By Godfree Roberts – selected from his extensive weekly newsletter : Here Comes China
China has had a record week in terms of the complete economy. From record exports to successfully bringing soil samples back from the moon, it is a long list. We mention a few BRI projects:
BRI projects in Central and Eastern Europe are on track:
- China’s Norinco Senj Wind Farm is 50% complete and 39 wind turbines will be up and running by April.
- At Montenegro’s Mt. Mozura, the wind turbines built by the Shanghai Electric Power Company have started spinning as the country’s new highway stretches to Serbia.
- The Peljesac Bridge, a 2.4-km-long bridge connecting the Croatian mainland with the Peljesac Peninsula, is expected to be finished next year.
- The Belgrade-South Adriatic highway, built by CRBC, will greatly facilitate the transportation of passengers and goods between the Balkans and the hinterland of Europe.
- COSCO’s Piraeus Port in Greece run by COSCO Shipping, increased 17.8% in container terminal revenues, as ship repair revenues rose by 21.8% in the first half of 2020.
- In southeast Poland, the Fabryka Lozysk Tocznych-Krasnik, a bearings manufacturer that was acquired by the Chinese Tri-Ring Group, is producing 1,500 types of bearings. Read full article →
If you take in from this video that the social credit system is more of an approach building in assessing risk, and providing for both ‘corrective action’ as well as punitive measures, then it is easy to understand that the People’s Bank of China (PBoC) called for broader use of “alternative credit data” in the assessment of lending risk.
Data collected is Public Credit Information (PCI) – government records generated by state agencies, and Market Credit Information (MCI) – other information generated through a company’s interaction with customers, industry associations, and other market actors
PCI is fairly standardized and easy to get. In fact, the PBoC is already using it. MCI is not standardized and hard to access reliably – but the PBoC wants to define and use it. Many small and medium-sized enterprises don’t have the collateral to back debts and wWithout accurate data to underpin lending risk assessments for small businesses, China will struggle to fund its innovative entrepreneurs.
This is not just a China issue. US credit rating bureaus Experian, Equifax, and TransUnion are also seeking alternative data sources to extend loans to those who are locked out of traditional credit models.
There are only several dozen of these DUV Lithography machines capable of making microchips on Earth and two years’ of back orders for the $120 M machines. Credit: Brookings.
Fabbing Tool Puts China in Driver’s Seat
by Dave Makichuk, Asia Times
The Trump administration is betting the farm that China won’t find a workaround to its semiconductor chip ban. I don’t know what the odds are, but owing to China’s rapidly expanding R&D and everything else the Middle Kingdom has achieved over the last ten years, I think I’d take him up on that bet.
Shanghai Micro Electronic Equipment (SMEE) is reportedly on track to deliver its second-gen deep ultraviolet (DUV) lithography scanner by the fourth quarter of 2021.The tool can produce chips using 28 nm process technologies and relies on components produced in China and Japan. And, more importantly, it does not rely on devices made in the US, a major factor in the ongoing Sino-US trade war.
Lithography machines play a crucial role in the production of chips as they etch patterns on wafers for placing transistors. One of the biggest breakthroughs has been EUV that creates extremely thin markings, Gizmo China online reported. However, the discovery is still at the theoretical state and it could take years as well as plenty of money to make this a reality. China is still behind when it comes to manufacturing chipsets, which is often outsourced to the likes of TSMC (Taiwan Semiconductor Manufacturing Company). Nonetheless, the discovery of a new process laser lithography by China is a major step forward for the country.
According to Brookings Tech Stream, a DUV lithography generator ejects 50,000 tiny droplets of molten tin per second. A high-powered laser blasts each droplet twice. The first shapes the tiny tin, so the second can vaporize it into plasma. The plasma emits extreme ultraviolet (EUV) radiation that is focused into a beam and bounced through a series of mirrors. The mirrors are so smooth that if expanded to the size of Germany they would not have a bump higher than a millimeter. Finally, the EUV beam hits a silicon wafer—itself a marvel of materials science — with a precision equivalent to shooting an arrow from Earth to hit an apple placed on the moon, Brookings reported. This allows the EUV machine to draw transistors into the wafer with features measuring only five nanometers — approximately the length your fingernail grows in five seconds. This wafer with billions or trillions of transistors is eventually made into computer chips.
An EUV machine is made of more than 100,000 parts, costs approximately US$120 million, and is shipped in 40 freight containers. There are only several dozen of them on Earth and approximately two years’ worth of back orders for more. It might seem unintuitive that the demand for a $120 million tool far outstrips supply, but only one company can make them. It’s a Dutch company called ASML, which nearly exclusively makes lithography machines for chip manufacturing. Despite this hyperspecialization, it has a market capitalization of more than US$150 billion — much higher than IBM’s and only slightly lower than Tesla’s, Brookings reported.
This is what China is up against. Yes, it could take years, but, it’s do-able. But a late start is better than none. Read full article →
A Chinese team made the first definitive demonstration of ‘quantum advantage’ –doing in minutes what would take half the age of Earth on the best supercomputers. Contrary to Google’s first demonstration of a quantum advantage, performed last year, their version is virtually unassailable by any classical computer. “We have shown that we can use photons, the fundamental unit of light, to demonstrate quantum computational power well beyond the classical counterpart,” says Jian-Wei Pan at the University of Science and Technology of China in Hefei. He adds that the calculation that they carried out — called the boson-sampling problem — is not just a convenient vehicle for demonstrating quantum advantage, but has potential practical applications in graph theory, quantum chemistry and machine learning.
“This is certainly a tour de force experiment, and an important milestone,” says physicist Ian Walmsley at Imperial College London.
Quantum advantage challenged
Teams at both academic and corporate laboratories have been vying to demonstrate quantum advantage (a term that has now largely replaced the earlier ‘quantum supremacy’).
Last year, researchers at Google’s quantum-computing laboratory in Santa Barbara, California, announced the first-ever demonstration of quantum advantage. They used their state-of-the-art Sycamore device, which has 53 quantum bits (qubits) made from superconducting circuits that are kept at ultracold temperatures2.
But some quantum researchers contested the claim, on the grounds that a better classical algorithm that would outperform the quantum one could exist3. And researchers at IBM claimed that its classical supercomputers could in principle already run existing algorithms to do the same calculations in 2.5 days.
To convincingly demonstrate quantum advantage, it should be unlikely that a significantly faster classical method could ever be found for the task being tested.
The Hefei team, led by Pan and Chao-Yang Lu, chose a different problem for its demonstration, called boson sampling. It was devised in 2011 by two computer scientists, Scott Aaronson and Alex Arkhipov4, then at the Massachusetts Institute of Technology in Cambridge. It entails calculating the probability distribution of many bosons — a category of fundamental particle that includes photons — whose quantum waves interfere with one another in a way that essentially randomizes the position of the particles. The probability of detecting a boson at a given position can be calculated from an equation in many unknowns.
But the calculation in this case is a ‘#P-hard problem’, which is even harder than notoriously tricky NP-hard problems, for which the number of solutions increases exponentially with the number of variables. For many tens of bosons, Aaronson and Arkhipov showed that there’s no classical shortcut for the impossibly long calculation.
A quantum computer, however, can sidestep the brute-force calculation by simulating the quantum process directly — allowing bosons to interfere and sampling the resulting distribution. To do this, Pan and colleagues chose to use photons as their qubits. They carried out the task on a photonic quantum computer working at room temperature.
Starting from laser pulses, the researchers encoded the information in the spatial position and the polarization of particular photon states — the orientation of the photons’ electromagnetic fields. These states were then brought together to interfere with one another and generate the photon distribution that represents the output. The team used photodetectors capable of registering single photons to measure that distribution, which in effect encodes the calculations that are so hard to perform classically.
In this way, Pan and colleagues could find solutions to the boson-sampling problem in 200 seconds. They estimate these would take 2.5 billion years to calculate on China’s TaihuLight supercomputer — a quantum advantage of around 1014.
“This is the first time that quantum advantage has been demonstrated using light or photonics,” says Christian Weedbrook, chief executive of quantum-computing startup Xanadu in Toronto, Canada, which is seeking to build practical quantum computers based on photonics.
Walmsley says this claim of quantum advantage is convincing. “Because [the experiment] hews very closely to the original Aaronson–Arkiphov scheme, it is unlikely that a better classical algorithm can be found,” he says.
However, Weedbrook points out that as yet, and in contrast to Google’s Sycamore, the Chinese team’s photonic circuit is not programmable, so at this point “it cannot be used for solving practical problems”.
But he adds that if the team is able to build an efficient enough programmable chip, several important computational problems could be solved. Among those are predicting how proteins dock to one another and how molecules vibrate, says Lu.
Weedbrook notes that photonic quantum computing started later than the other approaches, but it could now “potentially leap-frog the rest”. At any rate, he adds, “It is only a matter of time before quantum computers will leave classical computers in the dust.” The market for quantum hardware rentals is projected to rise to $9 billion in 2030 from $260 million today. [The results appeared in Science on 3 December1.] Read full article →
This represents but a fraction of what is included in the Here Comes China newsletter. If you want to learn about the Chinese world, get Godfree’s newsletter here
Cover Photograph : The shape of Steven Chilton Architects’ theatre in Guangzhou is informed by the city’s historical connection to silk and is imprinted with patterns that represent its current tattoo culture. Named the Sunac Guangzhou Grand Theatre, the building will host performances from visiting production companies as part of a group of entertainment venues being built in the city’s Huadu District. The building’s distinctive cladding was informed by Guangzhou’s history as a key trading port. Read full article →