Microsoft got where it is by ensuring that Windows ran on many different types of hardware. Monday, the company said its cloud computing platform will soon offer access to the most exotic hardware of all: quantum computers.
Microsoft is one of several tech giants investing in quantum computing, which by crunching data using strange quantum mechanical processes promises unprecedented computational power. The company is now preparing its Azure cloud computing service to offer select customers access to three prototype quantum computers, from engineering conglomerate Honeywell and two startups, IonQ, which emerged from the University of Maryland, and QCI, spun out of Yale. Read More
Tag Archives: Quantum
How to Turn a Quantum Computer Into the Ultimate Randomness Generator
Say the words “quantum supremacy” at a gathering of computer scientists, and eyes will likely roll. The phrase refers to the idea that quantum computers will soon cross a threshold where they’ll perform with relative ease tasks that are extremely hard for classical computers. Until recently, these tasks were thought to have little real-world use, hence the eye rolls.
But now that Google’s quantum processor is rumored to be close to reaching this goal, imminent quantum supremacy may turn out to have an important application after all: generating pure randomness. Read More
Quantum supremacy using a programmable superconducting processor
The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor1. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here we report the use of a processor with programmable superconducting qubits2–7 to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 253 (about 1016). Measurements from repeated experiments sample the resulting probability distribution, which we verify using classical simulations. Our Sycamore processor takes about 200 seconds to sample one instance of a quantum circuit a million times—our benchmarks currently indicate that the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy8–14 for this specific computational task, heralding a much-anticipated computing paradigm. Read More
Google’s ‘Quantum Supremacy’ Isn’t the End of Encryption
Google accidentally made computer science history last week. In recent years the company has been part of an intensifying competition with rivals such as IBM and Intel to develop quantum computers, which promise immense power on some problems by tapping into quantum physics. The search company has attempted to stand out by claiming its prototype quantum processors were close to demonstrating “quantum supremacy,” an evocative phrase referring to an experiment in which a quantum computer outperforms a classical one. One of Google’s lead researchers predicted the company would reach that milestone in 2017.
Friday, news slipped out that Google had reached the milestone. The Financial Times drew notice to a draft research paper that had been quietly posted to a NASA website in which Google researchers describe achieving quantum supremacy. Read More
Why Google's Quantum Victory Is a Huge Deal—and a Letdown
They finally did it. After years—no, decades—of declaring their hopes and dreams with hardly any practical results, researchers in the quantum computing community have delivered on a promise. Or have they?
Last week, news leaked that researchers at Google and other institutions had solved a problem on a quantum computer 1 billion times faster than a classical computer. Google did not respond to a request for comment, but according to a draft manuscript describing the experiment, they have realized “quantum supremacy,” an achievement that “heralds the advent of a much-anticipated computing paradigm.”
The reactions from the rest of the quantum community, however, have been downright contradictory. Read More
The key to bigger quantum computers could be to build them like Legos
Visit any startup or university lab where quantum computers are being built, and it’s like entering a time warp to the 1960s—the heyday of mainframe computing, when small armies of technicians ministered to machines that could fill entire rooms. ….
The big challenge facing the nascent industry is to create machines that can be scaled up both reliably and relatively cheaply. Generating and managing the quantum bits, or qubits, that carry information in the computers is hard. Even the tiniest vibrations or changes in temperature—phenomena known as “noise” in quantum jargon—can cause qubits to lose their fragile quantum state. And when that happens, errors creep into calculations. Read More
Quantum radar: Experimental Microwave Quantum Illumination
Quantum illumination is a powerful sensing technique which employs entangled photons to boost the detection of low-reflectivity objects in environments with bright thermal noise. The promised advantage over classical strategies is particularly evident at low signal photon flux, a feature which makes the protocol an ideal prototype for non-invasive biomedical scanning or low-power short-range radar detection. In this work we experimentally demonstrate quantum illumination at microwave frequencies. We generate entangled fields using a Josephson parametric converter at millikelvin temperatures to illuminate a room-temperature object at a distance of 1 meter in a proof of principle bistatic radar setup. Using heterodyne detection and suitable data-processing at the receiver we observe an up to three times improved signal-to-noise ratio compared to the classical benchmark,the coherent-state transmitter, outperforming any classically-correlated radar source at the same signal powerand bandwidth. Quantum illumination is a first room-temperature application of microwave quantum circuits demonstrating quantum supremacy in detection and sensing. Read More
What is Quantum Computing and How is it Useful for Artificial Intelligence?
After decades of a heavy slog with no promise of success, quantum computing is suddenly buzzing! Nearly two years ago, IBM made a quantum computer available to the world. The 5-quantum-bit (qubit) resource they now call the IBM Q experience. It was more like a toy for researchers than a way of getting any serious number crunching done. But 70,000 users worldwide have registered for it, and the qubit count in this resource has now quadrupled. With so many promises by quantum computing and data science being at the helm currently, are there any offerings by quantum computing for the AI? Let us explore that in this blog! Read More
The Problem with Quantum Computers
By now, most people have heard that quantum computing is a revolutionary technology that leverages the bizarre characteristics of quantum mechanics to solve certain problems faster than regular computers can. Those problems range from the worlds of mathematics to retail business, and physics to finance. If we get quantum technology right, the benefits should lift the entire economy and enhance U.S. competitiveness.
The promise of quantum computing was first recognized in the 1980s yet remains unfulfilled. Quantum computers are exceedingly difficult to engineer, build, and program. As a result, they are crippled by errors in the form of noise, faults, and loss of quantum coherence, which is crucial to their operation and yet falls apart before any nontrivial program has a chance to run to completion. Read More
How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits
We significantly reduce the cost of factoring integers and computing discrete logarithms over finite fields on a quantum computer by combining techniques from Griffiths-Niu 1996, Zalka 2006,Fowler 2012, Eker ̊a-H ̊astad 2017, Eker ̊a 2017, Eker ̊a 2018, Gidney-Fowler 2019, Gidney 2019. We estimate the approximate cost of our construction using plausible physical assumptions for large-scale superconducting qubit platforms: a planar grid of qubits with nearest-neighbor connectivity,a characteristic physical gate error rate of 10−3, a surface code cycle time of 1 microsecond, and a reaction time of 10 microseconds. We account for factors that are normally ignored such as noise,the need to make repeated attempts, and the space time layout of the computation. When factoring2048 bit RSA integers, our construction’s space time volume is a hundredfold less than comparable estimates from earlier works (Fowler et al. 2012, Gheorghiu et al. 2019). In the abstract circuit model (which ignores overheads from distillation, routing, and error correction) our construction uses 3n+ 0.002nlgnlogical qubits, 0.3n3+ 0.0005n3lgnToffolis, and 500n2+n2lgnmeasurementdepth to factor n-bit RSA integers. We quantify the cryptographic implications of our work, both for RSA and for schemes based on the DLP in finite fields. Read More
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