20 independently authored research notes and primary sources.
The researchers describe a system for turning scientific papers and associated resources into interactive AI agents. The work raises questions about how reliable executable paper assistants can be and how their outputs should be checked.
This study investigates how confidence-related signals affect language-model decisions about when to answer or abstain. It provides experimental evidence that changes to such signals can influence model behaviour.
The study presents an AI-agent arrangement using two smaller cooperating models for materials-research tasks. It examines a way to combine reasoning and scientific tool use without relying only on very large models.
Researchers investigate controlling robotic operation using physical wave-based neuromorphic hardware. The work explores how unconventional computing devices might contribute to autonomous control.
This paper explores quantum-field-theory dynamics using a hybrid computing platform with spins and phonons. The study illustrates the use of different quantum degrees of freedom in physical simulation.
The authors investigate string-breaking phenomena using an engineered quantum simulator. It connects controlled laboratory dynamics with phenomena studied in lattice gauge theories.
The paper reports an approach to quantum random-access memory demonstrated on superconducting quantum hardware. Quantum information can be addressed through a cascaded memory design.
This work uses a hybrid qubit–oscillator architecture to investigate interference associated with a lattice gauge theory. It provides an example of controlled analogies between quantum information hardware and theoretical physics.
The study examines chemical passivation of defects in perovskite solar-cell materials using sterically controlled Lewis acid–base interactions. It addresses an important part of semiconductor-device materials research.
Researchers investigate the synthesis and properties of semiconducting two-dimensional metal–organic frameworks using directional chemical design. The work contributes to tunable electronic materials.
This astronomy study examines chemical evidence in a metal-poor galaxy environment from near the end of cosmic reionization. Such observations can inform investigations of early stellar populations.
The authors use fast radio bursts as probes of the cosmic matter distribution. The study explores implications for understanding how astrophysical processes influence matter clustering.
This molecular-biology study investigates how specific patient-derived BRCA1 mutations affect genome stability and distinct protein functions. It adds mechanistic evidence to research on DNA repair.
NanoTS is presented as a deep-learning approach to detecting single-nucleotide changes from nanopore long-read transcriptome sequencing. The work sits at the intersection of genomics and computational methods.
This paper introduces an approach for balancing fine-grained pixel information and broader context in automated biological-image segmentation. It focuses on improving computational analysis of microscopy images.
The researchers analyze genetic variation across sheep breeds distributed in different climates. The work examines genomic patterns relevant to environmental adaptation and vulnerability.
The study evaluates relationships between tree establishment, soil biological communities and carbon storage across sites. It brings ecosystem and climate-related outcomes into a common framework.
This study uses generative AI to design protein domains involved in non-ribosomal peptide synthesis. It explores whether computational protein design can help reprogram biochemical assembly systems.
The authors investigate a thermophone-based ultrasonic sonar method intended to work amid drone flight noise. It combines acoustic sensing, hardware and signal processing.
This theoretical study proposes a strengthened quantum uncertainty relation including an additional term related to noncommutativity. The result supplies a new perspective on bounds involving quantum observables.