Lifeboat Foundation

Collections of mobile, interacting objects—flocks of birds, colonies of bacterial, or teams of robots—can sometimes behave like solid materials, executing organized rotations or gliding coherently in one direction. But why such systems display one kind of collective organization rather than another has remained unclear. Now researchers have developed a theory that can predict the pattern most likely to emerge under specific conditions [1]. The theory, they hope, may be of use in designing living and artificial materials that can autonomously adapt to their environment.

An “active material” is any system made up of interacting objects able to move under their own power, such as animals, cells, or robots. In so-called active solids, a subset of active materials, strong cohesion between neighboring elements makes the collective act somewhat like a solid. Examples include clusters of certain cell types and networks of robots with rigid connections.

Active solids can display several kinds of collective, organized motion, says Claudio Hernández-López, a PhD student at the École Normale Supérieure and Sorbonne University in France. For example, researchers have observed both coherent rotations and coherent translations in collections of microbes from the phylum Placozoa. Existing theories, however, fail to explain pattern selection—why, if several patterns are possible, does one pattern of behavior emerge rather than another?

Primordial black holes (PBHs)—hypothetical objects formed by the gravitational collapse of dense regions in the early Universe—have been invoked as dark-matter candidates. But for PBHs to constitute all dark matter, they’d have to be extremely light, possibly weighing less than small asteroids. Now Elba Alonso-Monsalve and David Kaiser of the Massachusetts Institute of Technology show that these diminutive PBHs could possess an exotic property—a net color charge (such a charge characterizes quarks and gluons in quantum chromodynamics theory) [1]. Such color-charged PBHs might have left potentially observable signatures, says Kaiser.

Observations rule out that stellar-mass PBHs could fully explain dark matter, but PBHs weighing between 10¹⁷ and 10²² g remain viable candidates. Since a PBH’s mass should relate to its age, this mass range corresponds to PBH formation immediately after the big bang, when the Universe was still a hot plasma of unconfined quarks and gluons. Most PBHs would have formed by engulfing large numbers of quarks and gluons having a distribution of color charges. These PBHs would be color-charge neutral and sufficiently massive to live until today. However, the duo’s calculations show that a few PBHs could have formed from regions so tiny that the charges of the absorbed gluons would be correlated, giving these PBHs a net charge.

Color-charged black holes have long been considered to be mathematically possible, but the new study is the first to propose a realistic formation mechanism, says Kaiser. The small sizes imply that they would have since evaporated. Yet their presence in the early Universe might have disrupted the distribution of protons and neutrons when the big bang created the first nuclear isotopes, leaving subtle traces in the cosmic abundance of the elements.

On 5 July 2022, protons began colliding again in the LHCb detector after a three-and-a-half-year break known as Long Shutdown 2 (LS2), marking the start of the third run of the Large Hadron Collider (LHC).

During this period, the original LHCb detector at the LHC was largely dismantled and an almost completely new detector constructed. The 2020 update of the European Strategy for Particle Physics approved by the CERN Council strongly supported exploiting the full potential of the LHC for studying flavor physics.

A further upgrade of the LHCb detector, known as Upgrade II, is planned to allow LHCb to operate at a much higher instantaneous luminosity and cope with the demanding data-taking conditions of the High-Luminosity LHC (HL-LHC). The latest technological developments will be taken into account to design the new detectors.

A simple concept of decay and fission of “magnetic quivers” helps to clarify complex quantum physics and mathematical structures.

Researchers employed magnetic quivers to delve into the fundamentals of quantum physics, specifically through the lens of supersymmetric quantum field theories. They have provided a novel interpretation of the Higgs mechanism, illustrating how particles gain mass and the potential decay and fission within QFTs.

Pioneering Quantum Physics Study

Discover the groundbreaking Self-Interacting Dark Matter (SIDM) theory that suggests dark matter particles might collide and interact with each other. Learn how recent studies on the El Gordo galaxy cluster support this revolutionary idea, potentially changing our understanding of the universe’s structure and evolution. Dive into the cosmic dance and stay updated with the latest space discoveries!

Chapters:
00:00 Introduction.
00:44 The Dance of Self-Interacting Dark Matter.
02:39 Unveiling the Strengths and Weaknesses of CDM and SIDM
05:14 Exploring Dark Matter: Methods and Future Prospects.
09:20 Outro.
09:37 Enjoy.

Continue reading “New Theory Changes Everything: SIDM and Dark Matter Collision!” »

The authors show that dipolar condensates are prevalent in bosonic systems due to a self-proximity effect. Furthermore, they propose a new type of Josephson effect called dipolar Josephson effect, where a supercurrent of dipoles happens in the absence of particle flow.

Currently, computing technologies are rapidly evolving and reshaping how we imagine the future. Quantum computing is taking its first toddling steps toward delivering practical results that promise unprecedented abilities. Meanwhile, artificial intelligence remains in public conversation as it’s used for everything from writing business emails to generating bespoke images or songs from text prompts to producing deep fakes.

Some physicists are exploring the opportunities that arise when the power of machine learning — a widely used approach in AI research—is brought to bear on quantum physics. Machine learning may accelerate quantum research and provide insights into quantum technologies, and quantum phenomena present formidable challenges that researchers can use to test the bounds of machine learning.

When studying quantum physics or its applications (including the development of quantum computers), researchers often rely on a detailed description of many interacting quantum particles. But the very features that make quantum computing potentially powerful also make quantum systems difficult to describe using current computers. In some instances, machine learning has produced descriptions that capture the most significant features of quantum systems while ignoring less relevant details—efficiently providing useful approximations.

The expansion of the universe has been a well-established fact of physics for almost a century. By the turn of the millennium the rate of this expansion, referred to as the Hubble constant (H ₀), had converged to a value of around 70 km s ^–1 Mpc ^–1. However, more recent measurements have given rise to a tension: whereas those derived from the cosmic microwave background (CMB) cluster around a value of 67 km s ^–1 Mpc ^–1, direct measurements using a local distance-ladder (such as those based on Cepheids) mostly prefer larger values around 73 km s ^–1 Mpc ^–1. This disagreement between early-and late-universe measurements, respectively, stands at the 4–5 σ level, thereby calling for novel measurements.

One such source of new information are large galaxy surveys, such as the one currently being performed by the Dark Energy Spectroscopic Instrument (DESI). This Arizona-based instrument uses 5,000 individual robots that optimise the focal plane of the detector to allow it to measure 5,000 galaxies at the same time. The goal of the survey is to provide a detailed 3D map, which can be used to study the evolution of the universe by focussing on the distance between galaxies. During its first year of observation, the results of which have now been released, DESI has provided a catalogue of millions of objects.

Small fluctuations in the density of the early universe resulted not only in signatures in the CMB, as measured for example by the Planck probe, but also left imprints in the distribution of baryonic matter. Each over-dense region is thought to contain dark matter, baryonic matter and photons. The gravitational force from dark matter on the baryons is countered by radiation pressure from the photons. From the small over-densities, baryons are dragged along by photon pressure until these two types of particles decoupled during the recombination era. The original location of the over-density is surrounded by a sphere of baryonic matter, which typically is at a distance referred to as the sound horizon. The sound horizon at the moment of decoupling, denoted r _d, leaves an imprint that has since evolved to produce the density fluctuations in the universe that seeded large-scale structures.

Calcium oxide is a cheap, chalky chemical compound commonly used in the manufacturing of cement, plaster, paper, and steel. But the material may soon have a more high-tech application.

UChicago Pritzker School of Molecular Engineering researchers and their collaborator in Sweden have used theoretical and computational approaches to discover how tiny, lone atoms of bismuth embedded within solid calcium oxide can act as qubits — the building blocks of quantum computers and quantum communication devices.

These qubits are described in Nature Communications (“Discovery of atomic clock-like spin defects in simple oxides from first principles”).