Lifeboat Foundation

When the theoretical physicist Leonard Susskind encountered a head-scratching paradox about black holes, he turned to an unexpected place: computer science. In nature, most self-contained systems eventually reach thermodynamic equilibrium… but not black holes. The interior volume of a black hole appears to forever expand without limit. But why? Susskind had a suspicion that a concept called computational complexity, which underpins everything from cryptography to quantum computing to the blockchain and AI, might provide an explanation.

He and his colleagues believe that the complexity of quantum entanglement continues to evolve inside a black hole long past the point of what’s called “heat death.” Now Susskind and his collaborator, Adam Brown, have used this insight to propose a new law of physics: the second law of quantum complexity, a quantum analogue of the second law of thermodynamics.

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Quantum computers have the potential to outperform conventional computers on some tasks, including complex optimization problems. However, quantum computers are also vulnerable to noise, which can lead to computational errors.

Engineers have been trying to devise fault-tolerant quantum computing approaches that could be more resistant to noise and could thus be scaled up more robustly. One common approach to attain fault-tolerance is the preparation of magic states, which introduce so-called non-Clifford gates.

Researchers at University of Science and Technology of China, the Henan Key Laboratory of Quantum Information and Cryptography and the Hefei National Laboratory recently demonstrated the preparation of a logical magic state with fidelity beyond the distillation threshold on a superconducting quantum processor. Their paper, published in Physical Review Letters, outlines a viable and effective strategy to generate high-fidelity logical magic states, an approach to realize fault-tolerant quantum computing.

Computer-generated holography (CGH) represents a cutting-edge technology that employs computer algorithms to dynamically reconstruct virtual objects. This technology has found extensive applications across diverse fields such as three-dimensional display, optical information storage and processing, entertainment, and encryption.

Despite the broad application spectrum of CGH, contemporary techniques predominantly rely on projection devices like spatial light modulators (SLMs) and digital micromirror devices (DMDs). These devices inherently face limitations in display capabilities, often resulting in narrow field-of-view and multilevel diffraction in projected images.

In recent developments, metasurfaces composed of an array of subwavelength nanostructures have demonstrated exceptional capabilities in modulating electromagnetic waves. By introducing abrupt changes to fundamental wave properties like amplitude and phase through nanostructuring at subwavelength scales, metasurfaces enable modulation effects that are challenging to achieve with traditional devices.

Regulatory efforts to protect data are making strides globally. Patient data is protected by law in the United States and elsewhere. In Europe the General Data Protection Regulation (GDPR) guards personal data and recently led to a US $1.3 billion fine for Meta. You can even think of Apple’s App Store policies against data sharing as a kind of data-protection regulation.

“These are good constraints. These are constraints society wants,” says Michael Gao, founder and CEO of Fabric Cryptography, one of the startups developing FHE-accelerating chips. But privacy and confidentiality come at a cost: They can make it more difficult to track disease and do medical research, they potentially let some bad guys bank, and they can prevent the use of data needed to improve AI.

“Fully homomorphic encryption is an automated solution to get around legal and regulatory issues while still protecting privacy,” says Kurt Rohloff, CEO of Duality Technologies, in Hoboken, N.J., one of the companies developing FHE accelerator chips. His company’s FHE software is already helping financial firms check for fraud and preserving patient privacy in health care research.

No one knows who might get there first. The United States and China are considered the leaders in the field; many experts believe America still holds an edge.

As the race to master quantum computing continues, a scramble is on to protect critical data. Washington and its allies are working on new encryption standards known as post-quantum cryptography – essentially codes that are much harder to crack, even for a quantum computer. Beijing is trying to pioneer quantum communications networks, a technology theoretically impossible to hack, according to researchers. The scientist spearheading Beijing’s efforts has become a minor celebrity in China.

Quantum computing is radically different. Conventional computers process information as bits – either 1 or 0, and just one number at a time. Quantum computers process in quantum bits, or “qubits,” which can be 1, 0 or any number in between, all at the same time, which physicists say is an approximate way of describing a complex mathematical concept.

Years after Mark Zuckerberg said encrypted chats were coming to Messenger, it’s finally being enabled by default.

Meta is rolling out end-to-end encryption for one-on-one chats and calls on Messenger, finally fulfilling a promise that’s been in the works for quite awhile.

The switch to default has been in the works for a long time.

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It seems for every proponent for quantum computing there is also a detractor.

Given the amount of quantum computing investment, advancements, and activity, the industry is set for a dynamic change, similar to that caused by AI – increased performance, functionality, and intelligence. This also comes with the same challenges presented by AI, such as security, as outlined in the recent Quantum Safe Cryptography article. But just like AI, quantum computing is coming. You might say that quantum computing is where AI was in 2015, fascinating but not widely utilized. Fast forward just five years and AI was being integrated into almost every platform and application. In just five years, quantum computing could take computing and humanity to a new level of knowledge and understanding.

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Zero-knowledge proof (ZKP) is a cryptographic tool that allows for the verification of validity between mutually untrusted parties without disclosing additional information. Non-interactive zero-knowledge proof (NIZKP) is a variant of ZKP with the feature of not requiring multiple information exchanges. Therefore, NIZKP is widely used in the fields of digital signature, blockchain, and identity authentication.

Since it is difficult to implement a true random number generator, deterministic pseudorandom number algorithms are often used as a substitute. However, this method has potential security vulnerabilities. Therefore, how to obtain true random numbers has become the key to improving the security of NIZKP.

In a study published in PNAS, a research team led by Prof. Pan Jianwei and Prof. Zhang Qiang from the University of Science and Technology of China (USTC) of the Chinese Academy of Sciences, and the collaborators, realized a set of random number beacon public services with device-independent quantum random number generators as entropy sources and post-quantum cryptography as identity authentication.

Quantum advantage is the milestone the field of quantum computing is fervently working toward, where a quantum computer can solve problems that are beyond the reach of the most powerful non-quantum, or classical, computers.

Quantum refers to the scale of atoms and molecules where the laws of physics as we experience them break down and a different, counterintuitive set of laws apply. Quantum computers take advantage of these strange behaviors to solve problems.

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