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Earth Day is approaching, reminding us of the importance of decreasing our carbon footprint, preserving natural resources, and adopting sustainable habits. I've always been conscious of environmental protection and have been working on reducing my waste and taking care of nature. To prepare for Earth Day, I'd like to share some apps that can help you make your lifestyle more sustainable. PaperKarma Let's start with paper waste. Aren't you tired of the piles of catalogs, brochures, coupons, and other paper waste that clutters your mailbox? Honestly, does anyone really look through all of them? You probably just put them in the recycling bin right away. The good news is that in the USA, with the app, you can opt out of all unnecessary catalogs and brochures. The app allows you to remove your contact information from all paper mailing lists in just a few taps. Simply snap a picture of your unwanted mail and tap Send to remove yourself from a marketing list. Within 24 hours, you’ll receive a notification that you’ve been unsubscribed. PaperKarma The fewer paper catalogs and brochures are distributed, the fewer trees are cut down to make paper. iScanner Once you're free from junk mail, it's time to tackle your shelves and cabinets. You'll likely find old notebooks, printouts of lectures, sketches, catalogs, and unnecessary documents. You might find papers or magazines that you don't want to throw away because they might be useful in the future or you have fond memories of them. In this case, you can scan these documents and send paper counterparts for recycling. With the help of a mobile scanner, such as you can easily capture high-quality scans of documents from photos and convert them into different formats. Plus, you can conveniently store them in a file manager. iScanner, Too Good To Go Now let's talk about food waste. Every day, tons of food in the USA and Europe goes to waste because it's nearing its expiration date. If a croissant or chop isn't bought in time, it will simply be thrown away. helps solve this problem. On the app, restaurants, cafes, and supermarkets post information about products and dishes that will soon expire and give them away at a discount. By using this app, you can both reduce waste and save money. Too Good To Go Olio If you like to cook, you might also have food leftovers. Of course, you can plan your menu to prepare new dishes from all leftover products. But if you miscalculate and buy more of it than you can use or cook too much food, you need to make sure that it doesn't go to the trash can. In such cases, the app will come to the rescue. Just take a photo of the products or food you want to donate, and other users nearby will get a notification. You can agree on a time the other person will pick up the item right in the app. In addition to food, you can donate tableware, cosmetics, toys, clothes, and other items through the app. Olio Tap Hydration & Water Stations Plastic waste is one of the most pressing issues for our planet. Most of you have probably seen video clips of how much plastic now pollutes our oceans, forests, and every other place where people reside. Eliminating all plastic from your life is difficult, but you can take small steps in this direction. For example, start carrying a reusable water bottle instead of buying bottled water. You can refill your bottle not only at home or in the office but also in many public places where drinking fountains are available or in cafes and restaurants that offer water. Finding such places in the US is easy with the , which shows locations where you can get water and the fastest route to get there. Tap app The list of apps that help reduce your carbon footprint is extensive. However, from personal experience, I know that having too many options makes it difficult to choose, so I will not distract your attention. Try any of these five apps, and by using at least one of them, you will begin contributing to the preservation of the environment today. There is no need to wait for Earth Day or any other environmental event to start your eco-conscious journey.

5 Apps to Check Out for Earth Day

Authors: (1) Eugene Y. S. Chua, Division of the Humanities and Social Sciences, California Institute of Technology; (2) Eddy Keming Chen, ‡Department of Philosophy, University of California. Table of Links Abstract & Introduction Decoherence and Branching The Born Rule Discussion Conclusion and References 5 Conclusion We suggest that the Evereian understanding of decoherence and branching, as well as the justifications for the Born rule, apply to both WFRE and DMRE. Hence, the theoretical benefits of DMR are available on EQM. Another consequence is that Everettians face a choice between two types of theories, one allowing only pure states for the multiverse and the other allowing mixed states also. The choice will not be based on different understandings of the branching structure or the Born rule, as the Everettian justifications equally apply in both theories, but must involve some other theoretical considerations. In any case, the availability of different versions of EQM is an interesting example of empirical underdetermination. Its implications and possible resolutions are questions we leave for future work. Acknowledgements For helpful feedback, we thank Jefferey Barrett, Charles Sebens, Kelvin McQueen, Katie Robertson, Simon Saunders, Tony Short, Karim Thebault, David Wallace, and the ´ participants at the 2023 Workshop on Relational Clocks, Decoherence, and the Arrow of Time at the University of Bristol, and the 2022 California Quantum Interpretation Network Conference at Chapman University. References Albert, David. “Elementaryantum Metaphysics”. In: Bohmian Mechanics and Quantum theory: An Appraisal. Ed. by J. T. Cushing, Arthur Fine, and Sheldon Goldstein. Kluwer Academic Publishers, 1996, pp. 277–284. — Time and chance. Cambridge: Harvard University Press, 2000. Allori, Valia et al. “Predictions and primitive ontology in quantum foundations: a study of examples”. In: The British Journal for the Philosophy of Science 65.2 (2013), pp. 323–352. Baker, David. “Measurement outcomes and probability in Everettian quantum mechanics”. In: Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 38.1 (2007), pp. 153–169. Barrett, Jeffrey. “Everettian Quantum Mechanics”. In: The Stanford Encyclopedia of Philosophy. Ed. by Edward N. Zalta and Uri Nodelman. Summer 2023. Metaphysics Research Lab, Stanford University, 2023. Chen, Eddy Keming. “From time asymmetry to quantum entanglement: The Humean unification”. In: Nousˆ 56 (2022), pp. 227–255. — “Fundamental Nomic Vagueness”. In: The Philosophical Review 131(1) (2022). — “Quantum Mechanics in a Time-Asymmetric Universe: On the Nature of the Initial Quantum State”. In: The British Journal for the Philosophy of Science 72.4 (2021), pp. 1155–1183. — “Realism about the wave function”. In: Philosophy Compass 14.7 (2019). — “Strong Determinism”. In: Philosophers’ Imprint forthcoming (2022). — “Time’s Arrow in a Quantum Universe: On the Status of Statistical Mechanical Probabilities”. In: Statistical Mechanics and Scientific Explanation: Determinism, Indeterminism and Laws of Nature. Ed. by Valid Allori. Singapore: World Scientific, 2020. Deutsch, David. “Quantum Theory of probability and decisions”. In: Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 455.1988 (1999), pp. 3129–3137. Durr, Detlef et al. “On the role of density matrices in Bohmian m ¨ echanics”. In: Foundations of Physics 35.3 (2005), pp. 449–467. Kent, Adrian. “307One World Versus Many: e Inadequacy of Everettian Accounts of Evolution, Probability, and Scientific Confirmation”. In: Many Worlds?: Everett, Quantum Theory, and Reality. Oxford University Press, June 2010. Maroney, Owen. “The Density Matrix in the de Broglie–Bohm Approach”. In: Foundations of Physics 35.3 (2005), pp. 493–510. McQueen, Kelvin J. and Lev Vaidman. “In defence of the self-location uncertainty account of probability in the many-worlds interpretation”. In: Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 66 (2018), pp. 14–23. Ney, Alyssa. The world in the wave function: a metaphysics for quantum physics. Oxford University Press, 2021. Nielsen, Michael A and Isaac L Chuang. Quantum computation and quantum information. Cambridge university press, 2010. Robertson, Katie. “In search of the holy grail: How to reduce the second law of thermodynamics”. In: The British Journal for the Philosophy of Science 73.4 (2022), pp. 987– 1020. Saunders, Simon. “Branch-counting in the Everett interpretation of quantum mechanics”. In: Proceedings of the Royal Society A 477.2255 (2021), p. 20210600. Schlosshauer, Maximilian A.Decoherence: and the quantum-to-classical transition. Springer Science & Business Media, 2007. Sebens, Charles T. and Sean M. Carroll. “Self-Locating Uncertainty and the Origin of Probability in Everettian Quantum Mechanics”. In: British Journal for the Philosophy of Science 1 (2018), axw004. Tappenden, Paul. “Evidence and Uncertainty in Everett?s Multiverse”. In: British Journal for the Philosophy of Science 62.1 (2011), pp. 99–123. Vaidman, Lev. “Derivations of the Born Rule”. In: antum, Probability, Logic: The Work and Influence of Itamar Pitowsky. Ed. by Meir Hemmo and Orly Shenker. Cham: Springer International Publishing, 2020, pp. 567–584. — “Many-Worlds Interpretation of Quantum Mechanics”. In: The Stanford Encyclopedia of Philosophy. Ed. by Edward N. Zalta. Fall 2021. Metaphysics Research Lab, Stanford University, 2021. — “On schizophrenic experiences of the neutron or why we should believe in the many-worlds interpretation of quantum theory”. In: International Studies in the Philosophy of Science 12.3 (1998), pp. 245–261. Wallace, David. e Emergent Multiverse: Quantum Theory According to the Everett Interpretation. Oxford University Press, 2012. — “The sky is blue, and other reasons quantum mechanics is not underdetermined by evidence”. In: arXiv preprint: 2205.00568 (2022). This paper is under CC 4.0 license. available on arxiv

Decoherence, Branching, and the Born Rule in a Mixed-State Everettian Multiverse: Conclusion

Authors: (1) Eugene Y. S. Chua, Division of the Humanities and Social Sciences, California Institute of Technology; (2) Eddy Keming Chen, ‡Department of Philosophy, University of California. Table of Links Abstract & Introduction Decoherence and Branching The Born Rule Discussion Conclusion and References 3 The Born Rule 3.1 The Sebens-Carroll Program Sebens and Carroll (2018) proposes a strategy for justifying the Born rule for Alice above: the probabilities ascribed to each branch by the Born rule are to be interpreted as Alice’s self-locating uncertainty as to which branch they’re located in, postmeasurement but before they observe the measurement outcome. In their words: If we assume that the experimenter knows the relevant information about the wave function, it’s unclear what the agent might be uncertain of before a measurement is made. They know that every outcome will occur and that they will have a successor who sees each possible result. […] We must answer the question: What can one assign probabilities to? Our answer will be that agents performing measurements pass through a period of self-locating uncertainty, in which they can assign probabilities to being one of several identical copies, each on a different branch of the wave function. (ibid., 33) To elaborate, their strategy relies on (i) the fact that Alice knows the universal wave function, (ii) has undergone branching due to some measurement having been performed, but (iii) may not be able to discern which branch they’re on prior to observing the measurement outcome due to each copy of Alice, post-branching, having qualitatively identical internal states as each other. For Sebens and Carroll, “two agents are in the same internal qualitative state if they have identical current evidence: the paerns of colors in their visual fields are identical, they recall the same apparent memories, they both feel equally hungry, etc.” (2018, 36) In this ‘post-measurement pre-observation’ period, as they call it, the universal wave function is: Sebens and Carroll (2018) then proposes an intuitive epistemic principle with which they justify Alice’s use of the Born rule, where the probabilities are now interpreted in terms of subjective credences: Epistemic Separability Principle (ESP): Suppose that universe U contains within it a set of subsystems S such that every agent in an internally qualitatively identical state to agent A is located in some subsystem which is an element of S. The probability that A ought to assign to being located in a particular subsystem S given that they’re in U is identical in any possible universe which also contains subsystems S in the same exact states (and does not contain any copies of the agent in an internally qualitatively identical state that are not located in S). Case 1: Pure states 3.2 The McQueen-Vaidman Program Similar to the Sebens-Carroll program, Mceen and Vaidman (2018) also proposes an interpretation of the Born rule in terms of self-locating uncertainty. is follows earlier aempts initiated by e.g. Vaidman (1998) and Tappenden (2011). Mceen and Vaidman’s setup depends on the fiction of a sleeping pill, which induces the same post-measurement pre-observation uncertainty as the Sebens-Carroll program: The experimenter performs the experiment without looking at the result; she instead arranges to be put to sleep with a sleeping pill and taken to room A if the result was a, and room B if the result was b. e rooms are identical from the inside. So when each of the experimenter’s descendants [post-branching copies] wakes up, they will be uncertain as to which room they’re in, and therefore uncertain as to which result, a or b, obtains in their own world. The question: What is the probability for result a? makes sense for them. It’s not a question about what happened, it’s a question about their self-location. The descendants might know everything relevant regarding the wavefunction of the universe, but still be ignorant about who they are. The descendants are in states of self-location uncertainty. (2018, 2) However, instead of relying on ESP, they rely on three physical principles: • Symmetry: Symmetric situations should be assigned equal probabilities. • No-FTL: Faster-than-light signaling is impossible; the probability of finding a particle in some location with some state cannot be influenced by actions occurring remotely. • Locality: The probability of finding a particle somewhere in some state depends only on that particle’s quantum state. Given this situation, each agent – well aware of the symmetry of the situation – is put in a sleeping pill situation: they’re put to sleep before measurement in a ‘ready’ room, and then moved to a ‘found’ room – stipulated to be internally identical as the ‘ready’ room – if the particle is found by the measurement apparatus in their space-station. e measurement then takes place. 3.3 The Deutsch-Wallace Program Finally, we turn to the Deutsch-Wallace program. In contrast to the previous two, this program provides a justification of the Born rule in WFRE by appealing not to self-locating uncertainty, but to rational choice theory. A rational agent betting on outcomes of measurements for some wave function ought to bet in such a way that the credences they have over these outcomes are governed by the squared-amplitudes of the wave function. Deutsch (1999) provided one of the earliest proofs for this result. However, the most refined result is due to Wallace (2012), who proves a representation theorem to this effect given certain axioms of rational choice and assumptions about the structure of quantum bets. The decision problem can be summarized schematically as such: a system’s state space – its Hilbert space – can be decomposed into various macrostates π, with their fineness (i.e. size) determined by decoherence and the environment. Any system in a macrostate π is compatible with a set of unitary transformations, which are understood as acts on the system by an agent (for instance, measurement). These acts lead to outcomes in the form of the system ending up in different macrostates on different branches as a result of the unitary transformations. Agents are then asked how they would place monetary bets on these outcomes, on which they will collect rewards after the act is performed; that is, agents are asked to state their preferences for bets on these outcomes. Now, the question is this: what credences should agents rationally assign to these outcomes? Wallace assumes a set of four ‘richness’ axioms on the structure of the set of possible bets,[2] as well as a set of six ‘rationality’ axioms on the structure of the agent’s rational preferences on pairs of bets.[3] Thee first two are general axioms of rationality, while the latter four are ‘Everettian’ rationality axioms proposed by Wallace. We won’t go into detail stating the axioms, except for one (which we’ll discuss in the following section). e interested reader is invited to read Wallace (2012, §5). Wallace (2012, 172) proves the following theorem with the above set-up: There is a utility function on the set of rewards, unique up to positive affine transformations, such that one act is preferred to another if and only if its expected utility, calculated with respect to this utility function and to the quantum-mechanical weights of each reward, is higher. Born Rule Theorem: [1] We could also have made a measurement for z-spin, in which case completely analogous results follow: the density matrix gives rise to a different branching structure. [2] They are called Reward Availability, Branching Availability, Erasure, and Problem Continuity respectively. [3] They are called Ordering, Diachronic Consistency, Macrostate Indifference, Branching Indifference, State Supervenience, Solution-Continuity, respectively. [4] Many thanks to David Wallace for discussions about this point. This paper is under CC 4.0 license. available on arxiv

The Born Rule in a Mixed-State Everettian Multiverse

THE TULIPOMANIA

Haskell is not without its faults. One of the most universally acknowledged annoyances, even for pros, is keeping track of the . There are, in total, five different types representing strings in Haskell. Remember Haskell is strongly typed. So if we want to represent strings in different ways, we have to have different types for them. This motivates the need for these five types, all with slightly different use cases. It’s not so bad when you’re using any one of them. But when you constantly have to convert back and forth between them, it can be a major hassle. In this article we’ll go over these five different types. We’ll examine their different use cases, and observe how to convert between them. different string types Strings The type is the most basic form of representing strings in Haskell. It is a simple type synonym for a (the type). So whenever you see in your compile errors, know this refers to the basic type. By default, when you enter in a string literal in your Haskell code, the compiler infers it as a . String list of unicode characters Char [Char] String String myFirstString :: StringmyFirstString = “Hello” The list representation of strings gives us some useful behavior. Since a string is actually a list, we can use all kinds of familiar functions from Data.List. >> let a = “Hello”>> map Data.Char.toUpper a“HELLO”>> ‘x’ : a“xHello”>> a ++ “ Person!”“Hello Person!”>> Data.List.sort “dbca”“abcd” The main drawback of the vanilla string type is its . This comes as a consequence of immutability. For instance suppose we have: inefficiency myFirstString :: StringmyFirstString = “Hello”

myModifiedString :: StringmyModifiedString = map toLower (sort (myFirstString ++ “ Person!”)) This will allocate a total of 4 strings. The first is . The second is the “ Person!” literal. We can then append these without making another string. But then the sorted version will be a third allocation, and the fourth will be the lowercased version. This constant allocation can make our code non-performant and . myFirstString inappropriate for heavy duty operations Text The family of string types solves this dilemma. There are two types: strict and lazy. Most often, you will use the strict form. However, the lazy form is useful in certain circumstances where you know you won’t need the full string. Text Text The main advantage has is that its functions are subject to “fusion”. This means the compiler can actually of multiple allocations we saw in the last example. For instance, if we look at this: Text prevent the issue import qualified Data.Char as Cimport qualified Data.Text as ToptimizedTextVersion :: T.TextoptimizedTextVersion = T.cons ‘c’ (T.map C.toLower (T.append (T.Text “Hello “) (T.Text “ Person!”))) This will only actually allocate a single object at runtime. This will make it it than the version. So for industrial use of heavy text processing, you are much better off using the type than the type. Text substantially more efficient String Text String ByteString The third family of types fall into the category. As with , there are strict and lazy variants of bytestrings. Lazy bytestrings are a bit more common than lazy text values though. Bytestrings are the of the characters. It is the closest you can get to the real machine level interpretation of them. At their core, bytestrings are a list of objects. A is simply an 8-bit number representing a unicode character. ByteString Text lowest level representation Word8 Word8 Most networking libraries will use bytestrings, as they make the most sense for . When you send information across platforms, you can’t be sure about the encoding on the other end. If you store information in a database, you will often want to use bytestrings as well. Like types, they are generally far more efficient than strings. serialization Text Conversion So with all these types floating around, the real problem is converting between them. It can be enormously frustrating when you want to write some basic code but you have a different string type. You’ll have to look up the conversion if you don’t remember, and this can be annoying. Our first example will be with and . This is quite straightforward. The package exports these two functions, which do exactly what you want: String Text Data.Text pack :: String -> Textunpack :: Text -> String There are equivalents in . We’ll find similar functions for going between and . They exist in the package: Data.Text.Lazy ByteStrings Strings Data.ByteString.Char8 pack :: String -> ByteStringunpack :: ByteString -> String Note these only work with strict . To convert between strict and lazy, you'll want functions from the version of a text type. For instance, exports: ByteStrings .Lazy Data.Text.Lazy toStrict :: Data.Text.Lazy.Text -> Data.Text.Text -- (Lazy to strict)fromStrict :: Data.Text.Text -> Data.Text.Lazy.Text -- (Strict to lazy) There are equivalents in . The final conversion we’ll go over is between and . You could use as an intermediate type with the functions above. But this makes certain assumptions about the encoding and is subject to failure. Going from to is straightforward, assuming . The following functions exist in : Data.ByteString.Lazy Text ByteString String Text ByteString you know your data format Data.Text.Encoding encodeUtf8 :: Text -> ByteString

-- LE = Little Endian format, BE = Big Endian

encodeUtf16LE :: Text -> ByteStringencodeUtf16BE :: Text -> ByteStringencodeUtf32LE :: Text -> ByteStringencodeUtf32BE :: Text -> ByteString In general, you’ll use UTF8 encoded text and thus . Decoding is a little more complicated. Simple functions exist in this same library: encodeUtf8 decodeUtf8 :: ByteString -> TextdecodeUtf16LE :: ByteString -> TextdecodeUtf16BE :: ByteString -> TextdecodeUtf32LE :: ByteString -> TextdecodeUtf32BE :: ByteString -> Text But these can throw errors if your bytestring does not match the format. Run-time exceptions are bad, so for UTF8, we have this function: decodeUtf8’ :: ByteString -> Either UnicodeException Text Which let’s us wrap this in an and handle possible errors. For the other formats, we have to rely on functions like: Either decodeUtf16LEWith :: OnDecodeError -> ByteString -> Text Where is a specific type of handler. These functions can be particularly cumbersome and difficult to deal with. Luckily, you’ll most often be using UTF8. OnDecodeError OverloadedStrings So we haven’t touched too much on language extensions yet in my articles. But here’s our first real example of one. It’s intended to show you ! As we saw earlier, Haskell will in general interpret string literals in your code as the type. This means you are unable to have the following code: language extensions aren’t particularly scary String -- FailsmyText :: TextmyText = “Hello”

myBytestring :: ByteStringmyBytestring = “Hello” The compiler expects both of these values to be of type, and not the types you gave. So this will normally throw compiler errors. However, with the extension, you can fix this! Extensions use tags like . They are generally added at the top of your source file. String OverloadedStrings {-# LANGUAGE … #-} {-# LANGUAGE OverloadedStrings #-}-- This works!myText :: TextmyText = “Hello”

myBytestring :: ByteStringmyBytestring = “Hello” In fact, for any type you make, you can create an instance of the typeclass. This will allow you to use string literals to represent it. IsString {-# LANGUAGE OverloadedStrings #-}

import qualified Data.String (IsString(..))

data MyType = MyType String

instance IsString MyType where  fromString s = MyType s

myTypeAsString :: MyTypemyTypeAsString = “Hello” You can also enable this extension within GHCI. You need to use the command . :set -XOverloadedStrings Summary Haskell uses 5 different types for representing strings. Two of these are lazy versions. The type is a type synonym for a list of characters, and is generally inefficient. represents strings somewhat differently, and can fuse operations together for efficiency. is a low level representation most suited to serialization. There are a lot of ways to convert between types, and it's hard to keep them straight. Finally, the compiler can make your life easier. It allows you to use a string literal refer to any of your different string types. String Text ByteString OverloadedStrings If you haven’t had a chance to get started with Haskell yet, you should get our . It will guide you through installation and some basics! Getting Started Checklist Be sure to check back next week! Now that we understand strings, we’ll divide into another potentially thorny system of different types. We’ll investigate the different numeric types and the simple conversions we can run between them. is how hackers start their afternoons. We’re a part of the family. We are now and happy to opportunities. Hacker Noon @AMI accepting submissions discuss advertising & sponsorship To learn more, , , or simply, read our about page like/message us on Facebook tweet/DM @HackerNoon. If you enjoyed this story, we recommend reading our and . Until next time, don’t take the realities of the world for granted! latest tech stories trending tech stories

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