“We do not use any ancilla qubits,” Yan says. “Instead, we use ancilla states.”
In the new study, the scientists implemented quantum AND gates on a superconducting quantum processor with tunable-coupling architecture. Google also employs this architecture with its quantum computers, and IBM plans to start using it in 2023.
“We think that our scheme is well-suited for superconducting qubit systems where ancilla states are abundant and easy to access,” Yan says.
DNA — nicknamed “nature’s storage medium” — has accurately stored the instruction sets for all life on Earth for billions of years. But it also may hold the keys to managing explosive data growth and storing archival data for generations to come.
The idea of storing digital data in DNA dates back more than a half century, but making it a reality has accelerated in recent years with advances in biotechnology and declining costs of genome sequencing.
Dave Landsman is the senior director of industry standards and a distinguished engineer at Western Digital. For the past two years, he’s been one of the principals in the company’s exploration of DNA data storage.
Error-prone qubits mean quantum systems do not yet surpass classical methods.
In a talk at the Massachusetts Institute of Technology in 1981, Richard Feynman spoke about ‘simulating physics with computers’. This was already being done at the time, but Feynman said he wanted to talk ‘about the possibility that there is to be an exact simulation, that the computer will do exactly the same as nature.’ But as nature is quantum-mechanical, he pointed out, what you need for that is a quantum computer.
The rest is history – but history still in the making. When I recently asked David Deutsch, the visionary physicist who in 1985 laid out what quantum computing might look like, whether he was surprised at how quickly the idea became a practical technology, he replied with characteristic terseness: ‘It hasn’t.’ You can see his point. Sure, in October President Joe Biden visited IBM’s new quantum data centre in Poughkeepsie, New York, to see an entire room filled with the company’s quantum computers. And on 9 November IBM announced its 433-quantum-bit (qubit) Osprey processor, although it seems only yesterday that we were getting excited at Google’s 53-qubit Sycamore chip – with which the Google team claimed in 2016 to demonstrate ‘quantum supremacy’, meaning that it could perform a calculation in a few days that would take the best classical computer many millennia.1 This claim has since been disputed.
Researchers at the University of California, Irvine have discovered that the safe operation of a negative pressure room—a space in a hospital or biological research laboratory designed to protect outside areas from exposure to deadly pathogens—can be disrupted by an attacker armed with little more than a smartphone.
According to UCI cyber-physical systems security experts, who shared their findings with attendees at the Association for Computing Machinery’s recent Conference on Computer and Communications Security in Los Angeles, mechanisms that control airflow in and out of biocontainment facilities can be tricked into functioning irregularly by a sound of a particular frequency, possibly tucked surreptitiously into a popular song.
“Someone could play a piece of music loaded on their smartphone or get it to transmit from a television or other audio device in or near a negative pressure room,” said senior co-author Mohammad Al Faruque, UCI professor of electrical engineering and computer science. “If that music is embedded with a tone that matches the resonant frequency of the pressure controls of one of these spaces, it could cause a malfunction and a leak of deadly microbes.”
Quantum circuits still can’t outperform classical ones when simulating molecules.
Quantum computers promise to directly simulate systems governed by quantum principles, such as molecules or materials, since the quantum bits themselves are quantum objects. Recent experiments have demonstrated the power of these devices when performing carefully chosen tasks. But a new study shows that for problems of real-world interest, such as calculating the energy states of a cluster of atoms, quantum simulations are no more accurate than those of classical computers [1]. The results offer a benchmark for judging how close quantum computers are to becoming useful tools for chemists and materials scientists.
Richard Feynman proposed the idea of quantum computers in 1982, suggesting they might be used to calculate the properties of quantum matter. Today, quantum processors are available with several hundred quantum bits (qubits), and some can, in principle, represent quantum states that are impossible to encode in any classical device. The 53-qubit Sycamore processor developed by Google has demonstrated the potential to perform calculations in a few days that would take many millennia on current classical computers [2]. But this “quantum advantage” is achieved only for selected computational tasks that play to these devices’ strengths. How well do such quantum computers fare for the sorts of everyday challenges that researchers studying molecules and materials actually wish to solve?
Femtosecond pulsed lasers—which emit light in ultrafast bursts lasting a millionth of a billionth of a second—are powerful tools used in a range of applications from medicine and manufacturing, to sensing and precision measurements of space and time. Today, these lasers are typically expensive table-top systems, which limits their use in applications that have size and power consumption restrictions.
An on-chip femtosecond pulse source would unlock new applications in quantum and optical computing, astronomy, optical communications and beyond. However, it’s been a challenge to integrate tunable and highly efficient pulsed lasers onto chips.
Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a high-performance, on-chip femtosecond pulse source using a tool that seems straight out of science fiction: a time lens.
It’s diversifying from its initial reliance on Taiwan-made chips.
Apple is diversifying its supply chain away from Taiwan as it has plans to buy some of its chips from a factory in Arizona, company CEO Tim Cook said last month at an internal meeting in Germany, according to a report by Bloomberg News.
Manufacturing A-series and M-series processors
All of the firm’s current processors are sourced from factories in Taiwan. Although Apple currently designs its own chips, the Taiwan Semiconductor Manufacturing Company (TSMC) is responsible for manufacturing the A-series and M-series processors that power the ever popular iPhones and Mac computers.
As part of its quest to develop cognitive systems, IBM Research is exploring whether a computer can be creative by designing a machine that can create surprising yet flavorful recipe ideas no cookbook has ever thought of in order to enhance human creativity.
http://www.research.ibm.com/cognitive-computing/computational-creativity.shtml
Universitat Autònoma de Barcelona (UAB) researchers have developed a magnetic material capable of imitating the way the brain stores information. The material makes it possible to emulate the synapses of neurons and mimic, for the first time, the learning that occurs during deep sleep.
Neuromorphic computing is a new computing paradigm in which the behavior of the brain is emulated by mimicking the main synaptic functions of neurons. Among these functions is neuronal plasticity: the ability to store information or forget it depending on the duration and repetition of the electrical impulses that stimulate neurons, a plasticity that would be linked to learning and memory.
Among the materials that mimic neuron synapses, memresistive materials, ferroelectrics, phase change memory materials, topological insulators and, more recently, magneto-ionic materials stand out. In the latter, changes in the magnetic properties are induced by the displacement of ions within the material caused by the application of an electric field.