Quantum Annealers Get the Heat Treatment

New research reveals how accurately these specialized quantum computers mimic thermal sampling, and identifies systematic errors in temperature readings.

New research reveals how accurately these specialized quantum computers mimic thermal sampling, and identifies systematic errors in temperature readings.

A new theoretical framework reveals how to engineer entanglement in multi-photon states generated through high-harmonic generation by precisely controlling laser parameters.

New research demonstrates that cubic phase states can surpass the sensitivity of conventional Gaussian states in quantum metrology, paving the way for more accurate measurements.

New research shows that harnessing the unique properties of non-Gaussian quantum states can significantly improve the precision of temperature measurements in noisy quantum systems.

A new framework clarifies the behavior of quantum superchannels, offering a powerful lens for understanding complex quantum processes.

Researchers have devised a streamlined method for determining the initial state of a quantum walk by strategically measuring absorption at multiple points along its path.

A new analysis contrasts leading interpretations of quantum mechanics, advocating for a pragmatic focus on empirical observation over the pursuit of a fully realized underlying reality.

Researchers have demonstrated a novel method for dynamically controlling interactions between light and magnetic spin waves across significant distances, paving the way for advanced quantum devices.

Researchers have successfully simulated key properties of fundamental particles using a noisy quantum computer, paving the way for more complex quantum simulations in high-energy physics.
![Quantum circuits are designed to estimate specific terms-namely, $-\frac{1}{2}\left\langle\left\{O,\Phi\_{\theta}(G\_{j})\right\}\right\rangle\_{\rho\_{\theta}}$ and $-\frac{i}{2}\left\langle\left[O,\Psi\_{\phi}(H\_{k})\right]\right\rangle\_{\omega\_{\theta,\phi}}$-through probabilistic sampling; the first utilizes a high-peak probability density $p(t)$ to select a random real value $t$, while the second employs uniform sampling from the unit interval $[0,1]$, leveraging gates such as Hadamard and the phase gate $S\coloneqq\begin{bmatrix}1&0\\ 0&i\end{bmatrix}$ to facilitate these estimations.](https://arxiv.org/html/2512.02721v1/x1.png)
Researchers have developed a practical method for training quantum Boltzmann machines, paving the way for new generative models.