It is a hardware component that is used to generate unpredictable random numbers, typically for cryptography or computation applications.
QRNGs provide several advantages to generate random numbers in applications as cryptography, including the strongest form of unpredictability, the ability to measure the quality through first principles and typically faster performance.
A quantum random number generator (QRNG) generates streams of random digits by sampling a signal that contains sufficiently large quantum dynamics.
The term Quantum technology refers to those technologies that are based on or exploit the effects of quantum mechanics, which are physical effects at the subatomic level and cannot be explained by classical physics. The first quantum revolution has set the base of many modern technologies, such as lasers, semiconductors, and GPS. The “second” generation of quantum technology are brought on by a deeper understanding of the quantum world and precision control individual particles, exploiting principles such as superposition and entanglement. This second quantum revolution includes several areas as quantum computing, quantum communication, quantum sensing and quantum simulation.
RPU stands for “Randomness Processing Unit”, Quside’s new acceleration device based on high-speed, high-quality, quantum-based random number generation and fine-tuned hardware acceleration. Quside’s RPUs allow customers to offload their randomness generation and processing tasks from the CPU, thereby accelerating and optimizing their randomized workloads. This fact simultaneously improves their effective computational capacity and the quality of their simulation, optimization, and prediction needs.
Customers that rely on Quside’s RPU have shown faster simulation speeds and better convergence of their stochastic simulations. Besides, the introduction of the device into their pipelines has enabled the deployment of new, advanced algorithms for their workloads, for which they didn’t have enough computing capabilities before.
Quside’s RPU utilizes ultrafast quantum RNGs and offloads RN processing, improving efficiency and reducing hidden patterns in PRNGs.
Random number generation subroutines may involve up to 95% of the total simulation resources for stochastic workloads. Quside’s RPU technology accelerates randomized workloads, thus improving your effective computational capacity and the quality of your simulation, optimization, and prediction needs. Thanks to these improvements you can obtain competitive advantages with the possibility of making better decision in a shorter time and reduce your infrastructure costs in terms of CAPEX and OPEX.
Any randomness-intensive workload can hugely take benefit from the enhanced randomness generation and acceleration capabilities of Quside’s RPUs. Different industries use a variety of randomized workloads. Monte Carlo based calculations are extensively used in the Financial industry for risk or asset valuation calculations, Engineering industries uses it for the simulation of material or fluxes behaviour, Logistic industries uses optimization algorithms to calculate the best routes, etc.
A device that performs data manipulation following the laws of quantum mechanics, which are pretty different from the standard rules of classical physics.
Quantum computers are quite a promising platform for many problems in areas such as simulation, optimization, machine learning, or database searching.
A quantum computer can be exponentially faster than a classical computer for some specific problems, such as the integer factorization problem.
Quantum cryptography is the science that exploits the properties of quantum mechanics to perform cryptographic tasks. There are two main areas of development:
In theory, quantum cryptography is unhackable, because eavesdropping would always be detected. QKD offers information-theoretic security (ITS), meaning that the vulnerability of the generated key to attacks depends on the protocol implementation and does not require any assumptions on the resources available to an adversary. This property is fundamental to provide long-term security and to avoid harvest now, decrypt later attacks. Nevertheless, a truly usable system may require the combination of quantum cryptography with classical elements, which could be vulnerable if not properly considered.
Quantum encryption is the method by which information is converted into secret code by exploiting the properties of quantum mechanics. Quantum key distribution (QKD) is the most widely studied and viable method which enables two trusted users to produce and share keys to encrypt (decrypt) messages in a secure way.
We mean using cryptographic primitives based on post-quantum algorithms to guarantee the confidentiality, authenticity, and integrity of the data.
They are two fundamentally different things. On the one hand, post-quantum cryptography consists of developing algorithms that are resistant to quantum computers, but the algorithms themselves can still be executed by classical devices. On the other hand, quantum cryptography uses purely quantum phenomena to provide cryptographic guarantees and requires a quantum infrastructure in place to be used.
Data protection is not only a moral obligation to protect our customer’s and organization’s data, there are specific regulations for the different industries and sectors that we all must comply with when managing data. This is not different when we move to the cloud. We are responsible of the data protection in any case.
Encryption is the main mechanism to ensure data privacy. By encrypting the data you will be sure that nobody could access to the information in case a leakage or security incident.
For generating pseudo-random numbers, an algorithm makes some transformation on a given state of the generator. Both a new state and the pseudo-random number are returned from this transformation.
These PRNGs are used when so much randomness is needed that the entropy sources themselves cannot cope with the demand. They are also widely used in simulation environments.
There are different concrete instantiations of the abstract notion of entropy in quantum information theory, many of them with a clearly defined operational interpretation. In this post, we have briefly reviewed two of them: the von Neumann entropy and the quantum min-entropy.
In abstract terms, entropy is a measure of the amount of uncertainty or randomness in the state of a system.