Bacteria are super sensitive to heat and raising the water to boiling temperatures will inactivate them. To prevent disease, water can be boiled in preparation for consumption. Heating it at least at 145 Fahrenheit is an easy way to purify the water, and the minimum boiling point is 212 F!

What temperature does water have to be to kill bacteria?

If you are wondering if you can stall a virus with heat, the answer is yes. Much like with other water filters, heating up water has many benefits!

Facts

What Water Temperature Do You Need to Kill a Virus?

Dry ice is frozen carbon dioxide. A block of dry ice has a surface temperature of -109.3 degrees Fahrenheit (-78.5 degrees C). Dry ice also has the very nice feature of sublimation -- as it breaks down, it turns directly into carbon dioxide gas rather than a liquid.

What is the temperature of dry ice?

I saw your question on fog machines and dry ice and would like to know more -- how exactly does dry ice work?

How Does Dry Ice Work?

Quantum teleportation is a technique for transferring quantum information from a sender at one location to a receiver some distance away. While teleportation is portrayed in science fiction as a means to transfer physical objects from one location to the next, quantum teleportation only transfers quantum information .

Quantum Teleportation

For the first time, a team of scientists and researchers have achieved sustained, high-fidelity ‘quantum teleportation’ — the instant transfer of ‘qubits’ (quantum bits) the basic unit of quantum information. the collaborative team, which includes NASA’s jet propulsion laboratory, successfully demonstrated sustained, long-distance teleportation of qubits of photons (quanta of light) with fidelity greater than 90%. the qubits were teleported 44 kilometers (27 miles) over a fiber-optic network using state-of-the-art single-photon detectors and off-the-shelf equipment.

NASA’s Achievement

Important point to keep in mind is quantum teleportation is the transfer of quantum states from one location to another using quantum entanglement, where the two particles in separate locations are connected by an invisible force, famously referred to as “spooky action at a distance ” by Albert Einstein. Regardless of the distance, the encoded information shared by the “entangled” pair of particles can be passed between them. An interesting note is that the sender knows neither the location of the recipient nor the quantum state that will be transferred.

By sharing these quantum qubits, the basic units of quantum computing, researchers are hoping to create networks of quantum computers that can share information at blazing-fast speeds. But keeping this information flow stable over long distances has proven extremely difficult due to changes in the environment including noise. Researchers are now hoping to scale up such a system, using both entanglement to send information and quantum memory to store it as well.

....

On the same front, scientists have advanced their quantum technology research with the development of a chip that could be scaled up and used to build the quantum simulator of the future using nanochip that allows them to produce enough stable photons encoded with quantum information to scale up the technology. The chip, which is said to be less than one-tenth of the thickness of a human hair, may enable the scientists to achieve ‘quantum supremacy’ – where a quantum device can solve a given computational task faster than the world’s most powerful supercomputer.

The Chip

In quantum entanglement particles that have interacted at some point retain a type of connection and can be entangled with each other in pairs, in a process known as correlation .Knowing the spin state of one entangled particle – up or down – allows one to know that the spin of its mate is in the opposite direction. Quantum entanglement allows qubits that are separated by incredible distances to interact with each other instantaneously (not limited to the speed of light). No matter how great the distance between the correlated particles, they will remain entangled as long as they are isolated.

Quantum Entanglement

In July, the US Department of Energy unveiled a blueprint for the first <a href="https://www.bbvaopenmind.com/en/technology/digital-world/quantum-internet-explained/">quantum internet </a>, connecting several of its National Laboratories across the country. A quantum internet would be able to transmit large volumes of data across immense distances at a rate that exceeds the speed of light . You can imagine all the applications that can benefit from such speed. Traditional computer data is coded in either zeros or ones. Quantum information is superimposed in both zeros and ones simultaneously. Academics, researchers and IT professionals will need to create devices for the

Quantum Teleportation: Paving the Way for a Quantum Internet

quantum routers, quantum repeaters, quantum gateways, quantum hubs, and other quantum tools. A whole new industry will be born based on the idea of quantum internet exists in parallel to the current ecosystem of companies we have in regular internet. The “traditional internet “, as the regular internet is sometimes called, will still exist. It is expected that large organizations will rely on the quantum internet to safeguard data, but that individual consumers will continue to use the classical internet.

Experts predict that the financial sector will benefit from the quantum internet when it comes to securing online transactions. The healthcare sectors and the public sectors are also expected to see benefits. In addition to providing a faster, safer internet experience, quantum computing will better position organizations to solve complex problems, like supply chain management. Furthermore, it will expedite the exchange of vast amounts of data, and carrying out large-scale sensing experiments in astronomy, materials discovery and life sciences.

What Experts Say

Quantum teleportation is a technique for transferring quantum information from a sender at one location to a receiver some distance away.

Quantum Veda

Quantum Teleportation: Facts and Myths | OpenMind

The ability for an organ to take photons from the outsight world, focus them, and then convert them into electrical signals is pure awesomeness! But what’s even more awesome is the organ behind your eyeballs — the brain!The brain is able to take those electrical signals, convert them into images, and then figure out things like, who that person is across the street or what those funny symbols mean. It’s a miracle that we’re able to see, but an even greater miracle is our ablity to grant that gift to machines . One way to do it is through Machine Learning.

Sight. One of nature’s finest gifts.

Let’s do a quick run through of how a machine could see. First let’s take the MNIST Dataset, a dataset of digits from 0 to 9: Each digit is a 28 x 28 image, meaning there’s a total of 784 pixels in the whole image. We take our image and flatten it (instead of 28 x 28, we turn the shape into 784 x 1). We pop this guy into our neural network and on the other side we end up with our prediction !

A Machine That Sees

Turns out this simple neural network is able to achieve an <a href="http://yann.lecun.com/exdb/publis/pdf/lecun-98.pdf">88% accuracy </a>! That’s pretty impressive, considering that it’s just a bunch of linear layers and activations. But let’s try something even better…

CNNs are actually able to achieve pretty insane results — <a href="https://github.com/Coderx7/SimpleNet">99.75% accuracy </a>! The reason why CNNs’ incredible power is due to it’s ability to look at the surrounding pixels and based off of that, extract features and information from that patch of pixels. Normal NNs can’t do that, so they’re a bit less powerful.CNNs look like this:The 3 main parts of a CNN areConvolutional Layers : These are the layers which have kernels, they're really good at extracting features from the image and passing it on

CNNs

Max Pooling Layers : These layers reduce the feature map (the size of the features), reduce the computational resources needed and prevents overfittingFully Connected Layers : They appear at the end of the CNN, they’re just linear layers which takes the results of the CNN as inputs and outputs the lable That’s the architecture, but the really amazing part of a CNN are it’s kernels inside it’s convolutional layers! These kernels are only matrixes (basically a bunch of numbers sorted in a box), but they’re able to extract tons of features about the image.

By the first layer the kernels can start telling which images have verticle lines, horizontal lines and different colors. By layer 2 you can put those features together and form more comple shapes like corners or circles.Layer 3 becomes even cooler! Repeating patterns, car wheels and even humans.And as you stack your convolutions more and more you get more and more complex features — that’s insane becuase CNNs are able to extract those meta structures of the image.

A Bit Detailing

By extracting those features you can put them in a neural network and classify your image! But as cool as that sounds, there are 2 Achilles heels: <ol><li>When input dimensions increase exponentially, the time it takes to run the CNN also becomes exponential . An example of a problem like that would be when you’re modeling quantum systems to classical computers, the input space grows exponentially</li><li>As you increase the kernel size, the time it takes to run the CNN becomes exponential </li></ol>But Quantum’s here to the rescue!

To tackle the first problem, we could just let qubits represent the quantum system! Introducing: Quantum Convolutional Neural Networks . This is a neural network that literally replicates the whole CNN architecture. C onvolutional layers and max pooling are all translated to the quantum realm! The architecture itself looks like this:

Quantum Convoluional Neural Networks

1.Convolutional layers : Instead of kernals, you have gates that are applied to the qubits adjacent to it2.Pooling Layers : Where you just measure half of the qubits and kick out the rest3.Fully Connected Layer: Just like the normal oneIf you’re a super quantum nerd you might have noticed that this architechture might have some resemblence to a reverse MERA (Multi-scale Entanglement Renormalization Ansatz).A normal MERA takes 1 qubit and then exponentially increases the number of qubits by introducing new qubits into the circuit.But in the reverse MERA, we’re doing the

And it has the familar parts of your classical CNN:

opposite by exponentially decreasing the number of qubits.The bottleneck here is the range of possible qubits which the reversed MERA can reach.In other words, the QCNN might not be able to produce the labels. But we can overcome this by implementing Quantum Error Correction(QEC),the thing you see in the red box in the diagram.This architecture works super well with problems that require a small input size,since our current quantum computers can’t hold that many qubits.But what if we wanted to use QCNN’s for image classifiction or other problems that need more input space?

Reverse MERA And  QEC

A Quanvolutional Neural Network (QNN) is basically a CNN but with quanvolutional layers (much like how CNN’s have convolutioanl layers). A Quanvolutional layer acts and behaves just like a convolutional layer! Much like a normal convolutional layer, we take a subset of the image, pass it through our kernal , and then it outputs a part of the new image. We do this over and over again until we reach the linear layer, which classify’s the image. Since it acts so much like a normal Convolutional layer, you could literally use both a QNN and a CNN together in the same model!

Quanvolutional Neural Networks

<ul><li>Noise Resistant : With Quantum Error Correction, along with it’s quantum nature, QNNs are resistant to constant noise. In current quatnum computers, there’s always a constant noise / error that occurs in quantum gates, but QNNs overcome it </li><li>Better Results : In <a href="https://arxiv.org/pdf/2102.06535v1.pdf">this paper </a>, researchers use QNNs to diagnose Covid just from chest X-rays! They obtained a 98% accuracy, 2% better than standard CNNs! </li><li>Faster Training Time : Classical CNNs have O(n²) time, where n is the kernal size. QNNs have O(log(n)) time! That’s an insane speedup! </li> </ul>

Advantages

<ul><li>Many Executions Needed: Since we have to stamp the kernal all over the image, and do this to the potential of thousands of images, you’re going to have to run run the quantum circuit a lot. Current quantum computers aren’t able to handle that many executions</li><li>Difficult to optimize : Inside QNNs there are things call encoding protocals . These protocals are very difficult to optimize. Researchers don’t know which protocols are good, useless or even counter productive!</li></ul>

Disadvantages

These new Quantum Machine Learning algorithms are but a testament to what there is to come. Even though quantum computers are at it’s infancy, we have already seen these new QML algorithms which are already outperforming our old ones!Many of our existing ML algorithms could be translated into QML algorithms, allowing them take avantage of new properties like entanglement, superpostion and insane parallel computing! It’s only a matter of time before these algorithms are changing the world!

The World Is Changing 

The ability for an organ to take photons from the outsight world, focus them, and then convert them into electrical signals is pure awesomeness! But what’s even more awesome is the organ behind your…

Quantum Eyes

If you know a bit about computers, you may know that computers use bits, which can either be on or off, usually referred to as 1 and 0 respectively. The states of these bits can be modified using logic gates like <a href="https://www.tutorialspoint.com/computer_logical_organization/logic_gates.htm">AND, OR, XOR </a>, etc. Quantum computers also have bits and logic gates, though they get a bit more complicated.

BITS And LOGIC GATES

Qubits are the quantum equivalent of bits, but they work very differently from classical bits (the bits used in our computers). Qubits, like classical bits, can be in states of 0 and 1, also known as spin up and spin down, but what makes qubits useful is the concept of quantum superposition.

Qubits

In Brief,Superposition is essentially when a qubit is in a state somewhere in between 0 and 1 that then becomes either 0 or 1 when observed. A very common example is one of a spinning coin. When you flip a coin, there is a mixture of heads and tails (like a qubit being in the states of 0 and 1) but when it stops, it is either heads or tails (this is what happens when we observe the qubit to get the result of our calculation).Calculations can be performed while the qubit is in a superposition, which is what makes quantum computers so powerful.

Superposition

Qubits can be represented using an equation, which is what we will do.This equation is very useful when working with the Bloch sphere, which is a great tool for visualizing the state of a qubit.Now let me explain what is going on. The |0> and |1> are just the states of 0 and 1, using a notation commonly used in quantum equations called the bra-ket notation. e is <a href="https://www.youtube.com/watch?v=AuA2EAgAegE">Euler’s number </a>and <a href="https://www.khanacademy.org/math/algebra2/x2ec2f6f830c9fb89:complex/x2ec2f6f830c9fb89:imaginary/v/introduction-to-i-and-imaginary-numbers">i is the imaginary unit </a>.

Now some math

For this article, you won’t need to worry too much about these. Just know that they are important when representing the states of the qubit because a lot of quantum mechanics uses imaginary numbers.The theta and phi symbols are used to describe a vector on the Bloch sphere. In quantum mechanics, the theta influences the magnitude and phi determines the phase of the qubit. Again, you don’t need to understand this terminology for the purposes of this article as they can be thought of as angles on the Bloch sphere but I will link more information at the end of the article.

Introduction 

You’ve heard a bunch about this Bloch sphere throughout this article and it is just a sphere that is used to visualize the state of a qubit. So how does any of this relate to qubit logic gates? Well, logic gates correspond to rotations on the Bloch sphere, which modify the equation previously mentioned. Each gate also corresponds to a transformation matrix, but I won’t be talking about that in this article. As you can see both theta and phi correspond to angles.

Finally, for the Bloch sphere

This is the Bloch sphere in the 0 state. Both theta and phi are at 0 right now.cos(0/2) = 1sin(0/2) = 0This means that there is a 100% chance that this qubit is in the state of 0. This is generally the starting state of qubits when it comes to quantum computing.The gray circle at the bottom corresponds to phi.A gate will cause the vector (the arrow in this case) to rotate in a certain way

Depiction

One important thing to remember when it comes to the Bloch sphere and quantum gates is the phase of the qubit. The phase will generally “point” in the same direction as the arrow. If we look at the equation, phi is the angle of the arrow on the 2D (x and y axes) plane. The phase is very important in quantum computing but it is a separate subject altogether, so I will link more resources at the bottom. So now let’s look at some common gates.

The phase

First we will look at the Pauli-X gate,also known as the NOT gate,and works very similarly to the NOT gate in classical computer science.All it does is switch the probabilities of |0>and |1>. So if we start the qubit with a 100%possibility of being0,then this gate will change it to a 100% possibility of being in the 1 state.This is how the Blochsphere representation of the qubit will look if the NOTgate was applied on the previously shown gate of 0.Notice the 180degree rotation around thex-axis.The Pauli-Ygate corresponds to a 180degree rotation around they-axis,similar to thePauli-Xgate

The Pauli-X And Pauli-Y Gates

The Hadamard gate is very important because it puts the qubit into a state of superposition. It corresponds to a 90-degree rotation around the x and the z axes. After applying the Hadamard gate you are in between the 0 and 1 states, meaning there is a 50% chance that the qubit will result in a 0 and a 50% chance that the qubit results in a 1. There are in-between states. For example, 25% chance for 0 and 75% chance for 1.

The Hadamard Gate

These three gates correspond to rotations around the z-axis by different amounts, with T being a 45-degree rotation, S being a 90-degree rotation and Pauli-Z being a 180-degree rotation. The T gate was applied after a Hadamard gate. The T gate changed the phase to π/4

The T, S and Pauli-Z Gates

The Z gate was applied after a Hadamard gate. The Z gate changed the phase to π The T and S gates both have inverse gates that correspond to a rotation in the opposite direction. For example, if the inverse of the S gate was applied after a Hadamard gate, the phase would be 3π/2. The Pauli-Z gate does not have an inverse because applying it twice brings it back to the original position. (180-degrees + 180-degrees = 360-degrees which is a full rotation)

In Continuation...

I hope that this article was a nice introduction to quantum gates and some of the math behind it. There are many things I could not mention or explain in this article for the sake of time and staying on-topic but this is the groundwork to start learning more concepts.

Conclusion

If you know a bit about computers, you may know that computers use bits, which can either be on or off, usually referred to as 1 and 0 respectively. The states of these bits can be modified using…

What Water Temperature Do You Need to Kill a Virus?

How Does Dry Ice Work?

Quantum Teleportation: Facts and Myths | OpenMind

Quantum Eyes

Quantum Logic Gates

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