Dirac Solutions (United States)

© The Author(s) 2025. Published by Oxford University Press on behalf of the Microscopy Society of America.

One of the open challenges in quantum computing is to find meaningful and practical methods to leverage quantum computation to accelerate classical machine-learning workflows. A ubiquitous problem in machine-learning workflows is sampling from probability distributions that we only have access to via their log probability. To this end, we extend the well-known Hamiltonian Monte Carlo (HMC) method for Markov chain Monte Carlo (MCMC) sampling to leverage quantum computation in a hybrid manner as a proposal function. Our new algorithm, Quantum Dynamical Hamiltonian Monte Carlo (QD-HMC), replaces the classical symplectic integration proposal step with simulations of quantum-coherent continuous-space dynamics on digital or analog quantum computers. We show that QD-HMC maintains key characteristics of HMC, such as maintaining the detailed balanced condition with momentum inversion, while also having the potential for polynomial speedups over its classical counterpart in certain scenarios. As sampling is a core subroutine in many forms of probabilistic inference, and MCMC in continuously parametrized spaces covers a large class of potential applications, this work widens the areas of applicability of quantum devices. Published by the American Physical Society 2024

The construction industry is known for its inherent risks, contributing to ~170,000 workplace injuries and illnesses annually in the United States. Engaging in prejob safety discussions presents a crucial chance to safeguard workers by proactively recognizing hazards and ensuring that crews are well-oriented with safety protocols before commencing work each day. However, research shows prejob meetings are often conducted hastily without the depth required to fully uncover risks. This study examines the characteristics that distinguish high-impact, high-quality prejob safety conversations from lower- quality counterparts. Strategies are provided for improving engagement, psychological safety, hazard analysis, accountability, and leadership support to transform safety talks into dynamic interactions that empower employees to operate safely. Additionally, this study reviews leading-edge artificial intelligence techniques, enabling construction firms to capture, analyze, and optimize their daily planning conversations at scale to drive safety excellence. Implementing the evidence-based strategies discussed allows organizations to realize the immense potential of prejob conversations for preventing injuries and fatalities.

In this study, we present an efficient integral decomposition approach called the restricted-kinetic-balance resolution-of-the-identity (RKB-RI) algorithm, which utilizes a tunable RI method based on the Cholesky integral decomposition for in-core relativistic quantum chemistry calculations. The RKB-RI algorithm incorporates the restricted-kinetic-balance condition and offers a versatile framework for accurate computations. Notably, the Cholesky integral decomposition is employed not only to approximate symmetric large-component electron repulsion integrals but also those involving small-component basis functions. In addition to comprehensive error analysis, we investigate crucial conditions, such as the kinetic balance condition and variational stability, which underlie the applicability of Dirac relativistic electronic structure theory. We compare the computational cost of the RKB-RI approach with the full in-core method to assess its efficiency. To evaluate the accuracy and reliability of the RKB-RI method proposed in this work, we employ actinyl oxides as benchmark systems, leveraging their properties for validation purposes. This investigation provides valuable insights into the capabilities and performance of the RKB-RI algorithm and establishes its potential as a powerful tool in the field of relativistic quantum chemistry.

The perceptual phenomenon of change blindness has been widely researched in the scientific literature, mostly in laboratory studies. This case study reviews the fatal shooting of a woman who suddenly backed her car in the general direction of law enforcement officers as other officers were attempting to extract her from the car. The deputy who eventually fired at the woman initially had his TASER drawn; when he perceived the car reversing toward officers, he tried to holster his TASER before drawing and firing his handgun. By the time the deputy fired, the woman had stopped reversing and was driving the car forward (i.e., not toward officers). Even after viewing police in-car-camera video, the deputy was adamant that he perceived the car as still moving backward when he fired. The facts are compared to the characteristics of change blindness and other human factors potentially at play.

Military operations often require Service Members (SMs) to make life-and-death decisions based on information they can only obtain auditorily. However, the wide variety of critical sounds, essential spoken messages, and masking environments encountered while performing military missions makes it difficult to use clinical tests to predict the operational performance of hearing-impaired SMs. In this study, ≈2400 SMs performed listening tasks derived from binaural recordings made during realistic battlefield exercises at the US Army Joint Readiness Training Center. The listening tasks included standardized speech recognition tasks based on the Oldenburg Matrix Test and Modified Rhyme Test (MRT), as well as scenario-based multiple-choice tasks where questions were asked about unmodified verbal exchanges that occurred between SMs engaged in the battlefield simulation. The scores SMs achieved on these operational tasks were then compared to their hearing thresholds and to their scores on the MRT80. The results show that an auditory fitness-for-duty standard that requires individuals with thresholds that exceed the values defined in the new US Army H3 Profile to obtain a minimum score on the MRT80 is generally able to identify individuals who are most at risk of performing abnormally poorly on militarily relevant listening tasks. [The views expressed in this abstract are those of the authors and do not reflect the official policy of the Department of the Army, Department of Defense, or U.S. Government.]

Makes ArviZ an optional dependency and adds minimum Python version (3.6).

See the changelog for release notes.

We present ZTF20aajnksq (AT2020blt), a fast-fading ($\Delta r=2.4$ mag in $\Delta t=1.3$ days) red ($g-r\approx0.6$ mag) and luminous ($M_{1626}=-25.9$) optical transient at $z=2.9$ discovered by the Zwicky Transient Facility (ZTF). AT2020blt shares several features in common with afterglows to long-duration gamma-ray bursts (GRBs): (1) an optical light curve well-described by a broken power-law with a break at $t_\mathrm{j}=1$ day (observer-frame); (2) a luminous $(L_X = 10^{46}$ $\mathrm{erg}$ $\mathrm{s}^{-1})$ X-ray counterpart; and (3) luminous ($L_\nu = 4 \times 10^{31}$ $\mathrm{erg}$ $\mathrm{sec}^{-1}$ $\mathrm{Hz}^{-1}$ at 10 GHz) radio emission. However, no GRB was detected in the 0.74d between the last ZTF non-detection ($r > 20.64$) and the first ZTF detection ($r = 19.57$), with an upper limit on the isotropic-equivalent gamma-ray energy release of $E_{\gamma,\mathrm{iso}} < 7 \times 10^{52}$ erg. AT2020blt is thus the third afterglow-like transient discovered without a detected GRB counterpart (after PTF11agg and ZTF19abvizsw) and the second (after ZTF19abvizsw) with a redshift measurement. We conclude that the properties of AT2020blt are consistent with a classical (initial Lorentz factor $\Gamma_0 \gtrsim 100$) on-axis GRB that was missed by high-energy satellites. Furthermore, by estimating the rate of transients with light curves similar to that of AT2020blt in ZTF high-cadence data, we agree with previous results that there is no evidence for an afterglow-like phenomenon that is significantly more common than classical GRBs. We conclude by discussing the status and future of fast-transient searches in wide-field high-cadence optical surveys.