People selectively help others based on perceptions of their merit or need. Here, we develop a neurocomputational account of how these social perceptions translate into social choice. Using a novel fMRI social perception task, we show that both merit and need perceptions recruited the brain's social inference network. A behavioral computational model identified two non-exclusive mechanisms underlying variance in social perceptions: a consistent tendency to perceive others as meritorious/needy (bias) and a propensity to sample and integrate normative evidence distinguishing high from low merit/need in other people (sensitivity). Variance in people's merit (but not need) bias and sensitivity independently predicted distinct aspects of altruism in a social choice task completed months later. An individual's merit bias predicted context-independent variance in people's overall other-regard during altruistic choice, biasing people toward prosocial actions. An individual's merit sensitivity predicted context-sensitive discrimination in generosity toward high and low merit recipients by influencing other- and self-regard during altruistic decision-making. This context-sensitive perception-action link was associated with activation in the right temporoparietal junction. Together, these findings point toward stable, biologically based individual differences in perceptual processes related to abstract social concepts like merit, and suggest that these differences may have important behavioral implications for an individual's tendency toward favoritism or discrimination in social settings.

Due to the presence of flat Chern bands, moiré transition-metal dichalcogenide (TMD) bilayers are a platform to realize strongly correlated topological phases of fermions such as fractional Chern insulators. TMDs are also known to host long-lived excitons, which inherit the topology of the underlying Chern bands. For the particular example of MoTe2/WSe2 heterobilayers we perform a time-dependent Hartree-Fock calculation to identify a regime in the phase diagram where the excitons themselves form a topological flat band. This paves a way towards realizing strongly correlated states of bosons in moiré TMDs. Published by the American Physical Society 2025

Partial molar volumes ( V¯) of SiO2, K2O, Na2O, Li2O and BaO have been re-evaluated in binary silicate melts at 1673 K. Volumetrically, the SiO2 component mixes ideally in K2O-SiO2 melts but mixes non-ideally in Li, Na and Ba melts, with V¯SiO2 displaying maxima between ~80–95 mole% SiO2. K2O partial molar volumes ( V¯K2O) display weak, non-ideal behaviour in K2O-SiO2 melts due to electrostriction, where tetrahedra collapse around the modifier cation, K+, in response to K-O Coulombic attraction. V¯Na2O, V¯Li2O and V¯BaO also behave non-ideally in their respective binary melts due to electrostriction. The combined effects of non-ideal mixing of SiO2 and electrostriction associated with the modifier cations result in molar volumes of the four melts being less than expected for ideal mixing. The extent of non-ideal volumetric mixing in the binary melts increases in the order K<Na<Li<Ba, which is the same as the order of the consolute temperatures of the miscibility gaps for these binary melts. The similar order leads us to suggest that non-ideal volumetric mixing results from the same chemical interactions that give rise to melt immiscibility and that these interactions are due primarily to non-ideal behaviour of the SiO2 component. The non-ideal volumetric mixing behaviour required use of quadratic expressions to fit molar volume-compositional trends of the four melt systems studied. Although mixing is non-ideal, the partial molar volumes of SiO2 and modifier oxides are remarkably similar to values obtained from linear mixing models for melts containing ~45–70 wt.% SiO2. Pronounced effects of non-ideal mixing are mostly restricted to highly siliceous melts (XSiO2>0.75) where V¯SiO2 values are appreciably greater than the molar volume of liquid SiO2 (V°SiO2), which is ~26.75 cm3/mole at 1673 K. The findings are consistent with volumetric (density) studies of highly siliceous (haplogranitic) melts.

The recent discovery of ultralong wavelength gravitational waves through the advent of pulsar timing arrays (PTA) has opened up new avenues for fundamental science. Here we show that every PTA source will be diffractively lensed by potentially hundreds of galactic disks transverse to its line of sight, leading to modest modulations in the strain, Δh/h∼10^{-3}λ_{1 pc}^{-1}, due to wave lensing effects. The induced interference, or scintillation, pattern will be resolvable by coherent PTAs and may be leveraged, alongside foreground redshift information, to make precise measurements of cosmic expansion. If future PTA experiments can achieve enough signal to noise to detect these small modulations, hundreds of redshift-distance pairs may be inferred from the diffractive lensing of an individual PTA source.

We investigate the optimal clearing policy for a financial payment system composed of a number of member banks and a central bank in a dynamic setting, when new payment obligations or debts between member banks are generated over time. The central bank clears the debts among members in the system in order to minimize the costs, including the setup cost of each clearing, the variable cost of clearing the net debts, and the liquidity cost of uncleared debts. We formulate the problem using dynamic programming via state space reduction that provides a tractable framework to analyze and compute the optimal policy. We characterize the structure of the optimal policy and show that it is optimal for the central bank either to clear all the debts in the system or not to clear at all in each period under mild conditions. This structure leads to efficient computation of the optimal clearing policy. We further characterize the optimal clearing frequency based upon the deterministic approximation for the debt process. We conduct a comprehensive case study based on the data acquired from our industry partner, Payments Canada, to demonstrate the performance of the policy and its feasibility in industrial-size problems. This paper was accepted by Chung Piaw Teo, optimization. Funding: S. Chen’s research was supported by the National Natural Science Foundation of China [Grants 72101273, 72188101, 72101258, and 71991463], the Humanities and Social Science General Foundation of the Ministry of Education of China [Grant 21YJC630008], and the Hunan Provincial Natural Science Foundation of China [Grant 2022JJ40643]. Support for O. Baron’s research on this paper was provided by a grant from the Natural Science and Engineering Research Council of Canada (NSERC). N. Chen’s research was supported by the NSERC [Discovery Grant RGPIN-2020-04038]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00380 .