From Bar Ilon University and Riken via Science Alert: “Physicists Have Finally Built a Quantum X-Ray Device”

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From Bar Ilon University

and

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From RIKEN

via

ScienceAlert

Science Alert

2 SEP 2019
MICHELLE STARR

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(APS/Alan Stonebraker)

A team of researchers has just demonstrated quantum enhancement in an actual X-ray machine, achieving the desirable goal of eliminating background noise for precision detection.

The relationships between photon pairs on quantum scales can be exploited to create sharper, higher-resolution images than classical optics. This emerging field is called quantum imaging, and it has some really impressive potential – particularly since, using optical light, it can be used to show objects that can’t usually be seen, like bones and organs.

Quantum correlation describes a number of different relationships between photon pairs. Entanglement is one of these, and is applied in optical quantum imaging.

But the technical challenges of generating entangled photons in X-ray wavelengths are considerably greater than for optical light, so in the building of their quantum X-ray, the team took a different approach.

They used a technique called quantum illumination to minimise background noise. Usually, this uses entangled photons, but weaker correlations work, too. Using a process called parametric down-conversion (PDC), the researchers split a high-energy – or “pump” – photon into two lower-energy photons, called a signal photon and an idler photon.

“X-ray PDC has been demonstrated by several authors, and the application of the effect as a source for ghost imaging has been demonstrated recently,” the researchers write in their paper.

“However, in all previous publications, the photon statistics have not been measured. Essentially, to date, there is no experimental evidence that photons, which are generated by X-ray PDC, exhibit statistics of quantum states of radiation. Likewise, observations of the quantum enhanced measurement sensitivity have never been reported at X-ray wavelengths.”

The researchers achieved their X-ray PDC with a diamond crystal. The nonlinear structure of the crystal splits a beam of pump X-ray photons into signal and idler beams, each with half the energy of the pump beam.

Normally, this process is very inefficient using X-rays, so the team scaled up the power. Using the SPring-8 synchrotron in Japan, they shot a 22 KeV beam of X-rays at their crystal, which split into two beams, each carrying 11 KeV.

SPring-8 synchrotron


SPring-8 synchrotron, located in Hyōgo Prefecture, Japan

The signal beam is sent towards the object to be imaged – in the case of this research, a small piece of metal with three slits – with a detector on the other side. The idler beam is sent straight to a different detector. This is set up so that each beam hits its respective detector at the same place and at the same time.

“The perfect time-energy relationship we observed could only mean that the two photons were quantum correlated,” said physicist Sason Sofer of Bar-Ilan University in Israel.

For the next step, the researchers compared their detections. There were only around 100 correlated photons per point in the image, and around 10,000 more background photons. But the researchers could match each idler to a signal, so they could actually tell which photons in the image were from the beam, thus easily separating out the background noise.

They then compared these images to images taken using regular, non-correlated photons – and the correlated photons clearly produced a much sharper image.

It’s early days yet, but it’s definitely a step in the right direction for what could be a greatly exciting tool. Quantum X-ray imaging could have a number of uses outside the range of current X-ray technology.

One promise is that it could lower the amount of radiation required for X-ray imaging. This would mean that samples easily damaged by X-rays could be imaged, or samples that require low temperatures; less radiation would mean less heat. It could also enable physicists to X-ray atomic nuclei to see what’s inside.

Obviously, since these quantum X-rays require a hardcore particle accelerator, medical applications are currently off the table. The team has demonstrated that it can be done, but scaling down is going to be tricky.

Currently, determining whether the photons are entangled is the next step. That would require the photons’ arrival at the detectors to be measured within attosecond scales, which is beyond our current technology.

Still, this is a pretty amazing achievement.

“We have demonstrated the ability to utilise the strong time-energy correlations of photon pairs for quantum enhanced photodetection. The procedure we have presented possesses great potential for improving the performances of X-ray measurements,” the researchers write.

“We anticipate that this work will open the way for more quantum enhanced x-ray regime detection schemes, including the area of diffraction and spectroscopy.”

The research has been published in Physical Review X.

See the full article here .


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From Lawrence Berkeley National Lab: “Is your Supercomputer Stumped? There May Be a Quantum Solution”

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From Lawrence Berkeley National Lab

August 1, 2019
Glenn Roberts Jr.
geroberts@lbl.gov
(510) 486-5582

Berkeley Lab-led team solves a tough math problem with quantum computing.

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(Credit: iStock/metamorworks)

Some math problems are so complicated that they can bog down even the world’s most powerful supercomputers. But a wild new frontier in computing that applies the rules of the quantum realm offers a different approach.

A new study led by a physicist at Lawrence Berkeley National Laboratory (Berkeley Lab), published in the journal Scientific Reports, details how a quantum computing technique called “quantum annealing” can be used to solve problems relevant to fundamental questions in nuclear physics about the subatomic building blocks of all matter. It could also help answer other vexing questions in science and industry, too.

Seeking a quantum solution to really big problems

“No quantum annealing algorithm exists for the problems that we are trying to solve,” said Chia Cheng “Jason” Chang, a RIKEN iTHEMS fellow in Berkeley Lab’s Nuclear Science Division and a research scientist at RIKEN, a scientific institute in Japan.

“The problems we are looking at are really, really big,” said Chang, who led the international team behind the study, published in the Scientific Reports journal. “The idea here is that the quantum annealer can evaluate a large number of variables at the same time and return the right solution in the end.”

The same problem-solving algorithm that Chang devised for the latest study, and that is available to the public via open-source code, could potentially be adapted and scaled for use in systems engineering and operations research, for example, or in other industry applications.

Classical algebra with a quantum computer

“We are cooking up small ‘toy’ examples just to develop how an algorithm works. The simplicity of current quantum annealers is that the solution is classical – akin to doing algebra with a quantum computer. You can check and understand what you are doing with a quantum annealer in a straightforward manner, without the massive overhead of verifying the solution classically.”

Chang’s team used a commercial quantum annealer located in Burnaby, Canada, called the D-Wave 2000Q that features superconducting electronic elements chilled to extreme temperatures to carry out its calculations.

Access to the D-Wave annealer was provided via the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory (ORNL).

“These methods will help us test the promise of quantum computers to solve problems in applied mathematics that are important to the U.S. Department of Energy’s scientific computing mission,” said Travis Humble, director of ORNL’s Quantum Computing Institute.

Quantum data: A one, a zero, or both at the same time

There are currently two of these machines in operation that are available to the public. They work by applying a common rule in physics: Systems in physics tend to seek out their lowest-energy state. For example, in a series of steep hills and deep valleys, a person traversing this terrain would tend to end up in the deepest valley, as it takes a lot of energy to climb out of it and the least amount of energy to settle in this valley.

The annealer applies this rule to calculations. In a typical computer, memory is stored in a series of bits that are occupied by either one or a zero. But quantum computing introduces a new paradigm in calculations: quantum bits, or qubits. With qubits, information can exist as either a one, a zero, or both at the same time. This trait makes quantum computers better suited to solving some problems with a very large number of possible variables that must be considered for a solution.

Each of the qubits used in the latest study ultimately produces a result of either a one or a zero by applying the lowest-energy-state rule, and researchers tested the algorithm using up to 30 logical qubits.

The algorithm that Chang developed to run on the quantum annealer can solve polynomial equations, which are equations that can have both numbers and variables and are set to add up to zero. A variable can represent any number in a large range of numbers.

When there are ‘fewer but very dense calculations’

Berkeley Lab and neighboring UC Berkeley have become a hotbed for R&D in the emerging field of quantum information science, and last year announced the formation of a partnership called Berkeley Quantum to advance this field.

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Berkeley Quantum

Chang said that the quantum annealing approach used in the study, also known as adiabatic quantum computing, “works well for fewer but very dense calculations,” and that the technique appealed to him because the rules of quantum mechanics are familiar to him as a physicist.

The data output from the annealer was a series of solutions for the equations sorted into columns and rows. This data was then mapped into a representation of the annealer’s qubits, Chang explained, and the bulk of the algorithm was designed to properly account for the strength of the interaction between the annealer’s qubits. “We repeated the process thousands of times” to help validate the results, he said.

“Solving the system classically using this approach would take an exponentially long time to complete, but verifying the solution was very quick” with the annealer, he said, because it was solving a classical problem with a single solution. If the problem was quantum in nature, the solution would be expected to be different every time you measure it.

Some math problems are so complicated that they can bog down even the world’s most powerful supercomputers. But a wild new frontier in computing that applies the rules of the quantum realm offers a different approach.

A new study led by a physicist at Lawrence Berkeley National Laboratory (Berkeley Lab), published in the journal Scientific Reports, details how a quantum computing technique called “quantum annealing” can be used to solve problems relevant to fundamental questions in nuclear physics about the subatomic building blocks of all matter. It could also help answer other vexing questions in science and industry, too.

Real-world applications for a quantum algorithm

As quantum computers are equipped with more qubits that allow them to solve more complex problems more quickly, they can also potentially lead to energy savings by reducing the use of far larger supercomputers that could take far longer to solve the same problems.

The quantum approach brings within reach direct and verifiable solutions to problems involving “nonlinear” systems – in which the outcome of an equation does not match up proportionately to the input values. Nonlinear equations are problematic because they may appear more unpredictable or chaotic than other “linear” problems that are far more straightforward and solvable.

Chang sought the help of quantum-computing experts in quantum computing both in the U.S. and in Japan to develop the successfully tested algorithm. He said he is hopeful the algorithm will ultimately prove useful to calculations that can test how subatomic quarks behave and interact with other subatomic particles in the nuclei of atoms.

While it will be an exciting next step to work to apply the algorithm to solve nuclear physics problems, “This algorithm is much more general than just for nuclear science,” Chang noted. “It would be exciting to find new ways to use these new computers.”

The Oak Ridge Leadership Computing Facility is a DOE Office of Science User Facility.

Researchers from Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, and the RIKEN Computational Materials Science Research Team also participated in the study.

The study was supported by the U.S. Department of Energy Office of Science; and by Oak Ridge National Laboratory and its Laboratory Directed Research and Development funds. The Oak Ridge Leadership Computing Facility is supported by the DOE Office of Science’s Advanced Scientific Computing Research program.

See the full article here .

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In the world of science, Lawrence Berkeley National Laboratory (Berkeley Lab) is synonymous with “excellence.” Thirteen Nobel prizes are associated with Berkeley Lab. Seventy Lab scientists are members of the National Academy of Sciences (NAS), one of the highest honors for a scientist in the United States. Thirteen of our scientists have won the National Medal of Science, our nation’s highest award for lifetime achievement in fields of scientific research. Eighteen of our engineers have been elected to the National Academy of Engineering, and three of our scientists have been elected into the Institute of Medicine. In addition, Berkeley Lab has trained thousands of university science and engineering students who are advancing technological innovations across the nation and around the world.

Berkeley Lab is a member of the national laboratory system supported by the U.S. Department of Energy through its Office of Science. It is managed by the University of California (UC) and is charged with conducting unclassified research across a wide range of scientific disciplines. Located on a 202-acre site in the hills above the UC Berkeley campus that offers spectacular views of the San Francisco Bay, Berkeley Lab employs approximately 3,232 scientists, engineers and support staff. The Lab’s total costs for FY 2014 were $785 million. A recent study estimates the Laboratory’s overall economic impact through direct, indirect and induced spending on the nine counties that make up the San Francisco Bay Area to be nearly $700 million annually. The Lab was also responsible for creating 5,600 jobs locally and 12,000 nationally. The overall economic impact on the national economy is estimated at $1.6 billion a year. Technologies developed at Berkeley Lab have generated billions of dollars in revenues, and thousands of jobs. Savings as a result of Berkeley Lab developments in lighting and windows, and other energy-efficient technologies, have also been in the billions of dollars.

Berkeley Lab was founded in 1931 by Ernest Orlando Lawrence, a UC Berkeley physicist who won the 1939 Nobel Prize in physics for his invention of the cyclotron, a circular particle accelerator that opened the door to high-energy physics. It was Lawrence’s belief that scientific research is best done through teams of individuals with different fields of expertise, working together. His teamwork concept is a Berkeley Lab legacy that continues today.

A U.S. Department of Energy National Laboratory Operated by the University of California.

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From RIKEN: “Light pulses provide a new route to enhance superconductivity”

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From RIKEN

March 4, 2019

Chief Scientist
Seiji Yunoki
Computational Condensed Matter Physics Laboratory
Chief Scientist Laboratories

Jens Wilkinson
RIKEN International Affairs Division
Tel: +81-(0)48-462-1225 / Fax: +81-(0)48-463-3687
Email: pr@riken.jp

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Schematic of eta-pairing

Materials known as Mott insulators are odd things. Under normal electron band theory they ought to conduct electricity, but they do not, due to interactions among their electrons. But now, scientists from the RIKEN Cluster for Pioneering Research have shown that pulses of light could be used to turn these materials beyond simple conductors to superconductors—materials that conduct electricity without energy loss. This process would happen through an unconventional type of superconductivity known as “eta pairing.”

Using numerical simulations, the researchers found that this unconventional type of conductivity, which is believed to take place under non-equilibrium conditions in strongly correlated materials such as high-Tc cuprates and iron-pnictides, arises due to a phenomenon known as eta pairing. This is different form the superconductivity observed in the same strongly correlated materials under equilibrium conditions, and is thought to involve repulsive interactions between certain electrons within the structure. It is also different from traditional superconductivity, where the phenomenon arises due to interactions between electrons and vibrations of the crystal structure, inducing mutual interactions between electrons through vibrations and thus overcoming the repulsion between the electrons.

Thirty years ago, the mathematical physicist Chen-Ning Yang originally proposed the idea of eta-pairing, but because it was a purely mathematical concept, it was understood as a virtual phenomenon that would not take place in the real world. But for the present study, the researchers used non-equilibrium dynamics to analyze the effect of pulses of light on a Mott insulator, and found that the effect would in fact happen in the real world. “What is interesting,” says first author Tatsuya Kaneko, a postdoctoral researcher at the RIKEN Cluster for Pioneering Research, “is that our calculations showed that this takes place based on the beautiful mathematical structure that Yang and his followers formulated so many years ago.”

According to Seiji Yunoki, who led the research team, “This work provides new insights not only into the phenomenon of non-equilibrium dynamics, but also could lead to the development of new high-temperature superconductors, which could be useful in applications. What remains is to perform actual experiments with Mott insulators to verify that this process actually takes place.”

The research was published in Physical Review Letters.

See the full article here .


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#what-is-interesting-says-first-author-tatsuya-kaneko-a-postdoctoral-researcher-at-the-riken-cluster-for-pioneering-research-is-that-our-calculations-showed-that-this-takes-p, #but-for-the-present-study-the-researchers-used-non-equilibrium-dynamics-to-analyze-the-effect-of-pulses-of-light-on-a-mott-insulator-and-found-that-the-effect-would-in-fact-happen-in-the-real-world, #mott-insulators, #riken, #scientists-from-the-riken-cluster-for-pioneering-research-have-shown-that-pulses-of-light-could-be-used-to-turn-these-materials-beyond-simple-conductors-to-superconductors-materials-that-condu, #superconductors, #thirty-years-ago-the-mathematical-physicist-chen-ning-yang-originally-proposed-the-idea-of-eta-pairing-but-because-it-was-a-purely-mathematical-concept-it-was-understood-as-a-virtual-phenomenon-that-w, #this-process-would-happen-through-an-unconventional-type-of-superconductivity-known-as-eta-pairing, #under-normal-electron-band-theory-they-ought-to-conduct-electricity-but-they-do-not-due-to-interactions-among-their-electrons, #what-remains-is-to-perform-actual-experiments-with-mott-insulators-to-verify-that-this-process-actually-takes-place

From RIKEN: “Brain clock ticks differently in autism”

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From RIKEN

February 15, 2019
Adam Phillips
RIKEN International Affairs Division
Tel: +81-(0)48-462-1225
Fax: +81-(0)48-463-3687
Email: pr@riken.jp

The neural ‘time windows’ in certain small brain areas contribute to the complex cognitive symptoms of autism, new research suggests. In a brain imaging study of adults, the severity of autistic symptoms was linked to how long these brain areas stored information. The differences in neural timescales may underlie features of autism like hypersensitivity and could be useful as a future diagnostic tool.

Sensory areas of the brain that receive input from the eyes, skin and muscles usually have shorter processing periods compared with higher-order areas that integrate information and control memory and decision-making. The new study, published in the journal eLife on February 5, shows that this hierarchy of intrinsic neural timescales is disrupted in autism. Atypical information processing in the brain is thought to underlie the repetitive behaviors and socio-communicational difficulties seen across the spectrum of autistic neurodevelopmental disorders (ASD), but this is one of the first indications that small-scale temporal dynamics could have an outsized effect.

Magnetic resonance imaging of the brains of high-functioning male adults with autism were compared to those of people without autism. In the resting state, both groups showed the expected pattern of longer timescales in frontal brain areas linked to executive control, and shorter timescales in sensory and motor areas. “Shorter timescales mean higher sensitivity in a particular brain region, and we found the most sensitive neural responses in those individuals with the most severe autistic symptoms,” says lead author Takamitsu Watanabe of the RIKEN Center for Brain Science. One brain area that displayed the opposite pattern was the right caudate, where the neural timescale was longer than normal, particularly in individuals with more severe repetitive, restricted behaviors. These differences in brain activity were also found in separate scans of autistic and neurotypical children.

The team of Japanese and UK researchers think that structural changes in small parts of the brain link these local dynamics to ASD symptoms. They found changes in grey matter volume in the areas with atypical neural timescales. A greater density of neurons can contribute to recurrent, repetitive neural activity patterns, which underlie the longer and shorter timescales observed in the right caudate and bilateral sensory/visual cortices, respectively. “The neural timescale is a measure of how predictable the activity is in a given brain region. The shorter timescales we observed in the autistic individuals suggest their brains have trouble holding onto and processing sensory input for as long as neurotypical people,” says Watanabe. “This may explain one prominent feature of autism, the great weight given by the brain to local sensory information and the resulting perceptual hypersensitivity.”

See the full article here .


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Stem Education Coalition

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RIKEN is Japan’s largest comprehensive research institution renowned for high-quality research in a diverse range of scientific disciplines. Founded in 1917 as a private research foundation in Tokyo, RIKEN has grown rapidly in size and scope, today encompassing a network of world-class research centers and institutes across Japan.

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From RIKEN: “Hybrid qubits solve key hurdle to quantum computing”

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From RIKEN

December 28, 2018

Spin-based quantum computers have the potential to tackle difficult mathematical problems that cannot be solved using ordinary computers, but many problems remain in making these machines scalable. Now, an international group of researchers led by the RIKEN Center for Emergent Matter Science have crafted a new architecture for quantum computing. By constructing a hybrid device made from two different types of qubit—the fundamental computing element of quantum computers—they have created a device that can be quickly initialized and read out, and that simultaneously maintains high control fidelity.

Quantum computing – IBM – the current state

In an era where conventional computers appear to be reaching a limit, quantum computers—which do calculations using quantum phenomena—have been touted as potential replacements, and they can tackle problems in a very different and potentially much more rapid way. However, it has proven difficult to scale them up to the size required for performing real-world calculations.

In 1998, Daniel Loss, one of the authors of the current study, came up with a proposal, along with David DiVincenzo of IBM, to build a quantum computer by using the spins of electrons embedded in a quantum dot—a small particle that behaves like an atom, but that can be manipulated, so that they are sometimes called “artificial atoms.” In the time since then, Loss and his team have endeavored to build practical devices.

There are a number of barriers to developing practical devices in terms of speed. First, the device must be able to be initialized quickly. Initialization is the process of putting a qubit into a certain state, and if that cannot be done rapidly it slows down the device. Second, it must maintain coherence for a time long enough to make a measurement. Coherence refers to the entanglement between two quantum states, and ultimately this is used to make the measurement, so if qubits become decoherent due to environmental noise, for example, the device becomes worthless. And finally, the ultimate state of the qubit must be able to be quickly read out.

While a number of methods have been proposed for building a quantum computer, the one proposed by Loss and DiVincenzo remains one of the most practically feasible, as it is based on semiconductors, for which a large industry already exists.

For the current study, published in Nature Communications, the team combined two types of quits on a single device. The first, a type of single-spin qubit called a Loss-DiVincenzo qubit, has very high control fidelity—meaning that it is in a clear state, making it ideal for calculations, and has a long decoherence time, so that it will stay in a given state for a relatively long time before losing its signal to the environment.

Unfortunately, the downside to these qubits is that they cannot be quickly initialized into a state or read out. The second type, called a singlet-triplet qubit, is quickly initialized and read out, but it quickly becomes decoherent. For the study, the scientists combined the two types with a type of quantum gate known as a controlled phase gate, which allowed spin states to be entangled between the qubits in a time fast enough to maintain the coherence, allowing the state of the single-spin qubit to be read out by the fast singlet-triplet qubit measurement.

According to Akito Noiri of CEMS, the lead author of the study, “With this study we have demonstrated that different types of quantum dots can be combined on a single device to overcome their respective limitations. This offers important insights that can contribute to the scalability of quantum computers.”

See the full article here .


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Stem Education Coalition

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RIKEN is Japan’s largest comprehensive research institution renowned for high-quality research in a diverse range of scientific disciplines. Founded in 1917 as a private research foundation in Tokyo, RIKEN has grown rapidly in size and scope, today encompassing a network of world-class research centers and institutes across Japan.

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From Riken and Science Alert: “Hunting the unseen – Scientists Are Hinting at The Existence of a Strange New Type of Particle”

RIKEN bloc

From RIKEN

July 15, 2011

Sighting a theoretical exotic particle may become possible thanks to recently developed mathematical simulations.

A better knowledge about the composition of sub-atomic particles such as protons and neutrons has sparked conjecture about, as yet, unseen particles. A tool based on theoretical calculations that could aid the search for these particles has been developed by a team of researchers in Japan called the HAL QCD Collaboration.

Science paper from 2011
Bound H Dibaryon in Flavor SU(3) Limit of Lattice QCD Physical Review Letters 20 April 2011

At its most fundamental level, matter consists of particles known as quarks. Particle physicists refer to the six different types as ‘flavors’: up, down, charm, strange, top and bottom. The protons and neutrons found in the nucleus of an atom are examples of a class of particle called baryons: particles consisting of three quarks. Two baryons bound together are called dibaryons, but only one dibaryon has been found to date: a bound proton and neutron that has three up quarks and three down quarks in total.

Models that reveal the potential physical properties of dibaryons, such as their mass and binding energy, are crucial if more of these particles are to be discovered in the future. To this end, the collaboration, including Tetsuo Hatsuda from the RIKEN Nishina Center for Accelerator-Based Science in Wako, developed simulations that shed new light on one promising candidate: the H dibaryon, which comprises two up, two down and two strange quarks (Fig. 1).

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Figure 1: An artistic impression of a bound H dibaryon, a theoretical particle consisting of two up, two down and two strange quarks. © 2011 Keiko Murano

The dynamics of quarks are described by an intricate theory known as quantum chromodynamics (QCD). The simulations, however, become increasingly difficult when more particles need to be included: dibaryons with six quarks are particularly testing. Hatsuda and his colleagues used an approach known as lattice QCD in which time and space are considered as a grid of discrete points. They simplified the calculation by assuming that all quarks have the same mass, but the strange quark is actually heavier than the up and down quarks. “We know from previous theoretical studies that the binding energy should be at its largest in the equal mass case,” says Hatsuda. “If we had not found a bound state in the equal mass case, there would be no hope that the bound state exists in the realistic unequal mass case.”

The results from the collaboration’s simulations showed that the total energy of the dibaryon is less than the combined energy of two separate baryons, which verifies that H dibaryons are energetically stable. “We next hope to find the precise binding energy for unequal quark masses, which represents one of the major challenges in numerical QCD simulations,” Hatsuda adds.

From Science Alerts 29 MAY 2018

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(Keiko Murano/RIKEN) Science Alert 29 MAY 2018

Using one of the most powerful computers in the world to perform complex simulations, scientists have predicted a new type of dibaryon particle – one that has two baryons instead of the usual one, with quarks all of the same colour.

The researchers, from the Japanese HAL QCD Collaboration, are calling the particle di-Omega.

Baryons are particles that contain three quarks, the subatomic particles that are one of the fundamental constituents that make up matter, and they make up most of the normal matter in the Universe. Protons and neutrons – which make up atomic nuclei – are baryons.

The charge of baryons is dependent on the “colours,” or types, of the quarks inside, of which there are six – up, down, top, bottom, charm, and strange.

In nature, there is only one known particle that’s made up of two baryons, or a dibaryon particle (also known as a hexaquark). It’s called deuteron, and it consists of a proton and a neutron bound together to form the nucleus of deuterium, or heavy hydrogen.

Although scientists believe that other dibaryons might exist, so far none have been conclusively found.

But by running simulations based on quantum chromodynamics (QCD), the theory that describes quark interactions, the HAL-QCD Collaboration is able to model potential stable dibaryons.

But it’s not easy – the more quarks there are in the mix, the more complex their interactions, which means more computing power is needed.

That’s why the researchers employed the K Computer at RIKEN’s Advanced Institute for Computational Science, which has a computational power of 10 petaflops, or 10 quadrillion operations per second.

Riken Fujitsu K Computer at Riken Advanced Institute for Computational Science campus in Kobe, Hyōgo Prefecture, Japan

Even so, it took almost three years to reach a conclusion on the particle. But reach a conclusion it did.

Di-Omega consists of two Omega baryons, containing three strange quarks each. It is, the researchers said, the “most strange” of all the potential dibaryons.

The research builds on the collaboration’s previous work – in 2011, they announced the discovery of a theoretical dibaryon with two up, two down and two strange quarks [above Riken article]. But since then they have refined their methods, devising a new theoretical framework, and a new algorithm, to allow for more efficient calculations.

And, of course, the access to the K Computer, which became available for use by researchers in 2012, made an enormous difference.

Going forward, the researchers believe their work can be applied to experimental settings to search for evidence of these particles in the real world.

“We believe that these special particles could be generated by the experiments using heavy ion collisions that are planned in Europe and in Japan,” said quantum physicist Tetsuo Hatsuda of RIKEN.

“We look forward to working with colleagues there to experimentally discover the first dibaryon system outside of deuteron.”

This most recent work is also published in Physical Review Letters, Most Strange Dibaryon from Lattice QCD 23 May 2018

See the full Riken article here .

See the full Science Alert article here .


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RIKEN is Japan’s largest comprehensive research institution renowned for high-quality research in a diverse range of scientific disciplines. Founded in 1917 as a private research foundation in Tokyo, RIKEN has grown rapidly in size and scope, today encompassing a network of world-class research centers and institutes across Japan.

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From Riken: “Geostationary satellite enables better precipitation and flood predictions”

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RIKEN

Using the power of Japan’s K computer, scientists from the RIKEN Advanced Institute for Computational Science and collaborators have shown that incorporating satellite data at frequent intervals—ten minutes in the case of this study—into weather prediction models can significantly improve the rainfall predictions of the models and allow more precise predictions of the rapid development of a typhoon.

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No image caption or credit.

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Fujitsu SPARC Riken K supercomputer

Weather prediction models attempt to predict future weather by running simulations based on current conditions taken from various sources of data. However, the inherently complex nature of the systems, coupled with the lack of precision and timeliness of the data, makes it difficult to conduct accurate predictions, especially with weather systems such as sudden precipitation.

As a means to improve models, scientists are using powerful supercomputers to run simulations based on more frequently updated and accurate data. The team led by Takemasa Miyoshi of AICS decided to work with data from Himawari-8, a geostationary satellite that began operating in 2015.

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Himawari-8 geostationary satellite

Its instruments can scan the entire area it covers every ten minutes in both visible and infrared light, at a resolution of up to 500 meters, and the data is provided to meteorological agencies. Infrared measurements are useful for indirectly gauging rainfall, as they make it possible to see where clouds are located and at what altitude.

For one study, they looked at the behavior of Typhoon Soudelor (known in the Philippines as Hanna), a category 5 storm that wreaked damage in the Pacific region in late July and early August 2015. In a second study, they investigated the use of the improved data on predictions of heavy rainfall that occurred in the Kanto region of Japan in September 2015. These articles were published in Monthly Weather Review [N/A] and Journal of Geophysical Research: Atmospheres.

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Simulation of Typhoon Soudelor at 22:00 on August 2, 2015

For the study on Typhoon Soudelor, the researchers adopted a recently developed weather model called SCALE-LETKF—running an ensemble of 50 simulations—and incorporated infrared measurements from the satellite every ten minutes, comparing the performance of the model against the actual data from the 2015 tropical storm. They found that compared to models not using the assimilated data, the new simulation more accurately forecast the rapid development of the storm. They tried assimilating data at a slower speed, updating the model every 30 minutes rather than ten minutes, and the model did not perform as well, indicating that the frequency of the assimilation is an important element of the improvement.

To perform the research on disastrous precipitation, the group examined data from heavy rainfall that occurred in the Kanto region in 2015. Compared to models without data assimilation from the Himawari-8 satellite, the simulations more accurately predicted the heavy, concentrated rain that took place, and came closer to predicting the situation where an overflowing river led to severe flooding.

According to Miyoshi, “It is gratifying to see that supercomputers along with new satellite data, will allow us to create simulations that will be better at predicting sudden precipitation and other dangerous weather phenomena, which cause enormous damage and may become more frequent due to climate change. We plan to apply this new method to other weather events to make sure that the results are truly robust.”

See the full article here .

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