Researchers from Austria and the U.S. have designed a new type of quantum computer that uses fermionic atoms to simulate complex physical systems. The processor uses programmable neutral atom arrays and is capable of simulating ...
Rice University physicists have shown that immutable topological states, which are highly sought for quantum computing, can be entangled with other manipulable quantum states in some materials.
When your laptop or smartphone heats up, it's due to energy that's lost in translation. The same goes for power lines that transmit electricity between cities. In fact, around 10 percent of the generated energy is lost in ...
Excitons are electron-hole pairs in semiconductors that are electrostatically bound by strong Coulombic interactions. In ultrathin 2D semiconductors that are a few atoms thick (typically ~0.7 nm), the decreased z-dimension ...
Chiral spin liquids are one of the most fascinating phases of matter ever imagined by physicists. These exotic liquids exhibit quasi-particles known as non-Abelian anyons that are neither bosons nor fermions, and whose manipulation ...
If you know the atoms that compose a particular molecule or solid material, the interactions between those atoms can be determined computationally, by solving quantum mechanical equations—at least, if the molecule is small ...
A model system created by stacking a pair of monolayer semiconductors is giving physicists a simpler way to study confounding quantum behavior, from heavy fermions to exotic quantum phase transitions.
Polarons are localized quasiparticles that result from the interaction between fermionic particles and bosonic fields. Specifically, polarons are formed when individual electrons in crystals distort their surrounding atomic ...
In condensed matter systems, an essential characteristic of electrons besides charge and spin is the orbital degree of freedom (ODoF). It plays a crucial role in understanding unconventional properties in solid-state materials ...
Architectures based on artificial neural networks (ANNs) have proved to be very helpful in research settings, as they can quickly analyze vast amounts of data and make accurate predictions. In 2020, Google's British AI subsidiary ...
