A new approach focuses uncertainty quantification in neural operator models on key structural components, improving the accuracy and efficiency of predictions for complex physical systems.
![As a system approaches an electronic quantum critical point, phonon softening and renormalization of the long-wavelength dispersion increase the density of low-energy phonon states, with the thermally excited phonon phase-space volume scaling as [latex]T^{d/z_p}[/latex], where [latex]d[/latex] represents spatial dimension and [latex]z_p[/latex] is the phonon dynamical exponent-a larger [latex]z_p[/latex] indicating a greater low-energy phonon phase space and, consequently, increased scattering potential, particularly when [latex]z_p > d[/latex].](https://arxiv.org/html/2603.11176v1/x1.png)
New research explores whether the softening of atomic vibrations driven by electronic quantum criticality can account for the unusual linear temperature dependence observed in certain metallic materials.
Apparently, corporate treasuries are now the cool kids in the Bitcoin playground, swinging their satchels of cash around like it’s no big deal. Publicly traded companies are tapping into stock and preferred-share financing faster than I can say “market bubble.” And according to industry bigwigs like Blockstream CEO Adam Back, these firms are on track to buy up 10 times the daily mined Bitcoin supply. Because, you know, why not?
![The distributions of B(GT(-)) transition strengths in [latex]^{16}C[/latex] nuclei were analyzed using the SkP, SLy4, and SGII parameterizations, demonstrating the sensitivity of these spectroscopic properties to the chosen nuclear force model.](https://arxiv.org/html/2603.11429v1/x15.png)
A new study delves into the subtle interplay of shape and structure within carbon isotopes to better understand the forces governing nuclear decay.
Renewed strength in bitcoin relative to U.S. equities is fueling optimism about a potential shift in crypto market sentiment. Coinbase Institutional, part of crypto exchange Coinbase (Nasdaq: COIN), shared analysis on social media platform X on March 13, highlighting bitcoin’s stronger performance and improving market participation. “Ah, the old adage: when the markets tremble, the crypto crowd dances.”
Researchers are demonstrating a way to steer large language models towards creating more secure code by directly influencing their internal thought processes.
A new approach to managing memory in large language models prioritizes the position of data, not just the data itself, enabling more efficient processing of extended text.
Last week, our Virginia-based hero added 17,994 BTC to its collection, dropping $1.28 billion like it’s hot. Average price? A cool $70,946 per coin. That’s right, 102nd purchase, 11th straight week of “I’m definitely not panicking” energy. Someone get this company a shopping intervention.
Per court docs, the company allegedly overcharged California users aged 29+ for Gold plans between 2015 and 2016. The lawsuit, led by some guy named Allan Candelore (a name that sounds like it belongs on a Seinfeld episode), claimed this violated California’s Unruh Act. Tinder, of course, denies everything-because admitting guilt would require a soul.
![The study demonstrates that jailbreak success against Llama-3.1-8B-Instruct exhibits diminishing returns with increased attack compute (measured in FLOPs), following a saturating exponential relationship formalized in [latex]Eq. (7)[/latex], as evidenced by the convergence of average red-team scores (ASR) despite escalating computational effort.](https://arxiv.org/html/2603.11149v1/x1.png)
New research reveals predictable patterns in how effectively attackers can circumvent safeguards in large language models, offering a surprising look at the economics of AI security.