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A European radio telescope array just reached a major milestone in its quest to paint a picture of the radio night sky—and you can explore highlights of this mind-blowing cosmic map for yourself.

A team of scientists working on the LOw Frequency ARray (LOFAR) radio telescope in Europe published an overview of a new, freely available data package that covers 27 percent of the Northern sky. The data will be useful for researchers studying everything from the evolution of galaxies, black holes, exoplanets, and certain types of stars. These researchers are also looking for non-experts to get involved–they need your help to spot the wonders of the cosmos in all of those images.

LOFAR senses radio waves, as opposed to optical light captured by telescopes such as NASA’s Hubble Space Telescope. LOFAR also targets lower-frequency light than most other radio telescopes. It will map the entire Northern sky with very good resolution, says Timothy Shimwell, an astronomer at ASTRON, the Netherlands Institute for Radio Astronomy, which operates the LOFAR telescope.

The map is already incredibly detailed. With more than 4 million radio sources, most of which are galaxies, this data release has “more radio sources in it than all other surveys of the entire sky combined,” says Joe Callingham, a radio astronomer at Leiden University who contributed to LOFAR and will use its data in his research.

The telescope is essentially a large antenna stretching across Europe, built from smaller antennas. The hardware of the telescope doesn’t look cutting edge. The setup that detects lower frequencies is literally “a stick in the ground with some wires coming off it,” says Shimwell. The machine that detects higher frequencies, meanwhile, is essentially “a big styrofoam box with, like, a bow-tie shaped antenna inside it.” These are both relatively inexpensive compared to building a set of huge radio dishes like many other chúng tôi real brains of LOFAR are in the processing that’s done afterwards, Shimwell says. “It’s almost like a software telescope.”

On the “ground” of the visualization you can see a circle of disembodied Earth where the main antennas based in the Netherlands are planted. The cones of bright spots represent the view of the telescope—the areas of the sky it has scanned already. The bright spots are mostly galaxies that the telescope has imaged.

[Related: The ‘double-disk’ shape of the Milky Way could be common across galaxies]

Like the constellations you see when you look up at the night sky, LOFAR sees radio sources as a flat canvas. But the stars and galaxies spotted are actually spread out in three dimensions—two objects might appear to be close to each other in the sky while, in reality, one is much farther away. For example, the stars Betelgeuse and Bellatrix make up each shoulder in the constellation Orion, appear close together in the sky. But Betelgeuse is roughly twice as far away as Bellatrix is from Earth.

By combining the radio maps with data from another project, the LOFAR team could figure out how far away many of the radio sources in their dataset were. A team member used these measurements to make the distance of each bright spot correspond to its real distance in the cosmos.

“All of the data in that visualization is actually real,” Shimwell says. The radio sources aren’t all galaxies, but astronomers expect around 99.9 percent should be, Callingham says. Stars, unless they’re doing something strange, aren’t as bright as galaxies in radio frequencies, he says.

In 2023 the team published their first data release on 2 percent of the sky. They hope to complete the whole Northern sky in three or four years, Shimwell says.

With the enormous amount of data, scientists need people to help sort through images and train algorithms to sort through them better. You can join a citizen science project to help spot supermassive black holes and star forming galaxies in the images.

The new LOFAR dataset “is a really exciting and fantastic data product,” says Marin Anderson, an astronomer at NASA’s Jet Propulsion Laboratory and the Project Scientist for the Owens Valley Long Wavelength Array, a different radio observatory. The density of radio sources it has detected is more than eight times what other similar radio telescopes have been able to pick up, she says. 

Anderson’s research focuses on radio signals that change over time—like those from stars and chúng tôi low-frequency range of the telescope will assist that kind of research, because emissions from stars and exoplanets are also better seen in low-frequency radio, compared to the frequencies that most radio telescopes see. Anderson is also gratified to see the sharpness of images from LOFAR.

“When you look at an image from Hubble…it’s mind blowing,” Anderson says. But usually when you look at a radio image, even if there’s lots of science packed into it, it’s “just a fuzzy blob.” In these sharper images, radio astronomers finally have something equivalent.

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The Physics Of Time Travel

by Courtesy of Dreamworks

Dreamworks’ remake of The Time Machine is the latest expression of our fascination with time travel.

Start with a Black Hole …

The physical possibility of time traveL is something of a catch-22. Any object that’s surrounded by the twisted space-time that time travel requires must by its very nature be fantastically perilous, a maelstrom that would inevitably tear apart the foolhardy traveler. So physicists have labored to create a theoretically acceptable time machine that’s free from nasty side effects like certain death. Their starting point: black holes.

Black holes are famous for sucking in everything around them-including light-and never letting go. But black holes have other characteristics, namely the way they bend nearby space-time. A black hole is infinitely dense, which means that it pulls the fabric of space-time to the breaking point-creating a deep pockmark, complete with a tiny rip at the bottom.

Many have wondered what lies on the other side of this rip. In 1935, Einstein and his colleague Nathan Rosen developed a scenario in which the tiny rip in a black hole could be connected to another tiny rip in another black hole, joining two disparate parts of space-time via a narrow channel, or throat. The Einstein-Rosen bridge, as the notion was then called, looks like a black hole attached to a mirror image of itself.

This bridge-a sort of back door leading from the interior of one black hole into another-is today known as a wormhole. Such a portal could in theory create a shortcut through space-time-just the thing a time traveler would need if he wanted to cheat Father Time out of a few million years.

Next, Modify the Wormhole …

created between two black holes is minuscule, smaller than the center of a single atom, and remains open for only a fraction of a second. Even light, the fastest entity in the universe, would not have enough time to pass through. And no matter how sturdy his spacecraft, our traveler would inevitably be ripped apart by the black hole’s immense gravitational forces. Because of these and other problems, the Einstein-Rosen bridge was for many years thought of as a geometric curiosity, a theoretical quirk that could never be of use to even a fictional time traveler. Einstein’s equations might allow for wormholes, but the universe certainly did not. All that changed in the 1980s, however, when a physicist at the California Institute of Technology devised a better way to use wormholes as time machines.

If Einstein and Rosen are the architects of the space-time shortcut, then Kip Thorne of Caltech is its structural engineer. Starting from the rough sketch that Einstein and Rosen left behind, Thorne created an algorithm that describes in strict mathematical terms the physics of a working time machine. Of course, actually building Thorne’s time portal would require a technological prowess that is at least many centuries away. But his work proves that time travel is possible-at least in theory.

Thorne’s problem was finding a way to hold open the wormhole’s channel, or throat, long enough for an explorer to pass through. Ordinary matter won’t do: No matter how strong it is, any scaffolding made of matter cannot brace against the crush of space-time. Thorne needed a substance that could counteract the squeeze of a black hole. Thorne needed antigravity.

Antigravity does the trick; the problem is finding it. Einstein first postulated the existence of antigravity on cosmic scales in 1915, a conjecture proven correct eight decades later. But Einstein’s antigravity is wispy and dilute, a spoonful of sugar dissolved in the Pacific Ocean. Opening a wormhole requires a regular torrent of antigravity.

The best current candidate for creating concentrated antigravity is called the Casimir effect. Because of the quirks of quantum mechanics, two flat metal plates held a hair’s width apart generate a small amount of negative energy. That energy, multiplied many times over, could in principle be used to create a traversable wormhole. The widening, meanwhile, would dilute the strength of nearby gravity, preventing the traveler from being torn apart.

Once the antigravity scaffolding is holding open the portal, the traveler passing through would emerge in a distant place. But time travelers, of course, want to journey not just geographically but temporally. So Thorne’s next step was to desynchronize the two regions on either side of the wormhole.

To do this, he applied an old trick of Einstein’s. A major consequence of Einstein’s Special Theory of Relativity is that time slows for objects that move quickly. Thorne applied this principle to one of the two black holes that make up a wormhole. Imagine lassoing one of the black holes-perhaps by trapping it inside a cage of negative energy-and towing it around the universe at close to the speed of light. That black hole, and therefore that end of the wormhole, would age more slowly than the stationary end of the wormhole. Over time, the black holes would become desynchronized, two objects connected through the wormhole but existing in different eras. An explorer who entered the stationary end of the wormhole would exit the moving end, many years earlier than when he departed, making the wormhole a true time portal.

Or Try It on a Shoestring

The most recent development in the physics of time travel came in 1991, when Princeton astrophysicist J. Richard Gott III suggested that hypothetical objects called cosmic strings might enable an astronaut to travel backward in time. Cosmic strings are long, thin objects that some cosmologists believe coalesced out of the universe’s very earliest days. They are infinitely long, no wider than a single atom, and so dense that a few miles of a single cosmic string would outweigh Earth itself.

Gott’s proposal relies on idealized versions of cosmic strings. In order to be em-ployed in the service of a time traveler, two cosmic strings, perfectly parallel and traveling at nearly the speed of light, must whiz past one another like two cars traveling in opposite directions on a highway. As the strings pass each other, space-time would become profoundly distorted by the influence of these fast-moving filaments. A savvy time traveler, waiting in a nearby spaceship, could exploit those distortions by flying around the coupled strings. If he timed it just right, the twists in space-time would enable him to return to his starting point before he began-making the voyage a one-way trip back in time. Which means that, according to the laws of physics, journeys through time are conceivable, if rather difficult to arrange. It may be only a matter of time.

Esims And International Travel: Let’S Debunk This Misconception

Dhruv Bhutani / Android Authority

The Apple iPhone 14 announcement earlier this week brought the spotlight on eSIMs because all iPhone 14 units in the US won’t have a physical SIM slot, but will instead support eSIMs. Suddenly, this feature that was often considered secondary is on everyone’s lips. And just like it did with the 3.5mm plug and the charger in the box, Apple will likely drag the entire industry behind it. We’ll soon have eSIM-only Android phones — that’s a certainty.

Among all the digital ink that’s being spilled around eSIMs, there seems to be one general misconception that keeps coming back and back: People think that having no SIM slot is very inconvenient for international travel and that American operators will profit because you’ll be forced to use roaming on your US iPhone.

In my experience, that couldn’t be further from the truth. I have gone on more than 15 trips in the past 18 months. I visited eight different countries and used free roaming where my SIM card allowed it, but bought a prepaid data eSIM in four countries: Belgium, Switzerland, Turkey, and Canada. And my personal verdict is indisputable: eSIMs are a win for travelers.

In many instances, a prepaid data eSIM from sites like Airalo and Mobimatter will be significantly cheaper than a traditional SIM too. The cheapest traditional prepaid SIM I could find in Canada was around 50 CAD, for example, compared to the $20 that I paid. And when I went to Istanbul for a day, I got a cheap $6 or $7 eSIM because I didn’t need more than 1GB of data.

Prepaid eSIMs are also likely to be cheaper than traditional SIM plans.

Sure, if you’re planning to travel for several months, a proper data plan with a more traditional SIM may be less expensive. But for most travelers who are likely to spend a week or two at most in a foreign country, odds are in favor of the eSIM being cheaper.

Do you use a prepaid eSIM while traveling?

1045 votes

The only caveat is that prepaid data eSIMs aren’t available for every country. More than 80 countries are supported by Mobimatter, and more than 190 by Airalo, covering a substantial chunk of earth, but leaving some smaller countries behind. Incidentally, I can’t find a data eSIM for my home country of Lebanon. In these instances, you’ll need to find another solution if your phone only supports eSIMs. Or you can wait a bit. Local operators will likely join the eSIM rank soon, whether they’re ready or not — this is a case of Apple taking the industry hostage and forcing it to move in one direction.

eSIMs aren’t fully ready to take on the world, but don’t assume they’re bad for travel.

And sure, there are many issues with eSIMs and the way some operators have implemented them around the world, but let’s not add the false assumption that they’re bad for international travel. The truth is that they’re super convenient to buy and set up for short vacations, but somehow most of the tech industry hasn’t caught up to that yet.

The Map() Function In Swift

In Swift, the map() function can be used to apply a function for each element in a collection.

For example, let’s square an array of numbers:

let numbers = [1, 2, 3, 4, 5] let squared = chúng tôi { $0 * $0 } print(squared)

Output:

[1, 4, 9, 16, 25]

Here is an illustration of how the above code works:

In this guide, you learn how to use the map() function with closures on different collection types in Swift.

Before learning about the map() function it is important you understand what a closure is in Swift.

Closures in Swift – A Quick Primer

In Swift, a closure is a function that has no name. It is a block of code that can be passed around, for example as an argument to a function.

Closure Syntax

The syntax of closure looks like this:

statements }

Where:

params represents the function arguments for the closure.

return type is the type of the return value.

statements refers to any valid Swift expressions.

Calling a Closure

When you call a regular function, you call the name of the function followed by a set of parenthesis (with possible arguments):

f(arg)

Where f is a function and arg is an argument.

Calling a closure works the same way but it looks different. A closure has no name so is no way to call a closure by name. Thus you have to “use” a closure instantly as you define it.

Here is the syntax of calling a closure in general:

Here the closure is defined on the same line as it is called.

Closure Example

Let’s square a number using a closure function that takes a number as an argument and squares it:

print(result)

Output:

81

As you can see, we define the closure and call it in the making. After this line has been executed, there is no trace of that closure.

Simplifying a Closure in Swift

Usually, closures are written in a simpler form. This is because the Swift compiler can infer a lot of things about the closure without you having to specify them.

Here are the steps to reducing the above closure into a simpler form:

({ (num: Double) in return num * num })(9.0) ({ num in return num * num })(9.0) ({ num in num * num })(9.0) ({ $0 * $0 })(9.0) { $0 * $0 }(9.0) When Use Closures in Swift

A closure is useful when you only need the functionality once in your code.

Commonly, a closure is passed as an argument into another function. This is useful when you do not want to define a separate function for it.

A great example is when performing an operation on a collection of values using the map() function.

Now that you understand what a closure is it is time to learn how the map() function works.

The map() Function in Swift

In Swift, you can use the built-in map() function to modify each element in a collection.

The map() function loops through the collection, applying a function for each element. The map() function always returns an array where the transformed values are.

Before using the map() function, let’s use a for loop to transform an array of numbers.

A For Loop

Let’s create an array of numbers and square each number in the array using a for loop:

let numbers = [1, 2, 3, 4, 5] var squared: [Int] = [] for n in numbers { let sq = n * n squared.append(sq) } print(squared)

Output:

[1, 4, 9, 16, 25]

This approach is perfectly valid and it works as expected. However, this loop can be made significantly shorter by using the map() function.

Next, let’s use the map() function to solve the same problem.

Map with the map() Function

The map() function takes a function as an argument and applies it for each element in a collection.

For example, given a function that squares numbers, let’s use map() function to call it on each element in an array:

return num * num } let numbers = [1, 2, 3, 4, 5] let squared = numbers.map(square) print(squared)

Output:

[1, 4, 9, 16, 25]

If you have only called functions with parenthesis before, numbers.map(square) might look strange to you.

But it is easy to understand.

The map() function does not want you to call a function. Instead, it wants to know the name of the function to be called on each element.

Under the hood, the map() function operates like a for loop such that it:

Picks an element from the collection.

Calls the function on that element.

Stores the result in another collection.

Repeats 1-3 until there are no elements left after which it returns the result collection.

Now you understand how the map() function works. Next, let’s take a more conventional approach to using the map() function by calling it with closure arguments.

Map with Closures

The map() function calls a function for each element in a collection. This function can be a regular function defined separately or a closure function defined inline.

If you need the mapping functionality only once, it is better practice to declare it as a closure directly into the map() function. This prevents you from leaving unused functions in your codebase.

For example, let’s define the squaring functionality directly into the map() function in a form of a closure:

let numbers = [1, 2, 3, 4, 5] return num * num })

Now there is no need for a separate function that defines how to square a number. Instead, it is a closure that is defined in the map() call.

As you learned before, you can clean up the closure quite a bit. This is because you do not need to be explicit about:

The parameter type.

The return type.

The return statement.

The parameter name.

With this in mind, the above map() function call becomes significantly shorter and more concise:

let squared = numbers.map({ $0 * $0 })

Now you know how to use the map() function with closures. Let’s take a look at calling map() on different data types in Swift.

Use map() with Other Data Types

So far you have seen how to use the map() function with arrays. As it turns out, you can also call map() on other collection types in Swift. However, the result is always an array! This means for example that mapping a dictionary to another dictionary is not directly possible.

Dictionaries And the map() Function

In Swift, you can call the map() function on a dictionary. Just remember that the map() function always returns an array.

For instance, let’s convert all values in a dictionary to upper case:

let data = [ "name": "alice", "address": "imaginary street", "college": "oxford university" ] let upperCased = chúng tôi { $1.uppercased() } print(upperCased)

Output:

["IMAGINARY STREET", "OXFORD UNIVERSITY", "ALICE"]

Notice that a dictionary is an unordered collection. This means the order of the result varies.

To map a dictionary to another dictionary in Swift:

Call map() function on a dictionary to create an array of tuples of key-value pairs.

Convert the array of tuples to a dictionary using Dictionary(uniqueKeysWithValues:).

For example, let’s convert a dictionary to a dictionary with uppercased values.

let data = [ "name": "alice", "address": "imaginary street", "college": "oxford university" ] let upperCased = chúng tôi { ($0, $1.uppercased()) } let formattedDict = Dictionary(uniqueKeysWithValues: upperCased) print(formattedDict)

Output:

["college": "OXFORD UNIVERSITY", "address": "IMAGINARY STREET", "name": "ALICE"] Range And the map() Function

In Swift, a range is a collection of values between a starting value and the ending value.

In Swift, you can call map() function range to transform the range to an array of transformed values.

For example, let’s create a range of numbers from 1 to 10 and square each number:

let squaredRange = (1...10).map { $0 * $0 } print(squaredRange)

Output:

[1, 4, 9, 16, 25, 36, 49, 64, 81, 100] Set And the map() Function

In Swift, a set is an unordered collection of unique values.

You can call map() on a set to transform it to an array of transformed values.

For example, let’s square a set of numbers:

let numbers: Set = [1, 2, 3, 4, 5] let squared = chúng tôi { $0 * $0 } print(squared)

Output:

[1, 9, 16, 25, 4] Conclusion

Today you learned how to use the map() function in Swift.

To recap, the map() function calls a function for each element in the collection. It returns a new array with the updated values.

You can call the map() function on an array, dictionary, string, or set. However, you always get an array back.

Using the map() function lets you replace the for loops with much more elegant expressions.

Thanks for reading.

Happy coding!

Further Reading

50 Swift Interview Questions

How To Extend An Existing Javascript Array With Another Array?

In this tutorial, let’s find out how to extend an existing JavaScript array with another array. Before explaining the steps, we need to be aware that there is a requirement for several arrays at various times, and learning the right method can save our coding time. You will find more than four methods to extend an array with another. So, most likely, find an easy-to-remember method in the tutorial.

Using Array push() Method and Spread Syntax

The push() method is extremely useful in adding items to an existing JavaScript array. Moreover, you can pass a variety of different arguments based on the output that is preferred.

The spread operator can be used in this scenario to extend the items from an array with another array.

Syntax array1.push( ...array2 )

In the above syntax, we are extending the array1 with array2 values.

Algorithm

Step 1 − Create an array.

Step 2 − Create another array that might be added to the previous array.

Step 3 − Use the push() method with the first array.

Step 4 − Mention another array in the brackets.

Example

In this example, we have created two arrays and used the push method to extend the numbers listed in array number 2 in array number 1. You can also use multiple arrays and provide conditions using the “if and else” method.

const

number1

=

[

1

,

2

,

3

]

const

number2

=

[

4

,

5

,

6

]

const

text

=

“New Array is: “

document

.

getElementById

(

“my”

)

.

innerHTML

=

text

+

number1

;

Using Array push.apply() Method

While the push method is commonly used, apply method can also provide similar output. This method will likely consider the mentioned array as the first argument and extend other arguments using the push method.

Syntax array1.push.apply(array1, array2) Algorithm

Step 1 − Make a new array of numbers or words.

Step 2 − Create another array that will be used to extend.

Step 3 − Use the apply method with the push one using the array that needs to be extended with another one.

Step 4 − Mention the list of arrays that needs to be added following the correct order.

Example

In the example below, we have used the array.push.apply() method to extend the JavaScript array.

const number1 = [1, 2, 3] const number2 = [4, 5, 6] number1.push.apply(number1, number2) const text = “New Array are: ” document.getElementById(“my”).innerHTML = text + number1;

The output of the array is similar to the one we got previously using the Push method. You can also use the prototype with the push and apply the method to get the same result.

Using Array concat() Method

Here we will write four arrays and use the concat() method twice to see how the arrays get extended with another array.

Syntax array1.concat(array2) Example

Here is an example of writing JavaScript code using the concat() method. One thing you have to remember is that you have to use “let” or “var” instead of “const” for the array that will be used in the concat method. For instance, here we have used the “number1” array and the “num1” array.

const number1 = [3, 6, 9] const number2 = [12, 15, 18] num1 = number1.concat(number2) const text = “New Array of numbers is : ” document.getElementById(“result”).innerHTML = text + num1;

Compared to other methods, the spread operator is easy to remember and makes the code look clear.

Syntax array1 = [...array1, ...array2] Example

Here we have used two let variables because the const variable can’t be used for the spread operator method. After running this script, you will find that array “number2” repeats the output of the spread method of array “number1” and the numbers of array “number2”.

The reason is that the array number1 is first assigned with the method, and when it gets used in the second method, it repeats the output.

let number1 = [4, 5, 6] let number2 = [1, 2, 3] number1 = […number2, …number1] number2 = […number2, …number1] const text = “New number are: ” document.getElementById(“result1”).innerHTML = text + number1; document.getElementById(“result2”).innerHTML = text + number2;

Realizing the desired output before writing the code is the first step. You can get lasting results and use these methods for various websites.

The methods like spread operators and concat() can be used to experiment with arrays and get different outputs. Although these methods look straightforward, you can only make the best use of them through trial and error.

How To Optimize A Map In Hammer Editor: 10 Steps (With Pictures)

In Fig. 1a, the room is obviously not sealed. If you compile this map with that leak, vvis (the portion of the compile that determines visibility data) won’t be able to determine the boundaries of the map, since the visleaves  will just “leak” out into the black void outside our map.

In Fig. 1b, the room is sealed and will be compiled correctly.

Create brushes with “tools/toolsnodraw”. Make sure you always create brushes with the tools/toolsnodraw texture first and then texture only what the player can see from the player’s point-of-view. If you are only going to see one side of a wall, then texture that visible side only.

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In Fig. 3a, there are two brushes: the one on the left was created using the Arch Tool which created an 8-sided brush with 40 faces, and the one on the right was made from a single clipped brush with only 11 faces. The latter was achieved by utilizing the Clipping Tool (Shift + X). To achieve the latter, it is recommended to first create the desired geometric shape out of the Arch Tool first for reference. Then, create a brush with the same length, width, and height as the reference arch and place it slightly above the reference. Select the brush and clip the angles. (you may need to change the grid size (“-” to decrease, “+” to increase) and/or manually move the vertices (Shift + V) of the reference arch to snap to the nearest grid point.) Now you have a geometrically identical brush, but only with fewer faces!

Make good use of detail brushes. World brushes block visibility, seal the map, and split the BSP into “leaves”, which are basically the compiler’s way of determining what can and can’t be seen at any given time and place. Detail brushes were designed to essentially be “invisible” to the compiler. The only brushes that should be world brushes are the walls, floor and ceiling of a room. Pretty much everything else in the room that isn’t a working entity and doesn’t significantly block the player’s vision should be tied to a func_detail brush (tie using Ctrl + T). Since detail brushes don’t block visibility, they won’t be compiled in vvis calculations and won’t split the map into more visleaves (which is good in most cases). Be warned though that it won’t seal the map either. Just make sure that all the world brushes seal the map and there shouldn’t be any problems.

Use area-portals and hint brushes appropriately. Area-portals and hint brushes are great ways to limit visibility and increase performance if done correctly. However, you should not place these in every corridor and window, as the amount to calculate what’s supposed to be rendered and when could very well surpass that of just rendering the entire room all at once. Instead, you should only separate rooms with lots of details. This will spare your computer having to render many unnecessary objects, and help increase performance without putting a major strain on visibility calculations.

Use occluders (sparingly). Occluders are similar to a closed area portal, as it doesn’t render what is behind it. However, it is different than a closed area-portal in that it doesn’t need to seal a room (it can be free-standing and not touch world brushes) and it only blocks 3D models (aka props). This tool is very costly in terms of memory usage, so you should only use occluders when there is an expensive 3D model behind a free-standing wall that cannot be sealed by areaportals.

Add 3D Sky-boxes. Not totally necessary, but it’ll help make the map look much larger without drastically slowing down FPS (frames per second). 3D skyboxes are usually made for “large” outdoor maps, but it is possible to make it for an indoor map if you can see an exterior through a window or something. 3D skyboxes are very cheap to render and can make a small map appear up to 16x larger since 3D skyboxes are set to a 1/16 scale in Hammer and then scaled up during compile.

Add fog. On large outdoor maps, fog can limit the amount of detail being rendered, and it can make your map look more realistic in the process. Simply add an env_fog_controller entity in your map. On the “Enable Fog” option in the Object Properties tab, select “Yes”. Next, edit the Far Z Clip Plane to your liking, which will remove all brushes after that distance, eliminating the engine rendering unnecessary objects (The Far Z Clip Plane value should be greater than the Fog End value).

Don’t go crazy on the Lightmap Scale. The lightmap scale essentially determines how sharp or blurry shadows are rendered on geometry. Larger numbers degrade the shadow quality, but can increase performance. Contrariwise, a lower lightmap scale increases the visuals of the shadows, but can severely lower performance. Either too large or too small of a lightmap scale could produce an unrealistic lighting effect that is either too dull or too sharp, respectively. The default lightmap scale for all brushes is 16, which is a balanced area between visuals and performance.

If your map has water, place a “water_lod_control” entity in the map. This entity determines how far away you have to be from “expensive” water in order for it to transition to “cheap” water. Expensive water looks much more realistic than cheap water, and therefore costs more in terms of memory usage and calculations on the computer. A shorter transitional distance will produce cheaper water at a shorter distance, and therefore will lose a lot of visual quality when at a distance, but will also increase performance.

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