IBM Claims Major Breakthrough in Quantum Computing Reliability

Claims have been many.

IBM Claims Major Breakthrough in Quantum Computing Reliability  in Extremetech

Quantum computers are fast, but they produce a lot of wrong answers. IBM says its error mitigation technique could fix that.

By Ryan Whitwam,  June 15, 2023

Today's most powerful supercomputers can simulate complex weather patterns and the birth of stars, but even a modest quantum computer could outperform those machines. The mysterious nature of quantum mechanics has thus far made quantum computing little more than a curiosity, but IBM is claiming a significant breakthrough. According to IBM's Jay Gambetta, we've reached "the era of utility."

Quantum computers are a hot topic for research, but they haven't been useful for doing calculations yet. We keep trying because of the incredible potential of quantum computing, which takes advantage of weird quantum properties like entanglement, interference, and superposition to accelerate calculations. For example, the digital computers we've used for decades use transistors to signify a 1 or a 0. Using superposition, a quantum bit (qubit) can be a 1, 0, or both. Holding multiple values allows a qubit to perform multiple calculations, whereas a classical computer must do them individually.

These systems are incredibly fast, true, but they don't produce consistent results—at least until now, claims the study published in Nature. Google claimed quantum supremacy in 2019, producing calculations it says would have taken thousands of years on a digital computer. However, a follow-up analysis has shown that a conventional computer can do the same tabulations if given a little more time. IBM's claim is not about speed as much as it's about reliability. For a quantum computer to be useful, it needs to give the same answer every time, and IBM took a big step in that direction with a demonstration of error mitigation.

The team created a simulation of 127-atom bar magnets with a 127-qubit computer, a system known as an Ising model that is often used to study magnetism. At that scale, the magnets are affected by quantum factors, making it impossible to simulate on a classical computer accurately. The researchers leveraged quantum interference to nudge the results, pushing them farther from the solution. By introducing noise into the calculations, the IBM Quantum team could understand the effects of noise in the simulation, working backward to reach the ideal, low-noise result ....'

Erasure Key to Practical Quantum Computing

Tips towards Quantum improvement.

Erasure Key to Practical Quantum Computing

Researchers at Princeton University, Yale University, and the University of Wisconsin-Madison have developed a method for error correction in a quantum computer's calculations.   The researchers focused on physical causes of error; in their proposed system, the most common source of error eliminates damaged data instead of corrupting it.

They studied the electrons in ytterbium qubits, and when errors cause the electrons to fall to the ground state from their excited state, they visibly scatter light.  This means that when shining a light on ytterbium qubits, only the faulty ones light up and can be written off as errors.

Said Princeton's Jeff Thompson, "These erasure errors are vastly easier to correct because you know where they are." ... 

Said Princeton's Jeff Thompson, “We see this project as laying out a kind of architecture that could be applied in many different ways. We are already seeing a lot of interest in finding adaptations for this work.”  ... 

From Princeton University School of Engineering and Applied Science

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Quantum Computer Could Catch Its Own Errors

 Don't understand fully,  worth a look, complex.  

Quantum Computer Could Catch Its Own Errors

New Scientist, Karmela Padavic-Callaghan, May 25, 2022

A team of Austrian and German scientists has constructed a 16-quantum bit (qubit) computer that runs error-free calculations. The researchers developed a series of quantum gates to serve as components of more sophisticated computations, which prevent errors within even the most complex. They corralled 14 calcium ions with electric fields, forming two logical qubits composed of seven entangled ions each; two additional qubits flagged erroneous computations requiring correction. "With this universal set of gates, you can approximate every calculation that you can possibly want to do with a quantum computer," said Lukas Postler of Austria’s University of Innsbruck. The researchers found each logic gate in the system that works reduces the number of errors. ....' 

Faster Computing Results Without Fear of Errors

Interesting look at how to minimize errors in computing, could be especially useful if it included security aspects.

Faster Computing Results Without Fear of Errors

MIT News  Adam Zewe, June 7, 2022

A multi-institutional team of researchers has developed PaSh, a system that can dramatically speed up certain types of computer programs while ensuring the accuracy of results. The system accelerates programs or scripts that run in the Unix shell, parsing their components into segments that can be run on multiple processors. PaSh parallelizes program components "just in time" to predict program behavior, speeding up more elements than traditional methods that attempt to parallelize in advance while still returning accurate results. The researchers tested PaSh on hundreds of scripts without breaking one; the system also ran programs an average six times faster than unparallelized scripts, and realized a nearly 34-fold maximum speed increase. ... '

Quantum Computing: A Useful Look at Why

How broadly might Quantum computing realistically improve  our algorithmic capabilities  Below a short intro. 

Quantum computer succeeds where a classical algorithm fails

Quantum computers coupled with traditional machine learning show clear benefits.

By JOHN TIMMER  in Arstechnica

People have performed many mathematical proofs to show that a quantum computer will vastly outperform traditional computers on a number of algorithms. But the quantum computers we have now are error-prone and don't have enough qubits to allow for error correction. The only demonstrations we've had involve quantum computing hardware evolving out of a random configuration and traditional computers failing to simulate their normal behavior. Useful calculations are an exercise for the future.

But a new paper from Google's quantum computing group has now moved beyond these sorts of demonstrations and used a quantum computer as part of a system that can help us understand quantum systems in general, rather than the quantum computer. And they show that, even on today's error-prone hardware, the system can outperform classical computers on the same problem.

Probing quantum systems

To understand what the new work involves, it helps to step back and think about how we typically understand quantum systems. Since the behavior of these systems is probabilistic, we typically need to measure them repeatedly. The results of these measurements are then imported into a classical computer, which processes them to generate a statistical understanding of the system's behavior. With a quantum computer, by contrast, it can be possible to mirror a quantum state using the qubits themselves, reproduce it as often as needed, and manipulate it as necessary. This method has the potential to provide a route to a more direct understanding of the quantum system at issue.

Much of the paper is devoted to describing situations where this should be the case, in part elaborating on ideas described in earlier papers.  .... ' 

AI Efficiently Fixes Mistakes in Error-Prone Quantum Computers

AI Efficiently Fixes Mistakes in Error-Prone Quantum Computers

By New Scientist, February 11, 2022

Artificial intelligence (AI) can eliminate errors from a group of quantum bits, thanks to Lorenzo Cardarelli and colleagues at Germany's RWTH Aachen University.

The researchers used a small quantum computer model to generate a quantum version of a machine learning autoencoder algorithm. They fed data into the system to see which errors it produced, creating pairs of correct and error-saturated data with which they trained the quantum autoencoder to detect and fix errors.

Cardarelli said the AI could be trained on a specific quantum computer and learn to correct errors unique to that system. "This is almost like custom designing an error-correction code according to the characteristics of the particular hardware," said Sonika Johri at U.S.-based quantum computing firm IonQ.

From New Scientist

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AI Fixing Quantum Errors

 Patterns to correct errors/

AI Efficiently Fixes Mistakes in Error-Prone Quantum Computers

By New Scientist  February 11, 2022

Artificial intelligence (AI) can eliminate errors from a group of quantum bits, thanks to Lorenzo Cardarelli and colleagues at Germany's RWTH Aachen University.  The researchers used a small quantum computer model to generate a quantum version of a machine learning autoencoder algorithm.

They fed data into the system to see which errors it produced, creating pairs of correct and error-saturated data with which they trained the quantum autoencoder to detect and fix errors.Cardarelli said the AI could be trained on a specific quantum computer and learn to correct errors unique to that system.

"This is almost like custom designing an error-correction code according to the characteristics of the particular hardware," said Sonika Johri at U.S.-based quantum computing firm IonQ.

 In New Scientist

Flawed Algorithms

Always looking at data and context involved when algorithms fail.  Like any kind of predictive approach, its rarely perfect.   The same for classing analytics and for machine learning based methods.  And for that matter for human predictive methods as well.   And that can change as data and context changes over time.    So these kinds of test examples are useful.

Algorithm That Predicts Deadly Infections Is Often Flawed   By Wired

A study using data from nearly 30,000 patients in University of Michigan hospitals suggests Epic Systems' early warning system for sepsis infections performs poorly.

An algorithm designed by U.S. electronic health record provider Epic Systems to forecast sepsis infections is significantly lacking in accuracy, according to an analysis of data on about 30,000 patients in University of Michigan (U-M) hospitals.

U-M researchers said the program overlooked two-thirds of the approximately 2,500 sepsis cases in the data, rarely detected cases missed by medical staff, and was prone to false alarms.

The researchers said Epic tells customers its sepsis alert system can correctly differentiate two patients with and without sepsis with at least 76% accuracy, but they determined it was only 63% accurate.

U-M's Karandeep Singh said the study highlights wider shortcomings with proprietary algorithms increasingly used in healthcare, noting that the lack of published science on these models is "shocking."

From Wired