1594945740

You are given a list of numbers and a target number, and you are asked to find the index in the list at which the target number appears. If the list is sorted, you can use search algorithms such as binary search. But if the list is not sorted, there isn’t really much you can do; you simply have to traverse the whole list till you find the element. In terms of algorithmic complexity, this takes O(N) time. With a quantum computer, however, you can solve this problem in just O(√N) time. This article explains how this is achieved by the Grover’s search algorithm.

**_If you’re new to quantum computing, you should first read this short primer: _***Quantum parallelism — where quantum computers get their mojo from**.*

Needle in a haystack (Image from Pixabay)

Let’s start by framing the problem. We are given:

- A set of N elements
`X = {x_1, …, x_i, … ,x_N}`

such that each`x_i`

is an m-bit string made of 0s and 1s. - A target element
`x*`

that is also an m-bit string made of 0s and 1s - A function _f _that takes as input an m-bit string and returns 1 if the string is
`x*`

and 0 otherwise. This function can be written as:

Grover’s search works in three steps as described below.

**Step 1: Setup the state**

A quantum state is set up in an equal superposition of the basis states. As an example, consider N=8. We set up the state using 3 qubits as:

#search #machine-learning #algorithms #quantum-computing #algorithms

1619247660

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

As the world is gearing towards more automation and AI, the need for quantum computing has also grown exponentially. Quantum computing lies at the intersection of quantum physics and high-end computer technology, and in more than one way, hold the key to our AI-driven future.

Quantum computing requires state-of-the-art tools to perform high-end computing. This is where TPUs come in handy. TPUs or Tensor Processing Units are custom-built ASICs (Application Specific Integrated Circuits) to execute machine learning tasks efficiently. TPUs are specific hardware developed by Google for neural network machine learning, specially customised to Google’s Machine Learning software, Tensorflow.

The liquid-cooled Tensor Processing units, built to slot into server racks, can deliver up to 100 petaflops of compute. It powers Google products like Google Search, Gmail, Google Photos and Google Cloud AI APIs.

#opinions #alphabet #asics #floq #google #google alphabet #google quantum computing #google tensorflow #google tensorflow quantum #google tpu #google tpus #machine learning #quantum computer #quantum computing #quantum computing programming #quantum leap #sandbox #secret development #tensorflow #tpu #tpus

1598717940

Many people are looking to quantum computing as the next revolutionary technology. Nature analyzed that in 2017 and 2018 alone, more than $450 million of private funding was poured into the quantum industry. Even the classical finance community starts to smell an opportunity. Xavier Rolet, the former CEO of the London Stock Exchange and well-respected industry veteran, told The Quantum Daily that he considers such investments a solid bet on the future and believes in the transformational change of quantum computers.

If not all, the exciting topic made its way to a more mainstream audience. Even the tabloids have been writing extensively and with very catchy headlines about a Nature article published in 2019. Researchers at Google announced that they achieved what is called *quantum supremacy*. On their quantum processor named Sycamore (see Fig. 1), they ran some calculations within 200 seconds that would have taken the world’s most powerful (classical) supercomputer 10,000 years — at least they claim. It has to be added that the setup was very specific and the results are heavily debated by competitor IBM. But certainly, the expectation towards the field has been starting to skyrocket.

As smart and quirky physicists move towards the field of quantum computation, build hyped startups and get huge funding, it is very interesting to follow this space. Will we have the chance to see disruptive innovation live and in action?

#quantum #quantum-computing #technology #innovation #computer-science #data science

1594945740

You are given a list of numbers and a target number, and you are asked to find the index in the list at which the target number appears. If the list is sorted, you can use search algorithms such as binary search. But if the list is not sorted, there isn’t really much you can do; you simply have to traverse the whole list till you find the element. In terms of algorithmic complexity, this takes O(N) time. With a quantum computer, however, you can solve this problem in just O(√N) time. This article explains how this is achieved by the Grover’s search algorithm.

**_If you’re new to quantum computing, you should first read this short primer: _***Quantum parallelism — where quantum computers get their mojo from**.*

Needle in a haystack (Image from Pixabay)

Let’s start by framing the problem. We are given:

- A set of N elements
`X = {x_1, …, x_i, … ,x_N}`

such that each`x_i`

is an m-bit string made of 0s and 1s. - A target element
`x*`

that is also an m-bit string made of 0s and 1s - A function _f _that takes as input an m-bit string and returns 1 if the string is
`x*`

and 0 otherwise. This function can be written as:

Grover’s search works in three steps as described below.

**Step 1: Setup the state**

A quantum state is set up in an equal superposition of the basis states. As an example, consider N=8. We set up the state using 3 qubits as:

#search #machine-learning #algorithms #quantum-computing #algorithms

1603604460

Recently, D-Wave Systems announced the general availability of its next-generation quantum computing platform through Leap quantum cloud service. The platform incorporates new hardware, software, and tools to enable and accelerate the delivery of in-production quantum computing applications.

Leap quantum cloud service includes the Advantage quantum system, with more than 5000 qubits and 15-way qubit connectivity, in addition to an expanded hybrid solver service that can run problems with up to one million variables.

According to reports, the combination of the computing power of Advantage and the scale to address real-world problems with the hybrid solver service in Leap enables businesses to run performant, real-time, hybrid quantum applications for the first time.

As part of its commitment to enabling businesses to build in-production quantum applications, the company announced D-Wave Launch, which is a jump-start program for businesses who want to get started building hybrid quantum applications today but may need additional support.

The company also announced a new hybrid solver, known as the discrete quadratic model (DQM) solver. It provides developers as well as businesses the ability to apply the benefits of hybrid quantum computing to new problem classes.

#news #5000 qubits #d-wave #d-wave expands its quantum cloud service to india #leap quantum cloud service #quantum cloud computing #quantum cloud service

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Sometime in the 1970s, the computing world hit its first major breakthrough - Dennis Ritchie and Ken Thompson at AT&T Bell Laboratories founded the Holy Grail of C programming. It took another 50 years for programmers to achieve a milestone of similar force - a language that brought a comparable level of simplicity and functions to quantum computing.

Introducing Silq - “A new high-level programming language for quantum computing with a strong static type system”- the first and only one of its kind!

**Learn More:** Meet Silq- The First Intuitive High-Level Language for Quantum Computers

#quantum computing #artificial intelligence #programming language #silq #quantum-computers