Lifeboat Foundation

A deep tech startup building cryptographic solutions to secure hardware, software, and communications systems for a future when quantum computers may render many current cybersecurity approaches useless is today emerging out of stealth mode with $7 million in funding and a mission to make cryptographic security something that cannot be hackable, even with the most sophisticated systems, by building systems today that will continue to be usable in a post-quantum future.

PQShield (PQ being short for “post-quantum”), a spin out from Oxford University, is being backed in a seed round led by Kindred Capital, with participation also Crane Venture Partners, Oxford Sciences Innovation and various angel investors, including Andre Crawford-Brunt, Deutsche Bank’s former global head of equities.

PQShield was founded in 2018, and its time in stealth has not been in vain.

Optical frequency synthesizers – systems that output laser beams at precise and stable frequencies – have proven extremely valuable in a variety of scientific endeavors, including space exploration, gas sensing, control of quantum systems, and high-precision light detection and ranging (LIDAR). While they provide unprecedented performance, the use of optical frequency synthesizers has largely been limited to laboratory settings due to the cost, size, and power requirements of their components. To reduce these obstacles to widespread use, DARPA launched the Direct On-Chip Digital Optical Synthesizer (DODOS) program in 2014. Key to the program is the miniaturization of necessary components and their integration into a compact module, enabling broader deployment of the technology while unlocking new applications.

To accomplish its goals, DODOS is leveraging advances in microresonators – tiny structures that store light in microchips – to produce optical frequency combs in compact integrated packages. Frequency combs earn their name by converting a single-color input laser beam into a sequence of many additional colors that are evenly spaced and resemble a hair comb. With a sufficiently wide array of comb “teeth,” innovative techniques to eliminate noise become possible that make combs an attractive option for systems needing precise frequency references.

Until recently, creating frequency combs from microresonators was a complex affair that required sophisticated control schemes, dedicated circuitry, and oftentimes, an expert scientist to carefully observe and fine-tune the operation. This is primarily due to the sensitive properties of the microresonator, which needs the perfect amount of light at a special operating frequency – or color – to be provided by an input laser in order for the comb to turn on and even then, producing a coherent or stable comb state could not be guaranteed every time.

A central challenge in developing quantum computers and long-range quantum networks is the distribution of entanglement across many individually controllable qubits¹. Colour centres in diamond have emerged as leading solid-state ‘artificial atom’ qubits^2,3 because they enable on-demand remote entanglement⁴, coherent control of over ten ancillae qubits with minute-long coherence times⁵ and memory-enhanced quantum communication⁶. A critical next step is to integrate large numbers of artificial atoms with photonic architectures to enable large-scale quantum information processing systems. So far, these efforts have been stymied by qubit inhomogeneities, low device yield and complex device requirements. Here we introduce a process for the high-yield heterogeneous integration of ‘quantum microchiplets’—diamond waveguide arrays containing highly coherent colour centres—on a photonic integrated circuit (PIC). We use this process to realize a 128-channel, defect-free array of germanium-vacancy and silicon-vacancy colour centres in an aluminium nitride PIC. Photoluminescence spectroscopy reveals long-term, stable and narrow average optical linewidths of 54 megahertz (146 megahertz) for germanium-vacancy (silicon-vacancy) emitters, close to the lifetime-limited linewidth of 32 megahertz (93 megahertz). We show that inhomogeneities of individual colour centre optical transitions can be compensated in situ by integrated tuning over 50 gigahertz without linewidth degradation. The ability to assemble large numbers of nearly indistinguishable and tunable artificial atoms into phase-stable PICs marks a key step towards multiplexed quantum repeaters^7,8 and general-purpose quantum processors^9,10,11,12.

Neutron stars are an end state of stellar evolution, says astrophysicist Paul Lasky, at Australia’s Monash University and OzGrav. “They consist of the densest observable matter in the universe, under conditions that are impossible to produce in the laboratory, and theoretical modeling of the matter requires extrapolation by many orders of magnitude beyond the point where nuclear physics is well understood.”

“Gravitational-wave astronomy is reshaping our understanding of the universe,” said Lasky, about a new study co-authored by the ARC Center of Excellence for Gravitational Wave Discovery (OzGrav) that makes a compelling case for the development of “NEMO” —a new observatory in Australia that could deliver on some of the most exciting gravitational-wave science next-generation detectors have to offer, but at a fraction of the cost.

The study today presents the design concept and science case for a Neutron Star Extreme Matter Observatory (NEMO): a gravitational-wave interferometer optimized to study nuclear physics with merging neutron stars, using high circulating laser power, quantum squeezing and a detector topology specially designed to achieve the high frequency sensitivity necessary to probe nuclear matter using gravitational waves.

Physicists at MIT have designed a quantum “light squeezer” that reduces quantum noise in an incoming laser beam by 15 percent. It is the first system of its kind to work at room temperature, making it amenable to a compact, portable setup that may be added to high-precision experiments to improve laser measurements where quantum noise is a limiting factor.

The heart of the new squeezer is a marble-sized optical cavity, housed in a vacuum chamber and containing two mirrors, one of which is smaller than the diameter of a human hair. The larger mirror stands stationary while the other is movable, suspended by a spring-like cantilever.

The shape and makeup of this second “nanomechanical” mirror is the key to the system’s ability to work at room temperature. When a laser beam enters the cavity, it bounces between the two mirrors. The force imparted by the light makes the nanomechanical mirror swing back and forth in a way that allows the researchers to engineer the light exiting the cavity to have special quantum properties.

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Quantum computers (QC) are poised to drive important advances in several domains, including medicine, material science and internet security. While current QC systems are small, several industry and academic efforts are underway to build large systems with many hundred qubits.

Towards this, computer scientists at Princeton University and physicists from Duke University collaborated to develop methods to design the next generation of quantum computers. Their study focused on QC systems built using trapped ion (TI) technology, which is one of the current front-running QC hardware technologies. By bringing together computer architecture techniques and device simulations, the team showed that co-designing near-term hardware with applications can potentially improve the reliability of TI systems by up to four orders of magnitude.

Continue reading “Examining trapped ion technology for next generation quantum computers” »

Quantum information scientists have introduced a new method for machine-learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new insights for improving the accuracy of quantum machine learning, deemed able to outperform the current AI technology.

The research team led by Professor June-Koo Kevin Rhee from the School of Electrical Engineering, proposed a quantum classifier based on quantum state fidelity by using a different initial state and replacing the Hadamard classification with a swap test. Unlike the conventional approach, this method is expected to significantly enhance the classification tasks when the training dataset is small, by exploiting the quantum advantage in finding non-linear features in a large feature space.

Quantum machine learning holds promise as one of the imperative applications for quantum computing. In machine learning, one fundamental problem for a wide range of applications is classification, a task needed for recognizing patterns in labeled training data in order to assign a label to new, previously unseen data; and the kernel method has been an invaluable classification tool for identifying non-linear relationships in complex data.

Physicists at MIT have designed a quantum “light squeezer” that reduces quantum noise in an incoming laser beam by 15 percent. It is the first system of its kind to work at room temperature, making it amenable to a compact, portable setup that may be added to high-precision experiments to improve laser measurements where quantum noise is a limiting factor.

The heart of the new squeezer is a marble-sized optical cavity, housed in a vacuum chamber and containing two mirrors, one of which is smaller than the diameter of a human hair. The larger mirror stands stationary while the other is movable, suspended by a spring-like cantilever.

The shape and makeup of this second “nanomechanical” mirror is the key to the system’s ability to work at room temperature. When a laser beam enters the cavity, it bounces between the two mirrors. The force imparted by the light makes the nanomechanical mirror swing back and forth in a way that allows the researchers to engineer the light exiting the cavity to have special quantum properties.

By tuning the direction of the external magnetic field with respect to the crystallographic axis of the silicon wafer, an improvement of spin lifetime (relaxation time) by over two orders of magnitude was reported in silicon quantum dots. This breakthrough was carried out by a team led by academician Guo Guangcan from CAS Key Laboratory of Quantum Information, USTC, in which Prof. Guo Guoping, Prof. Li Hai-Ou with their colleagues and Origin Quantum Computing Company Limited. This work was published in Physical Review Letters on June 23, 2020.

Spin qubits based on silicon quantum dots have been a core issue in the development of large scale quantum computation due to its long coherence time and the compatibility with modern semiconductor technology. Recently, the relaxation time and dephasing time of spin qubits developed in Si MOS (Metal-Oxide-Semiconductor) and Si/SiGe heterostructure have surpassed hundreds of milliseconds and hundreds of microseconds, respectively, resulting in a single-qubit control fidelity over 99.9% and a two-qubit gate fidelity over 98%. With the success in college, labs and companies from the industry are starting to be involved in this field, such as Intel, CEA-Leti, and IMEC. However, the existence of valley states (a state associated with the dip in a particular electronic band) in silicon quantum dots could reduce spin relaxation time and dephasing time seriously via spin-valley mixing and limit the control fidelity of qubits.