of these technologies leverage entanglement, a quantum phenomenon via which two or more particles become intrinsically linked and share a unified quantum state, irrespective of the distance between them.

New X-ray vision for electronics lets scientists monitor working chips remotely

A team of international researchers have developed a breakthrough way to observe what is happening inside electronic chips while they are operating—without touching them, taking them apart, or switching them off. The new technique uses terahertz waves, a safe and non-ionizing form of electromagnetic radiation, to detect tiny movements of electrical charge inside fully packaged semiconductor devices. For the first time, this allows scientists and engineers to monitor electronic components as they function in the real world.

The study, published in the IEEE Journal of Microwaves, involves researchers from Adelaide University in Australia, US technology company Virginia Diodes Inc, the Hasso Plattner Institute and the University of Potsdam, Germany.

Adelaide University Group Leader of the Terahertz Engineering Laboratory (TEL), Professor Withawat Withayachumnankul, said that semiconductors underpin almost every modern technology, from smartphones and medical devices to vehicles, power grids and defense systems.

Frontiers: Information storage and transfer in the brain require a high computational power

Neuronal network display various local or global mechanisms to allow information storage and transfer in the brain. From synaptic to intrinsic plasticity, the rules of input–output function modulation have been well characterized in neurons. In the past years, astrocytes have been suggested to increase the computational power of the brain and we are only just starting to uncover their role in information processing. Astrocytes maintain a close bidirectional communication with neurons to modify neuronal network excitability, transmission, axonal conduction, and plasticity through various mechanisms including the release of gliotransmitters or local ion homeostasis. Astrocytes have been significantly studied in the context of long-term or short-term synaptic plasticity, but this is not the only mechanism involved in memory formation. Plasticity of intrinsic neuronal excitability also participates in memory storage through regulation of voltage-gated ion channels or axonal morphological changes. Yet, the contribution of astrocytes to these other forms of non-synaptic plasticity remains to be investigated. In this review, we summarized the recent advances on the role of astrocytes in different forms of plasticity and discuss new directions and ideas to be explored regarding astrocytes-neuronal communication and regulation of plasticity.

The rules governing changes in synaptic and intrinsic plasticity are diverse and complex, sometimes synergistic and sometimes not (Debanne et al., 2019). Most studies have been neuro-centric, despite growing evidence that astrocytes can intervene or interact to modify or modulate synaptic transmission (Araque et al., 1998; Jourdain et al., 2007; Bonansco et al., 2011), input integration, neuronal excitability (Tan et al., 2017), spike waveform or axonal conductivity (Sasaki et al., 2011; Lezmy et al., 2021). Astrocytes can detect neuronal activity, and depending on the firing rate of action potentials (APs), they can not only release gliotransmitters such as adenosine or glutamate (Hamilton et al., 2008; Lezmy et al., 2021), but also trigger intracellular calcium ([Ca2+]i) oscillations at different frequencies (Pasti et al., 1997).

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